Sociodemographic, Clinical, and Treatment-Related Factors Associated With Hyperglycemic Crises Among Adults With Type 1 or Type 2 Diabetes in the US From 2014 to 2020

Rozalina G. McCoy; Rodolfo J. Galindo; Kavya Sindhu Swarna; Holly K. Van Houten; Patrick J. O’Connor; Guillermo E. Umpierrez; Nilay D. Shah

doi:10.1001/jamanetworkopen.2021.23471

Sociodemographic, Clinical, and Treatment-Related Factors Associated With Hyperglycemic Crises Among Adults With Type 1 or Type 2 Diabetes in the US From 2014 to 2020

McCoy, Rozalina G.; Galindo, Rodolfo J.; Swarna, Kavya Sindhu; Van Houten, Holly K.; O’Connor, Patrick J.; Umpierrez, Guillermo E.; Shah, Nilay D. 2021-09-01 00:00:00 Key Points Question What factors are associated IMPORTANCE Hyperglycemic crises (ie, diabetic ketoacidosis [DKA] and hyperglycemic with the occurrence of hyperglycemic hyperosmolar state [HHS]) are life-threatening acute complications of diabetes. Efforts to prevent crises (diabetic ketoacidosis and these events at the population level have been hindered by scarce granular data and difficulty in hyperglycemic hyperosmolar state) identifying individuals at highest risk. among adults with diabetes? Findings In this cohort study of 816 538 OBJECTIVE To assess sociodemographic, clinical, and treatment-related factors associated with adults with diabetes in the US (20 156 hyperglycemic crises in adults with type 1 or type 2 diabetes in the US from 2014 to 2020. adults with type 1 diabetes and 796 382 with type 2 diabetes), younger age, low DESIGN, SETTING, AND PARTICIPANTS This retrospective cohort study analyzed administrative income, Black race/ethnicity, high claims and laboratory results for adults (aged 18 years) with type 1 or type 2 diabetes from the hemoglobin A level, prior OptumLabs Data Warehouse from January 1, 2014, through December 31, 2020. 1c hyperglycemic crises, severe hypoglycemia, depression, neuropathy, MAIN OUTCOMES AND MEASURES Rates of emergency department or hospital visits with a and nephropathy were associated with primary diagnosis of DKA or HHS (adjusted for age, sex, race/ethnicity, and region, and for year when increased risk of hyperglycemic crises in calculating annualized rates) were calculated separately for patients with type 1 diabetes and type 2 both groups. diabetes. The associations of sociodemographic factors (age, sex, race/ethnicity, region, and income), clinical factors (comorbidities), and treatment factors (glucose-lowering medications, Meaning The findings suggest that hemoglobin A ) with DKA or HHS in patients with type 1 or type 2 diabetes were assessed using 1c multidisciplinary interventions focusing negative binomial regression. on groups at high risk of hyperglycemic crises are needed to decrease the RESULTS Among 20 156 adults with type 1 diabetes (mean [SD] age, 46.6 [16.5] years; 51.2% male; incidence and impact of these 72.6% White race/ethnicity) and 796 382 with type 2 diabetes (mean [SD] age, 65.6 [11.8] years; potentially preventable complications of 50.3% female; 54.4% White race/ethnicity), adjusted rates of hyperglycemic crises were 52.69 per diabetes. 1000 person-years (95% CI, 48.26-57.12 per 1000 person-years) for type 1 diabetes and 4.04 per 1000 person-years (95% CI, 3.88-4.21 per 1000 person-years) for type 2 diabetes. In both groups, Supplemental content factors associated with the greatest hyperglycemic crisis risk were low income ($200 000 vs <$40 000: type 1 diabetes incidence risk ratio [IRR], 0.61 [95% CI, 0.46-0.81]; type 2 diabetes IRR, Author affiliations and article information are listed at the end of this article. 0.69 [95% CI, 0.56-0.86]), Black race/ethnicity (vs White race/ethnicity: type 1 diabetes IRR, 1.33 [95% CI, 1.01-1.74]; type 2 diabetes IRR, 1.18 [95% CI, 1.09-1.27]), high hemoglobin A level (10% vs 1c 6.5%-6.9%: type 1 diabetes IRR, 7.81 [95% CI, 5.78-10.54]; type 2 diabetes IRR, 7.06 [95% CI, 6.26-7.96]), history of hyperglycemic crises (type 1 diabetes IRR, 7.88 [95% CI, 6.06-9.99]; type 2 diabetes IRR, 17.51 [95% CI, 15.07-20.34]), severe hypoglycemia (type 1 diabetes IRR, 2.77 [95% CI, 2.15-3.56]; type 2 diabetes IRR, 4.18 [95% CI, 3.58-4.87]), depression (type 1 diabetes IRR, 1.62 [95% CI, 1.37-1.92]; type 2 diabetes IRR, 1.46 [95% CI, 1.34-1.59]), neuropathy (type 1 diabetes IRR, 1.64 [95% CI, 1.39-1.93]; type 2 diabetes IRR, 1.25 [95% CI, 1.17-1.34]), and nephropathy (type 1 diabetes IRR, 1.22 [95% CI, 1.01-1.48]; type 2 diabetes IRR, 1.23 [95% CI, 1.14-1.33]). Age had a U-shaped (continued) Open Access. This is an open access article distributed under the terms of the CC-BY License. JAMA Network Open. 2021;4(9):e2123471. doi:10.1001/jamanetworkopen.2021.23471 (Reprinted) September 1, 2021 1/17 JAMA Network Open | Diabetes and Endocrinology Factors Associated With Hyperglycemic Crises in Adults With Diabetes in the US, 2014-2020 Abstract (continued) association with hyperglycemic crisis risk in patients with type 1 diabetes (compared with patients aged 18-44 years: 45-64 years IRR, 0.72 [95% CI, 0.59-0.87]; 65-74 years IRR, 0.62 [95% CI, 0.47- 0.80]; 75 years IRR, 0.96 [95% CI, 0.66-1.38]). In type 2 diabetes, risk of hyperglycemic crises decreased progressively with age (45-64 years IRR, 0.57 [95% CI, 0.51-0.63]; 65-74 years IRR, 0.44 [95% CI, .39-0.49];75 years IRR, 0.41 [95% CI, 0.36-0.47]). In patients with type 2 diabetes, higher risk was associated with sodium-glucose cotransporter 2 inhibitor therapy (IRR, 1.30; 95% CI, 1.14- 1.49) and insulin dependency (compared with regimens with bolus insulin: regimens with basal insulin only, IRR, 0.69 [95% CI, 0.63-0.75]; and without any insulin, IRR, 0.36 [95% CI, 0.33-0.40]). CONCLUSIONS AND RELEVANCE In this cohort study, younger age, Black race/ethnicity, low income, and poor glycemic control were associated with an increased risk of hyperglycemic crises. The findings suggest that multidisciplinary interventions focusing on groups at high risk for hyperglycemic crises are needed to prevent these dangerous events. JAMA Network Open. 2021;4(9):e2123471. doi:10.1001/jamanetworkopen.2021.23471 Introduction More than 1 in 8 American adults are living with diabetes. Diabetic ketoacidosis (DKA) and 2 3 hyperglycemic hyperosmolar state (HHS) are life-threatening diabetes emergencies that are 4 5-7 8,9 5,10 associated with substantial morbidity, mortality, high costs, and health care use. Although 11-14 several studies have examined factors associated with DKA or HHS in the general population, there is limited contemporary evidence on patient-level risk factors, hindering efforts to proactively identify patients at risk and to reduce the frequency of these events at the population level. Most published research has focused on DKA in patients with type 1 diabetes, often among children or young adults. The frequently cited factors associated with DKA in this context are adolescence, socioeconomic disadvantage, female sex, elevated hemoglobin A (HbA ) level, prior 1c 1c DKA, and comorbid mental health conditions. A recent population-based analysis found that rates of DKA and HHS approximately doubled between 2009 and 2015, with higher rates among younger people and individuals residing in lower-income areas. However, these studies were limited by the lack of contemporary, longitudinal, patient-level data and granular information that differentiates patients by diabetes type, considers both type 1 diabetes and type 2 diabetes, and examines both DKA and HHS hyperglycemic crises. Accordingly, we examined emergency department (ED) visits and hospitalizations for hyperglycemic crises among adults with type 1 diabetes or type 2 diabetes in the US between 2014 and 2020, focusing on patient-level sociodemographic, clinical, and treatment-related factors associated with these events. Methods Study Design This retrospective cohort study used medical and pharmacy claims data from OptumLabs Data Warehouse (OLDW), a deidentified claims database for privately insured and Medicare Advantage enrollees in a nationwide private US health plan. The OLDW database contains longitudinal health information on enrollees, representing a diverse mix of ages, races/ethnicities, and geographic regions across the US. All study data were deidentified in accordance with Health Insurance Portability and Accountability Act expert deidentification determination. Mayo Clinic, Rochester, Minnesota, deemed this study to be exempt from institutional review board review and no informed consent was required (or feasible) because all data were deidentified. The results are reported in JAMA Network Open. 2021;4(9):e2123471. doi:10.1001/jamanetworkopen.2021.23471 (Reprinted) September 1, 2021 2/17 JAMA Network Open | Diabetes and Endocrinology Factors Associated With Hyperglycemic Crises in Adults With Diabetes in the US, 2014-2020 accordance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guideline. Study Population We identified adults (age18 years) with diabetes included in OLDW with available HbA data 1c between January 1, 2014, and December 31, 2019 (index date), and 1 year of uninterrupted insurance coverage before that date. The diagnosis of diabetes was established using Healthcare Effectiveness Data and Information Set criteria and categorized as type 1 diabetes or type 2 diabetes as 11,21,22 previously described. Outcomes The primary outcome was ED visit or hospitalization with a primary or first diagnosis of DKA or HHS (eTable 1 in the Supplement) that occurred between January 1, 2014, and December 31, 2020. In a secondary analysis, DKA and HHS were considered separately; in the event that both codes were present on the same encounter, events were classified as DKA in patients with type 1 diabetes and as HHS in patients with type 2 diabetes. Independent Variables Patient age, sex, race/ethnicity, annual household income, and US census region of residence were identified from OLDW enrollment files at the index date. Comorbidities were ascertained from all claims during the 12 months preceding the index date as described in eTable 1 in the Supplement. Glucose-lowering therapy was characterized based on prescriptions filled during the 120 days before the index date. For patients with type 1 diabetes, we assessed whether they had any prescriptions filled for noninsulin medication(s), prescriptions filled for insulin without noninsulin medications, or no prescriptions filled. For patients with type 2 diabetes, we first assessed whether there were any prescriptions filled, followed by whether there were prescriptions filled for bolus insulin (with or without basal insulin), prescriptions filled for basal insulin, or no prescriptions filled for insulin. Then, we identified fills for individual classes of noninsulin medications (eTable 2 in the Supplement). Statistical Analysis We assessed overall frequencies (percentages) and means (SDs) for baseline patient characteristics using the Mantel-Haenszel χ test for categorical variables and the t test for continuous variables. Crude and adjusted rates of ED visits or hospitalizations for hyperglycemic crises were calculated and presented as the total number of events per 1000 person-years among patients with type 1 diabetes or type 2 diabetes. Overall and annual adjusted rates of hyperglycemic crises were calculated using negative binomial estimates adjusted for age (during the year of the event), sex, race/ethnicity, region, and year. Adjusted rates of hyperglycemic crises for subgroups by age, sex, race/ethnicity, annual household income, and insulin use status (for type 2 diabetes only) were calculated using negative binomial estimates adjusted for age (at the index date), sex, race/ethnicity, and region. We tested for differences in the outcome by age, sex, race/ethnicity, income level, insulin use (in type 2 diabetes), and year using Wald tests. Multivariable negative binomial regression models were also used to examine the association between hyperglycemic crises (dependent variable) and the independent variables outlined above. We evaluated hyperglycemic crises as the total number of events per each person, reporting results as incidence risk ratios (IRRs), 95% CIs, and P values. Person-years were used as an exposure to determine the estimated rates of and factors associated with hyperglycemic crises. Secondary analyses examined the outcomes of DKA and of HHS separately. Analyses were conducted using SAS Enterprise Guide, version 7.1 (SAS Institute Inc) and STATA, version 15.1 (StataCorp LLC). A 2-sided P < .05 was considered statistically significant. JAMA Network Open. 2021;4(9):e2123471. doi:10.1001/jamanetworkopen.2021.23471 (Reprinted) September 1, 2021 3/17 JAMA Network Open | Diabetes and Endocrinology Factors Associated With Hyperglycemic Crises in Adults With Diabetes in the US, 2014-2020 Results Study Population The study cohort comprised 20 156 adults with type 1 diabetes (mean [SD] age, 46.6 [16.5] years; 51.2% male; 72.6% White race/ethnicity) and 796 382 adults with type 2 diabetes (mean [SD] age, 65.6 [11.8] years; 50.3% female; 54.4% White race/ethnicity) (Table 1 and Table 2). The mean (SD) durations of observation of patients in the 2 cohorts were 2.4 (1.8) years for type 1 diabetes and 2.6 (1.8) years for type 2 diabetes. Of patients with type 2 diabetes, 20.6% were treated with insulin. A higher proportion of patients with type 2 diabetes than with type 1 diabetes had an annual household income less than $40 000 (30.6% vs 14.9%). The mean (SD) HbA level among patients with type 1c 1 diabetes was 8.1% (1.6%), compared with 7.4% (1.6%) among patients with type 2 diabetes (to convert to proportion of total hemoglobin, multiply by 0.01). A total of 1273 patients with type 1 diabetes (6.3%) experienced 2397 episodes of hyperglycemic crises. A total of 2364 events (98.6%) were DKA, with only 33 episodes (1.4%) coded as HHS; thus, no secondary analysis by event type was conducted. The mean (SD) number of hyperglycemic crises among patients with at least 1 event was 1.9 (2.2). Compared with those who did not experience hyperglycemic crises, patients who did were more frequently young (mean [SD] age, 43.2 [18.4] vs 46.9 [16.4] years), Black (170 [13.4%] vs 1799 [9.5%]) or Hispanic (124 [9.7%] vs 1690 [9.0%]) individuals, and female (734 [57.7%] vs 9112 [48.3%]) and had lower income levels (<$40,000: 265 [20.8%] vs 2730 [14.5%]) and higher HbA levels (mean [SD], 9.4% [2.0%] vs 1c 8.0% [1.5%]) (Table 1). Among patients with type 2 diabetes, 5795 patients (0.7%) experienced 8005 hyperglycemic crises. The mean (SD) number of hyperglycemic crises among patients with at least 1 event was 1.4 (1.6). Compared with patients who did not experience hyperglycemic crises, patients who did were younger (mean [SD] age, 62.0 [13.7] vs 65.7 [11.8] years) and more likely to be Black individuals (1523 [26.3%] vs 140 476 [17.8%]) and had lower income levels (<$40 000: 2282 [39.4%] vs 241 339 [30.5%]) and higher HbA levels (mean [SD], 9.3% [1.5%] vs 7.3% [1.6%]) (Table 2). When DKA and 1c HHS outcomes were examined separately, 4264 patients (0.5%) experienced only DKA, 1329 (0.2%) experienced only HHS, and 202 (0.02%) experienced both types of events during the study period (eTable 3 in the Supplement). The group who experienced both HHS and DKA was analyzed together with the group with only DKA to ensure that patient deidentification was maintained because the characteristics of the 2 groups were similar. Compared with patients who experienced DKA, patients with HHS were older, were more likely to be Black individuals, had lower income levels, were less likely to have had a prior DKA or HHS event, and had higher prevalence of all comorbidities. Incidence Rates of Hyperglycemic Crises Adjusted overall rates of hyperglycemic crises were 52.69 events per 1000 person-years (95% CI, 48.26-57.12 events per 1000 person-years) among people with type 1 diabetes and 4.04 events per 1000 person-years (95% CI, 3.88-4.21 events per 1000 person-years) among people with type 2 diabetes. Event rates increased between 2014 and 2019 among patients with type 1 diabetes, from 43.30 events (95% CI, 33.37-53.24 events) to 61.36 events (95% CI, 52.90-69.82 events) but then decreased to 46.27 events (95% CI, 38.59-53.95 events) in 2020 (P =.01)(Figure 1 and Figure 2 and eTable 4 in the Supplement). In contrast, event rates among patients with type 2 diabetes remained stable throughout the study period. For both patients with type 1 diabetes and those with type 2 diabetes, rates of hyperglycemic crises were highest among younger patients, Black patients, patients with lower income, women, and (for type 2 diabetes) patients requiring insulin therapy (Figure 1 and Figure 2 and eTable 5 and eTable 6 in the Supplement). Indeed, among patients with type 2 diabetes treated with bolus insulin, with or without basal insulin, the adjusted rate of DKA or HHS was 17.73 events per 1000 person-years. Patients with type 1 diabetes whose annual household income was less than $40 000 experienced hyperglycemic crises at the adjusted rate of 101.52 events per 1000 person-years, compared with 26.25 events per 1000 person-years among patients JAMA Network Open. 2021;4(9):e2123471. doi:10.1001/jamanetworkopen.2021.23471 (Reprinted) September 1, 2021 4/17 JAMA Network Open | Diabetes and Endocrinology Factors Associated With Hyperglycemic Crises in Adults With Diabetes in the US, 2014-2020 Table 1. Baseline Sociodemographic, Clinical, and Diabetes Treatment Characteristics of Patients With Type 1 Diabetes Participants, No. (%) Without With Total hyperglycemic hyperglycemic Characteristic (N = 20 156) crises (n = 18 883) crises (n = 1273) P value Sociodemographic variables Age, y Mean (SD) 46.6 (16.5) 46.9 (16.4) 43.2 (18.4) <.001 18-44 9325 (46.3) 8649 (45.8) 676 (53.1) 45-64 7574 (37.5) 7175 (38.0) 399 (31.3) <.001 65-74 2367 (11.7) 2237 (11.8) 130 (10.2) ≥75 890 (4.4) 822 (4.4) 68 (5.3) Sex Female 9846 (48.8) 9112 (48.3) 734 (57.7) <.001 Male 10 310 (51.2) 9771 (51.7) 539 (42.3) Race/ethnicity White 14 630 (72.6) 13 756 (72.8) 874 (68.7) Black 1969 (9.8) 1799 (9.5) 170 (13.4) Hispanic 1814 (9.0) 1690 (9.0) 124 (9.7) <.001 Asian 523 (2.6) 492 (2.6) 31 (2.4) Other/unknown 1220 (6.0) 1146 (6.1) 74 (5.8) Annual household income, $ <40 000 2995 (14.9) 2730 (14.5) 265 (20.8) 40 000-74 999 4454 (22.1) 4134 (21.9) 320 (25.1) 75 000-124 999 5477 (27.2) 5139 (27.2) 338 (26.6) <.001 125 000-199 999 3283 (16.3) 3133 (16.6) 150 (11.8) ≥200 000 2468 (12.2) 2368 (12.5) 100 (7.9) Unknown 1479 (7.3) 1379 (7.3) 100 (7.9) US census region Midwest 3855 (19.1) 3581 (19.0) 274 (21.5) Northeast 2648 (13.1) 2517 (13.3) 131 (10.3) <.001 South 9740 (48.3) 9085 (48.1) 655 (51.4) West/unknown 3913 (19.4) 3700 (19.6) 213 (16.7) Index year 2014 5151 (25.6) 4791 (25.4) 360 (28.3) 2015 2628 (13.0) 2448 (13.0) 180 (14.1) 2016 2977 (14.8) 2780 (14.7) 197 (15.5) <.001 2017 3036 (15.1) 2834 (15.0) 202 (15.9) 2018 2931 (14.5) 2754 (14.6) 177 (13.9) 2019 3433 (17.0) 3276 (17.4) 157 (12.3) Clinical variables Comorbidity Hyperglycemic crisis 862 (4.3) 545 (2.9) 317 (24.9) <.001 Severe hypoglycemia 623 (3.1) 506 (2.7) 117 (9.2) <.001 Retinopathy 5888 (29.2) 5522 (29.2) 366 (28.8) .71 Neuropathy 5104 (25.3) 4625 (24.5) 479 (37.6) <.001 Nephropathy 2956 (14.7) 2671 (14.1) 285 (22.4) <.001 Cardiovascular disease 2920 (14.5) 2679 (14.2) 241 (18.9) <.001 Cerebrovascular disease 1038 (5.2) 928 (4.9) 110 (8.6) <.001 Peripheral vascular disease 1837 (9.1) 1680 (8.9) 157 (12.3) <.001 Heart failure 692 (3.4) 616 (3.3) 76 (6.0) <.001 Dementia 173 (0.9) 152 (0.8) 21 (1.6) .002 Hypertension 9336 (46.3) 8725 (46.2) 611 (48.0) .21 Depression 2549 (12.6) 2252 (11.9) 297 (23.3) <.001 COPD 1157 (5.7) 1054 (5.6) 103 (8.1) <.001 Cancer 832 (4.1) 776 (4.1) 56 (4.4) .62 c c Cirrhosis 85 (0.4) ≥74 (0.4) <11 .47 (continued) JAMA Network Open. 2021;4(9):e2123471. doi:10.1001/jamanetworkopen.2021.23471 (Reprinted) September 1, 2021 5/17 JAMA Network Open | Diabetes and Endocrinology Factors Associated With Hyperglycemic Crises in Adults With Diabetes in the US, 2014-2020 Table 1. Baseline Sociodemographic, Clinical, and Diabetes Treatment Characteristics of Patients With Type 1 Diabetes (continued) Participants, No. (%) Without With Total hyperglycemic hyperglycemic Characteristic (N = 20 156) crises (n = 18 883) crises (n = 1273) P value Treatment variables Hemoglobin A level, % 1c Mean (SD) 8.1 (1.6) 8.0 (1.5) 9.4 (2.0) <.001 Abbreviation: COPD, chronic obstructive c c ≤5.6 354 (1.8) ≥343 (1.8) <11 pulmonary disease. 5.7-6.4 1859 (9.2) 1822 (9.6) 37 (2.9) SI conversion factor: To convert hemoglobin A to 1c 6.5-6.9 2444 (12.1) 2378 (12.6) 66 (5.2) proportion of total hemoglobin, multiply by 0.01. 7.0-7.9 6359 (31.6) 6116 (32.4) 243 (19.1) <.001 Data are overall (total) and by whether patients 8.0-8.9 4493 (22.3) 4245 (22.5) 248 (19.5) experienced diabetic ketoacidosis or hyperglycemic 9.0-9.9 2387 (11.8) 2164 (11.5) 223 (17.5) hyperosmolar state during the follow-up period. ≥10 2260 (11.2) 1811 (9.6) 449 (35.3) Other is a racial/ethnicity choice in the OptumLabs Prescription fills for glucose- Data Warehouse database. lowering medication in the 120 d Patient counts less than 11 are masked to preserve before the index date deidentification. Thus, all numbers lower than 11 are Insulin only 16 805 (83.4) 15 724 (83.3) 1081 (84.9) reported as less than 11 and numbers within the same Any noninsulin medication 1829 (9.1) 1749 (9.3) 80 (6.3) <.001 row are presented with less precision to prevent None 1522 (7.6) 1410 (7.5) 112 (8.8) back-calculations of the masked sample. with an income of $200 000 or higher. Similarly, for patients with type 2 diabetes, adjusted rates of hyperglycemic crises were 5.78 events per 1000 person-years for individuals with low income and 2.23 events per 1000 person-years for individuals with high income. Tests of differences by age, sex, racial/ethnic groups, and (for type 2 diabetes) insulin use found significant heterogeneity across all (P .01 for all). Factors Associated With Hyperglycemic Crises For patients with type 1 diabetes and with type 2 diabetes, factors associated with increased risk of hyperglycemic crises were Black race/ethnicity (vs White race/ethnicity: type 1 diabetes incidence risk ratio [IRR], 1.33 [95% CI, 1.01-1.74]; type 2 diabetes IRR, 1.18 [95% CI, 1.09-1.27]) and lower annual household income ($200 000 vs <$40 000: type 1 diabetes IRR, 0.61 [95% CI, 0.46-0.81]; type 2 diabetes IRR, 0.69 [95% CI, 0.56-0.86]) (Table 3). Age had a U-shaped association with hyperglycemic crisis risk in patients with type 1 diabetes (compared with patients aged 18-44 years: 45-64 years IRR, 0.72 [95% CI, 0.59-0.87]; 65-74 years IRR, 0.62 [95% CI, 0.47-0.80]; 75 years IRR, 0.96 [95% CI, 0.66-1.38]). In type 2 diabetes, risk of hyperglycemic crises decreased progressively with age (45-64 years IRR, 0.57 [95% CI, 0.51-0.63]; 65-74 years IRR, 0.44 [95% CI, .39-0.49];75 years IRR, 0.41 [95% CI, 0.36-0.47]). In a secondary analysis that considered DKA and HHS separately for patients with type 2 diabetes, age was significantly associated with DKA (75 vs 18-44 years: IRR, 0.35; 95% CI, 0.30-0.41) but not with HHS (eTable 7 in the Supplement). Differences by sex were significant only for patients with type 1 diabetes, with men having lower risk than women (IRR, 0.75; 95% CI, 0.65-0.87). Among patients with type 1 diabetes, risk of hyperglycemic crises increased progressively in association with HbA levels above 7.0%; at HbA 1c 1c levels of 10% or higher, the risk was nearly 8-fold higher than at HbA levels from 6.5% to 6.9% (IRR, 1c 7.81; 95% CI, 5.78-10.54). Among patients with type 2 diabetes, risk of hyperglycemic crises increased progressively in association with all HbA levels, with an IRR of 0.56 (95% CI, 0.43-0.73) 1c at HbA levels of 5.6% or lower and an IRR of 7.06 (95% CI, 6.26-7.96) at HbA levels of 10% or 1c 1c higher compared with HbA levels from 6.5% to 6.9%. We observed similar results for HbA in 1c 1c patients with type 2 diabetes when DKA and HHS were examined separately. Patients who experienced hyperglycemic crises or severe hypoglycemia in the previous year were significantly more likely to experience recurrent DKA or HHS (Table 3). Among patients with type 1 diabetes, both prior hyperglycemic crises (IRR, 7.88; 95% CI, 6.06-9.99) and prior severe JAMA Network Open. 2021;4(9):e2123471. doi:10.1001/jamanetworkopen.2021.23471 (Reprinted) September 1, 2021 6/17 JAMA Network Open | Diabetes and Endocrinology Factors Associated With Hyperglycemic Crises in Adults With Diabetes in the US, 2014-2020 Table 2. Baseline Sociodemographic, Clinical, and Diabetes Treatment Characteristics of Patients With Type 2 Diabetes Participants, No. (%) Total Without hyperglycemic With hyperglycemic Characteristic (N = 796 382) crises (n = 790 587) crises (n = 5795) P value Sociodemographic variables Age, y Mean (SD) 65.6 (11.8) 65.7 (11.8) 62.0 (13.7) <.001 18-44 42 356 (5.3) 41 717 (5.3) 639 (11.0) 45-64 281 738 (35.4) 279 406 (35.3) 2332 (40.2) <.001 65-74 286 441 (36.0) 284 676 (36.0) 1765 (30.5) ≥75 185 847 (23.3) 184 788 (23.4) 1059 (18.3) Sex Female 400 346 (50.3) 397 272 (50.2) 3074 (53.0) <.001 Male 396 036 (49.7) 393 315 (49.8) 2721 (47.0) Race/ethnicity White 433 623 (54.4) 430 499 (54.4) 3124 (53.9) Black 141 999 (17.8) 140 476 (17.8) 1523 (26.3) Hispanic 133 664 (16.8) 132 901 (16.8) 763 (13.2) <.001 Asian 40 971 (5.1) 40 836 (5.2) 135 (2.3) Other/unknown 46 125 (5.8) 45 875 (5.8) 250 (4.3) Annual household income, $ <40 000 243 621 (30.6) 241 339 (30.5) 2282 (39.4) 40 000-74 999 222 612 (28.0) 220 975 (28.0) 1637 (28.2) 75 000-124 999 171 737 (21.6) 170 747 (21.6) 990 (17.1) <.001 125 000-199 999 64 332 (8.1) 64 057 (8.1) 275 (4.8) ≥200 000 28 576 (3.6) 28 449 (3.6) 127 (2.2) Unknown 65 504 (8.2) 65 020 (8.2) 484 (8.4) US census region Midwest 144 126 (18.1) 143 046 (18.1) 1080 (18.6) Northeast 120 946 (15.2) 120 193 (15.2) 753 (13.0) <.001 South 446 286 (56.0) 442 879 (56.0) 3407 (58.8) West/unknown 85 024 (10.7) 84 469 (10.7) 555 (9.6) Index year 2014 152 519 (19.2) 151 000 (19.1) 1159 (26.2) 2015 117 351 (14.7) 116 318 (14.7) 1033 (17.8) 2016 104 538 (13.1) 103 777 (13.1) 761 (13.1) <.001 2017 137 597 (17.3) 136 555 (17.3) 1042 (18.0) 2018 142 231 (17.9) 141 433 (17.9) 798 (13.8) 2019 142 146 (17.8) 141 504 (17.9) 642 (11.1) Clinical variables Comorbidity Hyperglycemic crisis 2646 (0.3) 2063 (0.3) 583 (10.1) <.001 Severe hypoglycemia 6727 (0.8) 6342 (0.8) 385 (6.6) <.001 Retinopathy 123 148 (15.5) 121 733 (15.4) 1415 (24.4) <.001 Neuropathy 218 245 (27.4) 215 790 (27.3) 2455 (42.4) <.001 Nephropathy 186 900 (23.5) 184 944 (23.4) 1956 (33.8) <.001 Cardiovascular disease 259 985 (32.6) 257 875 (32.6) 2110 (36.4) <.001 Cerebrovascular disease 92 517 (11.6) 91 584 (11.6) 933 (16.1) <.001 Peripheral vascular disease 132 101 (16.6) 130 770 (16.5) 1331 (23.0) <.001 Heart failure 85 846 (10.8) 84 889 (10.7) 957 (16.5) <.001 Dementia 24 052 (3.0) 23 788 (3.0) 264 (4.6) <.001 Hypertension 686 124 (86.2) 681 196 (86.2) 4928 (85.0) .01 Depression 99 487 (12.5) 98 313 (12.4) 1174 (20.3) <.001 COPD 114 033 (14.3) 112 987 (14.3) 1046 (18.0) <.001 Cancer 71 797 (9.0) 71 287 (9.0) 510 (8.80) .57 Cirrhosis 8952 (1.1) 8834 (1.1) 118 (2.0) <.001 (continued) JAMA Network Open. 2021;4(9):e2123471. doi:10.1001/jamanetworkopen.2021.23471 (Reprinted) September 1, 2021 7/17 JAMA Network Open | Diabetes and Endocrinology Factors Associated With Hyperglycemic Crises in Adults With Diabetes in the US, 2014-2020 Table 2. Baseline Sociodemographic, Clinical, and Diabetes Treatment Characteristics of Patients With Type 2 Diabetes (continued) Participants, No. (%) Total Without hyperglycemic With hyperglycemic Characteristic (N = 796 382) crises (n = 790 587) crises (n = 5795) P value Treatment variables Hemoglobin A level, % 1c Mean (SD) 7.4 (1.6) 7.3 (1.6) 9.3 (2.4) <.001 ≤5.6 46 822 (5.9) 46 736 (5.9) 86 (1.5) 5.7-6.4 217 748 (27.3) 217 308 (27.5) 440 (7.6) 6.5-6.9 144 631 (18.2) 144 177 (18.2) 454 (7.8) 7.0-7.9 182 928 (23.0) 181 943 (23.0) 985 (17.0) <.001 8.0-8.9 90 804 (11.4) 89 817 (11.4) 987 (19.5) 9.0-9.9 49 029 (6.2) 48 185 (6.1) 844 (14.6) ≥10 64 420 (8.1) 62 421 (7.9) 1999 (34.5) Prescription fills for glucose- lowering medication in the 120 d before the index date None 184 079 (23.1) 183 138 (23.2) 941 (16.2) <.001 Insulin Not treated with insulin 632 323 (79.4) 629 706 (79.6) 2617 (45.2) Basal only, no bolus 89 977 (11.3) 88 724 (11.2) 1253 (21.6) <.001 Abbreviations: COPD, chronic obstructive pulmonary Bolus, with or without basal 74 082 (9.3) 72 157 (9.1) 1925 (33.2) disease; DPP-4, dipeptidyl peptidase 4; GLP-1, Noninsulin glucose-lowering glucagon-like peptide 1; SGLT2, sodium-glucose medication cotransporter 2. Sulfonylurea 203 122 (25.5) 201 852 (25.5) 201 852 (25.5) <.001 SI conversion factor: To convert hemoglobin A to 1c Metformin 429 036 (53.9) 426 884 (54.0) 2152 (37.1) <.001 proportion of total hemoglobin, multiply by 0.01. SGLT2 inhibitor 40 247 (5.0) 39 933 (5.0) 314 (5.4) .20 Data are overall (total) and by whether patients GLP-1 receptor agonist 45 950 (5.8) 45 632 (5.8) 318 (5.5) .35 experienced at least 1 hyperglycemic crisis during the follow- DPP-4 inhibitor 96 962 (12.2) 96 377 (12.2) 585 (10.1) <.001 up period. Thiazolidinedione 38 668 (4.9) 38 439 (4.9) 229 (4.0) .001 Other is a racial/ethnicity choice in the OptumLabs Other 7685 (1.0) 7629 (1.0) 56 (1.0) .99 Data Warehouse database. hypoglycemia (IRR, 2.77; 95% CI, 2.15-3.56) were associated with increased risk of experiencing hyperglycemic crises. Similarly, among patients with type 2 diabetes, prior hyperglycemic crises (IRR, 17.51; 95% CI, 15.07-20.34) and prior severe hypoglycemia (IRR, 4.18; 95% CI, 3.58-4.87) were associated with increased risk of hyperglycemic crises. When DKA and HHS were examined separately, history of hyperglycemic crises had a greater association with DKA (IRR, 20.32; 95% CI, 17.31-23.86) than HHS (IRR, 7.18; 95% CI, 5.68-9.06) (eTable 7 in the Supplement). Compared with patients without the following health conditions, patients with depression (type 1 diabetes IRR, 1.62 [95% CI, 1.37-1.92]; type 2 diabetes IRR, 1.46 [95% CI, 1.34-1.59]), neuropathy (type 1 diabetes IRR, 1.64 [95% CI, 1.39-1.93]; type 2 diabetes IRR, 1.25 [95% CI, 1.17-1.34]), and nephropathy (type 1 diabetes IRR, 1.22 [95% CI, 1.01-1.48]; type 2 diabetes IRR, 1.23 [95% CI, 1.14-1.33]) had an increased risk of hyperglycemic crises (Table 3). For type 2 diabetes, additional risk was associated with the presence of retinopathy, cerebrovascular disease, heart failure, dementia, chronic obstructive pulmonary disease, cirrhosis, or cancer. Patients with type 2 diabetes who required basal insulin therapy (IRR, 0.69; 95% CI, 0.63-0.75) or no insulin therapy (IRR, 0.36; 95% CI, 0.33-0.40) had a lower risk of hyperglycemic crises compared with those treated with bolus, with or without basal, insulin therapy. Patients treated with sodium-glucose cotransporter 2 inhibitors (IRR, 1.30; 95% CI, 1.14-1.49) had an increased risk of hyperglycemic crises compared with patients not treated with these medications (Table 3). Therapy with a sodium-glucose cotransporter 2 inhibitor was specifically associated with an increased risk of DKA (IRR, 1.47; 95% CI, 1.27-1.70) but with a decreased risk of HHS (IRR, 0.65; 95% CI, 0.46-0.93) (eTable 7 in the Supplement). JAMA Network Open. 2021;4(9):e2123471. doi:10.1001/jamanetworkopen.2021.23471 (Reprinted) September 1, 2021 8/17 JAMA Network Open | Diabetes and Endocrinology Factors Associated With Hyperglycemic Crises in Adults With Diabetes in the US, 2014-2020 Discussion In this nationwide cohort study of insured adults with diabetes, adjusted rates of hyperglycemic crises were 52.69 events per 1000 person-years among people with type 1 diabetes, 4.04 events per 1000 person-years among people with type 2 diabetes, and 17.73 events per 1000 person-years among people with type 2 diabetes requiring intensive insulin therapy. In both patients with type 1 diabetes and those with type 2 diabetes, rates of hyperglycemic crises were significantly higher among younger adults, Black patients, individuals with lower income, patients with elevated HbA 1c levels, and patients with prior hyperglycemic crises or severe hypoglycemia, suggesting the need for timely patient identification, engagement, and treatment optimization to improve glycemic control and prevent these dangerous events. We found that the rates of hyperglycemic crises increased over time among patients with type 1 diabetes, from 43.30 per 1000 person-years in 2014 to 61.36 per 1000 person-years in 2019, consistent with previously described trends through 2015 and recent population-level data 23,24 showing an overall worsening of glycemic control among patients with diabetes in the US. There was no comparable temporal change in hyperglycemic crises rates among patients with type 2 diabetes. This persistent rise in rates of hyperglycemic crises among patients with type 1 diabetes underscores the urgency of improving glycemic control and diabetes management in this population. Why ED visits and hospitalizations for hyperglycemic crises among patients with type 1 diabetes declined in 2020 in the context of the COVID-19 pandemic is unknown. Although there may have been a delay in adjudication of claims, with not all 2020 claims finalized at the time of our final analysis (June 2021), this delay alone likely did not account for the observed decrease in hyperglycemic crises–associated ED visits or hospitalizations to 46.27 per 1000 person-years in 2020 (particularly as a similar decrease was not observed for patients with type 2 diabetes). Patients Figure 1. Adjusted Rates of Hyperglycemic Crises Among Adults With Type 1 Diabetes Stratified by Age, Sex, Race/Ethnicity, Annual Household Income, and Year A B C Age Sex Race/ethnicity 140 140 140 120 120 120 100 100 100 80 80 80 60 60 60 40 40 40 20 20 20 0 0 0 18-44 45-64 65-74 ≥75 Female Male White Black Hispanic Asian Age range, y Sex Race/ethnicity D Annual household income E Year 140 140 120 120 100 100 80 80 60 60 40 40 All rates are adjusted for age (age at index for all analyses except for annual rates, which used age at the 20 20 time of the event), sex, race/ethnicity, US region, and 0 0 year (for annualized rates). For age, P < .001; sex, <40 000 40 000- 75 000- 125 000- >200 000 2014 2015 2016 2017 2018 2019 2020 74 999 124 999 199 999 P < .001; race/ethnicity, P = .002; annual household Year Income range, $ income, P < .001; and year, P = .01. JAMA Network Open. 2021;4(9):e2123471. doi:10.1001/jamanetworkopen.2021.23471 (Reprinted) September 1, 2021 9/17 Hyperglycemic crises per 1000 Hyperglycemic crises per 1000 person-years person-years Hyperglycemic crises per 1000 person-years Hyperglycemic crises per 1000 person-years Hyperglycemic crises per 1000 person-years JAMA Network Open | Diabetes and Endocrinology Factors Associated With Hyperglycemic Crises in Adults With Diabetes in the US, 2014-2020 may have sought to avoid the ED or hospital to minimize COVID-19 exposure or because EDs and hospitals were overwhelmed by caring for patients with COVID-19. Alternatively, patients may have observed improvements in diabetes management in the context of evolving policy changes regarding insulin access and affordability. Further exploration will be needed to examine diabetes management in 2020, particularly among patients with type 1 diabetes, and to assess for changes in insulin use and adherence, glycemic control, and diabetes-related mortality. In the present study, incidence and risk of hyperglycemic crises was disproportionately higher for patients with lower income, a finding supporting the need for policies and systems to ensure 25,26 improved access to affordable glucose-lowering therapies. Building on earlier work in different 27,28 populations, we found that for individuals with type 1 diabetes, the adjusted rate of hyperglycemic crises was 101.52 events per 1000 person-years among patients with low income (<$40 000) compared with 26.25 events per 1000 person-years among patients with high income ($200 000). Income-based disparities in hyperglycemic crisis risk were also detected among patients with type 2 diabetes: 5.78 vs 2.23 per 1000 person-years, respectively. The association of an inability to afford insulin with increased risk of DKA has been observed for decades. Increasing 26,30,31 costs of insulin are associated with an increased prevalence of undertreatment of patients 32 33 with lower incomes and insulin rationing, which may lead to severe and uncontrolled hyperglycemia as a result of inadequate access to the medication that all patients with type 1 diabetes and some with insulin-requiring type 2 diabetes need to live. Although rates of hyperglycemic emergencies may be higher among uninsured patients owing to poor access to 16,34 medical care, healthy food, and housing, many people with employer-sponsored private health Figure 2. Adjusted Rates of Hyperglycemic Crises Among Adults With Type 2 Diabetes Stratified by Age, Sex, Race/Ethnicity, Annual Household Income, Insulin Therapy, and Year A Age B Sex C Race/ethnicity 20 10 10 16 8 8 12 6 6 8 4 4 4 2 2 0 0 0 18-44 45-64 65-74 ≥75 Female Male White Black Hispanic Asian Age range, y Sex Race/ethnicity D Annual household income E Insulin requirement F Year 10 20 10 18 9 8 16 8 14 7 6 12 6 10 5 4 8 4 6 3 2 4 2 2 1 0 0 0 <40 000 40 000- 75 000- 125 000- >200 000 No Basal Bolus ± 2014 2015 2016 2017 2018 2019 2020 74 999 124 999 199 999 insulin insulin basal Year only insulin Income range, $ Insulin regimen All rates are adjusted for age (age at index for all analyses except for annual rates, which used age at the time of the event), sex, race/ethnicity, US region, and year (for annualized rates). For age, P < .001; sex, P < .001; race/ethnicity, P < .001; annual household income, P < .001; insulin requirement, P < .001; and year, P = .16. JAMA Network Open. 2021;4(9):e2123471. doi:10.1001/jamanetworkopen.2021.23471 (Reprinted) September 1, 2021 10/17 Hyperglycemic crises per 1000 Hyperglycemic crises per 1000 person-years person-years Hyperglycemic crises per 1000 person-years Hyperglycemic crises per 1000 person-years Hyperglycemic crises per 1000 person-years Hyperglycemic crises per 1000 person-years JAMA Network Open | Diabetes and Endocrinology Factors Associated With Hyperglycemic Crises in Adults With Diabetes in the US, 2014-2020 Table 3. Factors Associated With Hyperglycemic Crises Among Adults With Type 1 or Type 2 Diabetes, 2014-2020 Type 1 diabetes Type 2 diabetes Factor IRR (95% CI) P value IRR (95% CI) P value Age, y 18-44 1 [Reference] NA 1 [Reference] NA 45-64 0.72 (0.59-0.87) .001 0.57 (0.51-0.63) <.001 65-74 0.62 (0.47-0.80) <.001 0.44 (0.39-0.49) <.001 ≥75 0.96 (0.66-1.38) .82 0.41 (0.36-0.47) <.001 Sex Female 1 [Reference] NA 1 [Reference] NA Male 0.75 (0.65-0.87) <.001 1.00 (0.94-1.07) .94 Race/ethnicity White 1 [Reference] NA 1 [Reference] NA Black 1.33 (1.01-1.74) .04 1.18 (1.09-1.27) <.001 Hispanic 0.88 (0.70-1.11) .28 0.69 (0.62-0.75) <.001 Asian 1.15 (0.73-1.80) .55 0.64 (0.51-0.80) <.001 Other/unknown 1.07 (0.79-1.44) .68 0.87 (0.73-1.03) .10 US census region Midwest 1 [Reference] NA 1 [Reference] NA Northeast 0.71 (0.56-0.90) .004 0.92 (0.82-1.03) .14 South 0.94 (0.78-1.12) .47 1.01 (0.93-1.09) .90 West/unknown 0.99 (0.78-1.25) .90 1.00 (0.88-1.13) .94 Annual household income, $ <40 000 1 [Reference] NA 1 [Reference] NA 40 000-74 999 0.85 (0.68-1.06) .15 0.84 (0.78-0.91) <.001 75 000-124 999 0.92 (0.73-1.17) .51 0.73 (0.66-0.80) <.001 125 000-199 999 0.71 (0.54-0.92) .009 0.57 (0.49-0.66) <.001 ≥200 000 0.61 (0.46-0.81) .001 0.69 (0.56-0.86) .001 Unknown 0.98 (0.72-1.35) .91 1.01 (0.88-1.16) .87 Index year 2014 1 [Reference] NA 1 [Reference] NA 2015 0.86 (0.69-1.07) .18 0.92 (0.84-1.01) .09 2016 1.22 (0.94-1.59) .13 0.93 (0.83-1.03) .16 2017 1.08 (0.86-1.37) .50 0.98 (0.89-1.08) .66 2018 1.05 (0.85-1.31) .66 0.99 (0.89-1.09) .81 2019 1.04 (0.82-1.31) .76 1.04 (0.93-1.17) .49 Comorbidity Hyperglycemic crisis 7.88 (6.06-9.99) <.001 17.51 (15.07-20.34) <.001 Severe hypoglycemia 2.77 (2.15-3.56) <.001 4.18 (3.58-4.87) <.001 Retinopathy 0.92 (0.79-1.08) .31 1.27 (1.18-1.38) <.001 Nephropathy 1.22 (1.01-1.48) .04 1.23 (1.14-1.33) <.001 Neuropathy 1.64 (1.39-1.93) <.001 1.25 (1.17-1.34) <.001 Cardiovascular disease 1.22 (0.97-1.53) .09 0.93 (0.87-1.01) .08 Cerebrovascular disease 1.04 (0.81-1.34) .77 1.18 (1.07-1.30) .001 Peripheral vascular disease 1.18 (0.92-1.51) .20 1.09 (1.00-1.18) .05 Heart failure 0.88 (0.64-1.22) .45 1.14 (1.03-1.25) .01 Dementia 1.50 (0.89-2.52) .13 1.49 (1.27-1.75) <.001 Hypertension 0.93 (0.79-1.10) .39 0.83 (0.76-0.91) <.001 Depression 1.62 (1.37-1.92) <.001 1.46 (1.34-1.59) <.001 COPD 1.03 (0.79-1.34) .85 1.11 (1.02-1.21) .02 Cancer 1.09 (0.77-1.53) .63 1.15 (1.03-1.28) .01 Cirrhosis 1.09 (0.51-2.37) .82 1.72 (1.36-2.18) <.001 (continued) JAMA Network Open. 2021;4(9):e2123471. doi:10.1001/jamanetworkopen.2021.23471 (Reprinted) September 1, 2021 11/17 JAMA Network Open | Diabetes and Endocrinology Factors Associated With Hyperglycemic Crises in Adults With Diabetes in the US, 2014-2020 Table 3. Factors Associated With Hyperglycemic Crises Among Adults With Type 1 or Type 2 Diabetes, 2014-2020 (continued) Type 1 diabetes Type 2 diabetes Factor IRR (95% CI) P value IRR (95% CI) P value Hemoglobin A % 1c, ≤5.6 0.56 (0.27-1.14) .11 0.56 (0.43-0.73) <.001 5.7-6.4 0.99 (0.58-1.68) .96 0.67 (0.58-0.77) <.001 6.5-6.9 1 [Reference] NA 1 [Reference] NA 7.0-7.9 1.63 (1.20-2.22) .002 1.48 (1.31-1.67) <.001 8.0-8.9 2.11 (1.55-2.86) <.001 2.61 (2.30-2.96) <.001 9.0-9.9 3.57 (2.61-4.89) <.001 3.72 (3.25-4.27) <.001 ≥10 7.81 (5.78-10.54) <.001 7.06 (6.26-7.96) <.001 Type 1 diabetes management Insulin only 1 [Reference] NA NA NA No medications 1.05 (0.80-1.38) .72 NA NA Any noninsulin medication 0.65 (0.49-0.87) .003 NA NA Type 2 diabetes management No medications NA NA 1.10 (0.98-1.23) .09 Insulin use Bolus with or without basal NA NA 1 [Reference] NA Basal only NA NA 0.69 (0.63-0.75) <.001 Not treated with insulin NA NA 0.36 (0.33-0.40) <.001 Noninsulin medication Abbreviations: COPD, chronic obstructive pulmonary Metformin NA NA 0.72 (0.67-0.78) <.001 disease; DPP-4, dipeptidyl peptidase 4; GLP-1, Sulfonylurea NA NA 0.90 (0.84-0.98) .01 glucagon-like peptide 1; IRR, incidence risk ratio; NA, not applicable; SGLT2, sodium-glucose SGLT2 inhibitor NA NA 1.30 (1.14-1.49) <.001 cotransporter 2. GLP-1 receptor agonist NA NA 0.77 (0.67-0.87) <.001 SI conversion factor: To convert hemoglobin A to 1c DPP-4 inhibitor NA NA 0.87 (0.79-0.96) .006 proportion of total hemoglobin, multiply by 0.01. Thiazolidinedione NA NA 1.12 (0.96-1.31) .15 Other is a racial/ethnicity choice in the OptumLabs Other NA NA 0.86 (0.64-1.15) .30 Data Warehouse database. plans have high deductibles and out-of-pocket cost-sharing expenses, which may be associated 36 37 with financial distress and greater likelihood of forgoing necessary medical care. Young patients 34,38 may be particularly susceptible to financial instability and underinsurance, which may be 21,34,39,40 associated with poor glycemic control, inadequate ambulatory care, and ultimately, higher rates of hyperglycemic crises, like those observed in our study. Thus, multidisciplinary teams should anticipate these barriers to care, develop care plans that are affordable and accessible, and help patients navigate available support programs. We believe that greater attention should be given to addressing racial/ethnic disparities in diabetes management. Black patients with type 1 diabetes or with type 2 diabetes had higher risks of hyperglycemic crises than individuals in the other racial/ethnic groups included in the study. This disparity persisted after adjustment for key socioeconomic, clinical, and treatment-related factors, suggesting that additional intrinsic and extrinsic factors are associated with hyperglycemic crises among Black patients. Black patients may be more likely to experience DKA in the context of ketosis- 41-43 prone type 2 diabetes, which is more prevalent among Black patients. In addition to biological risk factors, increased DKA and HHS risk among Black patients may be associated with unmeasured social determinants of health and manifestations of structural racism both within and outside health care. Black patients with type 2 diabetes are more likely than White patients to be undertreated, and undertreated patients are more likely to experience hyperglycemic crises than patients who 32 45 were treated appropriately. Black patients are also more likely to be cared for by clinicians and health systems that deliver lower-quality care or have fewer resources available to optimally care for their patients, which may contribute to worse health outcomes. Furthermore, Black patients 47 48-50 are more likely to reside in less walkable neighborhoods with fewer healthy food options, JAMA Network Open. 2021;4(9):e2123471. doi:10.1001/jamanetworkopen.2021.23471 (Reprinted) September 1, 2021 12/17 JAMA Network Open | Diabetes and Endocrinology Factors Associated With Hyperglycemic Crises in Adults With Diabetes in the US, 2014-2020 which may be associated with worse glycemic control. Thus, additional research is needed to understand the multiplicity of factors contributing to the undertreatment of Black patients with diabetes, barriers to managing their diabetes, and their increased risk of hyperglycemic crises. Poorly controlled diabetes was another factor associated with hyperglycemic crises. For patients with type 1 diabetes, risk of experiencing a hyperglycemic crisis increased when the HbA 1c level exceeded 7%, and the IRR was 7.81 (95% CI, 5.78-10.54) for HbA levels of 10% or higher 1c compared with HbA levels of 6.5% to 6.9%. For patients with type 2 diabetes, the risk increased 1c continuously for all HbA levels above 5.6%, and the IRR was 7.06 (95% CI, 6.26-7.96) for HbA 1c 1c levels of 10% or higher. This association of HbA level with increased risk of hyperglycemic 1c emergencies overlooks the importance of real-time glycemic variability that would be captured by self-monitoring or continuous glucose monitoring. The importance of glycemic variability is underscored by the finding that severe hypoglycemia was associated with a 3- to 4-fold increase in the risk of experiencing a hyperglycemic crisis. Because patients with high HbA levels also 1c frequently experience severe hypoglycemia, an elevated HbA level is a signal of susceptibility to 1c both hyperglycemic and hypoglycemic crises. Strengths and Limitations This study is strengthened by the ability to examine patient- and treatment-level factors associated with hyperglycemic crises at the population level using longitudinal analysis and is not limited to a single health care system. The present study also provides, to our knowledge, the most contemporary epidemiological data on DKA and HHS through the end of 2020, including during the COVID-19 pandemic in the US. This study also has limitations. First, this observational analysis was designed to examine the epidemiological features of and factors associated with hyperglycemic crises, not to establish a causal relationship between any factor(s) and these events. The classification scheme for type of diabetes and the adjudication of events as being DKA or HHS may not be accurate because both determinations were limited by data available in the claims database. Because all patients had established diabetes, we did not capture instances of newly diagnosed diabetes in patients presenting with DKA (particularly of interest in the context of COVID-19) or assess the impact of lapsed insurance. Our data also did not allow us to examine the factors leading up to and precipitating 2,34 hyperglycemic events, such as medication nonadherence or acute illness. However, our objectives were to characterize the frequency of hyperglycemic crises among adults with type 1 diabetes or with type 2 diabetes in the US and to identify patient- and treatment-related factors associated with these events. These epidemiologic data are necessary to inform targeted interventions at multiple levels to prevent hyperglycemic crises among individuals at highest risk of these conditions. Conclusions In this cohort study, younger age, Black race/ethnicity, low income, and poor glycemic control were associated with an increased risk of hyperglycemic crises. The findings suggest that efforts are needed to facilitate engagement of these groups with the health care system, assess and address potential barriers—financial, logistical, psychosocial, or medical—to optimal control of patients’ blood 15,51 glucose levels, and provide referral for diabetes self-management education and support. Health care delivery systems should incorporate educational, clinical, and social support systems into clinical practice, and payers should consider expanding reimbursement for self-management education and social services as well as more comprehensive coverage for glucose-lowering medications, insulin, and glucose-monitoring technologies. JAMA Network Open. 2021;4(9):e2123471. doi:10.1001/jamanetworkopen.2021.23471 (Reprinted) September 1, 2021 13/17 JAMA Network Open | Diabetes and Endocrinology Factors Associated With Hyperglycemic Crises in Adults With Diabetes in the US, 2014-2020 ARTICLE INFORMATION Accepted for Publication: June 29, 2021. Published: September 1, 2021. doi:10.1001/jamanetworkopen.2021.23471 Open Access: This is an open access article distributed under the terms of the CC-BY License.©2021McCoyRG et al. JAMA Network Open. Corresponding Author: Rozalina G. McCoy, MD, MS, Division of Community Internal Medicine, Department of Medicine, Mayo Clinic, 200 First St SW, Rochester, MN 55905 (mccoy.rozalina@mayo.edu). Author Affiliations: Division of Community Internal Medicine, Department of Medicine, Mayo Clinic, Rochester, Minnesota (McCoy); Mayo Clinic Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Rochester, Minnesota (McCoy, Swarna, Van Houten, Shah); Division of Endocrinology, Department of Medicine, Emory University School of Medicine, Grady Memorial Hospital, Atlanta, Georgia (Galindo, Umpierrez); HealthPartners Institute Center for Chronic Care Innovation, Minneapolis, Minnesota (Van Houten, O’Connor); OptumLabs, Eden Prairie, Minnesota (Shah). Author Contributions: Dr McCoy had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Concept and design: McCoy, Galindo, Van Houten, O’Connor, Umpierrez. Acquisition, analysis, or interpretation of data: McCoy, Galindo, Swarna, Van Houten, O’Connor, Shah. Drafting of the manuscript: McCoy, Galindo, Van Houten. Critical revision of the manuscript for important intellectual content: Galindo, Swarna, Van Houten, O’Connor, Umpierrez, Shah. Statistical analysis: Swarna, Van Houten. Obtained funding: McCoy. Administrative, technical, or material support: Galindo, O’Connor, Shah. Supervision: McCoy, O’Connor. Conflict of Interest Disclosures: Dr McCoy reported receiving an AARP Quality Measure Innovation Grant from the AARP and grants from the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) and the Mayo Clinic outside the submitted work. Dr Galindo reported receiving grants from the NIDDK and Novo Nordisk and Dexcom (to Emory University) and receiving personal fees from Abbott Diabetes Care, Eli Lilly and Company, Novo Nordisk, Sanofi, and Valeritas. Dr O’Connor reported receiving grants from the National Heart, Lung and Blood Institute, the NIDDK, the Patient Centered Outcomes Research Institute, the National Cancer Institute, and the National Institute on Drug Abuse. Dr Umpierrez reported receiving grants from the National Center for Advancing Translational Sciences and receiving unrestricted research support from AstraZeneca, Novo Nordisk, and Dexcom (to Emory University). Dr Shah reported receiving research support (through Mayo Clinic) from the US Food and Drug Administration and the Centers of Medicare and Medicaid Innovation and receiving grants from the Agency for Healthcare Research and Quality, the National Heart, Lung and Blood Institute, the National Science Foundation, and the Patient Centered Outcomes Research Institute. No other disclosures were reported. Funding/Support: This work was funded by grant K23DK114497 from the NIDDK (Dr McCoy). Role of the Funder/Sponsor: The study sponsor had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. Disclaimer: Dr McCoy affirms that the article is an honest, accurate, and transparent account of the study being reported; that no important aspects of the study have been omitted; and that any discrepancies from the study as planned have been explained. Study contents are the sole responsibility of the authors and do not necessarily represent the official views of the National Institutes of Health. Meeting Presentation: This paper was presented at the virtual meeting of the American Diabetes Association Scientific Sessions; June 25-29, 2021. REFERENCES 1. Centers for Disease Control and Prevention. National Diabetes Statistics Report, 2020. 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Wexler DJ, Beauharnais CC, Regan S, Nathan DM, Cagliero E, Larkin ME. Impact of inpatient diabetes management, education, and improved discharge transition on glycemic control 12 months after discharge. Diabetes Res Clin Pract. 2012;98(2):249-256. doi:10.1016/j.diabres.2012.09.016 SUPPLEMENT. eTable 1. Code Sets for Included Health Conditions eTable 2. Classification Scheme for Glucose-Lowering Medications eTable 3. Patients With Type 2 Diabetes eTable 4. Crude and Adjusted Rates of Hyperglycemic Crises Among Patients With Type 1 and Type 2 Diabetes, 2014-2020 eTable 5. Crude and Adjusted Rates of Hyperglycemic Crises Among Patients With Type 1 Diabetes by Prespecified Subgroup, 2014-2020 eTable 6. Crude and Adjusted Rates of Hyperglycemic Crises Among Patients With Type 2 Diabetes by Prespecified Subgroup, 2014-2020 eTable 7. Risk Factors for DKA and HHS (Examined as Independent Outcomes) Among Adults With Type 2 Diabetes, 2014-2020 JAMA Network Open. 2021;4(9):e2123471. doi:10.1001/jamanetworkopen.2021.23471 (Reprinted) September 1, 2021 17/17 Supplementary Online Content McCoy RG, Galindo RJ, Swarna KS, et al. Sociodemographic, clinical, and treatment- related factors associated with hyperglycemic crises among adults with type 1 or type 2 diabetes in the US from 2014 to 2020. JAMA Netw Open. 2021;4(9):e2123471. doi:10.1001/jamanetworkopen.2021.23471 eTable 1. Code Sets for Included Health Conditions eTable 2. Classification Scheme for Glucose-Lowering Medications eTable 3. Patients With Type 2 Diabetes eTable 4. Crude and Adjusted Rates of Hyperglycemic Crises Among Patients With Type 1 and Type 2 Diabetes, 2014-2020 eTable 5. Crude and Adjusted Rates of Hyperglycemic Crises Among Patients With Type 1 Diabetes by Prespecified Subgroup, 2014-2020 eTable 6. Crude and Adjusted Rates of Hyperglycemic Crises Among Patients With Type 2 Diabetes by Prespecified Subgroup, 2014-2020 eTable 7. Risk Factors for DKA and HHS (Examined as Independent Outcomes) Among Adults With Type 2 Diabetes, 2014-2020 This supplementary material has been provided by the authors to give readers additional information about their work. © 2021 McCoy RG et al. JAMA Network Open. eTable 1. Code Sets for Included Health Conditions. All conditions were ascertained during the baseline 12 months preceding the index date for cohort entry Comorbidity ICD-9 Codes ICD-10 codes Included code types Cancer (except 14x.xx, 15x.xx, 160.x-165.x, C00.x-C14.x, C15.x-C26.x, All claims non-melanoma 170.x-172.x, 174.x-176.x, C3x.xx, C40.xx-C41.x, C43.x, Codes in all skin cancer) 179-189.x, 190.x-195.x, C4A.xx, C45.x-C49.xx, C50.xxx, positions 199.xx-208.xx (except C51.x-C58, C60.x-C63.x, C64.x- 203.x1, 204.x1, 205.x1, C68.x, C69.xx-C72.x, C73- 206.x1, 207.x1, 208.x1) C76.x, C7A.xx, C80.xx-C96.x (except C90.x1, C91.x1, C92.x1, C93.x1, C94.x1, C95.x1) Cardiovascular 410.x, 411.x, 412, 413.x, I20.x, I21.x, I22.x, I23.x, I24.x, All claims disease 414.x, 427.1, 427.3x, I25.x, I46.x, I47.x, I48.x, I49.x, Codes in all 427.4x, 427.5, 429.2, 440.x, I70.x, I71.x positions 441.x Cerebrovascular 430, 431, 432.x, 433.xx, G45.0, G45.1, G45.2, G45.8, All claims disease 434.xx 435.x, 436, 437.x, G45.9, G46.x, I60.xx, I61.x Codes in all 438.xx, V12.54 (except I61.0), I62.xx, I63.xxx, positions I65.xx, I66.xx, I67.8x (except I67.83, I67.84), I67.9, I69.xxx, Z86.73 Chronic 490, 491.xx, 492.x, 494.x, J40, J41.x, J42, J43.x, J44.x, All claims obstructive 496 J47.x Codes in all pulmonary positions disease Cirrhosis 571.2, 571.5, 571.6 K70.3x, K74.3, K74.4, K74.5, All claims K74.6x Codes in all positions Dementia 046.1x, 290.1x, 290.2x, A81.0x, F01.5x, F02.8x, F03.9x, All claims 290.3, 290.4x, 291.2, F10.27, F10.97, F13.27, F13.97, Codes in all 292.82, 294.1x, 294.2x, F18.97, F19.17, F19.27, F19.97, positions 331.0, 331.1x, 331.2, 331.6, G30.x, G31.0x, G31.1, G31.83, 331.82, 331.89 G31.85 Depression 290.13, 290.21, 290.43, F01.51, F32.x (except F32.81), All claims 296.2x, 296.3x, 296.82, F33.x, F34.8x, F43.21, F43.23 Codes in all 298.0, 301.12, 309.0, 309.1, positions 309.28, 311 DKA 250.10, 250.11, 250.12, E10.10, E10.11, E11.10, E11.11, Hospital and 250.13 E13.10, E13.11 ED claims st Codes in 1 position HHS 250.20, 250.21, 250.22, E11.00, E11.01, E13.00, E13.01 Hospital and 250.23 ED claims st Codes in 1 position Heart failure 398.91, 402.01, 402.11, I09.81, I11.0, I13.0, I13.2, I50.xx All claims 402.91, 404.01, 404.03, Codes in all 404.11, 404.13, 404.91, positions 404.93, 428.xx Hypoglycemia 251.0, 251.1, 251.2, 962.3, E10.641, E10.649, E11.641, Hospital and 250.8x (for 250.8x: if no E11.649, E13.641, E13.649, ED claims st concurrent 259.8, 272.7, E16.0, E16.1, E16.2, T38.3X1A, Codes in 1 681.xx, 682.xx, 686.9x, T38.3X1D, T38.3X1S, position © 2021 McCoy RG et al. JAMA Network Open. Comorbidity ICD-9 Codes ICD-10 codes Included code types 707.1x-707.2x, 707.8, T38.3X2A, T38.3X2D, 707.9, 709.3, 730.0x- T38.3X2S, T38.3X3A, 730.2x, 731.8) T38.3X3D, T38.3X3S, T38.3X4A, T383X4D, T38.3X4S, T38.3X5A, T383X5D, T38.3X5S Hypertension 401.x, 402.x, 403.x, 404.x, I11.x, I12.x, I13.x, I15.x, I16.x, All claims 405.x I10 Codes in all positions Nephropathy 593.9, 586, 250.4x, 249.4x, E08.21, E08.22, E08.29, E09.21, All claims 580.x, 581.x, 582.x, 583.x, E09.22, E09.29, E10.21, E10.22, Codes in all 585.x E10.29, E11.21, E11.22, E11.29, positions E13.21, E13.22, E13.29, N19, N00.x, N03.x, N04.x, N05.x, N18.x Neuropathy 357.2, 337.1, 356.9, 358.1, G90.09, G90.8, G90.9, G99.0, All claims 458.0, 536.3, 564.5, 596.54, G60.9, G73.3, G90.01, I95.1, Codes in all 713.5, 951.0, 951.1, 951.3, K31.84, K59.1, N31.9, E08.4x, positions 250.6x, 249.6x, 337.0x, E09.4x, E10.4x, E11.4x, E13.4x, 354.x, 355.x G56.x, G57.x, H49.x, M14.6x, S04.x Peripheral 442.3, 440.21, 443.81, E08.51, E09.51, E10.51, E11.51, All claims vascular disease 443.9, 892.1, 040.0, 444.22, E13.51, E08.59, E09.59, E10.59, Codes in all 785.4, 250.7x, 249.7, E11.59, E13.59, E08.621, positions 707.1x E09.621, E10.621, E11.621, E13.621, I72.4, I73.89, I73.9, A48.0, I74.3, I96, E08.52, E09.52, E10.52, E11.52, E13.52, I70.21x, S91.3x, L97.x Retinopathy 362.01, 362.03, 362.04, H35.9, E08.3x, E09.3x, E10.3x, All claims 362.05, 362.06, 362.07, E11.3x, E13.3x, H35.0x, Codes in all 362.53, 362.81, 362.82, H35.35x, H35.6x, H35.8x, H33.x, positions 362.83, 362.02, 379.23, H54.x, H43.1x 250.5x, 249.5x, 362.1x, 361.x, 369.x Abbreviations: DKA, diabetic ketoacidosis; ED, emergency department; HHS, hyperglycemic hyperosmolar state. © 2021 McCoy RG et al. JAMA Network Open. eTable 2. Classification Scheme for Glucose-Lowering Medications Medication class Included agents Insulin: Basal NPH/isophane Determir Glargine Degludec Insulin: Bolus Regular Aspart Lispro Glulisine Inhaled powder insulin Sulfonylureas Glimepiride Glipizide Glyburide Biguanides Metformin GLP-1 receptor agonists Exenatide Liraglutide Albiglutide Dulaglutide Lixisenatide Semaglutide SGLT2 inhibitors Canagliflozin Empagliflozin Dapagliflozin Ertugliflozin DPP-4 inhibitors Sitagliptin Saxagliptin Linagliptin Alogliptin Glitazones Pioglitazone Rosiglitazone Glinides Nateglinide Repaglinide Amylin analogs Pramlintide -Glucosidase inhibitors Acarbose Miglitol © 2021 McCoy RG et al. JAMA Network Open. eTable 3. Patients With Type 2 Diabetes. Baseline sociodemographic, clinical, and diabetes treatment characteristics of included adults with type 2 diabetes, overall and subset by whether they experienced at least one episode of hyperglycemic crisis during the follow-up period. There were 4,264 patients who experienced at least one episode of DKA and 202 patients who experienced at least one episode of DKA and at le ast one episode of HHS during the observation period. Because of the small sample size of patients who experienced both DKA and HHS events, and our inability to present sample sizes smaller than 11 (as would be the case in many cells for this small group), the group with both types of events was combined with the group experiencing DKA only. Total No DKA/HHS DKA ± HHS HHS p-value Number of patients 796,382 790,587 4,466 1,329 Sociodemographic variables Age, years, mean (SD) 65.63 (11.79) 65.66 (11.78) 60.54 (13.95) 66.81 (11.53) <0.001 Age, N (%) <0.001 18-44 years 42,356 (5.32%) 41,717 (5.28%) 585 (13.10%) 54 (4.06%) 45-64 years 281,738 (35.38%) 279,406 (35.34%) 1,902 (42.59%) 430 (32.36%) 65-74 years 286,441 (35.97%) 284,676 (36.01%) 1,275 (28.55%) 490 (36.87%) 185,847 (23.34%) 184,788 (23.37%) 704 (15.76%) 355 (26.71%) Sex, N (%) Female 400,346 (50.27%) 397,272 (50.25%) 2,380 (53.29%) 694 (52.22%) Male 396,036 (49.73%) 393,315 (49.75%) 2,086 (46.71%) 635 (47.78%) Race/ethnicity, N (%) <0.001 White 433,623 (54.45%) 430,499 (54.45%) 2,502 (56.02%) 622 (46.80%) Black 141,999 (17.83%) 140,476 (17.77%) 1,088 (24.36%) 435 (32.73%) Hispanic 133,664 (16.78%) 132,901 (16.81%) 592 (13.26%) 171 (12.87%) Asian 40,971 (5.14%) 40,836 (5.17%) 93 (2.08%) 42 (3.16%) Other/unknown 46,125 (5.79%) 45,875 (5.80%) 191 (4.28%) 59 (4.44%) Annual household income, N (%) <0.001 <$40,000 243,621 (30.59%) 241,339 (30.53%) 1,647 (36.88%) 635 (47.78%) $40,000-$74,999 222,612 (27.95%) 220,975 (27.95%) 1,284 (28.75%) 353 (26.56%) $75,000-$124,999 171,737 (21.56%) 170,747 (21.60%) 815 (18.25%) 175 (13.17%) $125,000-$199,999 64,332 (8.08%) 64,057 (8.10%) 239 (5.35%) 36 (2.71%) 28,576 (3.59%) 28,449 (3.60%) 108 (2.42%) 19 (1.43%) Unknown 65,504 (8.23%) 65,020 (8.22%) 373 (8.35%) 111 (8.35%) Index year, N (%) <0.001 2014 152,519 (19.15%) 151,000 (19.10%) 1,193 (26.71%) 326 (24.53%) 2015 117,351 (14.74%) 116,318 (14.71%) 788 (17.64%) 245 (18.43%) 2016 104,538 (13.13%) 103,777 (13.13%) 603 (13.50%) 158 (11.89%) 2017 137,597 (17.28%) 136,555 (17.27%) 767 (17.17%) 275 (20.69%) 2018 142,231 (17.86%) 141,433 (17.89%) 619 (13.86%) 179 (13.47%) 2019 142,146 (17.85%) 141,504 (17.90%) 496 (11.11%) 146 (10.99%) © 2021 McCoy RG et al. JAMA Network Open. a Total No DKA/HHS DKA ± HHS HHS p-value U.S. census region, N (%) <0.001 Midwest 144,126 (18.10%) 143,046 (18.09%) 829 (18.56%) 251 (18.89%) Northeast 120,946 (15.19%) 120,193 (15.20%) 538 (12.05%) 215 (16.18%) South 446,286 (56.04%) 442,879 (56.02%) 2,643 (59.18%) 764 (57.49%) West/unknown 85,024 (10.68%) 84,469 (10.68%) 456 (10.21%) 99 (7.45%) Clinical variables Comorbidities, N (%) Hyperglycemic crisis 2,646 (0.33%) 2,063 (0.26%) 510 (11.42%) 73 (5.49%) <0.001 Severe hypoglycemia 6,727 (0.84%) 6,342 (0.80%) 305 (6.83%) 80 (6.02%) <0.001 Retinopathy 123,148 (15.46%) 121,733 (15.40%) 1,093 (24.47%) 322 (24.23%) <0.001 Neuropathy 218,245 (27.40%) 215,790 (27.29%) 1,883 (42.16%) 572 (43.04%) <0.001 Nephropathy 186,900 (23.47%) 184,944 (23.39%) 1,382 (30.94%) 574 (43.19%) <0.001 Cardiovascular disease 259,985 (32.65%) 257,875 (32.62%) 1,527 (34.19%) 583 (43.87%) <0.001 Cerebrovascular disease 92,517 (11.62%) 91,584 (11.58%) 643 (14.40%) 290 (21.82%) <0.001 Peripheral vascular disease 132,101 (16.59%) 130,770 (16.54%) 960 (21.50%) 371 (27.92%) <0.001 Heart failure 85,846 (10.78%) 84,889 (10.74%) 636 (14.24%) 321 (24.15%) <0.001 Dementia 24,052 (3.02%) 23,788 (3.01%) 176 (3.94%) 88 (6.62%) <0.001 Hypertension 686,124 (86.16%) 681,196 (86.16%) 3,680 (82.40%) 1,248 (93.91%) <0.001 Depression 99,487 (12.49%) 98,313 (12.44%) 918 (20.56%) 256 (19.26%) <0.001 COPD 114,033 (14.32%) 112,987 (14.29%) 727 (16.28%) 319 (24.00%) <0.001 Cancer 71,797 (9.02%) 71,287 (9.02%) 365 (8.17%) 145 (10.91%) 0.008 Cirrhosis 8,952 (1.12%) 8,834 (1.12%) 77 (1.72%) 41 (3.09%) <0.001 Treatment variables Hemoglobin A , %, mean (SD) 7.36 (1.63) 7.34 (1.61) 9.37 (2.33) 8.91 (2.42) <0.001 1c Hemoglobin A , N (%) <0.001 1c 46,822 (5.88%) 46,736 (5.91%) 57 (1.28%) 29 (2.18%) 5.7% 6.4% 217,748 (27.34%) 217,308 (27.49%) 288 (6.45%) 152 (11.44%) 6.5% 6.9% 144,631 (18.16%) 144,177 (18.24%) 317 (7.10%) 137 (10.31%) 7.0% 7.9% 182,928 (22.97%) 181,943 (23.01%) 729 (16.32%) 256 (19.26%) 8.0% 8.9% 90,804 (11.40%) 89,817 (11.36%) 800 (17.91%) 187 (14.07%) 9.0% 9.9% 49,029 (6.16%) 48,185 (6.09%) 677 (15.16%) 167 (12.57%) 64,420 (8.09%) 62,421 (7.90%) 1,598 (35.78%) 401 (30.17%) Fills for glucose-lowering medication in the 120 days prior to index date No fills 184,079 (23.11%) 183,138 (23.16%) 709 (15.88%) 232 (17.46%) Insulin fills, N (%) <0.001 Not treated with insulin 632,323 (79.40%) 629,706 (79.65%) 1,924 (43.08%) 693 (52.14%) Basal only (no bolus) 89,977 (11.30%) 88,724 (11.22%) 958 (21.45%) 295 (22.20%) © 2021 McCoy RG et al. JAMA Network Open. a Total No DKA/HHS DKA ± HHS HHS p-value Bolus (± basal) 74,082 (9.30%) 72,157 (9.13%) 1,584 (35.47%) 341 (25.66%) Non-insulin glucose-lowering medications, N (%) Sulfonylurea 203,122 (25.51%) 201,852 (25.53%) 930 (20.82%) 340 (25.58%) <0.001 Metformin 429,036 (53.87%) 426,884 (54.00%) 1,641 (36.74%) 511 (38.45%) <0.001 SGLT2 inhibitor 40,247 (5.05%) 39,933 (5.05%) 280 (6.27%) 34 (2.56%) <0.001 GLP-1 receptor agonist 45,950 (5.77%) 45,632 (5.77%) 248 (5.55%) 70 (5.27%) 0.60 DPP-4 inhibitor 96,962 (12.18%) 96,377 (12.19%) 426 (9.54%) 159 (11.96%) <0.001 Thiazolidinedione 38,668 (4.86%) 38,439 (4.86%) 182 (4.08%) 47 (3.54%) 0.004 Other glucose-lowering medication 7,685 (0.96%) 7,629 (0.96%) 41 (0.92%) 15 (1.13%) 0.79 Abbreviations: COPD, chronic obstructive pulmonary disease; DKA, diabetic ketoacidosis; HHS, hyperglycemic hyperosmolar state. © 2021 McCoy RG et al. JAMA Network Open. eTable 4. Crude and Adjusted Rates of Hyperglycemic Crises Among Patients With Type 1 and Type 2 Diabetes, 2014-2020. Rates adjusted for age (during event), sex, race/ethnicity, U.S. region, and year. Year Type 1 Diabetes Type 2 Diabetes Crude Adjusted Crude Adjusted N per 1000 PY N per 1000 PY N per 1000 PY N per 1000 PY 2014 41.75 43.30 (33.37, 53.24) 4.79 4.27 (3.66, 4.88) 2015 47.3 49.07 (40.24, 57.91) 4.00 3.77 (3.40, 4.13) 2016 48.14 49.80 (42.59, 57.01) 3.96 3.81 (3.46, 4.15) 2017 51.26 53.92 (44.62, 63.21) 3.89 3.95 (3.64, 4.25) 2018 53.43 56.77 (48.45, 65.10) 3.81 4.02 (3.76, 4.29) 2019 60.14 61.36 (52.90, 69.82) 3.96 4.29 (4.02, 4.56) 2020 43.52 46.27 (38.59, 53.95) 3.73 4.12 (3.86, 4.38) Total 50.62 52.69 (48.26, 57.12) 3.70 4.04 (3.88, 4.21) Abbreviations: DKA, diabetic ketoacidosis; HHS, hyperglycemic hyperosmolar state; PY, person-years © 2021 McCoy RG et al. JAMA Network Open. eTable 5. Crude and Adjusted Rates of Hyperglycemic Crises Among Patients With Type 1 Diabetes by Prespecified Subgroup, 2014-2020. These data were used to create Figure 1 in the manuscript. Rates adjusted for age (at index date), sex, race/ethnicity, U.S. region. Crude Adjusted N per 1000 PY N per 1000 PY Age group 18 - 44 years 66.27 77.57 (68.41, 86.72) 45 - 64 years 39.19 43.54 (36.98, 50.09) 65 - 74 years 36.68 38.82 (28.36, 49.27) 45.60 55.64 (38.13, 73.16) Gender Female 62.06 74.91 (66.07, 83.73) Male 39.57 44.04 (38.59, 49.49) Race/ethnicity White 45.69 53.16 (47.69, 58.63) Black 78.83 96.62 (69.44, 123.81) Hispanic 56.06 58.93 (45.24, 72.61) Asian 60.34 66.07 (31.14, 100.99) Annual household income <$40,000 84.73 101.52 (82.31, 120.73) $40,000-$74,999 55.66 65.04 (54.12, 75.96) $75,000-$124,999 46.06 52.97 (43.94, 62.01) $125,000-$199,999 34.42 36.22 (28.43, 44.01) 25.43 26.25 (19.75, 32.75) Abbreviations: DKA, diabetic ketoacidosis; HHS, hyperglycemic hyperosmolar state; PY, person-years. © 2021 McCoy RG et al. JAMA Network Open. eTable 6. Crude and Adjusted Rates of Hyperglycemic Crises Among Patients With Type 2 Diabetes by Prespecified Subgroup, 2014-2020. These data were used to create Figure 2 in the manuscript. Rates adjusted for age (at index date), sex, race/ethnicity, U.S. region. Crude Adjusted N per 1000 PY N per 1000 PY Age group 18 - 44 years 12.7 13.91 (11.82, 16.00) 45 - 64 years 5.12 5.28 (4.96, 5.60) 65 - 74 years 2.79 2.97 (2.79, 3.14) 2.47 2.70 (2.49, 2.90) Gender Female 4.09 4.55 (4.31, 4.79) Male 3.72 4.04 (3.80, 4.27) Race/ethnicity White 3.73 4.15 (3.93, 4.38) Black 5.80 6.34 (5.87, 6.81) Hispanic 3.21 3.26 (2.91, 3.60) Asian 1.44 1.71 (1.31, 2.11) Annual household income <$40,000 5.04 5.78 (5.40, 6.17) $40,000-$74,999 3.65 4.02 (3.75, 4.29) $75,000-$124,999 3.05 3.11 (2.83, 3.40) $125,000-$199,999 2.20 2.19 (1.80, 2.58) 2.36 2.23 (1.70, 2.79) Insulin regimen No insulin 1.87 2.00 (1.87, 2.08) Basal insulin only 7.79 8.35 (7.69, 9.01) Bolus ± basal insulin 17.3 17.73 (16.53, 18.93) Abbreviations: DKA, diabetic ketoacidosis; HHS, hyperglycemic hyperosmolar state; PY, person-years. © 2021 McCoy RG et al. JAMA Network Open. eTable 7. Risk Factors for DKA and HHS (Examined as Independent Outcomes) Among Adults With Type 2 Diabetes, 2014-2020 DKA HHS IRR (95% CI) P-value IRR (95% CI) P-value Age, years 18-44 Ref Ref 45-64 0.54 (0.48, 0.60) <0.001 0.95 (0.73, 1.24) 0.73 65-74 0.39 (0.34, 0.45) <0.001 0.89 (0.67, 1.17) 0.40 0.35 (0.30, 0.41) <0.001 0.92 (0.69, 1.23) 0.57 Gender Female Ref Ref Male 0.95 (0.89, 1.03) 0.19 1.17 (1.04, 1.31) 0.008 Race/Ethnicity White Black 1.04 (0.95, 1.15) 0.37 1.59 (1.40, 1.81) <0.001 Hispanic 0.65 (0.58, 0.73) <0.001 0.80 (0.67, 0.95) 0.01 Asian 0.55 (0.42, 0.71) <0.001 0.99 (0.69, 1.42) 0.95 Other/unknown 0.82 (0.67, 1.00) 0.05 1.01 (0.73, 1.41) 0.94 U.S. census region Midwest Ref Ref Northeast 0.87 (0.77, 0.99) 0.04 1.07 (0.89, 1.30) 0.46 South 1.04 (0.94, 1.14) 0.44 0.94 (0.82, 1.09) 0.44 West/unknown 1.03 (0.90, 1.19) 0.66 0.88 (0.69, 1.12) 0.29 Annual household income <$40,000 Ref Ref $40,000-$74,999 0.90 (0.83, 0.99) 0.03 0.70 (0.61, 0.81) <0.001 $75,000-$124,999 0.80 (0.72, 0.89) <0.001 0.54 (0.45, 0.64) <0.001 $125,000-$199,999 0.66 (0.56, 0.78) <0.001 0.31 (0.23, 0.44) <0.001 0.78 (0.62, 0.99) 0.04 0.42 (0.26, 0.65) <0.001 Unknown 1.06 (0.91, 1.23) 0.48 0.96 (0.76, 1.20) 0.71 Index year 2014 Ref Ref 2015 0.90 (0.81, 1.00) 0.05 1.03 (0.88, 1.22) 0.70 2016 0.93 (0.82, 1.05) 0.24 0.92 (0.76, 1.11) 0.38 2017 0.92 (0.82, 1.03) 0.15 1.18 (1.01, 1.40) 0.04 2018 1.00 (0.89, 1.13) 0.95 0.96 (0.80, 1.16) 0.68 2019 1.05 (0.92, 1.20) 0.48 1.02 (0.83, 1.26) 0.86 Comorbidities Hyperglycemic Crisis 20.32 (17.31, 23.86) <0.001 7.18 (5.68, 9.06) <0.001 Severe hypoglycemia 4.49 (3.77, 5.35) <0.001 3.26 (2.53, 4.20) <0.001 Retinopathy 1.34 (1.22, 1.47) <0.001 1.01 (0.97, 1.26) 0.15 Nephropathy 1.29 (1.19, 1.40) <0.001 1.19 (1.06, 1.34) 0.004 Neuropathy 1.12 (1.03, 1.23) 0.009 1.59 (1.40, 1.80) <0.0001 Cardiovascular disease 0.92 (0.84, 1.00) 0.05 1.00 (0.88, 1.14) 1.00 Cerebrovascular disease 1.12 (1.00, 1.26) 0.06 1.30 (1.12, 1.50) <0.001 Peripheral vascular disease 1.06 (0.96, 1.16) 0.28 1.13 (0.99, 1.30) 0.08 Heart failure 1.01 (0.90, 1.14) 0.89 1.41 (1.21, 1.65) <0.001 Dementia 1.39 (1.14, 1.70) 0.001 1.57 (1.22, 2.01) <0.001 Hypertension 0.74 (0.67, 0.82) <0.001 1.60 (1.29, 1.98) <0.001 Depression 1.48 (1.34, 1.63) <0.001 1.40 (1.21, 1.62) <0.001 COPD 1.03 (0.93, 1.15) 0.53 1.35 (1.18, 1.55) <0.001 Cancer 1.12 (0.98, 1.27) 0.09 1.22 (1.03, 1.46) 0.02 Cirrhosis 1.47 (1.08, 2.01) 0.02 2.71 (1.96, 3.74) <0.001 © 2021 McCoy RG et al. JAMA Network Open. Hemoglobin A 1c 0.54 (0.39, 0.75) <0.001 0.59 (0.40, 0.87) 0.008 5.7% 6.4% 0.63 (0.53, 0.75) <0.001 0.76 (0.60, 0.96) 0.02 6.5% 6.9% Ref Ref 7.0% 7.9% 1.49 (1.29, 1.72) <0.001 1.47 (1.20, 1.80) <0.001 8.0% 8.9% 2.80 (2.41, 3.24) <0.001 2.06 (1.64, 2.58) <0.001 9.0% 9.9% 3.89 (3.31, 4.56) <0.001 3.12 (2.46, 3.95) 0.008 7.22 (6.27, 8.31) <0.001 6.74 (5.49, 8.27) <0.001 Glucose-lowering therapy No fills 1.16 (1.02, 1.32) 0.02 1.00 (0.82, 1.23) 0.99 Insulin use Bolus ± basal Ref Ref Basal only 0.64 (0.57, 0.71) <0.001 0.92 (0.79, 1.08) 0.32 Not treated with insulin 0.31 (0.28, 0.35) <0.001 0.58 (0.49, 0.69) <0.001 Non-insulin medications Metformin 0.72 (0.66, 0.78) <0.001 0.79 (0.69, 0.90) <0.001 Sulfonylurea 0.88 (0.81, 0.96) 0.006 0.97 (0.84, 1.11) 0.66 SGLT2 inhibitor 1.47 (1.27, 1.70) <0.001 0.65 (0.46, 0.93) 0.02 GLP-1 receptor agonist 0.74 (0.64, 0.85) <0.001 0.94 (0.73, 1.20) 0.59 DPP-4 inhibitor 0.84 (0.75, 0.95) 0.004 0.95 (0.80, 1.14) 0.59 Thiazolidinedione 1.18 (0.99, 1.40) 0.07 0.96 (0.72, 1.28) 0.78 Other 0.85 (0.60, 1.20) 0.35 0.83 (0.49, 1.39) 0.47 Abbreviations: COPD, chronic obstructive pulmonary disease; DKA, diabetic ketoacidosis; HHS, hyperglycemic hyperosmolar state. © 2021 McCoy RG et al. JAMA Network Open. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png JAMA Network Open American Medical Association http://www.deepdyve.com/lp/american-medical-association/sociodemographic-clinical-and-treatment-related-factors-associated-ZYs7QZ1kzM

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DesaiD, MehtaD, MathiasP, MenonG, SchubartUK. Health care utilization and burden of diabetic ketoacidosis in the US over the past decade: a nationwide analysis. Diabetes Care. 2018;41(8):1631-1638. doi:10.2337/dc17-137929773640, DesaiD, MehtaD, MathiasP, MenonG, SchubartUK. Health care utilization and burden of diabetic ketoacidosis in the US over the past decade: a nationwide analysis. Diabetes Care. 2018;41(8):1631-1638. doi:10.2337/dc17-137929773640
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Crude and Adjusted Rates of Hyperglycemic Crises Among Patients With Type 1 Diabetes by Prespecified Subgroup

Publisher: American Medical Association
Copyright: Copyright 2021 McCoy RG et al. JAMA Network Open.
eISSN: 2574-3805
DOI: 10.1001/jamanetworkopen.2021.23471
Publisher site: See Article on Publisher Site

Abstract

Key Points Question What factors are associated IMPORTANCE Hyperglycemic crises (ie, diabetic ketoacidosis [DKA] and hyperglycemic with the occurrence of hyperglycemic hyperosmolar state [HHS]) are life-threatening acute complications of diabetes. Efforts to prevent crises (diabetic ketoacidosis and these events at the population level have been hindered by scarce granular data and difficulty in hyperglycemic hyperosmolar state) identifying individuals at highest risk. among adults with diabetes? Findings In this cohort study of 816 538 OBJECTIVE To assess sociodemographic, clinical, and treatment-related factors associated with adults with diabetes in the US (20 156 hyperglycemic crises in adults with type 1 or type 2 diabetes in the US from 2014 to 2020. adults with type 1 diabetes and 796 382 with type 2 diabetes), younger age, low DESIGN, SETTING, AND PARTICIPANTS This retrospective cohort study analyzed administrative income, Black race/ethnicity, high claims and laboratory results for adults (aged 18 years) with type 1 or type 2 diabetes from the hemoglobin A level, prior OptumLabs Data Warehouse from January 1, 2014, through December 31, 2020. 1c hyperglycemic crises, severe hypoglycemia, depression, neuropathy, MAIN OUTCOMES AND MEASURES Rates of emergency department or hospital visits with a and nephropathy were associated with primary diagnosis of DKA or HHS (adjusted for age, sex, race/ethnicity, and region, and for year when increased risk of hyperglycemic crises in calculating annualized rates) were calculated separately for patients with type 1 diabetes and type 2 both groups. diabetes. The associations of sociodemographic factors (age, sex, race/ethnicity, region, and income), clinical factors (comorbidities), and treatment factors (glucose-lowering medications, Meaning The findings suggest that hemoglobin A ) with DKA or HHS in patients with type 1 or type 2 diabetes were assessed using 1c multidisciplinary interventions focusing negative binomial regression. on groups at high risk of hyperglycemic crises are needed to decrease the RESULTS Among 20 156 adults with type 1 diabetes (mean [SD] age, 46.6 [16.5] years; 51.2% male; incidence and impact of these 72.6% White race/ethnicity) and 796 382 with type 2 diabetes (mean [SD] age, 65.6 [11.8] years; potentially preventable complications of 50.3% female; 54.4% White race/ethnicity), adjusted rates of hyperglycemic crises were 52.69 per diabetes. 1000 person-years (95% CI, 48.26-57.12 per 1000 person-years) for type 1 diabetes and 4.04 per 1000 person-years (95% CI, 3.88-4.21 per 1000 person-years) for type 2 diabetes. In both groups, Supplemental content factors associated with the greatest hyperglycemic crisis risk were low income ($200 000 vs <$40 000: type 1 diabetes incidence risk ratio [IRR], 0.61 [95% CI, 0.46-0.81]; type 2 diabetes IRR, Author affiliations and article information are listed at the end of this article. 0.69 [95% CI, 0.56-0.86]), Black race/ethnicity (vs White race/ethnicity: type 1 diabetes IRR, 1.33 [95% CI, 1.01-1.74]; type 2 diabetes IRR, 1.18 [95% CI, 1.09-1.27]), high hemoglobin A level (10% vs 1c 6.5%-6.9%: type 1 diabetes IRR, 7.81 [95% CI, 5.78-10.54]; type 2 diabetes IRR, 7.06 [95% CI, 6.26-7.96]), history of hyperglycemic crises (type 1 diabetes IRR, 7.88 [95% CI, 6.06-9.99]; type 2 diabetes IRR, 17.51 [95% CI, 15.07-20.34]), severe hypoglycemia (type 1 diabetes IRR, 2.77 [95% CI, 2.15-3.56]; type 2 diabetes IRR, 4.18 [95% CI, 3.58-4.87]), depression (type 1 diabetes IRR, 1.62 [95% CI, 1.37-1.92]; type 2 diabetes IRR, 1.46 [95% CI, 1.34-1.59]), neuropathy (type 1 diabetes IRR, 1.64 [95% CI, 1.39-1.93]; type 2 diabetes IRR, 1.25 [95% CI, 1.17-1.34]), and nephropathy (type 1 diabetes IRR, 1.22 [95% CI, 1.01-1.48]; type 2 diabetes IRR, 1.23 [95% CI, 1.14-1.33]). Age had a U-shaped (continued) Open Access. This is an open access article distributed under the terms of the CC-BY License. JAMA Network Open. 2021;4(9):e2123471. doi:10.1001/jamanetworkopen.2021.23471 (Reprinted) September 1, 2021 1/17 JAMA Network Open | Diabetes and Endocrinology Factors Associated With Hyperglycemic Crises in Adults With Diabetes in the US, 2014-2020 Abstract (continued) association with hyperglycemic crisis risk in patients with type 1 diabetes (compared with patients aged 18-44 years: 45-64 years IRR, 0.72 [95% CI, 0.59-0.87]; 65-74 years IRR, 0.62 [95% CI, 0.47- 0.80]; 75 years IRR, 0.96 [95% CI, 0.66-1.38]). In type 2 diabetes, risk of hyperglycemic crises decreased progressively with age (45-64 years IRR, 0.57 [95% CI, 0.51-0.63]; 65-74 years IRR, 0.44 [95% CI, .39-0.49];75 years IRR, 0.41 [95% CI, 0.36-0.47]). In patients with type 2 diabetes, higher risk was associated with sodium-glucose cotransporter 2 inhibitor therapy (IRR, 1.30; 95% CI, 1.14- 1.49) and insulin dependency (compared with regimens with bolus insulin: regimens with basal insulin only, IRR, 0.69 [95% CI, 0.63-0.75]; and without any insulin, IRR, 0.36 [95% CI, 0.33-0.40]). CONCLUSIONS AND RELEVANCE In this cohort study, younger age, Black race/ethnicity, low income, and poor glycemic control were associated with an increased risk of hyperglycemic crises. The findings suggest that multidisciplinary interventions focusing on groups at high risk for hyperglycemic crises are needed to prevent these dangerous events. JAMA Network Open. 2021;4(9):e2123471. doi:10.1001/jamanetworkopen.2021.23471 Introduction More than 1 in 8 American adults are living with diabetes. Diabetic ketoacidosis (DKA) and 2 3 hyperglycemic hyperosmolar state (HHS) are life-threatening diabetes emergencies that are 4 5-7 8,9 5,10 associated with substantial morbidity, mortality, high costs, and health care use. Although 11-14 several studies have examined factors associated with DKA or HHS in the general population, there is limited contemporary evidence on patient-level risk factors, hindering efforts to proactively identify patients at risk and to reduce the frequency of these events at the population level. Most published research has focused on DKA in patients with type 1 diabetes, often among children or young adults. The frequently cited factors associated with DKA in this context are adolescence, socioeconomic disadvantage, female sex, elevated hemoglobin A (HbA ) level, prior 1c 1c DKA, and comorbid mental health conditions. A recent population-based analysis found that rates of DKA and HHS approximately doubled between 2009 and 2015, with higher rates among younger people and individuals residing in lower-income areas. However, these studies were limited by the lack of contemporary, longitudinal, patient-level data and granular information that differentiates patients by diabetes type, considers both type 1 diabetes and type 2 diabetes, and examines both DKA and HHS hyperglycemic crises. Accordingly, we examined emergency department (ED) visits and hospitalizations for hyperglycemic crises among adults with type 1 diabetes or type 2 diabetes in the US between 2014 and 2020, focusing on patient-level sociodemographic, clinical, and treatment-related factors associated with these events. Methods Study Design This retrospective cohort study used medical and pharmacy claims data from OptumLabs Data Warehouse (OLDW), a deidentified claims database for privately insured and Medicare Advantage enrollees in a nationwide private US health plan. The OLDW database contains longitudinal health information on enrollees, representing a diverse mix of ages, races/ethnicities, and geographic regions across the US. All study data were deidentified in accordance with Health Insurance Portability and Accountability Act expert deidentification determination. Mayo Clinic, Rochester, Minnesota, deemed this study to be exempt from institutional review board review and no informed consent was required (or feasible) because all data were deidentified. The results are reported in JAMA Network Open. 2021;4(9):e2123471. doi:10.1001/jamanetworkopen.2021.23471 (Reprinted) September 1, 2021 2/17 JAMA Network Open | Diabetes and Endocrinology Factors Associated With Hyperglycemic Crises in Adults With Diabetes in the US, 2014-2020 accordance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guideline. Study Population We identified adults (age18 years) with diabetes included in OLDW with available HbA data 1c between January 1, 2014, and December 31, 2019 (index date), and 1 year of uninterrupted insurance coverage before that date. The diagnosis of diabetes was established using Healthcare Effectiveness Data and Information Set criteria and categorized as type 1 diabetes or type 2 diabetes as 11,21,22 previously described. Outcomes The primary outcome was ED visit or hospitalization with a primary or first diagnosis of DKA or HHS (eTable 1 in the Supplement) that occurred between January 1, 2014, and December 31, 2020. In a secondary analysis, DKA and HHS were considered separately; in the event that both codes were present on the same encounter, events were classified as DKA in patients with type 1 diabetes and as HHS in patients with type 2 diabetes. Independent Variables Patient age, sex, race/ethnicity, annual household income, and US census region of residence were identified from OLDW enrollment files at the index date. Comorbidities were ascertained from all claims during the 12 months preceding the index date as described in eTable 1 in the Supplement. Glucose-lowering therapy was characterized based on prescriptions filled during the 120 days before the index date. For patients with type 1 diabetes, we assessed whether they had any prescriptions filled for noninsulin medication(s), prescriptions filled for insulin without noninsulin medications, or no prescriptions filled. For patients with type 2 diabetes, we first assessed whether there were any prescriptions filled, followed by whether there were prescriptions filled for bolus insulin (with or without basal insulin), prescriptions filled for basal insulin, or no prescriptions filled for insulin. Then, we identified fills for individual classes of noninsulin medications (eTable 2 in the Supplement). Statistical Analysis We assessed overall frequencies (percentages) and means (SDs) for baseline patient characteristics using the Mantel-Haenszel χ test for categorical variables and the t test for continuous variables. Crude and adjusted rates of ED visits or hospitalizations for hyperglycemic crises were calculated and presented as the total number of events per 1000 person-years among patients with type 1 diabetes or type 2 diabetes. Overall and annual adjusted rates of hyperglycemic crises were calculated using negative binomial estimates adjusted for age (during the year of the event), sex, race/ethnicity, region, and year. Adjusted rates of hyperglycemic crises for subgroups by age, sex, race/ethnicity, annual household income, and insulin use status (for type 2 diabetes only) were calculated using negative binomial estimates adjusted for age (at the index date), sex, race/ethnicity, and region. We tested for differences in the outcome by age, sex, race/ethnicity, income level, insulin use (in type 2 diabetes), and year using Wald tests. Multivariable negative binomial regression models were also used to examine the association between hyperglycemic crises (dependent variable) and the independent variables outlined above. We evaluated hyperglycemic crises as the total number of events per each person, reporting results as incidence risk ratios (IRRs), 95% CIs, and P values. Person-years were used as an exposure to determine the estimated rates of and factors associated with hyperglycemic crises. Secondary analyses examined the outcomes of DKA and of HHS separately. Analyses were conducted using SAS Enterprise Guide, version 7.1 (SAS Institute Inc) and STATA, version 15.1 (StataCorp LLC). A 2-sided P < .05 was considered statistically significant. JAMA Network Open. 2021;4(9):e2123471. doi:10.1001/jamanetworkopen.2021.23471 (Reprinted) September 1, 2021 3/17 JAMA Network Open | Diabetes and Endocrinology Factors Associated With Hyperglycemic Crises in Adults With Diabetes in the US, 2014-2020 Results Study Population The study cohort comprised 20 156 adults with type 1 diabetes (mean [SD] age, 46.6 [16.5] years; 51.2% male; 72.6% White race/ethnicity) and 796 382 adults with type 2 diabetes (mean [SD] age, 65.6 [11.8] years; 50.3% female; 54.4% White race/ethnicity) (Table 1 and Table 2). The mean (SD) durations of observation of patients in the 2 cohorts were 2.4 (1.8) years for type 1 diabetes and 2.6 (1.8) years for type 2 diabetes. Of patients with type 2 diabetes, 20.6% were treated with insulin. A higher proportion of patients with type 2 diabetes than with type 1 diabetes had an annual household income less than $40 000 (30.6% vs 14.9%). The mean (SD) HbA level among patients with type 1c 1 diabetes was 8.1% (1.6%), compared with 7.4% (1.6%) among patients with type 2 diabetes (to convert to proportion of total hemoglobin, multiply by 0.01). A total of 1273 patients with type 1 diabetes (6.3%) experienced 2397 episodes of hyperglycemic crises. A total of 2364 events (98.6%) were DKA, with only 33 episodes (1.4%) coded as HHS; thus, no secondary analysis by event type was conducted. The mean (SD) number of hyperglycemic crises among patients with at least 1 event was 1.9 (2.2). Compared with those who did not experience hyperglycemic crises, patients who did were more frequently young (mean [SD] age, 43.2 [18.4] vs 46.9 [16.4] years), Black (170 [13.4%] vs 1799 [9.5%]) or Hispanic (124 [9.7%] vs 1690 [9.0%]) individuals, and female (734 [57.7%] vs 9112 [48.3%]) and had lower income levels (<$40,000: 265 [20.8%] vs 2730 [14.5%]) and higher HbA levels (mean [SD], 9.4% [2.0%] vs 1c 8.0% [1.5%]) (Table 1). Among patients with type 2 diabetes, 5795 patients (0.7%) experienced 8005 hyperglycemic crises. The mean (SD) number of hyperglycemic crises among patients with at least 1 event was 1.4 (1.6). Compared with patients who did not experience hyperglycemic crises, patients who did were younger (mean [SD] age, 62.0 [13.7] vs 65.7 [11.8] years) and more likely to be Black individuals (1523 [26.3%] vs 140 476 [17.8%]) and had lower income levels (<$40 000: 2282 [39.4%] vs 241 339 [30.5%]) and higher HbA levels (mean [SD], 9.3% [1.5%] vs 7.3% [1.6%]) (Table 2). When DKA and 1c HHS outcomes were examined separately, 4264 patients (0.5%) experienced only DKA, 1329 (0.2%) experienced only HHS, and 202 (0.02%) experienced both types of events during the study period (eTable 3 in the Supplement). The group who experienced both HHS and DKA was analyzed together with the group with only DKA to ensure that patient deidentification was maintained because the characteristics of the 2 groups were similar. Compared with patients who experienced DKA, patients with HHS were older, were more likely to be Black individuals, had lower income levels, were less likely to have had a prior DKA or HHS event, and had higher prevalence of all comorbidities. Incidence Rates of Hyperglycemic Crises Adjusted overall rates of hyperglycemic crises were 52.69 events per 1000 person-years (95% CI, 48.26-57.12 events per 1000 person-years) among people with type 1 diabetes and 4.04 events per 1000 person-years (95% CI, 3.88-4.21 events per 1000 person-years) among people with type 2 diabetes. Event rates increased between 2014 and 2019 among patients with type 1 diabetes, from 43.30 events (95% CI, 33.37-53.24 events) to 61.36 events (95% CI, 52.90-69.82 events) but then decreased to 46.27 events (95% CI, 38.59-53.95 events) in 2020 (P =.01)(Figure 1 and Figure 2 and eTable 4 in the Supplement). In contrast, event rates among patients with type 2 diabetes remained stable throughout the study period. For both patients with type 1 diabetes and those with type 2 diabetes, rates of hyperglycemic crises were highest among younger patients, Black patients, patients with lower income, women, and (for type 2 diabetes) patients requiring insulin therapy (Figure 1 and Figure 2 and eTable 5 and eTable 6 in the Supplement). Indeed, among patients with type 2 diabetes treated with bolus insulin, with or without basal insulin, the adjusted rate of DKA or HHS was 17.73 events per 1000 person-years. Patients with type 1 diabetes whose annual household income was less than $40 000 experienced hyperglycemic crises at the adjusted rate of 101.52 events per 1000 person-years, compared with 26.25 events per 1000 person-years among patients JAMA Network Open. 2021;4(9):e2123471. doi:10.1001/jamanetworkopen.2021.23471 (Reprinted) September 1, 2021 4/17 JAMA Network Open | Diabetes and Endocrinology Factors Associated With Hyperglycemic Crises in Adults With Diabetes in the US, 2014-2020 Table 1. Baseline Sociodemographic, Clinical, and Diabetes Treatment Characteristics of Patients With Type 1 Diabetes Participants, No. (%) Without With Total hyperglycemic hyperglycemic Characteristic (N = 20 156) crises (n = 18 883) crises (n = 1273) P value Sociodemographic variables Age, y Mean (SD) 46.6 (16.5) 46.9 (16.4) 43.2 (18.4) <.001 18-44 9325 (46.3) 8649 (45.8) 676 (53.1) 45-64 7574 (37.5) 7175 (38.0) 399 (31.3) <.001 65-74 2367 (11.7) 2237 (11.8) 130 (10.2) ≥75 890 (4.4) 822 (4.4) 68 (5.3) Sex Female 9846 (48.8) 9112 (48.3) 734 (57.7) <.001 Male 10 310 (51.2) 9771 (51.7) 539 (42.3) Race/ethnicity White 14 630 (72.6) 13 756 (72.8) 874 (68.7) Black 1969 (9.8) 1799 (9.5) 170 (13.4) Hispanic 1814 (9.0) 1690 (9.0) 124 (9.7) <.001 Asian 523 (2.6) 492 (2.6) 31 (2.4) Other/unknown 1220 (6.0) 1146 (6.1) 74 (5.8) Annual household income, $ <40 000 2995 (14.9) 2730 (14.5) 265 (20.8) 40 000-74 999 4454 (22.1) 4134 (21.9) 320 (25.1) 75 000-124 999 5477 (27.2) 5139 (27.2) 338 (26.6) <.001 125 000-199 999 3283 (16.3) 3133 (16.6) 150 (11.8) ≥200 000 2468 (12.2) 2368 (12.5) 100 (7.9) Unknown 1479 (7.3) 1379 (7.3) 100 (7.9) US census region Midwest 3855 (19.1) 3581 (19.0) 274 (21.5) Northeast 2648 (13.1) 2517 (13.3) 131 (10.3) <.001 South 9740 (48.3) 9085 (48.1) 655 (51.4) West/unknown 3913 (19.4) 3700 (19.6) 213 (16.7) Index year 2014 5151 (25.6) 4791 (25.4) 360 (28.3) 2015 2628 (13.0) 2448 (13.0) 180 (14.1) 2016 2977 (14.8) 2780 (14.7) 197 (15.5) <.001 2017 3036 (15.1) 2834 (15.0) 202 (15.9) 2018 2931 (14.5) 2754 (14.6) 177 (13.9) 2019 3433 (17.0) 3276 (17.4) 157 (12.3) Clinical variables Comorbidity Hyperglycemic crisis 862 (4.3) 545 (2.9) 317 (24.9) <.001 Severe hypoglycemia 623 (3.1) 506 (2.7) 117 (9.2) <.001 Retinopathy 5888 (29.2) 5522 (29.2) 366 (28.8) .71 Neuropathy 5104 (25.3) 4625 (24.5) 479 (37.6) <.001 Nephropathy 2956 (14.7) 2671 (14.1) 285 (22.4) <.001 Cardiovascular disease 2920 (14.5) 2679 (14.2) 241 (18.9) <.001 Cerebrovascular disease 1038 (5.2) 928 (4.9) 110 (8.6) <.001 Peripheral vascular disease 1837 (9.1) 1680 (8.9) 157 (12.3) <.001 Heart failure 692 (3.4) 616 (3.3) 76 (6.0) <.001 Dementia 173 (0.9) 152 (0.8) 21 (1.6) .002 Hypertension 9336 (46.3) 8725 (46.2) 611 (48.0) .21 Depression 2549 (12.6) 2252 (11.9) 297 (23.3) <.001 COPD 1157 (5.7) 1054 (5.6) 103 (8.1) <.001 Cancer 832 (4.1) 776 (4.1) 56 (4.4) .62 c c Cirrhosis 85 (0.4) ≥74 (0.4) <11 .47 (continued) JAMA Network Open. 2021;4(9):e2123471. doi:10.1001/jamanetworkopen.2021.23471 (Reprinted) September 1, 2021 5/17 JAMA Network Open | Diabetes and Endocrinology Factors Associated With Hyperglycemic Crises in Adults With Diabetes in the US, 2014-2020 Table 1. Baseline Sociodemographic, Clinical, and Diabetes Treatment Characteristics of Patients With Type 1 Diabetes (continued) Participants, No. (%) Without With Total hyperglycemic hyperglycemic Characteristic (N = 20 156) crises (n = 18 883) crises (n = 1273) P value Treatment variables Hemoglobin A level, % 1c Mean (SD) 8.1 (1.6) 8.0 (1.5) 9.4 (2.0) <.001 Abbreviation: COPD, chronic obstructive c c ≤5.6 354 (1.8) ≥343 (1.8) <11 pulmonary disease. 5.7-6.4 1859 (9.2) 1822 (9.6) 37 (2.9) SI conversion factor: To convert hemoglobin A to 1c 6.5-6.9 2444 (12.1) 2378 (12.6) 66 (5.2) proportion of total hemoglobin, multiply by 0.01. 7.0-7.9 6359 (31.6) 6116 (32.4) 243 (19.1) <.001 Data are overall (total) and by whether patients 8.0-8.9 4493 (22.3) 4245 (22.5) 248 (19.5) experienced diabetic ketoacidosis or hyperglycemic 9.0-9.9 2387 (11.8) 2164 (11.5) 223 (17.5) hyperosmolar state during the follow-up period. ≥10 2260 (11.2) 1811 (9.6) 449 (35.3) Other is a racial/ethnicity choice in the OptumLabs Prescription fills for glucose- Data Warehouse database. lowering medication in the 120 d Patient counts less than 11 are masked to preserve before the index date deidentification. Thus, all numbers lower than 11 are Insulin only 16 805 (83.4) 15 724 (83.3) 1081 (84.9) reported as less than 11 and numbers within the same Any noninsulin medication 1829 (9.1) 1749 (9.3) 80 (6.3) <.001 row are presented with less precision to prevent None 1522 (7.6) 1410 (7.5) 112 (8.8) back-calculations of the masked sample. with an income of $200 000 or higher. Similarly, for patients with type 2 diabetes, adjusted rates of hyperglycemic crises were 5.78 events per 1000 person-years for individuals with low income and 2.23 events per 1000 person-years for individuals with high income. Tests of differences by age, sex, racial/ethnic groups, and (for type 2 diabetes) insulin use found significant heterogeneity across all (P .01 for all). Factors Associated With Hyperglycemic Crises For patients with type 1 diabetes and with type 2 diabetes, factors associated with increased risk of hyperglycemic crises were Black race/ethnicity (vs White race/ethnicity: type 1 diabetes incidence risk ratio [IRR], 1.33 [95% CI, 1.01-1.74]; type 2 diabetes IRR, 1.18 [95% CI, 1.09-1.27]) and lower annual household income ($200 000 vs <$40 000: type 1 diabetes IRR, 0.61 [95% CI, 0.46-0.81]; type 2 diabetes IRR, 0.69 [95% CI, 0.56-0.86]) (Table 3). Age had a U-shaped association with hyperglycemic crisis risk in patients with type 1 diabetes (compared with patients aged 18-44 years: 45-64 years IRR, 0.72 [95% CI, 0.59-0.87]; 65-74 years IRR, 0.62 [95% CI, 0.47-0.80]; 75 years IRR, 0.96 [95% CI, 0.66-1.38]). In type 2 diabetes, risk of hyperglycemic crises decreased progressively with age (45-64 years IRR, 0.57 [95% CI, 0.51-0.63]; 65-74 years IRR, 0.44 [95% CI, .39-0.49];75 years IRR, 0.41 [95% CI, 0.36-0.47]). In a secondary analysis that considered DKA and HHS separately for patients with type 2 diabetes, age was significantly associated with DKA (75 vs 18-44 years: IRR, 0.35; 95% CI, 0.30-0.41) but not with HHS (eTable 7 in the Supplement). Differences by sex were significant only for patients with type 1 diabetes, with men having lower risk than women (IRR, 0.75; 95% CI, 0.65-0.87). Among patients with type 1 diabetes, risk of hyperglycemic crises increased progressively in association with HbA levels above 7.0%; at HbA 1c 1c levels of 10% or higher, the risk was nearly 8-fold higher than at HbA levels from 6.5% to 6.9% (IRR, 1c 7.81; 95% CI, 5.78-10.54). Among patients with type 2 diabetes, risk of hyperglycemic crises increased progressively in association with all HbA levels, with an IRR of 0.56 (95% CI, 0.43-0.73) 1c at HbA levels of 5.6% or lower and an IRR of 7.06 (95% CI, 6.26-7.96) at HbA levels of 10% or 1c 1c higher compared with HbA levels from 6.5% to 6.9%. We observed similar results for HbA in 1c 1c patients with type 2 diabetes when DKA and HHS were examined separately. Patients who experienced hyperglycemic crises or severe hypoglycemia in the previous year were significantly more likely to experience recurrent DKA or HHS (Table 3). Among patients with type 1 diabetes, both prior hyperglycemic crises (IRR, 7.88; 95% CI, 6.06-9.99) and prior severe JAMA Network Open. 2021;4(9):e2123471. doi:10.1001/jamanetworkopen.2021.23471 (Reprinted) September 1, 2021 6/17 JAMA Network Open | Diabetes and Endocrinology Factors Associated With Hyperglycemic Crises in Adults With Diabetes in the US, 2014-2020 Table 2. Baseline Sociodemographic, Clinical, and Diabetes Treatment Characteristics of Patients With Type 2 Diabetes Participants, No. (%) Total Without hyperglycemic With hyperglycemic Characteristic (N = 796 382) crises (n = 790 587) crises (n = 5795) P value Sociodemographic variables Age, y Mean (SD) 65.6 (11.8) 65.7 (11.8) 62.0 (13.7) <.001 18-44 42 356 (5.3) 41 717 (5.3) 639 (11.0) 45-64 281 738 (35.4) 279 406 (35.3) 2332 (40.2) <.001 65-74 286 441 (36.0) 284 676 (36.0) 1765 (30.5) ≥75 185 847 (23.3) 184 788 (23.4) 1059 (18.3) Sex Female 400 346 (50.3) 397 272 (50.2) 3074 (53.0) <.001 Male 396 036 (49.7) 393 315 (49.8) 2721 (47.0) Race/ethnicity White 433 623 (54.4) 430 499 (54.4) 3124 (53.9) Black 141 999 (17.8) 140 476 (17.8) 1523 (26.3) Hispanic 133 664 (16.8) 132 901 (16.8) 763 (13.2) <.001 Asian 40 971 (5.1) 40 836 (5.2) 135 (2.3) Other/unknown 46 125 (5.8) 45 875 (5.8) 250 (4.3) Annual household income, $ <40 000 243 621 (30.6) 241 339 (30.5) 2282 (39.4) 40 000-74 999 222 612 (28.0) 220 975 (28.0) 1637 (28.2) 75 000-124 999 171 737 (21.6) 170 747 (21.6) 990 (17.1) <.001 125 000-199 999 64 332 (8.1) 64 057 (8.1) 275 (4.8) ≥200 000 28 576 (3.6) 28 449 (3.6) 127 (2.2) Unknown 65 504 (8.2) 65 020 (8.2) 484 (8.4) US census region Midwest 144 126 (18.1) 143 046 (18.1) 1080 (18.6) Northeast 120 946 (15.2) 120 193 (15.2) 753 (13.0) <.001 South 446 286 (56.0) 442 879 (56.0) 3407 (58.8) West/unknown 85 024 (10.7) 84 469 (10.7) 555 (9.6) Index year 2014 152 519 (19.2) 151 000 (19.1) 1159 (26.2) 2015 117 351 (14.7) 116 318 (14.7) 1033 (17.8) 2016 104 538 (13.1) 103 777 (13.1) 761 (13.1) <.001 2017 137 597 (17.3) 136 555 (17.3) 1042 (18.0) 2018 142 231 (17.9) 141 433 (17.9) 798 (13.8) 2019 142 146 (17.8) 141 504 (17.9) 642 (11.1) Clinical variables Comorbidity Hyperglycemic crisis 2646 (0.3) 2063 (0.3) 583 (10.1) <.001 Severe hypoglycemia 6727 (0.8) 6342 (0.8) 385 (6.6) <.001 Retinopathy 123 148 (15.5) 121 733 (15.4) 1415 (24.4) <.001 Neuropathy 218 245 (27.4) 215 790 (27.3) 2455 (42.4) <.001 Nephropathy 186 900 (23.5) 184 944 (23.4) 1956 (33.8) <.001 Cardiovascular disease 259 985 (32.6) 257 875 (32.6) 2110 (36.4) <.001 Cerebrovascular disease 92 517 (11.6) 91 584 (11.6) 933 (16.1) <.001 Peripheral vascular disease 132 101 (16.6) 130 770 (16.5) 1331 (23.0) <.001 Heart failure 85 846 (10.8) 84 889 (10.7) 957 (16.5) <.001 Dementia 24 052 (3.0) 23 788 (3.0) 264 (4.6) <.001 Hypertension 686 124 (86.2) 681 196 (86.2) 4928 (85.0) .01 Depression 99 487 (12.5) 98 313 (12.4) 1174 (20.3) <.001 COPD 114 033 (14.3) 112 987 (14.3) 1046 (18.0) <.001 Cancer 71 797 (9.0) 71 287 (9.0) 510 (8.80) .57 Cirrhosis 8952 (1.1) 8834 (1.1) 118 (2.0) <.001 (continued) JAMA Network Open. 2021;4(9):e2123471. doi:10.1001/jamanetworkopen.2021.23471 (Reprinted) September 1, 2021 7/17 JAMA Network Open | Diabetes and Endocrinology Factors Associated With Hyperglycemic Crises in Adults With Diabetes in the US, 2014-2020 Table 2. Baseline Sociodemographic, Clinical, and Diabetes Treatment Characteristics of Patients With Type 2 Diabetes (continued) Participants, No. (%) Total Without hyperglycemic With hyperglycemic Characteristic (N = 796 382) crises (n = 790 587) crises (n = 5795) P value Treatment variables Hemoglobin A level, % 1c Mean (SD) 7.4 (1.6) 7.3 (1.6) 9.3 (2.4) <.001 ≤5.6 46 822 (5.9) 46 736 (5.9) 86 (1.5) 5.7-6.4 217 748 (27.3) 217 308 (27.5) 440 (7.6) 6.5-6.9 144 631 (18.2) 144 177 (18.2) 454 (7.8) 7.0-7.9 182 928 (23.0) 181 943 (23.0) 985 (17.0) <.001 8.0-8.9 90 804 (11.4) 89 817 (11.4) 987 (19.5) 9.0-9.9 49 029 (6.2) 48 185 (6.1) 844 (14.6) ≥10 64 420 (8.1) 62 421 (7.9) 1999 (34.5) Prescription fills for glucose- lowering medication in the 120 d before the index date None 184 079 (23.1) 183 138 (23.2) 941 (16.2) <.001 Insulin Not treated with insulin 632 323 (79.4) 629 706 (79.6) 2617 (45.2) Basal only, no bolus 89 977 (11.3) 88 724 (11.2) 1253 (21.6) <.001 Abbreviations: COPD, chronic obstructive pulmonary Bolus, with or without basal 74 082 (9.3) 72 157 (9.1) 1925 (33.2) disease; DPP-4, dipeptidyl peptidase 4; GLP-1, Noninsulin glucose-lowering glucagon-like peptide 1; SGLT2, sodium-glucose medication cotransporter 2. Sulfonylurea 203 122 (25.5) 201 852 (25.5) 201 852 (25.5) <.001 SI conversion factor: To convert hemoglobin A to 1c Metformin 429 036 (53.9) 426 884 (54.0) 2152 (37.1) <.001 proportion of total hemoglobin, multiply by 0.01. SGLT2 inhibitor 40 247 (5.0) 39 933 (5.0) 314 (5.4) .20 Data are overall (total) and by whether patients GLP-1 receptor agonist 45 950 (5.8) 45 632 (5.8) 318 (5.5) .35 experienced at least 1 hyperglycemic crisis during the follow- DPP-4 inhibitor 96 962 (12.2) 96 377 (12.2) 585 (10.1) <.001 up period. Thiazolidinedione 38 668 (4.9) 38 439 (4.9) 229 (4.0) .001 Other is a racial/ethnicity choice in the OptumLabs Other 7685 (1.0) 7629 (1.0) 56 (1.0) .99 Data Warehouse database. hypoglycemia (IRR, 2.77; 95% CI, 2.15-3.56) were associated with increased risk of experiencing hyperglycemic crises. Similarly, among patients with type 2 diabetes, prior hyperglycemic crises (IRR, 17.51; 95% CI, 15.07-20.34) and prior severe hypoglycemia (IRR, 4.18; 95% CI, 3.58-4.87) were associated with increased risk of hyperglycemic crises. When DKA and HHS were examined separately, history of hyperglycemic crises had a greater association with DKA (IRR, 20.32; 95% CI, 17.31-23.86) than HHS (IRR, 7.18; 95% CI, 5.68-9.06) (eTable 7 in the Supplement). Compared with patients without the following health conditions, patients with depression (type 1 diabetes IRR, 1.62 [95% CI, 1.37-1.92]; type 2 diabetes IRR, 1.46 [95% CI, 1.34-1.59]), neuropathy (type 1 diabetes IRR, 1.64 [95% CI, 1.39-1.93]; type 2 diabetes IRR, 1.25 [95% CI, 1.17-1.34]), and nephropathy (type 1 diabetes IRR, 1.22 [95% CI, 1.01-1.48]; type 2 diabetes IRR, 1.23 [95% CI, 1.14-1.33]) had an increased risk of hyperglycemic crises (Table 3). For type 2 diabetes, additional risk was associated with the presence of retinopathy, cerebrovascular disease, heart failure, dementia, chronic obstructive pulmonary disease, cirrhosis, or cancer. Patients with type 2 diabetes who required basal insulin therapy (IRR, 0.69; 95% CI, 0.63-0.75) or no insulin therapy (IRR, 0.36; 95% CI, 0.33-0.40) had a lower risk of hyperglycemic crises compared with those treated with bolus, with or without basal, insulin therapy. Patients treated with sodium-glucose cotransporter 2 inhibitors (IRR, 1.30; 95% CI, 1.14-1.49) had an increased risk of hyperglycemic crises compared with patients not treated with these medications (Table 3). Therapy with a sodium-glucose cotransporter 2 inhibitor was specifically associated with an increased risk of DKA (IRR, 1.47; 95% CI, 1.27-1.70) but with a decreased risk of HHS (IRR, 0.65; 95% CI, 0.46-0.93) (eTable 7 in the Supplement). JAMA Network Open. 2021;4(9):e2123471. doi:10.1001/jamanetworkopen.2021.23471 (Reprinted) September 1, 2021 8/17 JAMA Network Open | Diabetes and Endocrinology Factors Associated With Hyperglycemic Crises in Adults With Diabetes in the US, 2014-2020 Discussion In this nationwide cohort study of insured adults with diabetes, adjusted rates of hyperglycemic crises were 52.69 events per 1000 person-years among people with type 1 diabetes, 4.04 events per 1000 person-years among people with type 2 diabetes, and 17.73 events per 1000 person-years among people with type 2 diabetes requiring intensive insulin therapy. In both patients with type 1 diabetes and those with type 2 diabetes, rates of hyperglycemic crises were significantly higher among younger adults, Black patients, individuals with lower income, patients with elevated HbA 1c levels, and patients with prior hyperglycemic crises or severe hypoglycemia, suggesting the need for timely patient identification, engagement, and treatment optimization to improve glycemic control and prevent these dangerous events. We found that the rates of hyperglycemic crises increased over time among patients with type 1 diabetes, from 43.30 per 1000 person-years in 2014 to 61.36 per 1000 person-years in 2019, consistent with previously described trends through 2015 and recent population-level data 23,24 showing an overall worsening of glycemic control among patients with diabetes in the US. There was no comparable temporal change in hyperglycemic crises rates among patients with type 2 diabetes. This persistent rise in rates of hyperglycemic crises among patients with type 1 diabetes underscores the urgency of improving glycemic control and diabetes management in this population. Why ED visits and hospitalizations for hyperglycemic crises among patients with type 1 diabetes declined in 2020 in the context of the COVID-19 pandemic is unknown. Although there may have been a delay in adjudication of claims, with not all 2020 claims finalized at the time of our final analysis (June 2021), this delay alone likely did not account for the observed decrease in hyperglycemic crises–associated ED visits or hospitalizations to 46.27 per 1000 person-years in 2020 (particularly as a similar decrease was not observed for patients with type 2 diabetes). Patients Figure 1. Adjusted Rates of Hyperglycemic Crises Among Adults With Type 1 Diabetes Stratified by Age, Sex, Race/Ethnicity, Annual Household Income, and Year A B C Age Sex Race/ethnicity 140 140 140 120 120 120 100 100 100 80 80 80 60 60 60 40 40 40 20 20 20 0 0 0 18-44 45-64 65-74 ≥75 Female Male White Black Hispanic Asian Age range, y Sex Race/ethnicity D Annual household income E Year 140 140 120 120 100 100 80 80 60 60 40 40 All rates are adjusted for age (age at index for all analyses except for annual rates, which used age at the 20 20 time of the event), sex, race/ethnicity, US region, and 0 0 year (for annualized rates). For age, P < .001; sex, <40 000 40 000- 75 000- 125 000- >200 000 2014 2015 2016 2017 2018 2019 2020 74 999 124 999 199 999 P < .001; race/ethnicity, P = .002; annual household Year Income range, $ income, P < .001; and year, P = .01. JAMA Network Open. 2021;4(9):e2123471. doi:10.1001/jamanetworkopen.2021.23471 (Reprinted) September 1, 2021 9/17 Hyperglycemic crises per 1000 Hyperglycemic crises per 1000 person-years person-years Hyperglycemic crises per 1000 person-years Hyperglycemic crises per 1000 person-years Hyperglycemic crises per 1000 person-years JAMA Network Open | Diabetes and Endocrinology Factors Associated With Hyperglycemic Crises in Adults With Diabetes in the US, 2014-2020 may have sought to avoid the ED or hospital to minimize COVID-19 exposure or because EDs and hospitals were overwhelmed by caring for patients with COVID-19. Alternatively, patients may have observed improvements in diabetes management in the context of evolving policy changes regarding insulin access and affordability. Further exploration will be needed to examine diabetes management in 2020, particularly among patients with type 1 diabetes, and to assess for changes in insulin use and adherence, glycemic control, and diabetes-related mortality. In the present study, incidence and risk of hyperglycemic crises was disproportionately higher for patients with lower income, a finding supporting the need for policies and systems to ensure 25,26 improved access to affordable glucose-lowering therapies. Building on earlier work in different 27,28 populations, we found that for individuals with type 1 diabetes, the adjusted rate of hyperglycemic crises was 101.52 events per 1000 person-years among patients with low income (<$40 000) compared with 26.25 events per 1000 person-years among patients with high income ($200 000). Income-based disparities in hyperglycemic crisis risk were also detected among patients with type 2 diabetes: 5.78 vs 2.23 per 1000 person-years, respectively. The association of an inability to afford insulin with increased risk of DKA has been observed for decades. Increasing 26,30,31 costs of insulin are associated with an increased prevalence of undertreatment of patients 32 33 with lower incomes and insulin rationing, which may lead to severe and uncontrolled hyperglycemia as a result of inadequate access to the medication that all patients with type 1 diabetes and some with insulin-requiring type 2 diabetes need to live. Although rates of hyperglycemic emergencies may be higher among uninsured patients owing to poor access to 16,34 medical care, healthy food, and housing, many people with employer-sponsored private health Figure 2. Adjusted Rates of Hyperglycemic Crises Among Adults With Type 2 Diabetes Stratified by Age, Sex, Race/Ethnicity, Annual Household Income, Insulin Therapy, and Year A Age B Sex C Race/ethnicity 20 10 10 16 8 8 12 6 6 8 4 4 4 2 2 0 0 0 18-44 45-64 65-74 ≥75 Female Male White Black Hispanic Asian Age range, y Sex Race/ethnicity D Annual household income E Insulin requirement F Year 10 20 10 18 9 8 16 8 14 7 6 12 6 10 5 4 8 4 6 3 2 4 2 2 1 0 0 0 <40 000 40 000- 75 000- 125 000- >200 000 No Basal Bolus ± 2014 2015 2016 2017 2018 2019 2020 74 999 124 999 199 999 insulin insulin basal Year only insulin Income range, $ Insulin regimen All rates are adjusted for age (age at index for all analyses except for annual rates, which used age at the time of the event), sex, race/ethnicity, US region, and year (for annualized rates). For age, P < .001; sex, P < .001; race/ethnicity, P < .001; annual household income, P < .001; insulin requirement, P < .001; and year, P = .16. JAMA Network Open. 2021;4(9):e2123471. doi:10.1001/jamanetworkopen.2021.23471 (Reprinted) September 1, 2021 10/17 Hyperglycemic crises per 1000 Hyperglycemic crises per 1000 person-years person-years Hyperglycemic crises per 1000 person-years Hyperglycemic crises per 1000 person-years Hyperglycemic crises per 1000 person-years Hyperglycemic crises per 1000 person-years JAMA Network Open | Diabetes and Endocrinology Factors Associated With Hyperglycemic Crises in Adults With Diabetes in the US, 2014-2020 Table 3. Factors Associated With Hyperglycemic Crises Among Adults With Type 1 or Type 2 Diabetes, 2014-2020 Type 1 diabetes Type 2 diabetes Factor IRR (95% CI) P value IRR (95% CI) P value Age, y 18-44 1 [Reference] NA 1 [Reference] NA 45-64 0.72 (0.59-0.87) .001 0.57 (0.51-0.63) <.001 65-74 0.62 (0.47-0.80) <.001 0.44 (0.39-0.49) <.001 ≥75 0.96 (0.66-1.38) .82 0.41 (0.36-0.47) <.001 Sex Female 1 [Reference] NA 1 [Reference] NA Male 0.75 (0.65-0.87) <.001 1.00 (0.94-1.07) .94 Race/ethnicity White 1 [Reference] NA 1 [Reference] NA Black 1.33 (1.01-1.74) .04 1.18 (1.09-1.27) <.001 Hispanic 0.88 (0.70-1.11) .28 0.69 (0.62-0.75) <.001 Asian 1.15 (0.73-1.80) .55 0.64 (0.51-0.80) <.001 Other/unknown 1.07 (0.79-1.44) .68 0.87 (0.73-1.03) .10 US census region Midwest 1 [Reference] NA 1 [Reference] NA Northeast 0.71 (0.56-0.90) .004 0.92 (0.82-1.03) .14 South 0.94 (0.78-1.12) .47 1.01 (0.93-1.09) .90 West/unknown 0.99 (0.78-1.25) .90 1.00 (0.88-1.13) .94 Annual household income, $ <40 000 1 [Reference] NA 1 [Reference] NA 40 000-74 999 0.85 (0.68-1.06) .15 0.84 (0.78-0.91) <.001 75 000-124 999 0.92 (0.73-1.17) .51 0.73 (0.66-0.80) <.001 125 000-199 999 0.71 (0.54-0.92) .009 0.57 (0.49-0.66) <.001 ≥200 000 0.61 (0.46-0.81) .001 0.69 (0.56-0.86) .001 Unknown 0.98 (0.72-1.35) .91 1.01 (0.88-1.16) .87 Index year 2014 1 [Reference] NA 1 [Reference] NA 2015 0.86 (0.69-1.07) .18 0.92 (0.84-1.01) .09 2016 1.22 (0.94-1.59) .13 0.93 (0.83-1.03) .16 2017 1.08 (0.86-1.37) .50 0.98 (0.89-1.08) .66 2018 1.05 (0.85-1.31) .66 0.99 (0.89-1.09) .81 2019 1.04 (0.82-1.31) .76 1.04 (0.93-1.17) .49 Comorbidity Hyperglycemic crisis 7.88 (6.06-9.99) <.001 17.51 (15.07-20.34) <.001 Severe hypoglycemia 2.77 (2.15-3.56) <.001 4.18 (3.58-4.87) <.001 Retinopathy 0.92 (0.79-1.08) .31 1.27 (1.18-1.38) <.001 Nephropathy 1.22 (1.01-1.48) .04 1.23 (1.14-1.33) <.001 Neuropathy 1.64 (1.39-1.93) <.001 1.25 (1.17-1.34) <.001 Cardiovascular disease 1.22 (0.97-1.53) .09 0.93 (0.87-1.01) .08 Cerebrovascular disease 1.04 (0.81-1.34) .77 1.18 (1.07-1.30) .001 Peripheral vascular disease 1.18 (0.92-1.51) .20 1.09 (1.00-1.18) .05 Heart failure 0.88 (0.64-1.22) .45 1.14 (1.03-1.25) .01 Dementia 1.50 (0.89-2.52) .13 1.49 (1.27-1.75) <.001 Hypertension 0.93 (0.79-1.10) .39 0.83 (0.76-0.91) <.001 Depression 1.62 (1.37-1.92) <.001 1.46 (1.34-1.59) <.001 COPD 1.03 (0.79-1.34) .85 1.11 (1.02-1.21) .02 Cancer 1.09 (0.77-1.53) .63 1.15 (1.03-1.28) .01 Cirrhosis 1.09 (0.51-2.37) .82 1.72 (1.36-2.18) <.001 (continued) JAMA Network Open. 2021;4(9):e2123471. doi:10.1001/jamanetworkopen.2021.23471 (Reprinted) September 1, 2021 11/17 JAMA Network Open | Diabetes and Endocrinology Factors Associated With Hyperglycemic Crises in Adults With Diabetes in the US, 2014-2020 Table 3. Factors Associated With Hyperglycemic Crises Among Adults With Type 1 or Type 2 Diabetes, 2014-2020 (continued) Type 1 diabetes Type 2 diabetes Factor IRR (95% CI) P value IRR (95% CI) P value Hemoglobin A % 1c, ≤5.6 0.56 (0.27-1.14) .11 0.56 (0.43-0.73) <.001 5.7-6.4 0.99 (0.58-1.68) .96 0.67 (0.58-0.77) <.001 6.5-6.9 1 [Reference] NA 1 [Reference] NA 7.0-7.9 1.63 (1.20-2.22) .002 1.48 (1.31-1.67) <.001 8.0-8.9 2.11 (1.55-2.86) <.001 2.61 (2.30-2.96) <.001 9.0-9.9 3.57 (2.61-4.89) <.001 3.72 (3.25-4.27) <.001 ≥10 7.81 (5.78-10.54) <.001 7.06 (6.26-7.96) <.001 Type 1 diabetes management Insulin only 1 [Reference] NA NA NA No medications 1.05 (0.80-1.38) .72 NA NA Any noninsulin medication 0.65 (0.49-0.87) .003 NA NA Type 2 diabetes management No medications NA NA 1.10 (0.98-1.23) .09 Insulin use Bolus with or without basal NA NA 1 [Reference] NA Basal only NA NA 0.69 (0.63-0.75) <.001 Not treated with insulin NA NA 0.36 (0.33-0.40) <.001 Noninsulin medication Abbreviations: COPD, chronic obstructive pulmonary Metformin NA NA 0.72 (0.67-0.78) <.001 disease; DPP-4, dipeptidyl peptidase 4; GLP-1, Sulfonylurea NA NA 0.90 (0.84-0.98) .01 glucagon-like peptide 1; IRR, incidence risk ratio; NA, not applicable; SGLT2, sodium-glucose SGLT2 inhibitor NA NA 1.30 (1.14-1.49) <.001 cotransporter 2. GLP-1 receptor agonist NA NA 0.77 (0.67-0.87) <.001 SI conversion factor: To convert hemoglobin A to 1c DPP-4 inhibitor NA NA 0.87 (0.79-0.96) .006 proportion of total hemoglobin, multiply by 0.01. Thiazolidinedione NA NA 1.12 (0.96-1.31) .15 Other is a racial/ethnicity choice in the OptumLabs Other NA NA 0.86 (0.64-1.15) .30 Data Warehouse database. plans have high deductibles and out-of-pocket cost-sharing expenses, which may be associated 36 37 with financial distress and greater likelihood of forgoing necessary medical care. Young patients 34,38 may be particularly susceptible to financial instability and underinsurance, which may be 21,34,39,40 associated with poor glycemic control, inadequate ambulatory care, and ultimately, higher rates of hyperglycemic crises, like those observed in our study. Thus, multidisciplinary teams should anticipate these barriers to care, develop care plans that are affordable and accessible, and help patients navigate available support programs. We believe that greater attention should be given to addressing racial/ethnic disparities in diabetes management. Black patients with type 1 diabetes or with type 2 diabetes had higher risks of hyperglycemic crises than individuals in the other racial/ethnic groups included in the study. This disparity persisted after adjustment for key socioeconomic, clinical, and treatment-related factors, suggesting that additional intrinsic and extrinsic factors are associated with hyperglycemic crises among Black patients. Black patients may be more likely to experience DKA in the context of ketosis- 41-43 prone type 2 diabetes, which is more prevalent among Black patients. In addition to biological risk factors, increased DKA and HHS risk among Black patients may be associated with unmeasured social determinants of health and manifestations of structural racism both within and outside health care. Black patients with type 2 diabetes are more likely than White patients to be undertreated, and undertreated patients are more likely to experience hyperglycemic crises than patients who 32 45 were treated appropriately. Black patients are also more likely to be cared for by clinicians and health systems that deliver lower-quality care or have fewer resources available to optimally care for their patients, which may contribute to worse health outcomes. Furthermore, Black patients 47 48-50 are more likely to reside in less walkable neighborhoods with fewer healthy food options, JAMA Network Open. 2021;4(9):e2123471. doi:10.1001/jamanetworkopen.2021.23471 (Reprinted) September 1, 2021 12/17 JAMA Network Open | Diabetes and Endocrinology Factors Associated With Hyperglycemic Crises in Adults With Diabetes in the US, 2014-2020 which may be associated with worse glycemic control. Thus, additional research is needed to understand the multiplicity of factors contributing to the undertreatment of Black patients with diabetes, barriers to managing their diabetes, and their increased risk of hyperglycemic crises. Poorly controlled diabetes was another factor associated with hyperglycemic crises. For patients with type 1 diabetes, risk of experiencing a hyperglycemic crisis increased when the HbA 1c level exceeded 7%, and the IRR was 7.81 (95% CI, 5.78-10.54) for HbA levels of 10% or higher 1c compared with HbA levels of 6.5% to 6.9%. For patients with type 2 diabetes, the risk increased 1c continuously for all HbA levels above 5.6%, and the IRR was 7.06 (95% CI, 6.26-7.96) for HbA 1c 1c levels of 10% or higher. This association of HbA level with increased risk of hyperglycemic 1c emergencies overlooks the importance of real-time glycemic variability that would be captured by self-monitoring or continuous glucose monitoring. The importance of glycemic variability is underscored by the finding that severe hypoglycemia was associated with a 3- to 4-fold increase in the risk of experiencing a hyperglycemic crisis. Because patients with high HbA levels also 1c frequently experience severe hypoglycemia, an elevated HbA level is a signal of susceptibility to 1c both hyperglycemic and hypoglycemic crises. Strengths and Limitations This study is strengthened by the ability to examine patient- and treatment-level factors associated with hyperglycemic crises at the population level using longitudinal analysis and is not limited to a single health care system. The present study also provides, to our knowledge, the most contemporary epidemiological data on DKA and HHS through the end of 2020, including during the COVID-19 pandemic in the US. This study also has limitations. First, this observational analysis was designed to examine the epidemiological features of and factors associated with hyperglycemic crises, not to establish a causal relationship between any factor(s) and these events. The classification scheme for type of diabetes and the adjudication of events as being DKA or HHS may not be accurate because both determinations were limited by data available in the claims database. Because all patients had established diabetes, we did not capture instances of newly diagnosed diabetes in patients presenting with DKA (particularly of interest in the context of COVID-19) or assess the impact of lapsed insurance. Our data also did not allow us to examine the factors leading up to and precipitating 2,34 hyperglycemic events, such as medication nonadherence or acute illness. However, our objectives were to characterize the frequency of hyperglycemic crises among adults with type 1 diabetes or with type 2 diabetes in the US and to identify patient- and treatment-related factors associated with these events. These epidemiologic data are necessary to inform targeted interventions at multiple levels to prevent hyperglycemic crises among individuals at highest risk of these conditions. Conclusions In this cohort study, younger age, Black race/ethnicity, low income, and poor glycemic control were associated with an increased risk of hyperglycemic crises. The findings suggest that efforts are needed to facilitate engagement of these groups with the health care system, assess and address potential barriers—financial, logistical, psychosocial, or medical—to optimal control of patients’ blood 15,51 glucose levels, and provide referral for diabetes self-management education and support. Health care delivery systems should incorporate educational, clinical, and social support systems into clinical practice, and payers should consider expanding reimbursement for self-management education and social services as well as more comprehensive coverage for glucose-lowering medications, insulin, and glucose-monitoring technologies. JAMA Network Open. 2021;4(9):e2123471. doi:10.1001/jamanetworkopen.2021.23471 (Reprinted) September 1, 2021 13/17 JAMA Network Open | Diabetes and Endocrinology Factors Associated With Hyperglycemic Crises in Adults With Diabetes in the US, 2014-2020 ARTICLE INFORMATION Accepted for Publication: June 29, 2021. Published: September 1, 2021. doi:10.1001/jamanetworkopen.2021.23471 Open Access: This is an open access article distributed under the terms of the CC-BY License.©2021McCoyRG et al. JAMA Network Open. Corresponding Author: Rozalina G. McCoy, MD, MS, Division of Community Internal Medicine, Department of Medicine, Mayo Clinic, 200 First St SW, Rochester, MN 55905 (mccoy.rozalina@mayo.edu). Author Affiliations: Division of Community Internal Medicine, Department of Medicine, Mayo Clinic, Rochester, Minnesota (McCoy); Mayo Clinic Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Rochester, Minnesota (McCoy, Swarna, Van Houten, Shah); Division of Endocrinology, Department of Medicine, Emory University School of Medicine, Grady Memorial Hospital, Atlanta, Georgia (Galindo, Umpierrez); HealthPartners Institute Center for Chronic Care Innovation, Minneapolis, Minnesota (Van Houten, O’Connor); OptumLabs, Eden Prairie, Minnesota (Shah). Author Contributions: Dr McCoy had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Concept and design: McCoy, Galindo, Van Houten, O’Connor, Umpierrez. Acquisition, analysis, or interpretation of data: McCoy, Galindo, Swarna, Van Houten, O’Connor, Shah. Drafting of the manuscript: McCoy, Galindo, Van Houten. Critical revision of the manuscript for important intellectual content: Galindo, Swarna, Van Houten, O’Connor, Umpierrez, Shah. Statistical analysis: Swarna, Van Houten. Obtained funding: McCoy. Administrative, technical, or material support: Galindo, O’Connor, Shah. Supervision: McCoy, O’Connor. Conflict of Interest Disclosures: Dr McCoy reported receiving an AARP Quality Measure Innovation Grant from the AARP and grants from the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) and the Mayo Clinic outside the submitted work. Dr Galindo reported receiving grants from the NIDDK and Novo Nordisk and Dexcom (to Emory University) and receiving personal fees from Abbott Diabetes Care, Eli Lilly and Company, Novo Nordisk, Sanofi, and Valeritas. Dr O’Connor reported receiving grants from the National Heart, Lung and Blood Institute, the NIDDK, the Patient Centered Outcomes Research Institute, the National Cancer Institute, and the National Institute on Drug Abuse. Dr Umpierrez reported receiving grants from the National Center for Advancing Translational Sciences and receiving unrestricted research support from AstraZeneca, Novo Nordisk, and Dexcom (to Emory University). Dr Shah reported receiving research support (through Mayo Clinic) from the US Food and Drug Administration and the Centers of Medicare and Medicaid Innovation and receiving grants from the Agency for Healthcare Research and Quality, the National Heart, Lung and Blood Institute, the National Science Foundation, and the Patient Centered Outcomes Research Institute. No other disclosures were reported. Funding/Support: This work was funded by grant K23DK114497 from the NIDDK (Dr McCoy). Role of the Funder/Sponsor: The study sponsor had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. Disclaimer: Dr McCoy affirms that the article is an honest, accurate, and transparent account of the study being reported; that no important aspects of the study have been omitted; and that any discrepancies from the study as planned have been explained. Study contents are the sole responsibility of the authors and do not necessarily represent the official views of the National Institutes of Health. Meeting Presentation: This paper was presented at the virtual meeting of the American Diabetes Association Scientific Sessions; June 25-29, 2021. REFERENCES 1. Centers for Disease Control and Prevention. National Diabetes Statistics Report, 2020. 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Wexler DJ, Beauharnais CC, Regan S, Nathan DM, Cagliero E, Larkin ME. Impact of inpatient diabetes management, education, and improved discharge transition on glycemic control 12 months after discharge. Diabetes Res Clin Pract. 2012;98(2):249-256. doi:10.1016/j.diabres.2012.09.016 SUPPLEMENT. eTable 1. Code Sets for Included Health Conditions eTable 2. Classification Scheme for Glucose-Lowering Medications eTable 3. Patients With Type 2 Diabetes eTable 4. Crude and Adjusted Rates of Hyperglycemic Crises Among Patients With Type 1 and Type 2 Diabetes, 2014-2020 eTable 5. Crude and Adjusted Rates of Hyperglycemic Crises Among Patients With Type 1 Diabetes by Prespecified Subgroup, 2014-2020 eTable 6. Crude and Adjusted Rates of Hyperglycemic Crises Among Patients With Type 2 Diabetes by Prespecified Subgroup, 2014-2020 eTable 7. Risk Factors for DKA and HHS (Examined as Independent Outcomes) Among Adults With Type 2 Diabetes, 2014-2020 JAMA Network Open. 2021;4(9):e2123471. doi:10.1001/jamanetworkopen.2021.23471 (Reprinted) September 1, 2021 17/17 Supplementary Online Content McCoy RG, Galindo RJ, Swarna KS, et al. Sociodemographic, clinical, and treatment- related factors associated with hyperglycemic crises among adults with type 1 or type 2 diabetes in the US from 2014 to 2020. JAMA Netw Open. 2021;4(9):e2123471. doi:10.1001/jamanetworkopen.2021.23471 eTable 1. Code Sets for Included Health Conditions eTable 2. Classification Scheme for Glucose-Lowering Medications eTable 3. Patients With Type 2 Diabetes eTable 4. Crude and Adjusted Rates of Hyperglycemic Crises Among Patients With Type 1 and Type 2 Diabetes, 2014-2020 eTable 5. Crude and Adjusted Rates of Hyperglycemic Crises Among Patients With Type 1 Diabetes by Prespecified Subgroup, 2014-2020 eTable 6. Crude and Adjusted Rates of Hyperglycemic Crises Among Patients With Type 2 Diabetes by Prespecified Subgroup, 2014-2020 eTable 7. Risk Factors for DKA and HHS (Examined as Independent Outcomes) Among Adults With Type 2 Diabetes, 2014-2020 This supplementary material has been provided by the authors to give readers additional information about their work. © 2021 McCoy RG et al. JAMA Network Open. eTable 1. Code Sets for Included Health Conditions. All conditions were ascertained during the baseline 12 months preceding the index date for cohort entry Comorbidity ICD-9 Codes ICD-10 codes Included code types Cancer (except 14x.xx, 15x.xx, 160.x-165.x, C00.x-C14.x, C15.x-C26.x, All claims non-melanoma 170.x-172.x, 174.x-176.x, C3x.xx, C40.xx-C41.x, C43.x, Codes in all skin cancer) 179-189.x, 190.x-195.x, C4A.xx, C45.x-C49.xx, C50.xxx, positions 199.xx-208.xx (except C51.x-C58, C60.x-C63.x, C64.x- 203.x1, 204.x1, 205.x1, C68.x, C69.xx-C72.x, C73- 206.x1, 207.x1, 208.x1) C76.x, C7A.xx, C80.xx-C96.x (except C90.x1, C91.x1, C92.x1, C93.x1, C94.x1, C95.x1) Cardiovascular 410.x, 411.x, 412, 413.x, I20.x, I21.x, I22.x, I23.x, I24.x, All claims disease 414.x, 427.1, 427.3x, I25.x, I46.x, I47.x, I48.x, I49.x, Codes in all 427.4x, 427.5, 429.2, 440.x, I70.x, I71.x positions 441.x Cerebrovascular 430, 431, 432.x, 433.xx, G45.0, G45.1, G45.2, G45.8, All claims disease 434.xx 435.x, 436, 437.x, G45.9, G46.x, I60.xx, I61.x Codes in all 438.xx, V12.54 (except I61.0), I62.xx, I63.xxx, positions I65.xx, I66.xx, I67.8x (except I67.83, I67.84), I67.9, I69.xxx, Z86.73 Chronic 490, 491.xx, 492.x, 494.x, J40, J41.x, J42, J43.x, J44.x, All claims obstructive 496 J47.x Codes in all pulmonary positions disease Cirrhosis 571.2, 571.5, 571.6 K70.3x, K74.3, K74.4, K74.5, All claims K74.6x Codes in all positions Dementia 046.1x, 290.1x, 290.2x, A81.0x, F01.5x, F02.8x, F03.9x, All claims 290.3, 290.4x, 291.2, F10.27, F10.97, F13.27, F13.97, Codes in all 292.82, 294.1x, 294.2x, F18.97, F19.17, F19.27, F19.97, positions 331.0, 331.1x, 331.2, 331.6, G30.x, G31.0x, G31.1, G31.83, 331.82, 331.89 G31.85 Depression 290.13, 290.21, 290.43, F01.51, F32.x (except F32.81), All claims 296.2x, 296.3x, 296.82, F33.x, F34.8x, F43.21, F43.23 Codes in all 298.0, 301.12, 309.0, 309.1, positions 309.28, 311 DKA 250.10, 250.11, 250.12, E10.10, E10.11, E11.10, E11.11, Hospital and 250.13 E13.10, E13.11 ED claims st Codes in 1 position HHS 250.20, 250.21, 250.22, E11.00, E11.01, E13.00, E13.01 Hospital and 250.23 ED claims st Codes in 1 position Heart failure 398.91, 402.01, 402.11, I09.81, I11.0, I13.0, I13.2, I50.xx All claims 402.91, 404.01, 404.03, Codes in all 404.11, 404.13, 404.91, positions 404.93, 428.xx Hypoglycemia 251.0, 251.1, 251.2, 962.3, E10.641, E10.649, E11.641, Hospital and 250.8x (for 250.8x: if no E11.649, E13.641, E13.649, ED claims st concurrent 259.8, 272.7, E16.0, E16.1, E16.2, T38.3X1A, Codes in 1 681.xx, 682.xx, 686.9x, T38.3X1D, T38.3X1S, position © 2021 McCoy RG et al. JAMA Network Open. Comorbidity ICD-9 Codes ICD-10 codes Included code types 707.1x-707.2x, 707.8, T38.3X2A, T38.3X2D, 707.9, 709.3, 730.0x- T38.3X2S, T38.3X3A, 730.2x, 731.8) T38.3X3D, T38.3X3S, T38.3X4A, T383X4D, T38.3X4S, T38.3X5A, T383X5D, T38.3X5S Hypertension 401.x, 402.x, 403.x, 404.x, I11.x, I12.x, I13.x, I15.x, I16.x, All claims 405.x I10 Codes in all positions Nephropathy 593.9, 586, 250.4x, 249.4x, E08.21, E08.22, E08.29, E09.21, All claims 580.x, 581.x, 582.x, 583.x, E09.22, E09.29, E10.21, E10.22, Codes in all 585.x E10.29, E11.21, E11.22, E11.29, positions E13.21, E13.22, E13.29, N19, N00.x, N03.x, N04.x, N05.x, N18.x Neuropathy 357.2, 337.1, 356.9, 358.1, G90.09, G90.8, G90.9, G99.0, All claims 458.0, 536.3, 564.5, 596.54, G60.9, G73.3, G90.01, I95.1, Codes in all 713.5, 951.0, 951.1, 951.3, K31.84, K59.1, N31.9, E08.4x, positions 250.6x, 249.6x, 337.0x, E09.4x, E10.4x, E11.4x, E13.4x, 354.x, 355.x G56.x, G57.x, H49.x, M14.6x, S04.x Peripheral 442.3, 440.21, 443.81, E08.51, E09.51, E10.51, E11.51, All claims vascular disease 443.9, 892.1, 040.0, 444.22, E13.51, E08.59, E09.59, E10.59, Codes in all 785.4, 250.7x, 249.7, E11.59, E13.59, E08.621, positions 707.1x E09.621, E10.621, E11.621, E13.621, I72.4, I73.89, I73.9, A48.0, I74.3, I96, E08.52, E09.52, E10.52, E11.52, E13.52, I70.21x, S91.3x, L97.x Retinopathy 362.01, 362.03, 362.04, H35.9, E08.3x, E09.3x, E10.3x, All claims 362.05, 362.06, 362.07, E11.3x, E13.3x, H35.0x, Codes in all 362.53, 362.81, 362.82, H35.35x, H35.6x, H35.8x, H33.x, positions 362.83, 362.02, 379.23, H54.x, H43.1x 250.5x, 249.5x, 362.1x, 361.x, 369.x Abbreviations: DKA, diabetic ketoacidosis; ED, emergency department; HHS, hyperglycemic hyperosmolar state. © 2021 McCoy RG et al. JAMA Network Open. eTable 2. Classification Scheme for Glucose-Lowering Medications Medication class Included agents Insulin: Basal NPH/isophane Determir Glargine Degludec Insulin: Bolus Regular Aspart Lispro Glulisine Inhaled powder insulin Sulfonylureas Glimepiride Glipizide Glyburide Biguanides Metformin GLP-1 receptor agonists Exenatide Liraglutide Albiglutide Dulaglutide Lixisenatide Semaglutide SGLT2 inhibitors Canagliflozin Empagliflozin Dapagliflozin Ertugliflozin DPP-4 inhibitors Sitagliptin Saxagliptin Linagliptin Alogliptin Glitazones Pioglitazone Rosiglitazone Glinides Nateglinide Repaglinide Amylin analogs Pramlintide -Glucosidase inhibitors Acarbose Miglitol © 2021 McCoy RG et al. JAMA Network Open. eTable 3. Patients With Type 2 Diabetes. Baseline sociodemographic, clinical, and diabetes treatment characteristics of included adults with type 2 diabetes, overall and subset by whether they experienced at least one episode of hyperglycemic crisis during the follow-up period. There were 4,264 patients who experienced at least one episode of DKA and 202 patients who experienced at least one episode of DKA and at le ast one episode of HHS during the observation period. Because of the small sample size of patients who experienced both DKA and HHS events, and our inability to present sample sizes smaller than 11 (as would be the case in many cells for this small group), the group with both types of events was combined with the group experiencing DKA only. Total No DKA/HHS DKA ± HHS HHS p-value Number of patients 796,382 790,587 4,466 1,329 Sociodemographic variables Age, years, mean (SD) 65.63 (11.79) 65.66 (11.78) 60.54 (13.95) 66.81 (11.53) <0.001 Age, N (%) <0.001 18-44 years 42,356 (5.32%) 41,717 (5.28%) 585 (13.10%) 54 (4.06%) 45-64 years 281,738 (35.38%) 279,406 (35.34%) 1,902 (42.59%) 430 (32.36%) 65-74 years 286,441 (35.97%) 284,676 (36.01%) 1,275 (28.55%) 490 (36.87%) 185,847 (23.34%) 184,788 (23.37%) 704 (15.76%) 355 (26.71%) Sex, N (%) Female 400,346 (50.27%) 397,272 (50.25%) 2,380 (53.29%) 694 (52.22%) Male 396,036 (49.73%) 393,315 (49.75%) 2,086 (46.71%) 635 (47.78%) Race/ethnicity, N (%) <0.001 White 433,623 (54.45%) 430,499 (54.45%) 2,502 (56.02%) 622 (46.80%) Black 141,999 (17.83%) 140,476 (17.77%) 1,088 (24.36%) 435 (32.73%) Hispanic 133,664 (16.78%) 132,901 (16.81%) 592 (13.26%) 171 (12.87%) Asian 40,971 (5.14%) 40,836 (5.17%) 93 (2.08%) 42 (3.16%) Other/unknown 46,125 (5.79%) 45,875 (5.80%) 191 (4.28%) 59 (4.44%) Annual household income, N (%) <0.001 <$40,000 243,621 (30.59%) 241,339 (30.53%) 1,647 (36.88%) 635 (47.78%) $40,000-$74,999 222,612 (27.95%) 220,975 (27.95%) 1,284 (28.75%) 353 (26.56%) $75,000-$124,999 171,737 (21.56%) 170,747 (21.60%) 815 (18.25%) 175 (13.17%) $125,000-$199,999 64,332 (8.08%) 64,057 (8.10%) 239 (5.35%) 36 (2.71%) 28,576 (3.59%) 28,449 (3.60%) 108 (2.42%) 19 (1.43%) Unknown 65,504 (8.23%) 65,020 (8.22%) 373 (8.35%) 111 (8.35%) Index year, N (%) <0.001 2014 152,519 (19.15%) 151,000 (19.10%) 1,193 (26.71%) 326 (24.53%) 2015 117,351 (14.74%) 116,318 (14.71%) 788 (17.64%) 245 (18.43%) 2016 104,538 (13.13%) 103,777 (13.13%) 603 (13.50%) 158 (11.89%) 2017 137,597 (17.28%) 136,555 (17.27%) 767 (17.17%) 275 (20.69%) 2018 142,231 (17.86%) 141,433 (17.89%) 619 (13.86%) 179 (13.47%) 2019 142,146 (17.85%) 141,504 (17.90%) 496 (11.11%) 146 (10.99%) © 2021 McCoy RG et al. JAMA Network Open. a Total No DKA/HHS DKA ± HHS HHS p-value U.S. census region, N (%) <0.001 Midwest 144,126 (18.10%) 143,046 (18.09%) 829 (18.56%) 251 (18.89%) Northeast 120,946 (15.19%) 120,193 (15.20%) 538 (12.05%) 215 (16.18%) South 446,286 (56.04%) 442,879 (56.02%) 2,643 (59.18%) 764 (57.49%) West/unknown 85,024 (10.68%) 84,469 (10.68%) 456 (10.21%) 99 (7.45%) Clinical variables Comorbidities, N (%) Hyperglycemic crisis 2,646 (0.33%) 2,063 (0.26%) 510 (11.42%) 73 (5.49%) <0.001 Severe hypoglycemia 6,727 (0.84%) 6,342 (0.80%) 305 (6.83%) 80 (6.02%) <0.001 Retinopathy 123,148 (15.46%) 121,733 (15.40%) 1,093 (24.47%) 322 (24.23%) <0.001 Neuropathy 218,245 (27.40%) 215,790 (27.29%) 1,883 (42.16%) 572 (43.04%) <0.001 Nephropathy 186,900 (23.47%) 184,944 (23.39%) 1,382 (30.94%) 574 (43.19%) <0.001 Cardiovascular disease 259,985 (32.65%) 257,875 (32.62%) 1,527 (34.19%) 583 (43.87%) <0.001 Cerebrovascular disease 92,517 (11.62%) 91,584 (11.58%) 643 (14.40%) 290 (21.82%) <0.001 Peripheral vascular disease 132,101 (16.59%) 130,770 (16.54%) 960 (21.50%) 371 (27.92%) <0.001 Heart failure 85,846 (10.78%) 84,889 (10.74%) 636 (14.24%) 321 (24.15%) <0.001 Dementia 24,052 (3.02%) 23,788 (3.01%) 176 (3.94%) 88 (6.62%) <0.001 Hypertension 686,124 (86.16%) 681,196 (86.16%) 3,680 (82.40%) 1,248 (93.91%) <0.001 Depression 99,487 (12.49%) 98,313 (12.44%) 918 (20.56%) 256 (19.26%) <0.001 COPD 114,033 (14.32%) 112,987 (14.29%) 727 (16.28%) 319 (24.00%) <0.001 Cancer 71,797 (9.02%) 71,287 (9.02%) 365 (8.17%) 145 (10.91%) 0.008 Cirrhosis 8,952 (1.12%) 8,834 (1.12%) 77 (1.72%) 41 (3.09%) <0.001 Treatment variables Hemoglobin A , %, mean (SD) 7.36 (1.63) 7.34 (1.61) 9.37 (2.33) 8.91 (2.42) <0.001 1c Hemoglobin A , N (%) <0.001 1c 46,822 (5.88%) 46,736 (5.91%) 57 (1.28%) 29 (2.18%) 5.7% 6.4% 217,748 (27.34%) 217,308 (27.49%) 288 (6.45%) 152 (11.44%) 6.5% 6.9% 144,631 (18.16%) 144,177 (18.24%) 317 (7.10%) 137 (10.31%) 7.0% 7.9% 182,928 (22.97%) 181,943 (23.01%) 729 (16.32%) 256 (19.26%) 8.0% 8.9% 90,804 (11.40%) 89,817 (11.36%) 800 (17.91%) 187 (14.07%) 9.0% 9.9% 49,029 (6.16%) 48,185 (6.09%) 677 (15.16%) 167 (12.57%) 64,420 (8.09%) 62,421 (7.90%) 1,598 (35.78%) 401 (30.17%) Fills for glucose-lowering medication in the 120 days prior to index date No fills 184,079 (23.11%) 183,138 (23.16%) 709 (15.88%) 232 (17.46%) Insulin fills, N (%) <0.001 Not treated with insulin 632,323 (79.40%) 629,706 (79.65%) 1,924 (43.08%) 693 (52.14%) Basal only (no bolus) 89,977 (11.30%) 88,724 (11.22%) 958 (21.45%) 295 (22.20%) © 2021 McCoy RG et al. JAMA Network Open. a Total No DKA/HHS DKA ± HHS HHS p-value Bolus (± basal) 74,082 (9.30%) 72,157 (9.13%) 1,584 (35.47%) 341 (25.66%) Non-insulin glucose-lowering medications, N (%) Sulfonylurea 203,122 (25.51%) 201,852 (25.53%) 930 (20.82%) 340 (25.58%) <0.001 Metformin 429,036 (53.87%) 426,884 (54.00%) 1,641 (36.74%) 511 (38.45%) <0.001 SGLT2 inhibitor 40,247 (5.05%) 39,933 (5.05%) 280 (6.27%) 34 (2.56%) <0.001 GLP-1 receptor agonist 45,950 (5.77%) 45,632 (5.77%) 248 (5.55%) 70 (5.27%) 0.60 DPP-4 inhibitor 96,962 (12.18%) 96,377 (12.19%) 426 (9.54%) 159 (11.96%) <0.001 Thiazolidinedione 38,668 (4.86%) 38,439 (4.86%) 182 (4.08%) 47 (3.54%) 0.004 Other glucose-lowering medication 7,685 (0.96%) 7,629 (0.96%) 41 (0.92%) 15 (1.13%) 0.79 Abbreviations: COPD, chronic obstructive pulmonary disease; DKA, diabetic ketoacidosis; HHS, hyperglycemic hyperosmolar state. © 2021 McCoy RG et al. JAMA Network Open. eTable 4. Crude and Adjusted Rates of Hyperglycemic Crises Among Patients With Type 1 and Type 2 Diabetes, 2014-2020. Rates adjusted for age (during event), sex, race/ethnicity, U.S. region, and year. Year Type 1 Diabetes Type 2 Diabetes Crude Adjusted Crude Adjusted N per 1000 PY N per 1000 PY N per 1000 PY N per 1000 PY 2014 41.75 43.30 (33.37, 53.24) 4.79 4.27 (3.66, 4.88) 2015 47.3 49.07 (40.24, 57.91) 4.00 3.77 (3.40, 4.13) 2016 48.14 49.80 (42.59, 57.01) 3.96 3.81 (3.46, 4.15) 2017 51.26 53.92 (44.62, 63.21) 3.89 3.95 (3.64, 4.25) 2018 53.43 56.77 (48.45, 65.10) 3.81 4.02 (3.76, 4.29) 2019 60.14 61.36 (52.90, 69.82) 3.96 4.29 (4.02, 4.56) 2020 43.52 46.27 (38.59, 53.95) 3.73 4.12 (3.86, 4.38) Total 50.62 52.69 (48.26, 57.12) 3.70 4.04 (3.88, 4.21) Abbreviations: DKA, diabetic ketoacidosis; HHS, hyperglycemic hyperosmolar state; PY, person-years © 2021 McCoy RG et al. JAMA Network Open. eTable 5. Crude and Adjusted Rates of Hyperglycemic Crises Among Patients With Type 1 Diabetes by Prespecified Subgroup, 2014-2020. These data were used to create Figure 1 in the manuscript. Rates adjusted for age (at index date), sex, race/ethnicity, U.S. region. Crude Adjusted N per 1000 PY N per 1000 PY Age group 18 - 44 years 66.27 77.57 (68.41, 86.72) 45 - 64 years 39.19 43.54 (36.98, 50.09) 65 - 74 years 36.68 38.82 (28.36, 49.27) 45.60 55.64 (38.13, 73.16) Gender Female 62.06 74.91 (66.07, 83.73) Male 39.57 44.04 (38.59, 49.49) Race/ethnicity White 45.69 53.16 (47.69, 58.63) Black 78.83 96.62 (69.44, 123.81) Hispanic 56.06 58.93 (45.24, 72.61) Asian 60.34 66.07 (31.14, 100.99) Annual household income <$40,000 84.73 101.52 (82.31, 120.73) $40,000-$74,999 55.66 65.04 (54.12, 75.96) $75,000-$124,999 46.06 52.97 (43.94, 62.01) $125,000-$199,999 34.42 36.22 (28.43, 44.01) 25.43 26.25 (19.75, 32.75) Abbreviations: DKA, diabetic ketoacidosis; HHS, hyperglycemic hyperosmolar state; PY, person-years. © 2021 McCoy RG et al. JAMA Network Open. eTable 6. Crude and Adjusted Rates of Hyperglycemic Crises Among Patients With Type 2 Diabetes by Prespecified Subgroup, 2014-2020. These data were used to create Figure 2 in the manuscript. Rates adjusted for age (at index date), sex, race/ethnicity, U.S. region. Crude Adjusted N per 1000 PY N per 1000 PY Age group 18 - 44 years 12.7 13.91 (11.82, 16.00) 45 - 64 years 5.12 5.28 (4.96, 5.60) 65 - 74 years 2.79 2.97 (2.79, 3.14) 2.47 2.70 (2.49, 2.90) Gender Female 4.09 4.55 (4.31, 4.79) Male 3.72 4.04 (3.80, 4.27) Race/ethnicity White 3.73 4.15 (3.93, 4.38) Black 5.80 6.34 (5.87, 6.81) Hispanic 3.21 3.26 (2.91, 3.60) Asian 1.44 1.71 (1.31, 2.11) Annual household income <$40,000 5.04 5.78 (5.40, 6.17) $40,000-$74,999 3.65 4.02 (3.75, 4.29) $75,000-$124,999 3.05 3.11 (2.83, 3.40) $125,000-$199,999 2.20 2.19 (1.80, 2.58) 2.36 2.23 (1.70, 2.79) Insulin regimen No insulin 1.87 2.00 (1.87, 2.08) Basal insulin only 7.79 8.35 (7.69, 9.01) Bolus ± basal insulin 17.3 17.73 (16.53, 18.93) Abbreviations: DKA, diabetic ketoacidosis; HHS, hyperglycemic hyperosmolar state; PY, person-years. © 2021 McCoy RG et al. JAMA Network Open. eTable 7. Risk Factors for DKA and HHS (Examined as Independent Outcomes) Among Adults With Type 2 Diabetes, 2014-2020 DKA HHS IRR (95% CI) P-value IRR (95% CI) P-value Age, years 18-44 Ref Ref 45-64 0.54 (0.48, 0.60) <0.001 0.95 (0.73, 1.24) 0.73 65-74 0.39 (0.34, 0.45) <0.001 0.89 (0.67, 1.17) 0.40 0.35 (0.30, 0.41) <0.001 0.92 (0.69, 1.23) 0.57 Gender Female Ref Ref Male 0.95 (0.89, 1.03) 0.19 1.17 (1.04, 1.31) 0.008 Race/Ethnicity White Black 1.04 (0.95, 1.15) 0.37 1.59 (1.40, 1.81) <0.001 Hispanic 0.65 (0.58, 0.73) <0.001 0.80 (0.67, 0.95) 0.01 Asian 0.55 (0.42, 0.71) <0.001 0.99 (0.69, 1.42) 0.95 Other/unknown 0.82 (0.67, 1.00) 0.05 1.01 (0.73, 1.41) 0.94 U.S. census region Midwest Ref Ref Northeast 0.87 (0.77, 0.99) 0.04 1.07 (0.89, 1.30) 0.46 South 1.04 (0.94, 1.14) 0.44 0.94 (0.82, 1.09) 0.44 West/unknown 1.03 (0.90, 1.19) 0.66 0.88 (0.69, 1.12) 0.29 Annual household income <$40,000 Ref Ref $40,000-$74,999 0.90 (0.83, 0.99) 0.03 0.70 (0.61, 0.81) <0.001 $75,000-$124,999 0.80 (0.72, 0.89) <0.001 0.54 (0.45, 0.64) <0.001 $125,000-$199,999 0.66 (0.56, 0.78) <0.001 0.31 (0.23, 0.44) <0.001 0.78 (0.62, 0.99) 0.04 0.42 (0.26, 0.65) <0.001 Unknown 1.06 (0.91, 1.23) 0.48 0.96 (0.76, 1.20) 0.71 Index year 2014 Ref Ref 2015 0.90 (0.81, 1.00) 0.05 1.03 (0.88, 1.22) 0.70 2016 0.93 (0.82, 1.05) 0.24 0.92 (0.76, 1.11) 0.38 2017 0.92 (0.82, 1.03) 0.15 1.18 (1.01, 1.40) 0.04 2018 1.00 (0.89, 1.13) 0.95 0.96 (0.80, 1.16) 0.68 2019 1.05 (0.92, 1.20) 0.48 1.02 (0.83, 1.26) 0.86 Comorbidities Hyperglycemic Crisis 20.32 (17.31, 23.86) <0.001 7.18 (5.68, 9.06) <0.001 Severe hypoglycemia 4.49 (3.77, 5.35) <0.001 3.26 (2.53, 4.20) <0.001 Retinopathy 1.34 (1.22, 1.47) <0.001 1.01 (0.97, 1.26) 0.15 Nephropathy 1.29 (1.19, 1.40) <0.001 1.19 (1.06, 1.34) 0.004 Neuropathy 1.12 (1.03, 1.23) 0.009 1.59 (1.40, 1.80) <0.0001 Cardiovascular disease 0.92 (0.84, 1.00) 0.05 1.00 (0.88, 1.14) 1.00 Cerebrovascular disease 1.12 (1.00, 1.26) 0.06 1.30 (1.12, 1.50) <0.001 Peripheral vascular disease 1.06 (0.96, 1.16) 0.28 1.13 (0.99, 1.30) 0.08 Heart failure 1.01 (0.90, 1.14) 0.89 1.41 (1.21, 1.65) <0.001 Dementia 1.39 (1.14, 1.70) 0.001 1.57 (1.22, 2.01) <0.001 Hypertension 0.74 (0.67, 0.82) <0.001 1.60 (1.29, 1.98) <0.001 Depression 1.48 (1.34, 1.63) <0.001 1.40 (1.21, 1.62) <0.001 COPD 1.03 (0.93, 1.15) 0.53 1.35 (1.18, 1.55) <0.001 Cancer 1.12 (0.98, 1.27) 0.09 1.22 (1.03, 1.46) 0.02 Cirrhosis 1.47 (1.08, 2.01) 0.02 2.71 (1.96, 3.74) <0.001 © 2021 McCoy RG et al. JAMA Network Open. Hemoglobin A 1c 0.54 (0.39, 0.75) <0.001 0.59 (0.40, 0.87) 0.008 5.7% 6.4% 0.63 (0.53, 0.75) <0.001 0.76 (0.60, 0.96) 0.02 6.5% 6.9% Ref Ref 7.0% 7.9% 1.49 (1.29, 1.72) <0.001 1.47 (1.20, 1.80) <0.001 8.0% 8.9% 2.80 (2.41, 3.24) <0.001 2.06 (1.64, 2.58) <0.001 9.0% 9.9% 3.89 (3.31, 4.56) <0.001 3.12 (2.46, 3.95) 0.008 7.22 (6.27, 8.31) <0.001 6.74 (5.49, 8.27) <0.001 Glucose-lowering therapy No fills 1.16 (1.02, 1.32) 0.02 1.00 (0.82, 1.23) 0.99 Insulin use Bolus ± basal Ref Ref Basal only 0.64 (0.57, 0.71) <0.001 0.92 (0.79, 1.08) 0.32 Not treated with insulin 0.31 (0.28, 0.35) <0.001 0.58 (0.49, 0.69) <0.001 Non-insulin medications Metformin 0.72 (0.66, 0.78) <0.001 0.79 (0.69, 0.90) <0.001 Sulfonylurea 0.88 (0.81, 0.96) 0.006 0.97 (0.84, 1.11) 0.66 SGLT2 inhibitor 1.47 (1.27, 1.70) <0.001 0.65 (0.46, 0.93) 0.02 GLP-1 receptor agonist 0.74 (0.64, 0.85) <0.001 0.94 (0.73, 1.20) 0.59 DPP-4 inhibitor 0.84 (0.75, 0.95) 0.004 0.95 (0.80, 1.14) 0.59 Thiazolidinedione 1.18 (0.99, 1.40) 0.07 0.96 (0.72, 1.28) 0.78 Other 0.85 (0.60, 1.20) 0.35 0.83 (0.49, 1.39) 0.47 Abbreviations: COPD, chronic obstructive pulmonary disease; DKA, diabetic ketoacidosis; HHS, hyperglycemic hyperosmolar state. © 2021 McCoy RG et al. JAMA Network Open.

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Sociodemographic, Clinical, and Treatment-Related Factors Associated With Hyperglycemic Crises Among Adults With Type 1 or Type 2 Diabetes in the US From 2014 to 2020

Sociodemographic, Clinical, and Treatment-Related Factors Associated With Hyperglycemic Crises Among Adults With Type 1 or Type 2 Diabetes in the US From 2014 to 2020

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Sociodemographic, Clinical, and Treatment-Related Factors Associated With Hyperglycemic Crises Among Adults With Type 1 or Type 2 Diabetes in the US From 2014 to 2020

Sociodemographic, Clinical, and Treatment-Related Factors Associated With Hyperglycemic Crises Among Adults With Type 1 or Type 2 Diabetes in the US From 2014 to 2020

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