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Association of higher body mass index (BMI) with severe coronavirus disease 2019 (COVID-19) in younger patients

Association of higher body mass index (BMI) with severe coronavirus disease 2019 (COVID-19) in... Association of higher body mass index (BMI) with severe coronavirus disease 2019 (COVID-19) in younger patients 1,2 1,2,3 1,2,3,4 1,2,3,4 Sean Wei Xiang Ong , Barnaby Edward Young , Yee-Sin Leo , David Chien Lye National Centre for Infectious Diseases, Singapore Tan Tock Seng Hospital, Singapore Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore Yong Loo Lin School of Medicine, National University of Singapore Corresponding Author: Dr David Chien Lye National Centre for Infectious Diseases, 16 Jln Tan Tock Seng, Singapore 308442 [email protected] © The Author(s) 2020. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: [email protected]. Accepted Manuscript To the Editor: The coronavirus disease 2019 (COVID-19) pandemic has resulted in significant strain on healthcare systems and intensive care unit (ICU) resources worldwide. Advanced age is a well-recognized risk factor for development of severe disease [1, 2], however the impact of obesity on disease severity has not been thoroughly explored. Obesity was associated with increased severity and mortality in pandemic H1N1 influenza and other respiratory viruses [3, 4]. Lighter and colleagues reported that obesity (defined as body mass index [BMI] ≥30) was significantly associated with increased admission to hospital and critical care [5]. Simonnet and colleagues found that severe obesity (BMI ≥35) was associated with increased requirement of mechanical ventilation [6]. However, there has been limited data on the impact of obesity in Asian populations. It is known that Asian populations have higher disease risks at lower BMI thresholds, possibly due to variations in fat distribution and lipid metabolism [7, 8]. We hypothesized that a lower BMI cut-off level would be associated with severe disease manifestations of COVID-19 in our multi-ethnic Asian population in Singapore. We conducted a retrospective study of 182 patients with laboratory confirmed COVID-19 (by polymerase chain reaction assay) admitted to the National Centre for Infectious Diseases, Singapore. All patients gave written consent (approved by National Healthcare Group Domain Specific Review Board, Study Reference 2012/00917). Clinical data were collected from medical records by study investigators. 91 patients did not have either height or weight recorded and were excluded from analysis. Adverse outcomes analyzed were hypoxia requiring supplemental oxygen, ICU admission, mechanical ventilation, and mortality. In the study population, 51 (56.0%) had BMI <25, 29 (31.9%) had BMI 25 – 30, 7 (7.7%) had BMI 30 – 35, and 4 (4.4%) had BMI >35. There were no significant differences in baseline characteristics or clinical outcomes between patients with BMI ≥25 and patients with BMI <25 when all age groups Accepted Manuscript were included (Table 1). However, similar to findings by Lighter and colleagues, a sub-group analysis of patients aged <60 years old found that BMI ≥25 was significantly associated with pneumonia on chest radiograph on admission (p-value = 0.017), requiring low-flow supplemental oxygen (OR 6.32, 95% CI 1.23 – 32.34) and mechanical ventilation (OR 1.16, 95% CI 1.00 – 1.34). BMI ≥25 was also associated with significantly higher serum lactate dehydrogenase levels (p-value = 0.011), which was associated with disease severity in COVID-19 [9]. These findings add to the growing literature highlighting obesity as a significant risk factor for the development of severe COVID-19, especially in younger patients aged <60 years old. It illustrates the importance of a lower BMI cut-off for risk stratification in Asian populations, similar to what is seen in other metabolic and cardiovascular diseases [7]. As the COVID-19 pandemic progresses, risk stratification for optimal resource allocation will be increasingly important, and this distinct risk group should be emphasized to avoid under-triaging and potentially adverse outcomes. Accepted Manuscript Funding: This study was funded by the NMRC COVID-19 Research Fund (COVID19RF-001). Disclosures: No conflicts of interest declared. Accepted Manuscript References 1. Zhou F, Yu T, Du R, et al. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study. Lancet 2020. 2. Jordan RE, Adab P, Cheng KK. Covid-19: risk factors for severe disease and death. BMJ 2020; 368: m1198. 3. Louie JK, Acosta M, Winter K, et al. Factors associated with death or hospitalization due to pandemic 2009 influenza A(H1N1) infection in California. JAMA 2009; 302(17): 1896-902. 4. Moser JS, Galindo-Fraga A, Ortiz-Hernandez AA, et al. Underweight, overweight, and obesity as independent risk factors for hospitalization in adults and children from influenza and other respiratory viruses. Influenza Other Respir Viruses 2019; 13(1): 3-9. 5. Lighter J, Phillips M, Hochman S, et al. Obesity in patients younger than 60 years is a risk factor for Covid-19 hospital admission. Clin Infect Dis 2020. 6. Simonnet A, Chetboun M, Poissy J, et al. High prevalence of obesity in severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) requiring invasive mechanical ventilation. Obesity (Silver Spring) 2020. 7. Consultation WHOE. Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet 2004; 363(9403): 157-63. 8. Razak F, Anand SS, Shannon H, et al. Defining obesity cut points in a multiethnic population. Circulation 2007; 115(16): 2111-8. 9. Huang C, Wang Y, Li X, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet 2020; 395(10223): 497-506. Accepted Manuscript Table 1. Clinical characteristics and outcomes of patients with BMI ≥25 and BMI <25, for all age groups and those aged <60 years old. Characteristic BMI ≥25 BMI <25 Odds ratio p- value All patients n=40 n=51 Demographics Age, years 51 (35 – 61) 58 (43 – 68) 0.087 Male gender 27 (67.5%) 24 (47.1%) 0.059 Weight, kg 80.2 (69.9 – 57.6 (52.0 – <0.001 91.8) 66.0) Height, m 1.67 (1.60 – 1.63 (1.55 – 0.246 1.74) 1.72) BMI, kg/m 27.8 (25.9 – 22.3 (21.4 – <0.001 30.3) 23.5) Comorbidities Diabetes mellitus 7 (17.5%) 11 (21.6%) 0.792 Hypertension 15 (37.5%) 15 (29.4%) 0.502 Cardiovascular disease 5 (12.5%) 4 (7.8%) 0.499 Smoking 3 (7.9%) 1 (2.0%) 0.314 Charlson’s score 0 (0 – 1) 0 (0 – 1) 0.742 Baseline investigations Pneumonia on chest 21 (52.5%) 17 (33.3%) 0.087 radiograph White blood count (x10 /L) 5.05 (3.40 – 5.40 (4.40 – 0.224 6.15) 6.50) Neutrophil count (x10 /L) 3.18 (2.26 – 3.69 (2.39 – 0.401 4.55) 4.41) Lymphocyte count (x10 /L) 0.89 (0.76 – 1.08 (0.74 – 0.455 1.34) 1.42) C-reactive protein (mg/L) 17.2 (4.4 – 72.1) 12.3 (5.5 – 49.1, 0.375 n=48) Lactate dehydrogenase (U/L) 575 (421 – 655) 474 (375 – 634, 0.094 n=50) Creatinine (umol/L) 83.5 (61 – 94) 69 (60 – 83) 0.084 Clinical outcomes Low flow supplemental 18 (45.0%) 17 (33.3%) 1.64 (95% CI 0.70 – 3.84) 0.284 oxygen High flow supplemental 9 (22.5%) 9 (18.0%) 1.32 (95% CI 0.47 – 3.72) 0.608 oxygen ICU admission 12 (30.0%) 15 (29.4%) 1.03 (95% CI 0.42 – 2.54) 1.000 Mechanical ventilation 8 (20.0%) 8 (15.7%) 1.34 (95% CI 0.46 – 3.96) 0.594 Mortality 1 (2.6%) 3 (6.1%) 0.40 (95% CI 0.04 – 4.04) 0.426 Characteristic BMI ≥25 BMI <25 Odds ratio p- value Patients less than 60 years old n=29 n=26 Demographics Age, years 44 (30 – 52) 43 (27 – 52) 0.613 Male gender 21 (72.4%) 12 (46.2%) 0.058 Weight, kg 81.8 (72.1 – 58.8 (52.8 – <0.001 92.9) 67.3) Height, m 1.68 (1.61 – 1.64 (1.56 – 0.200 1.75) 1.72) BMI, kg/m 27.8 (25.9 – 22.4 (21.3 – <0.001 31.1) 23.6) Accepted Manuscript Comorbidities Diabetes mellitus 2 (6.9%) 2 (7.7%) 0.910 Hypertension 7 (24.1%) 3 (11.5%) 0.303 Cardiovascular disease 1 (3.4%) 0 (0.0%) 0.339 Smoking 2 (6.9%) 1 (3.8%) 0.337 Charlson’s score 0 (0 – 0) 0 (0 – 0) 0.168 Baseline investigations Pneumonia on chest 12 (41.4%) 3 (11.5%) 0.017 radiograph White blood count (x10 /L) 5.00 (3.40 – 5.35 (4.15 – 0.521 6.10) 6.40) Neutrophil count (x10 /L) 3.14 (2.39 – 3.33 (2.17 – 0.768 4.50) 4.38) Lymphocyte count (x10 /L) 0.90 (0.78 – 1.15 (0.83 – 0.197 1.29) 1.88) C-reactive protein (mg/L) 10.7 (3.3 – 54.6) 7.9 (1.8 – 15.5) 0.199 Lactate dehydrogenase (U/L) 512 (406 – 652) 387 (353 – 547, 0.011 n=25) Creatinine (umol/L) 83.0 (60.0 – 66.5 (58.8 – 0.026 94.0) 79.8) Clinical outcomes Low flow supplemental 10 (34.5%) 2 (7.7%) 6.32 (95% CI 1.23 – 0.022 oxygen 32.34) High flow supplemental 5 (17.2%) 1 (3.8%) 5.21 (95% CI 0.57 – 0.197 oxygen 47.90) ICU admission 6 (20.7%) 2 (7.7%) 3.13 (95% CI 0.57 – 0.257 17.13) Mechanical ventilation 4 (13.8%) 0 (0.0%) 1.16 (95% CI 1.00 – 1.34) 0.049 Mortality 0 (0.0%) 0 (0.0%) - - Low flow supplemental oxygen was defined as oxygen flow of ≤5L/min High flow supplemental oxygen was defined as oxygen flow of ≥5L/min, or using a Venturi face mask or high-flow nasal cannula device. Continuous variables are reported as median (interquartile range), and discrete variables are reported as number (percentage). Comparison of discrete variables was with Fisher’s exact test or chi-squared test as appropriate, and comparison of continuous variables was with Mann-Whitney U test. P-value of <0.05 was considered significant. Accepted Manuscript http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Clinical Infectious Diseases: An Official Publication of the Infectious Diseases Society of America Pubmed Central

Association of higher body mass index (BMI) with severe coronavirus disease 2019 (COVID-19) in younger patients

Clinical Infectious Diseases: An Official Publication of the Infectious Diseases Society of AmericaMay 8, 2020

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References (11)

Publisher
Pubmed Central
Copyright
© The Author(s) 2020. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: [email protected].
ISSN
1058-4838
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1537-6591
DOI
10.1093/cid/ciaa548
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Abstract

Association of higher body mass index (BMI) with severe coronavirus disease 2019 (COVID-19) in younger patients 1,2 1,2,3 1,2,3,4 1,2,3,4 Sean Wei Xiang Ong , Barnaby Edward Young , Yee-Sin Leo , David Chien Lye National Centre for Infectious Diseases, Singapore Tan Tock Seng Hospital, Singapore Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore Yong Loo Lin School of Medicine, National University of Singapore Corresponding Author: Dr David Chien Lye National Centre for Infectious Diseases, 16 Jln Tan Tock Seng, Singapore 308442 [email protected] © The Author(s) 2020. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: [email protected]. Accepted Manuscript To the Editor: The coronavirus disease 2019 (COVID-19) pandemic has resulted in significant strain on healthcare systems and intensive care unit (ICU) resources worldwide. Advanced age is a well-recognized risk factor for development of severe disease [1, 2], however the impact of obesity on disease severity has not been thoroughly explored. Obesity was associated with increased severity and mortality in pandemic H1N1 influenza and other respiratory viruses [3, 4]. Lighter and colleagues reported that obesity (defined as body mass index [BMI] ≥30) was significantly associated with increased admission to hospital and critical care [5]. Simonnet and colleagues found that severe obesity (BMI ≥35) was associated with increased requirement of mechanical ventilation [6]. However, there has been limited data on the impact of obesity in Asian populations. It is known that Asian populations have higher disease risks at lower BMI thresholds, possibly due to variations in fat distribution and lipid metabolism [7, 8]. We hypothesized that a lower BMI cut-off level would be associated with severe disease manifestations of COVID-19 in our multi-ethnic Asian population in Singapore. We conducted a retrospective study of 182 patients with laboratory confirmed COVID-19 (by polymerase chain reaction assay) admitted to the National Centre for Infectious Diseases, Singapore. All patients gave written consent (approved by National Healthcare Group Domain Specific Review Board, Study Reference 2012/00917). Clinical data were collected from medical records by study investigators. 91 patients did not have either height or weight recorded and were excluded from analysis. Adverse outcomes analyzed were hypoxia requiring supplemental oxygen, ICU admission, mechanical ventilation, and mortality. In the study population, 51 (56.0%) had BMI <25, 29 (31.9%) had BMI 25 – 30, 7 (7.7%) had BMI 30 – 35, and 4 (4.4%) had BMI >35. There were no significant differences in baseline characteristics or clinical outcomes between patients with BMI ≥25 and patients with BMI <25 when all age groups Accepted Manuscript were included (Table 1). However, similar to findings by Lighter and colleagues, a sub-group analysis of patients aged <60 years old found that BMI ≥25 was significantly associated with pneumonia on chest radiograph on admission (p-value = 0.017), requiring low-flow supplemental oxygen (OR 6.32, 95% CI 1.23 – 32.34) and mechanical ventilation (OR 1.16, 95% CI 1.00 – 1.34). BMI ≥25 was also associated with significantly higher serum lactate dehydrogenase levels (p-value = 0.011), which was associated with disease severity in COVID-19 [9]. These findings add to the growing literature highlighting obesity as a significant risk factor for the development of severe COVID-19, especially in younger patients aged <60 years old. It illustrates the importance of a lower BMI cut-off for risk stratification in Asian populations, similar to what is seen in other metabolic and cardiovascular diseases [7]. As the COVID-19 pandemic progresses, risk stratification for optimal resource allocation will be increasingly important, and this distinct risk group should be emphasized to avoid under-triaging and potentially adverse outcomes. Accepted Manuscript Funding: This study was funded by the NMRC COVID-19 Research Fund (COVID19RF-001). Disclosures: No conflicts of interest declared. Accepted Manuscript References 1. Zhou F, Yu T, Du R, et al. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study. Lancet 2020. 2. Jordan RE, Adab P, Cheng KK. Covid-19: risk factors for severe disease and death. BMJ 2020; 368: m1198. 3. Louie JK, Acosta M, Winter K, et al. Factors associated with death or hospitalization due to pandemic 2009 influenza A(H1N1) infection in California. JAMA 2009; 302(17): 1896-902. 4. Moser JS, Galindo-Fraga A, Ortiz-Hernandez AA, et al. Underweight, overweight, and obesity as independent risk factors for hospitalization in adults and children from influenza and other respiratory viruses. Influenza Other Respir Viruses 2019; 13(1): 3-9. 5. Lighter J, Phillips M, Hochman S, et al. Obesity in patients younger than 60 years is a risk factor for Covid-19 hospital admission. Clin Infect Dis 2020. 6. Simonnet A, Chetboun M, Poissy J, et al. High prevalence of obesity in severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) requiring invasive mechanical ventilation. Obesity (Silver Spring) 2020. 7. Consultation WHOE. Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet 2004; 363(9403): 157-63. 8. Razak F, Anand SS, Shannon H, et al. Defining obesity cut points in a multiethnic population. Circulation 2007; 115(16): 2111-8. 9. Huang C, Wang Y, Li X, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet 2020; 395(10223): 497-506. Accepted Manuscript Table 1. Clinical characteristics and outcomes of patients with BMI ≥25 and BMI <25, for all age groups and those aged <60 years old. Characteristic BMI ≥25 BMI <25 Odds ratio p- value All patients n=40 n=51 Demographics Age, years 51 (35 – 61) 58 (43 – 68) 0.087 Male gender 27 (67.5%) 24 (47.1%) 0.059 Weight, kg 80.2 (69.9 – 57.6 (52.0 – <0.001 91.8) 66.0) Height, m 1.67 (1.60 – 1.63 (1.55 – 0.246 1.74) 1.72) BMI, kg/m 27.8 (25.9 – 22.3 (21.4 – <0.001 30.3) 23.5) Comorbidities Diabetes mellitus 7 (17.5%) 11 (21.6%) 0.792 Hypertension 15 (37.5%) 15 (29.4%) 0.502 Cardiovascular disease 5 (12.5%) 4 (7.8%) 0.499 Smoking 3 (7.9%) 1 (2.0%) 0.314 Charlson’s score 0 (0 – 1) 0 (0 – 1) 0.742 Baseline investigations Pneumonia on chest 21 (52.5%) 17 (33.3%) 0.087 radiograph White blood count (x10 /L) 5.05 (3.40 – 5.40 (4.40 – 0.224 6.15) 6.50) Neutrophil count (x10 /L) 3.18 (2.26 – 3.69 (2.39 – 0.401 4.55) 4.41) Lymphocyte count (x10 /L) 0.89 (0.76 – 1.08 (0.74 – 0.455 1.34) 1.42) C-reactive protein (mg/L) 17.2 (4.4 – 72.1) 12.3 (5.5 – 49.1, 0.375 n=48) Lactate dehydrogenase (U/L) 575 (421 – 655) 474 (375 – 634, 0.094 n=50) Creatinine (umol/L) 83.5 (61 – 94) 69 (60 – 83) 0.084 Clinical outcomes Low flow supplemental 18 (45.0%) 17 (33.3%) 1.64 (95% CI 0.70 – 3.84) 0.284 oxygen High flow supplemental 9 (22.5%) 9 (18.0%) 1.32 (95% CI 0.47 – 3.72) 0.608 oxygen ICU admission 12 (30.0%) 15 (29.4%) 1.03 (95% CI 0.42 – 2.54) 1.000 Mechanical ventilation 8 (20.0%) 8 (15.7%) 1.34 (95% CI 0.46 – 3.96) 0.594 Mortality 1 (2.6%) 3 (6.1%) 0.40 (95% CI 0.04 – 4.04) 0.426 Characteristic BMI ≥25 BMI <25 Odds ratio p- value Patients less than 60 years old n=29 n=26 Demographics Age, years 44 (30 – 52) 43 (27 – 52) 0.613 Male gender 21 (72.4%) 12 (46.2%) 0.058 Weight, kg 81.8 (72.1 – 58.8 (52.8 – <0.001 92.9) 67.3) Height, m 1.68 (1.61 – 1.64 (1.56 – 0.200 1.75) 1.72) BMI, kg/m 27.8 (25.9 – 22.4 (21.3 – <0.001 31.1) 23.6) Accepted Manuscript Comorbidities Diabetes mellitus 2 (6.9%) 2 (7.7%) 0.910 Hypertension 7 (24.1%) 3 (11.5%) 0.303 Cardiovascular disease 1 (3.4%) 0 (0.0%) 0.339 Smoking 2 (6.9%) 1 (3.8%) 0.337 Charlson’s score 0 (0 – 0) 0 (0 – 0) 0.168 Baseline investigations Pneumonia on chest 12 (41.4%) 3 (11.5%) 0.017 radiograph White blood count (x10 /L) 5.00 (3.40 – 5.35 (4.15 – 0.521 6.10) 6.40) Neutrophil count (x10 /L) 3.14 (2.39 – 3.33 (2.17 – 0.768 4.50) 4.38) Lymphocyte count (x10 /L) 0.90 (0.78 – 1.15 (0.83 – 0.197 1.29) 1.88) C-reactive protein (mg/L) 10.7 (3.3 – 54.6) 7.9 (1.8 – 15.5) 0.199 Lactate dehydrogenase (U/L) 512 (406 – 652) 387 (353 – 547, 0.011 n=25) Creatinine (umol/L) 83.0 (60.0 – 66.5 (58.8 – 0.026 94.0) 79.8) Clinical outcomes Low flow supplemental 10 (34.5%) 2 (7.7%) 6.32 (95% CI 1.23 – 0.022 oxygen 32.34) High flow supplemental 5 (17.2%) 1 (3.8%) 5.21 (95% CI 0.57 – 0.197 oxygen 47.90) ICU admission 6 (20.7%) 2 (7.7%) 3.13 (95% CI 0.57 – 0.257 17.13) Mechanical ventilation 4 (13.8%) 0 (0.0%) 1.16 (95% CI 1.00 – 1.34) 0.049 Mortality 0 (0.0%) 0 (0.0%) - - Low flow supplemental oxygen was defined as oxygen flow of ≤5L/min High flow supplemental oxygen was defined as oxygen flow of ≥5L/min, or using a Venturi face mask or high-flow nasal cannula device. Continuous variables are reported as median (interquartile range), and discrete variables are reported as number (percentage). Comparison of discrete variables was with Fisher’s exact test or chi-squared test as appropriate, and comparison of continuous variables was with Mann-Whitney U test. P-value of <0.05 was considered significant. Accepted Manuscript

Journal

Clinical Infectious Diseases: An Official Publication of the Infectious Diseases Society of AmericaPubmed Central

Published: May 8, 2020

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