Hemoglobin concentration does not impact 3-month outcome following acute ischemic stroke

Hemoglobin concentration does not impact 3-month outcome following acute ischemic stroke Background: There is uncertainty regarding the effect of anemia and red blood cell transfusion on functional outcome following acute ischemic stroke. We studied the relationship of hemoglobin parameters and red cell transfusion with post stroke functional outcome after adjustment for neurological severity and medical comorbidities. Methods: Retrospective cohort study of 536 patients discharged with a diagnosis of ischemic stroke from a tertiary care hospital between January 2012 and April 2015. Hemoglobin level at hospital admission, lowest recorded value during hospitalization (nadir), delta hemoglobin (admission minus nadir), red cell transfusion during hospitalization were noted. Charlson Comorbidity Index (CCI) was computed as a summary measure of medical comorbidities. A multivariable logistic regression model was used to determine risk-adjusted odds of unfavorable outcome, defined as a modified Rankin Score of > 2. Results: Anemia was present on hospital admission in 31% of patients. Forty five percent of patients had unfavorable outcome. In the univariable analysis increasing age, admission National Institutes of Health Stroke Scale (NIHSS), CCI, nadir hemoglobin, delta hemoglobin and blood transfusion were associated with unfavorable outcome. In the multivariable model, only increasing age, CCI and NIHSS remained associated with unfavorable outcome. No quadratic association was found on repeating the model to identify a possible U-shaped relationship of hemoglobin with outcome. Conclusions: Our findings contradict prior observational studies and highlight an area of clinical equipoise regarding the optimal management of anemia in patients hospitalized for ischemic stroke. This uncertainty could be addressed with appropriately designed clinical trials. Keywords: Ischemic stroke, Anemia, Hemoglobin, Transfusion, Disability, Mortality, Charlson comorbidity index Background term post-stroke functional outcome [3, 7]. However, Anemia is a frequent comorbid or complicating factor in one study found this association only in a subgroup of patients with ischemic stroke, yet the influence of patients with less severe strokes [8] and another large hemoglobin (Hb) concentration on stroke outcome is a cohort study with meta-analysis did not find any associ- matter of considerable uncertainty. Increases in mortal- ation with functional outcome [2]. ity following ischemic stroke have been associated with Several factors may contribute to these differences in abnormally low Hb level [1–5] as well as abnormally findings. First, Hb-related exposure/predictor variables are high Hb level [6], or both high and low levels in the not consistently reported across studies. For example, dy- same cohort [7]. Observational studies have suggested namic assessments of anemia after ischemic stroke, such an unfavorable impact of admission anemia on long as the decrease in Hb or the nadir Hb, were shown to be independently predictive of worse outcome in one report [9], however most studies have not evaluated anemia in * Correspondence: ksharma@kumc.edu Department of Anesthesiology and Critical Care Medicine, Johns Hopkins this way. Second, statistical models vary widely across University School of Medicine, Baltimore, USA studies particularly regarding the use of multivariable ap- Department of Neurology, Johns Hopkins University School of Medicine, proaches, and in the selection of covariates used in the Baltimore, USA Full list of author information is available at the end of the article © The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Sharma et al. BMC Neurology (2018) 18:78 Page 2 of 5 multivariable models. For example, it is plausible that red as delta (difference between admission and nadir) Hb. In blood cell (RBC) transfusion will modify any presumed secondary analyses, we repeated our model to address two impact of anemia on stroke pathophysiology, yet RBC issues. First, to investigate a possible quadratic relation- transfusion is not consistently adjusted for across studies. ship of Hb with outcome, we included Hb squared as a Lastly, anemia can be regarded as a marker of underlying continuous variable. Second, instead of linear or quadratic medical illnesses which can influence outcome independ- Hb values, we used anemia as a categorical predictor (Hb ently of any direct mechanistic effect on the ischemic < 12 g/dl for women and < 13 g/dl for men) [10]. P value brain. Variability in study results may therefore reflect un- threshold was set at ≤0.05 for statistical significance. Ana- measured or unreported confounders (e.g. acquired im- lyses were performed using JMP®, Version 12.1 (SAS Insti- mune deficiency syndrome, malignancy, malnutrition and tute Inc., Cary, NC). liver failure) which can influence Hb level, functional out- come or both. Results To clarify these effects, we examined the relationship A total of 536 patients were included in the study. Patient of Hb indices including admission, nadir, discharge and characteristics and hemoglobin parameters are provided in change in Hb level with 3-month functional outcome in Table 1. The prevalence of anemia on admission was 31% a large hospital-based stroke registry, adjusting for RBC in the study sample. The proportion of anemic women transfusion and for medical comorbidities using the (38%) was significantly higher than men (26%), P =0.002. comprehensive Charlson Comorbidity Index (CCI). During the hospitalization, the prevalence of anemia in- creased to 59% based on nadir Hb values. Methods Three-month unfavorable outcome, defined as a We queried the Johns Hopkins Hospital stroke registry, mRS > 2, was noted in 243 (45%) patients, of whom 34 a prospective database, for patients aged 18 and above (6%) died within the 3-month follow up period. In the who were discharged with a diagnosis of ischemic stroke univariable analysis, greater age, higher NIHSS score, between Jan 1st 2012 and Apr 30th 2015. For patients CCI, lower nadir Hb, larger delta Hb, and RBC transfu- admitted more than once with acute ischemic stroke, we sion were associated with unfavorable outcome (Table 2). considered only the earliest hospitalization. Out of a In the multivariable model, age, CCI and NIHSS total of 802 patients, modified Rankin Scale (mRS) at remained associated with worse outcome (Table 2). 3 months was available for 536 patients. These patients However, the associations of nadir or delta Hb and RBC were cross-referenced against a separate Blood Product transfusion with unfavorable outcome were not signifi- Utilization Database established by one of the cant in the risk-adjusted analysis (Table 3). Modeling co-investigators (SMF). Predictor variables were clinical performed with admission Hb as a dichotomized value characteristics including pre-admission CCI, laboratory (anemia vs no anemia) did not reveal significant associ- values and record of blood product transfusions during ation on multivariable analysis (Table 3). In post hoc the hospitalization. Anemia was defined as per the analyses using only death as the outcome of interest, Hb World Health Organization as a serum Hb of < 13 g/dL indices were again not associated with mortality. There in men and < 12 g/dL in women [10]. The principal out- was no quadratic relationship of Hb with mortality or come variable was unfavorable functional status defined functional outcome (models not shown). as mRS > 2 at 3 months follow up. Statistical analyses: Exploratory univariable analysis Discussion was performed to determine strength of the association In this large cohort of patients admitted to a tertiary between potential predictors and the principal outcome care center with ischemic stroke, anemia was present on variable. Nominal logistic regression was used for con- admission in nearly one third of cases. Moreover, anemia tinuous variables and Pearson’s chi-squared test for cat- developed after admission in 28% of patients who were egorical variables. Covariates having a P value < 0.1 on initially hospitalized without anemia. Nevertheless, in univariable analysis were used in a multiple logistic re- carefully risk adjusted models, neither anemia on ad- gression model with unfavorable outcome as the mission nor anemia during hospitalization, nor any dependent variable. Of note, despite having no association Hb-associated variable, nor RBC transfusion was sig- on univariable testing (P = 0.59), intravenous tissue plas- nificantly associated with functional status at minogen activator (tPA) administration was included in 3 months. Taken in the context of other published the multivariable models because of its well-established ef- studies, the results illustrate an area of significant un- ficacy in improving stroke outcomes. We tested using sep- certainty in the evaluation and management of pa- arate models, the following Hb indices as continuous tients with ischemic stroke. variables for strength of association with outcome: admis- Putative mechanisms for how anemia may influence sion, nadir, last recorded serum Hb concentration, as well the pathophysiology and outcome of ischemic stroke Sharma et al. BMC Neurology (2018) 18:78 Page 3 of 5 Table 1 Patient characteristics (N = 536) include reduction of oxygen carrying capacity to the penumbral regions [11], the generation of a hyperkinetic Characteristic No. (%) of Patients thrombogenic state especially in acute blood loss [12] Female 244 (45.5) and the association with a proinflammatory state [13]. Age, mean (SD), y 62 (15) However, findings from studies looking at the associ- Admission NIHSS score ation of Hb with functional outcome after stroke have Median (IQR) 3 (5) been inconsistent. Tanne et al. reported significantly in- Mean (SD) 5.2 (5.5) creased odds of combined death and disability (Barthel NIHSS < 10 450 (84) Index < 75) at 1 year in patients with anemia [7]. Simi- larly, Milionis et al. reported significantly increased odds Hemoglobin parameters of poor functional status measured with mRS at Admission Hb, mean (SD), g/dl 13.2 (1.9) 3 months and 1 year in anemic vs non-anemic patients Nadir Hb, mean (SD), g/dl 11.7 (2.3) [3]. In contrast, Hao et al. found no association between Delta Hb, median (IQR), g/dl 1.1 (1.9) anemia and measures of disability in their cohort and Charlson Comorbidity Index, median (IQR) 3 (3) meta-analysis of similar studies published in the period Body mass index ≥30 58 (11) 2007–2013 [2]. Increased mortality in anemic patients has been demon- Congestive heart failure 66 (12) strated in studies with follow up periods ranging from Hypertension 90 (17) 1 month to 3 years [1–5]. This seemingly intuitive relation- Diabetes mellitus 157 (29) ship has not borne out uniformly. Furlan et al. noted no as- Renal disease 63 (12) sociation of low Hb with 7-day and 30-day mortality but Liver disease 14 (3) slight increase in 90-day mortality [6]. Some caveats bear HIV positive 6 (1) mentioning when interpreting these data. Two of these large cohort studies did not incorporate stroke severity as a Intravenous alteplase administered 39 (7) covariate influencing mortality [4, 5]. There also seems to Length of stay, median (IQR) 3 (5) be publication bias favoring reports with increased odds of Red blood cell transfusion 28 (5) mortality in anemic patients with stroke [5, 14]. 3-month modified Rankin scale score Some data suggest that both low and high Hb may be 0 98 (18) linked with increased mortality. In the study by Furlan et 1 90 (17) al., abnormally high Hb was robustly associated with in- creased mortality at all follow up intervals [6]. Tanne et al. 2 105 (20) found increased mortality rates at both low and high Hb 3 121 (23) concentrations [7]. Thrombogenic effects and compro- 4 68 (13) mised collateral flow have been postulated as mechanisms 5 20 (4) worsening outcomes in patients with supranormal serum 6 34 (6) Hb values. An alternative explanation would be that both Abbreviations: HIV human immunodeficiency virus, IQR interquartile range, extremes of Hb concentration are biomarkers of systemic NIHSS National Institutes of Health stroke scale, SD standard deviation medical comorbidities which are the true drivers of Table 2 Univariable and multivariable predictors of unfavorable outcome (mRS > 2) a b Univariable Analysis Multivariable analysis OR (95% CI) P Value Adjusted OR (95% CI) P value Age 1.02 (1.01–1.04) < 0.001 1.02 (1.01–1.04) 0.001 NIHSS score 1.26 (1.19–1.33) < 0.001 1.30 (1.23–1.39) < 0.001 IV alteplase use 0.84 (0.42–1.61) 0.59 0.19 (0.07–0.46) < 0.001 Charlson Comorbidity Index 1.30 (1.17–1.44) < 0.001 1.25 (1.11–1.41) < 0.001 Nadir Hb 0.82 (0.76–0.89) < 0.001 0.99 (0.89–1.10) 0.84 Delta Hb 1.40 (1.20–1.60) < 0.001 Anemia during hospitalization 1.60 (1.15–2.33) 0.006 Red blood cell transfusion 2.67 (1.21–6.31) 0.013 1.45 (0.49–4.40) 0.50 Abbreviations: CI Confidence interval, OR Odds ratio, Hb Hemoglobin Odds ratios are per unit change for continuous variables (Age,y; NIHSS score; Charlson Comorbidity Index; Nadir Hb, g/dl; Delta Hb, g/dl; Body Mass Index) Only one multivariable model shown here. Results for models with other Hb indices shown in Table 3. Sharma et al. BMC Neurology (2018) 18:78 Page 4 of 5 Table 3 Unadjusted and adjusted odds ratios for unfavorable outcome with different hemoglobin variables OR (95% CI) P value Adjusted OR (95% CI) P value Admission Hb 0.96 (0.88–1.05) 0.47 1.05 (0.94–1.17) 0.34 Nadir Hb 0.82 (0.76–0.89) < 0.001 0.99 (0.89–1.1) 0.84 Last Hb 0.82 (0.76–0.89) < 0.001 0.98 (0.88–1.09) 0.75 Delta Hb 1.40 (1.20–1.60) < 0.001 1.14 (0.97–1.34) 0.09 Nadir Hb in patients with NIHSS < 10 0.86 (0.79–0.94) 0.002 0.99 (0.88–1.1) 0.93 Anemia during hospitalization 1.60 (1.15–2.33) 0.006 0.83 (0.5–1.3) 0.41 Abbreviations: Hb hemoglobin Models were adjusted for age, NIHSS, Charlson Comorbidity Index, delta Hb and red blood cell transfusion mortality. Indeed, we did not find any such quadratic as- illness, does not materially affect prognosis from ischemic sociation of mortality with Hb parameters. stroke. Perhaps the central nervous system adaptation to It has been also been postulated that with increasing chronic anemia may be protective in the setting of acute severity of stroke, the relative impact of anemia on out- ischemia, similar to the neuroprotective effect of hypoxic come may become insignificant due to the extent of preconditioning in a rodent model of ischemic stroke [19]. neurological injury [8, 9, 15]. Sico et al. reported an as- Another potentially important factor is the intrinsic bio- sociation of low hematocrit (< 30%) with combined out- logical heterogeneity in populations of patients with ische- come of death and discharge to hospice in patients with mic stroke [20]. An emerging body of research is mild to moderate stroke (NIHSS < 10) but not in those demonstrating that variance in the risk, presentation and with more severe strokes [8]. In another set of studies, outcomes of ischemic stroke is determined to a significant Kellert et al. implicated post-admission drop in Hb levels degree by underlying genetic factors [21], suggesting that in worsening functional outcome in thrombolysed pa- anemia and RBC transfusion could have differential effects tients admitted to the stroke unit, but found no such as- depending on underlying (and yet insufficiently character- sociation in their neurological intensive care unit ized) patient-specific characteristics. patients with more severe illness [9, 15]. In our cohort, Inconsistent results from available studies suggest a however, there was no association of Hb parameters with state of clinical equipoise regarding the optimal manage- mortality or functional outcome in the subgroup of pa- ment of anemia in patients with acute ischemic stroke. tients with NIHSS < 10 (n = 450, Table 3). Resolving this uncertainty could involve 3 linked strat- Strengths of this study include the relatively large sample egies. First, prospective studies are needed with sample size, adjustment for stroke severity and the use of the CCI sizes adequately powered to answer primary hypotheses. as a summary measure for comorbidity information. Due Such studies must use carefully designed modeling ap- to the large number of conditions that may be covariant proaches that control for a range of potential con- with anemia and mortality, a summary measure provides founders and focus on functional outcomes in addition the convenience of a single number that adequately cap- to mortality. Consistency in the use of comorbidity sum- tures information from individual comorbidities [16]. The mary measures and outcome measures may enable pool- CCI hasbeeninextensive useinadministrativedatabases ing of data across studies to overcome the limitations of and has been validated as a prognostic indicator in ischemic sample size. Second, research is needed to discover and stroke as well [17, 18]. Consistent use of such a measure validate sensitive and specific biomarkers to guide man- will be useful in comparing and pooling data across studies agement of anemia (e.g. timing of transfusion, optimal in future. Limitations of the study include the retrospective Hb cutoffs) in stratified subsets or individuals with is- design and potential selection bias due to exclusion of pa- chemic stroke. Third, carefully designed and adequately tients with missing mRS data. We did not have docu- powered randomized controlled trials (preferably mented pre-stroke mRS for the study patients. Change in biomarker-guided) are warranted to address primary mRS would certainly be a more accurate outcome measure questions on the role of higher versus lower Hb manage- than post-stroke value alone. Lastly, we could not extract ment thresholds in ischemic stroke populations. information about mechanism of stroke in our patients. It is entirely plausible that different stroke subtypes may be Conclusion differentially affected by abnormal hemoglobin levels. Our study demonstrated no association of hemoglobin In summary, in our cohort of patients with ischemic parameters with mortality and 3-month functional out- stroke, admission, nadir or change in Hb were not pre- come, which contradicts prior observational evidence. dictive of 3-month functional outcome. It is possible that This uncertainty could be addressed with appropriately mild to moderate anemia, other than being a marker of designed clinical trials. Sharma et al. BMC Neurology (2018) 18:78 Page 5 of 5 Abbreviations 7. Tanne D, Molshatzki N, Merzeliak O, Tsabari R, Toashi M, Schwammenthal Y. CCI: Charlson Comorbidity Index; CI: Confidence interval; Hb: Hemoglobin; Anemia status, hemoglobin concentration and outcome after acute stroke: a HIV: Human immunodeficiency virus; IQR: Interquartile range; mRS: Modified cohort study. BMC Neurol. 2010;10:22. https://doi.org/10.1186/1471-2377-10-22. rankin scale; NIHSS: National Institutes of Health Stroke Scale; OR: Odds ratio; 8. Sico JJ, Concato J, Wells CK, Lo AC, Nadeau SE, Williams LS, et al. Anemia is RBC: Red blood cell; SD: Standard deviation; tPA: Tissue plasminogen associated with poor outcomes in patients with less severe ischemic stroke. activator J Stroke Cerebrovasc Dis. 2013;22:271–8. https://doi.org/10.1016/j. jstrokecerebrovasdis.2011.09.003. 9. Kellert L, Martin E, Sykora M, Bauer H, Gussmann P, Diedler J, et al. Cerebral Availability of data and materials oxygen transport failure?: decreasing hemoglobin and hematocrit levels The datasets used and/or analyzed during the current study are available after ischemic stroke predict poor outcome and mortality: STroke: RelevAnt from the corresponding author on reasonable request. impact of hemoGlobin, hematocrit and transfusion (STRAIGHT)–an observational study. Stroke. 2011;42:2832–7. https://doi.org/10.1161/ Authors’ contributions strokeaha.110.606665. Conception: KS, RDS, SMF; Data acquisition: KS, BJ, RDS, SMF, DJJ; Analysis 10. Fagnoul D, Combes A, De Backer D. Extracorporeal cardiopulmonary and interpretation of data: KS, RDS, SMF, DJJ; Manuscript drafting: KS, RDS, resuscitation. Curr Opin Crit Care. 2014;20:259–65. https://doi.org/10.1097/ SMF; All authors were involved in critical revision of the manuscript and mcc.0000000000000098. approved the final manuscript. 11. Dexter F, Hindman BJ. Effect of haemoglobin concentration on brain oxygenation in focal stroke: a mathematical modelling study. Br J Anaesth. Ethics approval and consent to participate 1997;79:346–51. Institutional review board approval (Johns Hopkins Hospital IRB, East 12. Kim JS, Kang SY. Bleeding and subsequent anemia: a precipitant for cerebral Baltimore Campus, NA_00078426) with a waiver for written informed infarction. Eur Neurol. 2000;43:201–8. doi: 8176 consent was obtained to retrospectively assess changes in blood utilization 13. Ferrucci L, Guralnik JM, Woodman RC, Bandinelli S, Lauretani F, Corsi AM, et and clinical outcomes at the Johns Hopkins Hospital. Only previously al. Proinflammatory state and circulating erythropoietin in persons with and collected data were analyzed and no study participants were asked to be without anemia. Am J Med. 2005;118:1288. https://doi.org/10.1016/j. involved. The IRB allowed review of patient records in a NON-de-identified amjmed.2005.06.039. fashion if necessary to verify or complete missing data elements in the 14. Li Z, Zhou T, Li Y, Chen P, Chen L. Anemia increases the mortality risk in database. patients with stroke: a meta-analysis of cohort studies. Sci Rep. 2016;6: 26636. https://doi.org/10.1038/srep26636. 15. Kellert L, Herweh C, Sykora M, Gussmann P, Martin E, Ringleb PA, et al. Loss of Competing interests penumbra by impaired oxygen supply? Decreasing hemoglobin levels predict Steven M. Frank has received compensation from Haemonetics and infarct growth after acute ischemic stroke: stroke: Relevant impact of Medtronic for serving on their advisory boards. The rest of the authors (KS, hemoglobin, hematocrit and transfusion (STRAIGHT) - an observational study. DJ, BJ, RS) declare that they have no conflict of interest. Cerebrovasc Dis Extra. 2012;2:99–107. https://doi.org/10.1159/000343731. 16. Austin SR, Wong Y-N, Uzzo RG, Beck JR, Egleston BL. Why summary comorbidity measures such as the Charlson comorbidity index and Publisher’sNote Elixhauser score work. Med Care. 2015;53:e65–72. https://doi.org/10.1097/ Springer Nature remains neutral with regard to jurisdictional claims in MLR.0b013e318297429c. published maps and institutional affiliations. 17. Goldstein LB, Samsa GP, Matchar DB, Horner RD. Charlson index comorbidity adjustment for ischemic stroke outcome studies. Stroke. 2004; Author details 1 35:1941–5. https://doi.org/10.1161/01.STR.0000135225.80898.1c. Department of Anesthesiology and Critical Care Medicine, Johns Hopkins 2 18. Tessier A, Finch L, Daskalopoulou SS, Mayo NE. Validation of the Charlson University School of Medicine, Baltimore, USA. Department of Neurology, 3 comorbidity index for predicting functional outcome of stroke. Arch Phys Johns Hopkins University School of Medicine, Baltimore, USA. Department Med Rehabil. 2008;89:1276–83. https://doi.org/10.1016/j.apmr.2007.11.049. of Neurology, University of Kansas Medical Center, Mailstop 2012, 3901 4 19. Wacker BK, Perfater JL, Gidday JM. Hypoxic preconditioning induces stroke Rainbow Blvd, Kansas City, KS 66160, USA. Department of Neurosurgery, tolerance in mice via a cascading HIF, sphingosine kinase, and CCL2 signaling Johns Hopkins University School of Medicine, Baltimore, USA. pathway. J Neurochem. 2012;123:954–62. https://doi.org/10.1111/jnc.12047. 20. Rostanski SK, Marshall RS. Precision medicine for ischemic stroke. JAMA Received: 18 January 2018 Accepted: 28 May 2018 Neurol. 2016;73:773–4. https://doi.org/10.1001/jamaneurol.2016.0087. 21. Falcone GJ, Malik R, Dichgans M, Rosand J. Current concepts and clinical applications of stroke genetics. Lancet Neurol. 2014;13:405–18. https://doi. References org/10.1016/s1474-4422(14)70029-8. 1. Nybo M, Kristensen SR, Mickley H, Jensen JK. The influence of anaemia on stroke prognosis and its relation to N-terminal pro-brain natriuretic peptide. Eur J Neurol. 2007;14:477–82. https://doi.org/10.1111/j.1468-1331.2006.01591.x. 2. Hao Z, Wu B, Wang D, Lin S, Tao W, Liu M. A cohort study of patients with anemia on admission and fatality after acute ischemic stroke. J Clin Neurosci. 2013;20:37–42. https://doi.org/10.1016/j.jocn.2012.05.020. 3. Milionis H, Papavasileiou V, Eskandari A, D’Ambrogio-Remillard S, Ntaios G, Michel P. Anemia on admission predicts short- and long-term outcomes in patients with acute ischemic stroke. Int J Stroke. 2015;10:224–30. https://doi. org/10.1111/ijs.12397. 4. Huang WY, Chen IC, Meng L, Weng WC, Peng TI. The influence of anemia on clinical presentation and outcome of patients with first-ever atherosclerosis-related ischemic stroke. J Clin Neurosci. 2009;16:645–9. https://doi.org/10.1016/j.jocn.2008.08.014. 5. Barlas RS, Honney K, Loke YK, McCall SJ, Bettencourt-Silva JH, Clark AB, et al. Impact of hemoglobin levels and Anemia on mortality in acute stroke: analysis of UK regional registry data, systematic review, and meta-analysis. J Am Heart Assoc. 2016;5 https://doi.org/10.1161/jaha.115.003019. 6. Furlan JC, Fang J, Silver FL. Acute ischemic stroke and abnormal blood hemoglobin concentration. Acta Neurol Scand. 2016;134:123–30. https://doi. org/10.1111/ane.12521. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png BMC Neurology Springer Journals

Hemoglobin concentration does not impact 3-month outcome following acute ischemic stroke

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Abstract

Background: There is uncertainty regarding the effect of anemia and red blood cell transfusion on functional outcome following acute ischemic stroke. We studied the relationship of hemoglobin parameters and red cell transfusion with post stroke functional outcome after adjustment for neurological severity and medical comorbidities. Methods: Retrospective cohort study of 536 patients discharged with a diagnosis of ischemic stroke from a tertiary care hospital between January 2012 and April 2015. Hemoglobin level at hospital admission, lowest recorded value during hospitalization (nadir), delta hemoglobin (admission minus nadir), red cell transfusion during hospitalization were noted. Charlson Comorbidity Index (CCI) was computed as a summary measure of medical comorbidities. A multivariable logistic regression model was used to determine risk-adjusted odds of unfavorable outcome, defined as a modified Rankin Score of > 2. Results: Anemia was present on hospital admission in 31% of patients. Forty five percent of patients had unfavorable outcome. In the univariable analysis increasing age, admission National Institutes of Health Stroke Scale (NIHSS), CCI, nadir hemoglobin, delta hemoglobin and blood transfusion were associated with unfavorable outcome. In the multivariable model, only increasing age, CCI and NIHSS remained associated with unfavorable outcome. No quadratic association was found on repeating the model to identify a possible U-shaped relationship of hemoglobin with outcome. Conclusions: Our findings contradict prior observational studies and highlight an area of clinical equipoise regarding the optimal management of anemia in patients hospitalized for ischemic stroke. This uncertainty could be addressed with appropriately designed clinical trials. Keywords: Ischemic stroke, Anemia, Hemoglobin, Transfusion, Disability, Mortality, Charlson comorbidity index Background term post-stroke functional outcome [3, 7]. However, Anemia is a frequent comorbid or complicating factor in one study found this association only in a subgroup of patients with ischemic stroke, yet the influence of patients with less severe strokes [8] and another large hemoglobin (Hb) concentration on stroke outcome is a cohort study with meta-analysis did not find any associ- matter of considerable uncertainty. Increases in mortal- ation with functional outcome [2]. ity following ischemic stroke have been associated with Several factors may contribute to these differences in abnormally low Hb level [1–5] as well as abnormally findings. First, Hb-related exposure/predictor variables are high Hb level [6], or both high and low levels in the not consistently reported across studies. For example, dy- same cohort [7]. Observational studies have suggested namic assessments of anemia after ischemic stroke, such an unfavorable impact of admission anemia on long as the decrease in Hb or the nadir Hb, were shown to be independently predictive of worse outcome in one report [9], however most studies have not evaluated anemia in * Correspondence: ksharma@kumc.edu Department of Anesthesiology and Critical Care Medicine, Johns Hopkins this way. Second, statistical models vary widely across University School of Medicine, Baltimore, USA studies particularly regarding the use of multivariable ap- Department of Neurology, Johns Hopkins University School of Medicine, proaches, and in the selection of covariates used in the Baltimore, USA Full list of author information is available at the end of the article © The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Sharma et al. BMC Neurology (2018) 18:78 Page 2 of 5 multivariable models. For example, it is plausible that red as delta (difference between admission and nadir) Hb. In blood cell (RBC) transfusion will modify any presumed secondary analyses, we repeated our model to address two impact of anemia on stroke pathophysiology, yet RBC issues. First, to investigate a possible quadratic relation- transfusion is not consistently adjusted for across studies. ship of Hb with outcome, we included Hb squared as a Lastly, anemia can be regarded as a marker of underlying continuous variable. Second, instead of linear or quadratic medical illnesses which can influence outcome independ- Hb values, we used anemia as a categorical predictor (Hb ently of any direct mechanistic effect on the ischemic < 12 g/dl for women and < 13 g/dl for men) [10]. P value brain. Variability in study results may therefore reflect un- threshold was set at ≤0.05 for statistical significance. Ana- measured or unreported confounders (e.g. acquired im- lyses were performed using JMP®, Version 12.1 (SAS Insti- mune deficiency syndrome, malignancy, malnutrition and tute Inc., Cary, NC). liver failure) which can influence Hb level, functional out- come or both. Results To clarify these effects, we examined the relationship A total of 536 patients were included in the study. Patient of Hb indices including admission, nadir, discharge and characteristics and hemoglobin parameters are provided in change in Hb level with 3-month functional outcome in Table 1. The prevalence of anemia on admission was 31% a large hospital-based stroke registry, adjusting for RBC in the study sample. The proportion of anemic women transfusion and for medical comorbidities using the (38%) was significantly higher than men (26%), P =0.002. comprehensive Charlson Comorbidity Index (CCI). During the hospitalization, the prevalence of anemia in- creased to 59% based on nadir Hb values. Methods Three-month unfavorable outcome, defined as a We queried the Johns Hopkins Hospital stroke registry, mRS > 2, was noted in 243 (45%) patients, of whom 34 a prospective database, for patients aged 18 and above (6%) died within the 3-month follow up period. In the who were discharged with a diagnosis of ischemic stroke univariable analysis, greater age, higher NIHSS score, between Jan 1st 2012 and Apr 30th 2015. For patients CCI, lower nadir Hb, larger delta Hb, and RBC transfu- admitted more than once with acute ischemic stroke, we sion were associated with unfavorable outcome (Table 2). considered only the earliest hospitalization. Out of a In the multivariable model, age, CCI and NIHSS total of 802 patients, modified Rankin Scale (mRS) at remained associated with worse outcome (Table 2). 3 months was available for 536 patients. These patients However, the associations of nadir or delta Hb and RBC were cross-referenced against a separate Blood Product transfusion with unfavorable outcome were not signifi- Utilization Database established by one of the cant in the risk-adjusted analysis (Table 3). Modeling co-investigators (SMF). Predictor variables were clinical performed with admission Hb as a dichotomized value characteristics including pre-admission CCI, laboratory (anemia vs no anemia) did not reveal significant associ- values and record of blood product transfusions during ation on multivariable analysis (Table 3). In post hoc the hospitalization. Anemia was defined as per the analyses using only death as the outcome of interest, Hb World Health Organization as a serum Hb of < 13 g/dL indices were again not associated with mortality. There in men and < 12 g/dL in women [10]. The principal out- was no quadratic relationship of Hb with mortality or come variable was unfavorable functional status defined functional outcome (models not shown). as mRS > 2 at 3 months follow up. Statistical analyses: Exploratory univariable analysis Discussion was performed to determine strength of the association In this large cohort of patients admitted to a tertiary between potential predictors and the principal outcome care center with ischemic stroke, anemia was present on variable. Nominal logistic regression was used for con- admission in nearly one third of cases. Moreover, anemia tinuous variables and Pearson’s chi-squared test for cat- developed after admission in 28% of patients who were egorical variables. Covariates having a P value < 0.1 on initially hospitalized without anemia. Nevertheless, in univariable analysis were used in a multiple logistic re- carefully risk adjusted models, neither anemia on ad- gression model with unfavorable outcome as the mission nor anemia during hospitalization, nor any dependent variable. Of note, despite having no association Hb-associated variable, nor RBC transfusion was sig- on univariable testing (P = 0.59), intravenous tissue plas- nificantly associated with functional status at minogen activator (tPA) administration was included in 3 months. Taken in the context of other published the multivariable models because of its well-established ef- studies, the results illustrate an area of significant un- ficacy in improving stroke outcomes. We tested using sep- certainty in the evaluation and management of pa- arate models, the following Hb indices as continuous tients with ischemic stroke. variables for strength of association with outcome: admis- Putative mechanisms for how anemia may influence sion, nadir, last recorded serum Hb concentration, as well the pathophysiology and outcome of ischemic stroke Sharma et al. BMC Neurology (2018) 18:78 Page 3 of 5 Table 1 Patient characteristics (N = 536) include reduction of oxygen carrying capacity to the penumbral regions [11], the generation of a hyperkinetic Characteristic No. (%) of Patients thrombogenic state especially in acute blood loss [12] Female 244 (45.5) and the association with a proinflammatory state [13]. Age, mean (SD), y 62 (15) However, findings from studies looking at the associ- Admission NIHSS score ation of Hb with functional outcome after stroke have Median (IQR) 3 (5) been inconsistent. Tanne et al. reported significantly in- Mean (SD) 5.2 (5.5) creased odds of combined death and disability (Barthel NIHSS < 10 450 (84) Index < 75) at 1 year in patients with anemia [7]. Simi- larly, Milionis et al. reported significantly increased odds Hemoglobin parameters of poor functional status measured with mRS at Admission Hb, mean (SD), g/dl 13.2 (1.9) 3 months and 1 year in anemic vs non-anemic patients Nadir Hb, mean (SD), g/dl 11.7 (2.3) [3]. In contrast, Hao et al. found no association between Delta Hb, median (IQR), g/dl 1.1 (1.9) anemia and measures of disability in their cohort and Charlson Comorbidity Index, median (IQR) 3 (3) meta-analysis of similar studies published in the period Body mass index ≥30 58 (11) 2007–2013 [2]. Increased mortality in anemic patients has been demon- Congestive heart failure 66 (12) strated in studies with follow up periods ranging from Hypertension 90 (17) 1 month to 3 years [1–5]. This seemingly intuitive relation- Diabetes mellitus 157 (29) ship has not borne out uniformly. Furlan et al. noted no as- Renal disease 63 (12) sociation of low Hb with 7-day and 30-day mortality but Liver disease 14 (3) slight increase in 90-day mortality [6]. Some caveats bear HIV positive 6 (1) mentioning when interpreting these data. Two of these large cohort studies did not incorporate stroke severity as a Intravenous alteplase administered 39 (7) covariate influencing mortality [4, 5]. There also seems to Length of stay, median (IQR) 3 (5) be publication bias favoring reports with increased odds of Red blood cell transfusion 28 (5) mortality in anemic patients with stroke [5, 14]. 3-month modified Rankin scale score Some data suggest that both low and high Hb may be 0 98 (18) linked with increased mortality. In the study by Furlan et 1 90 (17) al., abnormally high Hb was robustly associated with in- creased mortality at all follow up intervals [6]. Tanne et al. 2 105 (20) found increased mortality rates at both low and high Hb 3 121 (23) concentrations [7]. Thrombogenic effects and compro- 4 68 (13) mised collateral flow have been postulated as mechanisms 5 20 (4) worsening outcomes in patients with supranormal serum 6 34 (6) Hb values. An alternative explanation would be that both Abbreviations: HIV human immunodeficiency virus, IQR interquartile range, extremes of Hb concentration are biomarkers of systemic NIHSS National Institutes of Health stroke scale, SD standard deviation medical comorbidities which are the true drivers of Table 2 Univariable and multivariable predictors of unfavorable outcome (mRS > 2) a b Univariable Analysis Multivariable analysis OR (95% CI) P Value Adjusted OR (95% CI) P value Age 1.02 (1.01–1.04) < 0.001 1.02 (1.01–1.04) 0.001 NIHSS score 1.26 (1.19–1.33) < 0.001 1.30 (1.23–1.39) < 0.001 IV alteplase use 0.84 (0.42–1.61) 0.59 0.19 (0.07–0.46) < 0.001 Charlson Comorbidity Index 1.30 (1.17–1.44) < 0.001 1.25 (1.11–1.41) < 0.001 Nadir Hb 0.82 (0.76–0.89) < 0.001 0.99 (0.89–1.10) 0.84 Delta Hb 1.40 (1.20–1.60) < 0.001 Anemia during hospitalization 1.60 (1.15–2.33) 0.006 Red blood cell transfusion 2.67 (1.21–6.31) 0.013 1.45 (0.49–4.40) 0.50 Abbreviations: CI Confidence interval, OR Odds ratio, Hb Hemoglobin Odds ratios are per unit change for continuous variables (Age,y; NIHSS score; Charlson Comorbidity Index; Nadir Hb, g/dl; Delta Hb, g/dl; Body Mass Index) Only one multivariable model shown here. Results for models with other Hb indices shown in Table 3. Sharma et al. BMC Neurology (2018) 18:78 Page 4 of 5 Table 3 Unadjusted and adjusted odds ratios for unfavorable outcome with different hemoglobin variables OR (95% CI) P value Adjusted OR (95% CI) P value Admission Hb 0.96 (0.88–1.05) 0.47 1.05 (0.94–1.17) 0.34 Nadir Hb 0.82 (0.76–0.89) < 0.001 0.99 (0.89–1.1) 0.84 Last Hb 0.82 (0.76–0.89) < 0.001 0.98 (0.88–1.09) 0.75 Delta Hb 1.40 (1.20–1.60) < 0.001 1.14 (0.97–1.34) 0.09 Nadir Hb in patients with NIHSS < 10 0.86 (0.79–0.94) 0.002 0.99 (0.88–1.1) 0.93 Anemia during hospitalization 1.60 (1.15–2.33) 0.006 0.83 (0.5–1.3) 0.41 Abbreviations: Hb hemoglobin Models were adjusted for age, NIHSS, Charlson Comorbidity Index, delta Hb and red blood cell transfusion mortality. Indeed, we did not find any such quadratic as- illness, does not materially affect prognosis from ischemic sociation of mortality with Hb parameters. stroke. Perhaps the central nervous system adaptation to It has been also been postulated that with increasing chronic anemia may be protective in the setting of acute severity of stroke, the relative impact of anemia on out- ischemia, similar to the neuroprotective effect of hypoxic come may become insignificant due to the extent of preconditioning in a rodent model of ischemic stroke [19]. neurological injury [8, 9, 15]. Sico et al. reported an as- Another potentially important factor is the intrinsic bio- sociation of low hematocrit (< 30%) with combined out- logical heterogeneity in populations of patients with ische- come of death and discharge to hospice in patients with mic stroke [20]. An emerging body of research is mild to moderate stroke (NIHSS < 10) but not in those demonstrating that variance in the risk, presentation and with more severe strokes [8]. In another set of studies, outcomes of ischemic stroke is determined to a significant Kellert et al. implicated post-admission drop in Hb levels degree by underlying genetic factors [21], suggesting that in worsening functional outcome in thrombolysed pa- anemia and RBC transfusion could have differential effects tients admitted to the stroke unit, but found no such as- depending on underlying (and yet insufficiently character- sociation in their neurological intensive care unit ized) patient-specific characteristics. patients with more severe illness [9, 15]. In our cohort, Inconsistent results from available studies suggest a however, there was no association of Hb parameters with state of clinical equipoise regarding the optimal manage- mortality or functional outcome in the subgroup of pa- ment of anemia in patients with acute ischemic stroke. tients with NIHSS < 10 (n = 450, Table 3). Resolving this uncertainty could involve 3 linked strat- Strengths of this study include the relatively large sample egies. First, prospective studies are needed with sample size, adjustment for stroke severity and the use of the CCI sizes adequately powered to answer primary hypotheses. as a summary measure for comorbidity information. Due Such studies must use carefully designed modeling ap- to the large number of conditions that may be covariant proaches that control for a range of potential con- with anemia and mortality, a summary measure provides founders and focus on functional outcomes in addition the convenience of a single number that adequately cap- to mortality. Consistency in the use of comorbidity sum- tures information from individual comorbidities [16]. The mary measures and outcome measures may enable pool- CCI hasbeeninextensive useinadministrativedatabases ing of data across studies to overcome the limitations of and has been validated as a prognostic indicator in ischemic sample size. Second, research is needed to discover and stroke as well [17, 18]. Consistent use of such a measure validate sensitive and specific biomarkers to guide man- will be useful in comparing and pooling data across studies agement of anemia (e.g. timing of transfusion, optimal in future. Limitations of the study include the retrospective Hb cutoffs) in stratified subsets or individuals with is- design and potential selection bias due to exclusion of pa- chemic stroke. Third, carefully designed and adequately tients with missing mRS data. We did not have docu- powered randomized controlled trials (preferably mented pre-stroke mRS for the study patients. Change in biomarker-guided) are warranted to address primary mRS would certainly be a more accurate outcome measure questions on the role of higher versus lower Hb manage- than post-stroke value alone. Lastly, we could not extract ment thresholds in ischemic stroke populations. information about mechanism of stroke in our patients. It is entirely plausible that different stroke subtypes may be Conclusion differentially affected by abnormal hemoglobin levels. Our study demonstrated no association of hemoglobin In summary, in our cohort of patients with ischemic parameters with mortality and 3-month functional out- stroke, admission, nadir or change in Hb were not pre- come, which contradicts prior observational evidence. dictive of 3-month functional outcome. It is possible that This uncertainty could be addressed with appropriately mild to moderate anemia, other than being a marker of designed clinical trials. Sharma et al. BMC Neurology (2018) 18:78 Page 5 of 5 Abbreviations 7. Tanne D, Molshatzki N, Merzeliak O, Tsabari R, Toashi M, Schwammenthal Y. CCI: Charlson Comorbidity Index; CI: Confidence interval; Hb: Hemoglobin; Anemia status, hemoglobin concentration and outcome after acute stroke: a HIV: Human immunodeficiency virus; IQR: Interquartile range; mRS: Modified cohort study. BMC Neurol. 2010;10:22. https://doi.org/10.1186/1471-2377-10-22. rankin scale; NIHSS: National Institutes of Health Stroke Scale; OR: Odds ratio; 8. Sico JJ, Concato J, Wells CK, Lo AC, Nadeau SE, Williams LS, et al. Anemia is RBC: Red blood cell; SD: Standard deviation; tPA: Tissue plasminogen associated with poor outcomes in patients with less severe ischemic stroke. activator J Stroke Cerebrovasc Dis. 2013;22:271–8. https://doi.org/10.1016/j. jstrokecerebrovasdis.2011.09.003. 9. Kellert L, Martin E, Sykora M, Bauer H, Gussmann P, Diedler J, et al. Cerebral Availability of data and materials oxygen transport failure?: decreasing hemoglobin and hematocrit levels The datasets used and/or analyzed during the current study are available after ischemic stroke predict poor outcome and mortality: STroke: RelevAnt from the corresponding author on reasonable request. impact of hemoGlobin, hematocrit and transfusion (STRAIGHT)–an observational study. Stroke. 2011;42:2832–7. https://doi.org/10.1161/ Authors’ contributions strokeaha.110.606665. Conception: KS, RDS, SMF; Data acquisition: KS, BJ, RDS, SMF, DJJ; Analysis 10. Fagnoul D, Combes A, De Backer D. Extracorporeal cardiopulmonary and interpretation of data: KS, RDS, SMF, DJJ; Manuscript drafting: KS, RDS, resuscitation. Curr Opin Crit Care. 2014;20:259–65. https://doi.org/10.1097/ SMF; All authors were involved in critical revision of the manuscript and mcc.0000000000000098. approved the final manuscript. 11. Dexter F, Hindman BJ. Effect of haemoglobin concentration on brain oxygenation in focal stroke: a mathematical modelling study. Br J Anaesth. Ethics approval and consent to participate 1997;79:346–51. Institutional review board approval (Johns Hopkins Hospital IRB, East 12. Kim JS, Kang SY. Bleeding and subsequent anemia: a precipitant for cerebral Baltimore Campus, NA_00078426) with a waiver for written informed infarction. Eur Neurol. 2000;43:201–8. doi: 8176 consent was obtained to retrospectively assess changes in blood utilization 13. Ferrucci L, Guralnik JM, Woodman RC, Bandinelli S, Lauretani F, Corsi AM, et and clinical outcomes at the Johns Hopkins Hospital. Only previously al. Proinflammatory state and circulating erythropoietin in persons with and collected data were analyzed and no study participants were asked to be without anemia. Am J Med. 2005;118:1288. https://doi.org/10.1016/j. involved. The IRB allowed review of patient records in a NON-de-identified amjmed.2005.06.039. fashion if necessary to verify or complete missing data elements in the 14. Li Z, Zhou T, Li Y, Chen P, Chen L. Anemia increases the mortality risk in database. patients with stroke: a meta-analysis of cohort studies. Sci Rep. 2016;6: 26636. https://doi.org/10.1038/srep26636. 15. Kellert L, Herweh C, Sykora M, Gussmann P, Martin E, Ringleb PA, et al. Loss of Competing interests penumbra by impaired oxygen supply? Decreasing hemoglobin levels predict Steven M. Frank has received compensation from Haemonetics and infarct growth after acute ischemic stroke: stroke: Relevant impact of Medtronic for serving on their advisory boards. The rest of the authors (KS, hemoglobin, hematocrit and transfusion (STRAIGHT) - an observational study. DJ, BJ, RS) declare that they have no conflict of interest. Cerebrovasc Dis Extra. 2012;2:99–107. https://doi.org/10.1159/000343731. 16. Austin SR, Wong Y-N, Uzzo RG, Beck JR, Egleston BL. Why summary comorbidity measures such as the Charlson comorbidity index and Publisher’sNote Elixhauser score work. Med Care. 2015;53:e65–72. https://doi.org/10.1097/ Springer Nature remains neutral with regard to jurisdictional claims in MLR.0b013e318297429c. published maps and institutional affiliations. 17. Goldstein LB, Samsa GP, Matchar DB, Horner RD. Charlson index comorbidity adjustment for ischemic stroke outcome studies. Stroke. 2004; Author details 1 35:1941–5. https://doi.org/10.1161/01.STR.0000135225.80898.1c. Department of Anesthesiology and Critical Care Medicine, Johns Hopkins 2 18. Tessier A, Finch L, Daskalopoulou SS, Mayo NE. Validation of the Charlson University School of Medicine, Baltimore, USA. Department of Neurology, 3 comorbidity index for predicting functional outcome of stroke. Arch Phys Johns Hopkins University School of Medicine, Baltimore, USA. Department Med Rehabil. 2008;89:1276–83. https://doi.org/10.1016/j.apmr.2007.11.049. of Neurology, University of Kansas Medical Center, Mailstop 2012, 3901 4 19. Wacker BK, Perfater JL, Gidday JM. Hypoxic preconditioning induces stroke Rainbow Blvd, Kansas City, KS 66160, USA. Department of Neurosurgery, tolerance in mice via a cascading HIF, sphingosine kinase, and CCL2 signaling Johns Hopkins University School of Medicine, Baltimore, USA. pathway. J Neurochem. 2012;123:954–62. https://doi.org/10.1111/jnc.12047. 20. Rostanski SK, Marshall RS. Precision medicine for ischemic stroke. JAMA Received: 18 January 2018 Accepted: 28 May 2018 Neurol. 2016;73:773–4. https://doi.org/10.1001/jamaneurol.2016.0087. 21. Falcone GJ, Malik R, Dichgans M, Rosand J. Current concepts and clinical applications of stroke genetics. Lancet Neurol. 2014;13:405–18. https://doi. References org/10.1016/s1474-4422(14)70029-8. 1. Nybo M, Kristensen SR, Mickley H, Jensen JK. 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BMC NeurologySpringer Journals

Published: Jun 2, 2018

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