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ContributionsMagdy Selim --organized the trial hypotheses, designed the trial, provided guidance about the data analysis and interpretation and presentation of the data, and drafted most of the sections of the manuscript. Lydia Foster --involved in the statistical analysis and data interpretation, and Contributed to the development and revisions to the manuscript. Claudia Moy --involved in the oversight of the trial conduct and progress Guohua Xi --organized the trial hypotheses, and provided critical revisions to the manuscript. MH, MJ, VS, and WC contributed to recruitment and randomization of trial participants, and provided critical revisions to the manuscript. LM and SG were involved in the design of the trial and provided critical revisions to the manuscript. Casey Norton --provided volumetric measurements of imaging data. Yuko Palesch --involved in the design of the study, statistical analysis and data interpretation, and provided critical revisions to the manuscript. Sharon yeatts --involved in the design of the study, statistical analysis and data interpretation, and contributed to the development and revisions to the manuscript. The idef investigators (see appendix) --contributed to the identification and, when eligible, randomization of trial participants. DECLARATION OF INTERESTSThis was an investigator-initiated study, funded by the NINDS (U01 NS074425). Deferoxamine Mesylate is a generic drug, and there was no commercial or industrial support for the trial. None of the authors has any competing interests related to the submitted work. MS reports grants from the NIH/NINDS (i-DEF) and the American Heart Association (outside the submitted work), and personal fees for serving on the advisory board of CSL Behring (outside the submitted work) during the conduct of the trial. SDY reports grant support from the NINDS, personal fees from Genentech and other fees from CR Bard Inc. (outside the submitted work) during the conduct of the study. SG, LDF, YP, and GX report grants from the NIH/NINDS. MDH reports personal fees from Merck, nonfinancial support from Hoffmann-La Roche Canada Ltd, grants from Covidien (Medtronic), grants from Boehringer-Ingleheim, grants from Stryker Inc., grants from Medtronic LLC, grants from NoNO Inc., (outside the submitted work); In addition, MDH has a patent Systems and Methods for Assisting in Decision-Making and Triaging for Acute Stroke Patients pending to US Patent office Number: 62/086,077 and owns stock in Calgary Scientific Incorporated, a company that focuses on medical imaging software, is a director of the Canadian Federation of Neurological Sciences, a not-for-profit group and has received grant support from Alberta Innovates Health Solutions, CIHR, Heart & Stroke Foundation of Canada, and NINDS. LM, VS, WC, MJ, CM, and CN have nothing to disclose.

In ICH, black patients are less likely than white patients to have CMOs. However, in-hospital mortality is similar across all racial/ethnic groups. Further investigation is warranted to better understand the causes and implications of racial disparities in CMO decisions.

Introduction: Prior studies of critically ill patients found that non-whites are less likely to pursue comfort measures only status (CMOs). We sought to identify determinants of CMOs in a large multi-ethnic cohort study of intracerebral hemorrhage (ICH). Methods: We analyzed cases enrolled from 2010 to 2015 in the Ethnic/Racial Variations of ICH (ERICH) study, a multi-center study in the USA. Clinical, demographic and radiologic data on non-traumatic ICH patients were prospectively collected. Univariate and multivariate logistic regression was used to evaluate the association between ethnicity/race and CMOs after adjustment for potential confounders. Results: 2705 ICH cases were included in this study (mean age 62 (14), female sex 1119 [41%]). Of these, 912 were black (34%), 893 Hispanic (33%) and 900 white (33%). CMOs patients comprised 276 (10%), 64 (7%), 79 (9%) and 133 (15%) of the entire cohort and the black, Hispanic and white cohorts, respectively (p<0.001) (Table 1). In multivariate analysis, black patients were half as likely as white patients to be made CMO (OR 0.50, 95% CI 0.34-0.75; p=0.001) and there was a trend for Hispanic patients to have CMOs less often than white patients (OR 0.72, 95% CI 0.49-1.06, p=0.093) (Table 2). Other factors associated with CMOs included age, premorbid modified Rankin Scale, dementia, admission Glasgow Coma Scale, ICH volume, intraventricular hematoma volume, lobar and brainstem bleeds and intubation. Conclusion: Black patients were less likely than white patients to be made CMO after controlling for potential confounders. Further investigation is warranted to understand the causes and implications of racial disparities in CMO decisions.

Introduction: Neighborhood disadvantage is associated with various health factors. Given the mounting evidence linking social determinants to risk of, and outcomes after, spontaneous intracerebral hemorrhage (ICH), we tested the hypothesis that higher neighborhood disadvantage leads to poorer outcomes following ICH. Methods: We conducted a nested study within an ongoing longitudinal study that prospectively follows patients with acute brain injury admitted to Connecticut’s largest healthcare system. The nested study included ICH survivors and evaluated neighborhood deprivation using the Area Deprivation Index, a publicly available metric that uses 9-digit zip codes to rank neighborhoods’ socioeconomic disadvantage based on factors such as income, employment, and education. Patients were given a tertile designation according to the Area Deprivation Index: low, intermediate, and high deprivation. Functional outcome was evaluated through the 6-month post-ICH Modified Rankin Scale, dichotomized as 0-3 (good outcome) and 4-6 (poor outcome). We used chi-square tests and multivariable logistic regression for unadjusted and adjusted association analyses, respectively. Results: Out of 687 ICH patients enrolled from 2018 to 2022, 518 (mean age 67, 47.5 % female, 19% Black, 8% Hispanic) had 9-digit zip code and outcomes data. The unadjusted risk of poor outcome was 40%, 55%, and 61% for patients living in neighborhoods with low, intermediate, and high disadvantage (unadjusted p=0.02). This association was confirmed in multivariable analyses adjusting for potential confounders: compared to patients living in low-disadvantage neighborhoods, those living in neighborhoods with intermediate and high disadvantage had 66% (OR 1.66, 95% CI 0.82-3.40) and 2.5 times (OR 2.44, 95% CI 1.17-5.19) higher risk of poor outcomes (test-for-trend p=0.01). Conclusion: Among ICH survivors enrolled in a prospective study of acute brain injury, increased neighborhood disadvantage was associated with a higher risk of poor outcomes. Our results validate the Area Deprivation Index as a useful tool to assess the numerous social determinants of health. Additionally, our findings highlight the negative role of these social determinants in patients' recoveries.