Abstract

Background: Prior studies have shown that women present with more severe stroke. It has been suggested that sex differences in stroke severity are related to age, stroke subtype, or cardiovascular risk factors. We aimed to determine the proportion of sex disparity in stroke severity that can be explained by differences in these variables using Oaxaca decomposition, an econometric technique which quantifies the differences between groups. Methods: White and Black ischemic stroke patients who presented to two academic medical centers in the US (2004-2011) were identified using prospective stroke registries. In-hospital strokes were excluded. Patient demographics and medical history were collected. Stroke severity was measured by NIHSS. Linear regression was used to determine if female sex was associated with NIHSS score. This model was then adjusted for potential confounders including: age, race, stroke subtype, and cardiovascular risk factors. Oaxaca decomposition was then used to determine the proportion of the observed sex differences in stroke severity that can be explained by these variables. Results: 4925 patients met inclusion criteria. Nearly half (n=2346) were women and 39% (n=1942) were Black. Women presented with more severe strokes (median NIHSS 8 vs. 6). In addition, women were older on average (68 vs. 63 years) with more frequent atrial fibrillation (18% vs. 13%), diabetes (34% vs. 30%), and hypertension (78% vs. 72%). Oaxaca decomposition revealed that age, race, atrial fibrillation, large vessel etiology, diabetes, hypertension account for only 63% of the sex differences seen in NIHSS score on presentation. Conclusion: In our biracial sample, women presented with more severe strokes than men. This difference remained significant even after adjustment for age, stroke subtype, and cardiovascular risk factors. Further, over 1/3 of the observed gender difference in stroke severity was unexplained.. Additional study is warranted to investigate the etiology of the gender differences in stroke severity.

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