Abstract P111: Ischemic Stroke Associated With Covid-19 and Racial Outcome Disparity in North America
Bibliographic record
Abstract
Introduction: Underlying biological, genetic, or epigenetic characteristics may predispose to health differences and outcomes with COVID-19 associated stroke. Social determinants of health, access and geographical differences pertaining both to population density and other location-based factors may also be important. Methods: We report 69 cases of acute stroke in patients positive for SARS-CoV-2, in a dichotomized analysis of ischemic stroke outcomes between patients of African American background versus all other backgrounds. All patients presented to 14 major hospitals in the United States and Canada, from March 14-April 14, 2020. All patients had nasopharyngeal swab samples that were positive for SARS-CoV-2 on qualitative RT-PCR assays. Results: We found no significant difference in age (64.4 versus 62.9 years) or the proportion of females (51.9% versus 38.1%) (table 1). Diabetes mellitus was present significantly less in African American cases versus others (37% vs. 66.7%). The African American cohort had a similar mean NIHSS score of 16.3 compared with 14.9 in other races (p=0.63). The door-to-CT time was also similar (23 versus 19 minutes). The proportion of patients presenting with a large vessel occlusion was not significantly different (40.7% versus 47%). We noted 14.8% of African American cases received intravenous tPA compared to 31% in other races but was not significantly different. The proportion of thrombectomy cases mirrored this (14.8% versus 31%). Regarding stroke functional outcomes, there was no difference between African Americans and other races with respect to discharge mRS or proportion of favorable outcome (mRS 0-2). Symptomatic intracranial hemorrhage (sICH) was significantly higher for African Americans (11.1% versus 3%, p<0.001). Mortality was significantly higher in African Americans compared to other races (51.9% vs. 28.6%, p=0.03). Discussion: The reasons for increased mortality in African Americans with COVID-19-associated stroke are unknown. The finding in this study that mortality rate of COVID-19 positive stroke patients is greater than that previously reported in either COVID-19 respiratory infection alone or acute ischemic stroke alone, suggests an interaction that also warrants further study.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".