Abstract WP27: Sars-cov-2 And Stroke Characteristics: A Report From A Regional Medical Center Serving Three Counties In South Carolina
Bibliographic record
Abstract
Introduction: Recent studies have shown patients with coronavirus disease 2019 (COVID-19) develop significant coagulopathy with thromboembolic complications including ischemic stroke. However, data are sparse regarding the clinical characteristics, stroke mechanism, and patient outcomes. Methods: We conducted a retrospective cohort study of consecutive patients with ischemic stroke who were hospitalized between March 2020 and June 2021, within at a Regional Medical Center serving three large counties in South Carolina. We further investigated clinical and demographic characteristics, stroke severity as measured by the National Institutes of Health Stroke Scale (NIHSS), and stroke subtype as measured by the TOAST (Trial of ORG 10172 in Acute Stroke Treatment) criteria among patients with COVID-19 who also suffered from an acute ischemic stroke. Results: During the study period, out of 1087 hospitalized patients with a diagnosis of COVID-19 infection, 18 patients (1.6%) had an imaging-proven ischemic stroke. Of these 18 patients, 10 (56%) were men, 16 were African-Americans (89%), 2 (11.1%) patients were <55 years of age. All patients had at least one known vascular risk factor. Cryptogenic stroke was more common in patients with COVID-19 (83%). The median time (days) from COVID-19 symptom onset to stroke symptom onset was 11 (IQR 10-28), while the median time from being tested positive for COVID-19 to stroke diagnosis was 10 (IQR 2-24). Our study sample had a median admission NIHSS score of 5 (IQR 3-11) and a median peak D-dimer level of 2101 (IQR 1349 - 3213). Interestingly, 38% of these patients were already on therapeutic anticoagulation before the diagnosis of stroke. Patients with COVID-19 and stroke had an inpatient mortality rate of 11%. None of these patients met the criteria for IV-tPA treatment or thrombectomy. Conclusion: We observed a modest rate of ischemic stroke in hospitalized patients with COVID-19. Most strokes were cryptogenic, possibly secondary to coagulopathy associated with COVID-19 infection. Further studies are needed to guide management for stroke prevention in patients with COVID-19.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".