Concurrent Acute Ischemic Stroke and Non-Aneurysmal Subarachnoid Hemorrhage in COVID-19
Bibliographic record
Abstract
Cerebrovascular disease has been described as a potential sequela of the novel coronavirus disease of 2019 (COVID-19) with one study reporting its occurrence in 106 patients.In this rapid review, 83% of the patients had ischemic strokes, while 17% were hemorrhagic. 1Most of the hemorrhagic strokes were either intracerebral hemorrhage or aneurysmal subarachnoid hemorrhage.The mortality of COVID-19 patients with cerebrovascular events can be as high as 38%. 2 As of this writing, there has been no reported case of a COVID-19 patient with concurrent acute ischemic and hemorrhagic strokes.We report a case of a 64-year-old male, hypertensive and smoker, who came to our emergency department for sudden onset right-sided weakness, numbness, and dysarthria.There was no history of trauma or respiratory symptoms prior to admission.He had no prior use of antithrombotics.He works as a utility worker in the designated COVID-19 area of the hospital.On examination, he had a blood pressure of 150/90 with a normal heart rate and regular rhythm right superior quadrantanopia, right hypesthesia, and right hemiparesis.His National Institute of Health Stroke Scale (NIHSS) score was 7. A 12-lead electrocardiogram showed sinus rhythm.A plain cranial CT scan revealed an acute infarct on the left thalamus and left temporo-occipital lobe, as well as a small subarachnoid hemorrhage on the left parietal sulcus (Figure 1).The cranial CT angiogram (CTA) did not show any acute large vessel occlusions, aneurysms, or venous thrombosis.His
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.007 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".