The Potential Role of Gender in the Incidence, Management, and Outcomes of Stroke in Patients Suffering From COVID-19: A Brief Review
Bibliographic record
Abstract
Gender-disaggregated data are continuously needed in all aspects of the coronavirus disease 2019 (COVID-19) pandemic, including cerebrovascular disease in patients infected with SARS-CoV-2. This brief review was conducted to summarize available evidence and highlight potential sex differences regarding the incidence, applied therapies, and outcomes of stroke in patients with COVID-19. Local and global registries of such patients were included, where comparisons with historical (pre-pandemic era) and contemporary (stroke patients negative for SARS-CoV-2) cohorts formed the basis of the analysis. According to the herein reported evidence, the frequency of stroke under COVID-19 does not seem to vary according to gender, although a tendency toward male predominance cannot be excluded. In terms of management and outcomes, more advanced therapies are used in men. Follow-up data on gender differences are needed, as the pandemic is evolving (no lockdowns; new strains; vaccinated or naturally immune populations).
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".