Women and Stroke: Disparities in Clinical Presentations, Severity, and Short and Long-Term Outcome (P6-5.003)
Bibliographic record
Abstract
Objective: There is limited data on sex-related short-term and long-term stroke outcomes from the Middle East. We present the eight years of our Qatar stroke database. Background: NA Design/Methods: The Qatar stroke database is a prospective study, which began enrolling patients in 2014. We collected data on the demographics, clinical presentation, investigations, treatments, hospital complications and outcome (measured as 90-days modified Rankin Score [mRS]) on all patients admitted with acute stroke to the Hamad General Hospital where ~95% of stroke patients in Qatar are admitted. Multivariate analysis of risk factors, stroke type and severity, and in-hospital complications were compared to determine 90-days and one-year outcome in men and women. Results: 7300 patients (F: 1406 {19.3%} and M: 4894 {80.7%}, mean age 55.1±13.3 {F 61.6±15.1, M 53.5±12.3; p<0.001}) were admitted with acute ischemic stroke. Significantly fewer females presented within the 4.5 hours of onset [F: 29% versus M: 32.8%; p = 0.01]. Women had more severe stroke [NIHSS >10; F: 19.9 % versus M: 14.5 %; P <0.001]. Thrombolysis was less likely to be offered to women [F: 9.8% versus M: 12.1%; p 0.02]. Medical complications were more common in women [F: 11.7% versus M: 7.4%; p<0.001] and females had a prolonged length of stay in hospital [F: 6.4±7.6 versus M: 5.5±6.8; p<0.001]. 90-days good recovery was less frequent in women [mRS of 0–2: F: 53.3% versus M: 71.2%; p<0.001]. Poor prognosis increased with age. Conclusions: In this large series of prospectively collected acute stroke patients from Qatar, our study reveals that women are more likely to have a poor outcome when compared to men. Although there was a higher incidence of obesity and previous CAD in women, we were unable to explain the reasons for the poor outcome at 90 days and one year. Disclosure: Ms. Naveed has nothing to disclose. Miss Almasri has nothing to disclose. Mr. Kazani has nothing to disclose. Miss Nauman has nothing to disclose. Dr. Singh has nothing to disclose. Dr. Al Jerdi has nothing to disclose. Dr. Akhtar has nothing to disclose. Dr. Shuaib has nothing to disclose.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".