Sex-Specific Differences in Short-Term and Long-Term Outcomes in Acute Stroke Patients from Qatar
Bibliographic record
Abstract
BACKGROUND: Sex differences may determine presentation, utility of treatment, rehabilitation, and occurrences of major adverse cardiovascular events (MACEs) in acute stroke (AS). OBJECTIVE: The purpose of the study was to evaluate the short-term prognosis and long-term outcomes in MACEs in Qatari nationals admitted with AS. METHODS: All AS patients admitted between January 2014 and February 2019 were included. We evaluated the preadmission modified Rankin scale (mRS) score, etiology and severity of symptoms, complications, and functional recovery at discharge and 90 days. MACEs were recorded for 5 years. RESULTS: There were 891 admissions for AS (mean age 64.0 ± 14.2 years) (male, n = 519 [mean age ± SD 62.9 ± 14.1 years]; female, n = 372 [mean age ± SD 65.6 ± 14.2 years] p = 0.005). There were no differences in the preadmission mRS and severity of symptoms as measured on National Institute of Stroke Scale. At discharge, the outcome was better (mRS 0-2) in men (57.8 vs. 46.0%), p = 0.0001. This difference persisted at the 90-day follow-up (mRS 0-2, male 69.4% vs. female 53.2%, p = 0.0001). At the 90-day follow-up, more women died (total deaths 70; women 38 [10.2%] versus men 32 [6.2%], p = 0.03). MACEs occurred in 25.6% (133/519) males and 30.9% (115/372) females over the 5-year follow-up period (odds ratio 0.77, 95% confidence interval 0.57-1.0, p = 0.83). CONCLUSIONS: Female patients have a poor short-term outcome following an AS when corrected for age and comorbidities. While our study cannot explain the reasons for the discrepancies, higher poststroke depression and social isolation in women may be important contributory factors, and requires further studies are required to confirm these findings.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.003 | 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".