Differences in stroke outcome based on sex
Bibliographic record
Abstract
OBJECTIVE: Stroke thrombolysis may have a differential effect by sex. We sought to examine the relationship between sex and outcome after thrombolysis. METHODS: This is a retrospective cohort study of stroke patients from the Registry of Canadian Stroke Network phase 1 (June 2001-February 2002) and phase 2 (June 2002-December 2002). Variables including demographics, history, clinical data, process measures, and outcome were analyzed. The primary outcomes were the Stroke Impact Scale-16 score (SIS-16) and mortality at 6 months. We compared the outcomes of the thrombolyzed and nonthrombolyzed cohorts and examined the data for a tissue plasminogen activator (tPA)-by-sex interaction on the 2 primary outcomes. RESULTS: The overall proportion of patients who achieved an excellent outcome (SIS-16 >75) was not different by gender. However, the proportion of patients achieving an excellent outcome in the non-tPA cohort was much greater in males, with an absolute risk difference of 11.8%. A multiplicative treatment by sex interaction was evident (p = 0.054). This interaction was not present for stroke case fatality. CONCLUSIONS: Women fared poorly compared to men in the placebo groups, but this negative prognostic sex effect was neutralized by thrombolysis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.004 | 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".