Confounding by Pre-Morbid Functional Status in Studies of Apparent Sex Differences in Severity and Outcome of Stroke
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Several studies have reported unexplained worse outcomes after stroke in women but none included the full spectrum of symptomatic ischemic cerebrovascular events while adjusting for prior handicap. METHODS: Using a prospective population-based incident cohort of all transient ischemic attack/stroke (OXVASC [Oxford Vascular Study]) recruited between April 2002 and March 2014, we compared pre-morbid and post-event modified Rankin Scale score (mRS) in women and men and change in mRS score 1 month, 6 months, 1 year, and 5 years after stroke. Baseline stroke-related neurological impairment was measured with the National Institutes of Health Stroke Scale. RESULTS: Among 2553 patients (50.6% women) with a first transient ischemic attack/ischemic stroke, women had a worse handicap 1 month after ischemic stroke (age-adjusted odds ratio for mRS score, 1.35; 95% confidence interval, 1.12-1.63). However, women also had a higher pre-morbid mRS score compared with men (age-adjusted odds ratio, 1.58; 95% confidence interval, 1.36-1.84). There was no difference in stroke severity when adjusting for age and pre-morbid mRS (odds ratio, 1.10; 95% confidence interval, 0.90-1.35) and no difference in the pre-/poststroke change in mRS at 1 month (age-adjusted odds ratio, 1.00; 95% confidence interval, 0.82-1.21), 6 months, 1 year, and 5 years. Women had a lower mortality rate, and there was no sex difference in risk of recurrent stroke. CONCLUSIONS: We found no evidence of a worse outcome of stroke in women when adjusting for age and pre-morbid mRS. Failure to account for sex differences in pre-morbid handicap could explain contradictory findings in previous studies. Properties of the mRS may also contribute to these inconsistencies.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".