Sex Differences in Outcome After Thrombectomy for Acute Ischemic Stroke are Explained by Confounding Factors
Bibliographic record
Abstract
PURPOSE: The aim of this study was to analyze sex differences in outcome after thrombectomy for acute ischemic stroke in clinical practice in a large prospective multicenter registry. METHODS: Data of consecutive stroke patients treated with thrombectomy (June 2015-April 2018) derived from an industry-independent registry (German Stroke Registry-Endovascular Treatment) were prospectively analyzed. Multivariable binary logistic regression analyses were applied to determine whether sex is a predictor of functional independence outcome (defined as a modified Rankin scale [mRS] 0-2) 90 days after stroke. RESULTS: In total, 2316 patients were included in the analysis, 1170 (50.5%) were female and 1146 (49.5%) were male. Women were older (median age 78 vs. 72 years; p < 0.001) and more frequently had a prestroke functional impairment defined by mRS >1 (24.8% vs. 14.1%; p < 0.001). In unadjusted analyses, independent outcome at 90 days was less frequent in women (33.2%) than men (40.6%; p < 0.001). Likewise, mortality was higher in women than in men (30.7% vs. 26.4%; p = 0.024). In adjusted regression analyses, however, sex was not associated with outcome. Lower age, a lower baseline National Institutes of Health Stroke Scale score, a higher Alberta Stroke Program Early CT score, prestroke functional independence, successful reperfusion, and concomitant intravenous thrombolysis therapy predicted independent outcome. CONCLUSION: Women showed a worse functional outcome after thrombectomy for acute ischemic stroke in clinical practice; however, after adjustment for crucial confounders sex was not a predictor of outcome. The difference in outcome thus appears to result from differences in confounding factors such as age and prestroke functional status.
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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 | 0.002 |
| 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 | 0.001 |
| 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".