Predictors of mortality in acute ischemic stroke treated with endovascular thrombectomy despite successful reperfusion: subgroup analysis of a multicentre randomised clinical trial
Bibliographic record
Abstract
OBJECTIVES: We sought to determine the predictors of 90-day mortality despite successful reperfusion. DESIGN: Subgroup analysis of a multicentre randomised clinical trial (ClinicalTrials.gov Identifier: NCT03469206). SETTING: This study used data from the Direct Intra-arterial thrombectomy in order to Revascularize AIS patients with large vessel occlusion Efficiently in Chinese Tertiary hospitals: a Multicenter randomized clinical Trial (DIRECT-MT). PARTICIPANTS: 622 patients enrolled in DIRECT-MT. RESULTS: Overall successful reperfusion rate was 82.0% (510/622), and 18.5% (115/622) of patients died within 90 days. Univariate analysis identified increased risks of mortality for age ≥70 years, history of diabetes mellitus, National Institutes of Health Stroke Scale (NIHSS) score on admission ≥17, NIHSS score after thrombectomy (24±6 hours) ≥11, Alberta Stroke Program Early Computed Tomography Score (ASPECTS) <9, glucose level at hospital arrival ≥130 mg/dL, location of internal carotid artery occlusion, embolisation into a new territory, symptomatic intracranial haemorrhage (ICH) and a decreased risk of mortality for smoking. In multivariable analysis, smoking (OR 0.38; 95% CI 0.17 to 0.83; p=0.015), NIHSS score on admission ≥17 (OR 3.14; 95% CI 1.77 to 5.55; p<0.001), glucose level at hospital arrival ≥130 mg/dL (OR 2.54; 95% CI 1.51 to 4.27; p<0.001), symptomatic ICH (OR 11.70; 95% CI 4.74 to 28.89; p<0.001) and NIHSS score after thrombectomy (24±6 hours) ≥11 (OR 12.04; 95% CI 5.09 to 28.46; p<0.001) were significant independent predictors of 90-day mortality. CONCLUSIONS: Symptomatic ICH and high post-thrombectomy NIHSS score are strong predictor of 90-day mortality in acute ischaemic stroke treated with mechanical thrombectomy despite successful reperfusion, as well as high NIHSS score and high glucose level at hospital arrival. However, further studies need to be performed to confirm the association between smoking and mortality.
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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 | 0.011 | 0.015 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.011 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".