Outcome, efficacy and safety of endovascular thrombectomy in ischaemic stroke according to time to reperfusion: data from a multicentre registry
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: In acute ischaemic stroke (AIS) of the anterior circulation (AC) treated with mechanical thrombectomy (MT), data point to a decline of treatment effect with increasing time from symptom onset to treatment. However, the magnitude of the decline will depend on the clinical setting and imaging selection used. The aims of this study were (1) to evaluate the clinical effect of time to reperfusion (TTR); and (2) to assess the safety and technical efficacy of MT according to strata of TTR. METHODS: = 393). Clinical effect of TTR was evaluated using multivariable logistic regression analyses adjusting for pre-specified confounders [adjusted odds ratios (aOR) and 95% confidence intervals (95% CI)]. Primary outcome was good functional outcome (modified Rankin Scale: mRS 0-2) at day 90. RESULTS: Every hour delay in TTR was a significant factor related to mRS 0-2 (aOR 0.933, 95% CI 0.887-0.981) with an estimated 1.5% decreased probability of good functional outcome per hour delay of reperfusion, and mRS 0-1 (aOR 0.929, 95% CI 0.877-0.985). Patients with late TTR had lower rates of successful and excellent reperfusion, higher complication rates and number of passes. CONCLUSIONS: TTR is an independent factor related to long-term functional outcome. With increasing TTR, interventional procedures become technically less effective. Efforts should be made to shorten TTR through optimized prehospital and in-hospital pathways.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".