Influence of Time of Admission on Endovascular Thrombectomy (EVT): Comparison of Outcomes During Business Hours Versus Off-Business Hours
Bibliographic record
Abstract
Purpose:To investigate the differences in endovascular thrombectomy (EVT) outcomes of patients treated for acute ischaemic stroke (AIS) during business versus off-business hours. Methods: A single-centre retrospective cohort study of patients with AIS treated with EVT from February 1, 2015, to May 31, 2021, was performed at a comprehensive stroke centre (CSC). Patients were divided into business (Monday to Friday, 8 AM-5 PM) versus off-business hours groups. The primary outcome was functional neurological disability, scored using the modified Rankin Scale (mRS) at 90 days. Secondary outcomes included the rate of successful reperfusion and procedural workflow time delays. Differences in proportions were assessed using Fisher’s exact and Chi-Square tests as appropriate. For continuous variables, differences in medians between groups were assessed using Mann-Whitney U tests. Results: A total of 676 patients were included, with 399 patients (59%) comprising the off-business-hour group. No significant differences were seen in age, sex, ASPECTS score, or NIHSS at arrival. Off-business hours strokes had a longer delay between CSC arrival to groin puncture (minutes: 81 vs 44, P < .0001) and between imaging to groin puncture (minutes: 67 vs 32, P < .0001) compared to the business hours strokes. There were no differences in the rate of successful reperfusion (mTICI ≥2b) between groups (82% vs 83%, P = .61). At 90 days, 65% of patients in both groups had an mRS ≤2 ( P = .91). Conclusion: Despite workflow delays in initiating EVT during off-business hours, there were no differences in the rate of successful reperfusion or functional outcomes.
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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 | 0.001 | 0.004 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".