Influence of Guidelines in Endovascular Therapy Decision Making in Acute Ischemic Stroke
Bibliographic record
Abstract
Background and Purpose- The American Heart Association and the American Stroke Association guidelines for early management of patients with ischemic stroke offer guidance to physicians involved in acute stroke care and clarify endovascular treatment indications. The purpose of this study was to assess concordance of physicians' endovascular treatment decision-making with current American Heart Association and the American Stroke Association stroke treatment guidelines using a survey-approach and to explore how decision-making in the absence of guideline recommendations is approached. Methods- In an international cross-sectional survey (UNMASK-EVT), physicians were randomly assigned 10 of 22 case scenarios (8 constructed with level 1A and 11 with level 2B evidence for endovascular treatment and 3 scenarios without guideline coverage) and asked to declare their treatment approach (1) under their current local resources and (2) assuming there were no external constraints. The proportion of physicians offering endovascular therapy (EVT) was calculated. Subgroup analysis was performed for different specialties, geographic regions, with regard to physicians' age, endovascular, and general stroke treatment experience. Results- When facing level 1A evidence, participants decided in favor of EVT in 86.8% under current local resources and in 90.6% under assumed ideal conditions, that is, 9.4% decided against EVT even under assumed ideal conditions. In case scenarios with level 2B evidence, 66.3% decided to proceed with EVT under current local resources and 69.7% under assumed ideal conditions. Conclusions- There is potential for improving thinking around the decision to offer endovascular treatment, since physicians did not offer EVT even under assumed ideal conditions in 9.4% despite facing level 1A evidence. A majority of physicians would offer EVT even for level 2B evidence cases.
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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 | 0.092 | 0.422 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| 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".