Delays in Carotid Endarterectomy: The Process is the Problem
Bibliographic record
Abstract
BACKGROUND: Current recommendations for carotid endarterectomy (CEA) for symptomatic carotid stenosis state benefit is greatest when performed within two weeks of symptoms. However, only a minority of cases are operated on within this guideline, and no systematic examinations of reasons for these delays exist. METHODS: All CEA cases performed at our institution by vascular surgery for symptomatic carotid stenosis after neurologist referral in 2008-2009 were reviewed. Dates of symptom onset, initial presentation, referral to and evaluation by neurology and vascular surgery, vascular imaging, and CEA were collected, and the length of time between each analysed. Reasons for delays were noted where available. RESULTS: Of 36 included patients, 34 had CEA more than two weeks after symptom onset. Median time to CEA from onset was 76 days (IQR, 38-105 days). Longest intervals were between surgeon assessment and CEA (14 days; IQR, 9-21 days), neurology referral and neurologist assessment (9 days; IQR, 2-26 days), vascular imaging and referral to vascular surgery (9 days; IQR, 2-35 days) and vascular surgery referral and assessment (8 days; IQR, 6-15 days). Few patients (44.1%) had reasons for delays identified; of these, process-related delays were related to delayed vascular imaging, delayed referral by primary care physicians, or multiple conflicting referrals. CONCLUSIONS: There are significant delays between symptom onset and CEA in patients referred for CEA, with delay highest between specialist referral and evaluation. Strategies to reduce these delays may be effective in increasing the proportion of procedures performed within two weeks of symptom onset.
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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 | 0.013 | 0.094 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".