Wait Times for Carotid Endarterectomy, London Ontario 2006-2007
Bibliographic record
Abstract
OBJECTIVE: To examine time delays and identify factors that affect wait times from index neurological event to carotid endarterectomy in patients with symptomatic carotid stenosis treated at a regional neurosurgical referral centre. METHODS: We performed a retrospective audit over two years of all patients who underwent a carotid endarterectomy at University Hospital, London, Ontario. The number of days was calculated from first neurological event through until surgery. RESULTS: Eighty-nine carotid endarterectomies (CEAs) were performed by four surgeons during the years 2006 and 2007. From the first neurological event, the median wait time for surgery was 111 days, while from the last event the median wait time was 83 days. There was 19 days' wait between specialist / TIA clinic appointment and the receipt of neurosurgical referral. Median wait time for diagnostic imaging was eight days for carotid Doppler ultrasound and 15 days for CT or MR angiography. There was a 44 day wait from receipt of neurosurgical referral to the date of surgery. Only three patients (4%) received CEA within two weeks of their last neurological event. There was a trend towards a difference in wait times between inpatients and outpatients, but no difference between females compared with males, or between patients presenting with stroke versus TIA. DISCUSSION: Median wait times for CEA after first neurological event was over three months at our center, reflecting the diagnostic workup required in TIA as well as the lack of a systematic approach. This is the subject of continued study at our institution.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".