Assessment of patient waiting times for vascular surgery.
Bibliographic record
Abstract
OBJECTIVES: To assess patient waiting times for vascular surgery and to determine if complications of the disease develop while the patients are awaiting surgery. DESIGN: Prospective cohort study. SETTING: A university-affiliated tertiary care institution. PATIENTS: All 554 patients who underwent scheduled vascular surgical procedures between April 1995 and October 1996. OUTCOME MEASURES: A literature review carried out to develop guidelines for acceptable waiting times for surgery associated with various vascular disorders based on their natural history (benchmark target); actual waiting times, defined as the interval from the date each patient was booked for surgery to the date of admission to hospital for the procedure; the proportion of patients admitted within the benchmark targets; and whether prolonged waiting time placed patients at risk for complications of their disease. RESULTS: Of the 554 patients, 382 (69%) were admitted within the benchmark waiting times. Of 84 patients having an abdominal aortic aneurysm, the aneurysm ruptured during the waiting period in 6, and 4 of them died, for a complication rate of 7% and a death rate of 5%. Two of the 6 aneurysms ruptured after the patient had waited longer than the target time. Three of 100 patients with symptomatic carotid artery stenosis awaiting admission for carotid endarterectomy suffered ischemic stroke, for a 3% complication rate; all had waited longer than the target period. One patient suffered occlusion of a femoropopliteal bypass graft while awaiting revision of a stenosed bypass graft. CONCLUSIONS: This study suggests that although most patients are admitted for operation within the benchmark time, one-third are admitted late and may suffer serious complications of their disease while awaiting admission for the procedure.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".