Cumulative incidence for wait-list death in relation to length of queue for coronary-artery bypass grafting: a cohort study
Bibliographic record
Abstract
BACKGROUND: In deciding where to undergo coronary-artery bypass grafting, the length of surgical wait lists is often the only information available to cardiologists and their patients. Our objective was to compare the cumulative incidence for death on the wait list according to the length of wait lists at the time of registration for the operation. METHODS: The study cohort included 8966 patients who registered to undergo isolated coronary-artery bypass grafting (82.4% men; 71.9% semi-urgent; 22.4% non-urgent). The patients were categorized according to wait-list clearance time at registration: either "1 month or less" or "more than 1 month". Cumulative incidence for wait-list death was compared between the groups, and the significance of difference was tested by means of regression models. RESULTS: Urgent patients never registered on a wait list with a clearance time of more than 1 month. Semi-urgent patients registered on shorter wait lists more often than non-urgent patients (79.1% vs. 44.7%). In semi-urgent and non-urgent patients, the observed proportion of wait-list deaths by 52 weeks was lower in category "1 month or less" than in category "more than 1 month" (0.8% [49 deaths] vs. 1.6% [39 deaths], P < 0.005). After adjustment, the odds of death before surgery were 64% higher in patients on longer lists, odds ratio [OR] = 1.64 (95% confidence interval [CI] 1.02-2.63). The observed death rate was higher in category "more than 1 month" than in category "1 month or less", 0.79 (95%CI 0.54-1.04) vs. 0.58 (95% CI 0.42-0.74) per 1000 patient-weeks, the adjusted OR = 1.60 (95%CI 1.01-2.53). Longer wait times (log-rank test = 266.4, P < 0.001) and higher death rates contributed to a higher cumulative incidence for death on the wait list with a clearance time of more than 1 month. CONCLUSION: Long wait lists for coronary-artery bypass grafting are associated with increased probability that a patient dies before surgery. Physicians who advise patients where to undergo cardiac revascularization should consider the risk of pre-surgical death that is associated with the length of a surgical wait list.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".