Waiting for Cardiac Surgery
Bibliographic record
Abstract
Background The Queen Elizabeth II Health Sciences Centre uses a weekly peer-review conference of cardiovascular experts to prioritize each surgical case to 1 of 4 queues with the use of standardized criteria of coronary anatomy, stress test result, and symptoms. We examined the hazard of waiting as well as the impact of waiting on surgical outcomes. Methods and Results Analysis was performed for 2102 consecutive patients queued for CABG, aortic valve replacement, or CABG+aortic valve replacement between January 1, 1998, and December 31, 1999. Among 1854 patients undergoing surgery, median waiting times on the respective queues were as follows: in-house urgent group, 8 days; semiurgent A group, 37 days; semiurgent B group, 64 days; and elective group, 113 days. There were 13 deaths (12 cardiac) that occurred during the waiting period (0.7% of the patients). Of the 8.7% patients upgraded to a more urgent queue, 86.1% required hospitalization before surgery. Although female sex was not associated with prolonged waiting time, it was predictive of urgent status ( P =0.001). The incidence of postoperative complications was 25.0%, and operative mortality was 2.86%. Both were more frequent among patients undergoing surgery early ( P =0.01); however, this difference was attributable to the in-house urgent queue. The median length of stay was 7 days for all patients and was not affected by waiting time. Conclusions Death and upgrades while the patients were waiting tended to occur early in the queuing process, and prolonged waiting was not associated with worse surgical outcomes. The cost of reducing waiting times could in part be offset by prevention of hospital admissions among upgraded patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".