Outcomes after coronary artery bypass graft surgery in Canada: 1992/93 to 2000/01.
Bibliographic record
Abstract
BACKGROUND: The authors have previously reported on Canada-wide outcomes of coronary artery bypass graft (CABG) surgery for 1992/93 through 1995/96. OBJECTIVE: To provide an updated Canada-wide CABG surgery outcome report with outcome data organized by province and by year for 1992/93 through 2000/01. METHODS: Hospital discharge abstract data were obtained from the Canadian Institute for Health Information and were used to identify all patients who underwent isolated CABG surgery in eight provinces from fiscal year 1992/93 through 2000/01. Crude data from Quebec hospitals were available for calendar years 1998 and 1999. Logistic regression modelling was used to calculate risk-adjusted in-hospital mortality rates by year and province. RESULTS: Patients undergoing CABG surgery in the later years studied were on average older and had more comorbidities than did patients undergoing this surgery in earlier years. Despite increasing case complexity, risk-adjusted mortality rates decreased significantly from 3.5% (95% CI 3.2% to 3.8%) to 2.0% (95% CI 1.8% to 2.3%). Risk-adjusted mortality rates varied between provinces. Provincial risk-adjusted mortality rates ranged from 2.0% to 3.3%. However, all provinces studied had either persistently low mortality rates (Nova Scotia) or declining mortality rates across years studied, such that all provinces achieved risk-adjusted mortality rates of 2.7% or lower in 2000/01. CONCLUSIONS: This evaluation of Canadian CABG surgery outcomes demonstrates a pattern of either steadily improving or persistently favourable provincial in-hospital mortality rates after isolated CABG surgery. These favourable provincial outcome trends have been achieved despite an accompanying increase in the average case complexity of patients undergoing CABG in Canada.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".