Outcomes after aortic and mitral valve replacement surgery in Canada: 1994/95 to 1999/2000.
Bibliographic record
Abstract
BACKGROUND: Although outcomes after coronary artery bypass grafting (CABG) have been studied extensively across Canada, using both clinical and administrative databases, studies examining outcomes after valve surgery in Canada have been restricted to regional investigations using clinical data sources of limited scope. The objective of the present study was to report on observed and risk-adjusted in-hospital mortality rates after aortic valve replacement (AVR) and mitral valve replacement (MVR) across Canada between 1994/95 and 1999/2000 using administrative data. METHODS: All cases of AVR and MVR (with and without concomitant CABG) performed between 1994/95 and 1999/2000 were identified using hospital discharge abstract data obtained from the Canadian Institute for Health Information. Rates of in-hospital mortality were risk-adjusted using logistic regression modelling techniques to account for variations in sociodemographic, comorbidity, and disease-specific indicators of average severity of illness across years and provinces. Risk-adjusted outcomes were unavailable for the province of Quebec. RESULTS: The overall in-hospital mortality rate, excluding Quebec, between 1994/95 and 1999/2000 after isolated AVR with or without CABG was 3.7% and isolated MVR with or without CABG was 5.7%. Although risk-adjusted in-hospital mortality rates by year were unchanged between 1994/95 and 1999/2000, significant interprovincial variation did exist, ranging from 2.6% to 6.8% for AVR with or without CABG and 2.5% to 13.0% for MVR with or without CABG. CONCLUSION: In-hospital mortality rates after valve surgery have remained stable over time. However, significant variation in outcomes was noted between provinces. The results of this study provide the first comprehensive account of valve surgery outcomes across 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 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".