The European System for Cardiac Operative Risk Evaluation (EuroSCORE) is not appropriate for withholding surgery in high-risk patients with aortic stenosis: a retrospective cohort study
Bibliographic record
Abstract
BACKGROUND: The European System for Cardiac Operative Risk Evaluation (EuroSCORE) is a widely used risk assessment tool in patients with severe aortic stenosis to determine operability and to select patients for alternative therapies such as transcatheter aortic valve implantation. The objective of this study was to determine the accuracy of the EuroSCORE in predicting mortality following aortic valve replacement (AVR). METHODS: The logistic EuroSCORE was determined for all consecutive patients that underwent conventional AVR between 1995 and 2005 at our institution. Provincial Vital Statistics were used to determine all-cause mortality. The accuracy of the prognostic risk prediction provided by logistic EuroSCORE was assessed by comparing observed and expected operative mortality. RESULTS: During the study period, a total of 1,421 patients underwent AVR including 237 patients (16.7%) that had a logistic EuroSCORE > 20. Among these patients, the mean predicted operative mortality was 38.7% (SD = 18.1). The actual mortality of these patients was significantly lower than that predicted by EuroSCORE (11.4% vs. 38.7%, observed/expected ratio 0.29, 95% CI 0.15-0.52, P < 0.05). The EuroSCORE overestimated mortality within all strata of predicted risk. Although medium-term mortality is significantly higher among patients with EuroSCORE > 20 (log rank P = 0.0001), approximately 60% are alive at five years. CONCLUSION: Actual operative mortality in patients undergoing AVR is significantly lower than that predicted by the logistic EuroSCORE. Additionally, medium-term survival following AVR is acceptable in high-risk patients with EuroSCORE > 20. More accurate risk prediction models are needed for risk-stratifying patients with severe aortic stenosis.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".