Comparison of 5 Risk Scales in the Results of Aortic Valvular Surgery With Rapid Deployment Prostheses
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Bibliographic record
Abstract
Objective: Aortic prostheses with rapid deployment have recently emerged with shorter surgical times and less invasive approaches for the treatment of aortic stenosis. The appearance of the treatment via TAVR has caused the calculation of the preoperative risk to become more interesting to select the right treatment. We studied the prognostic utility of 5 surgical risk scales (Euroscore logistic, EuroScore II, STSAVR score, NNEAVRscore and OntarioScore) to detect mortality in a cohort of patients who received rapid deployment aortic prostheses. Methods: From September 2012 to November 2016 we reviewed the patients who received Edwards Intuity prostheses. We calculated 5 risk scales assessing their effectiveness in hospital mortality. Results: Seventy-two patients (68% males, 75.6 ± 4.8 years). Two patients died (2.8%). The mean values of the Euroscore logistic, EuroScore 2, STSAVRScore, NNEAVRScore and OntarioScore were: 7.7 ± 4.9; 2.6 ± 1.9; 3 ± 1.7; 3.5 ± 2.6 and 5.5 ± 1.3 respectively. For mortality discrimination the results were: EuroScore logistic: 0.92 (95% CI 0.83-1), EuroScore 2: 0.83 (95% CI 0.64-1), STSAVRScore: 0.93 (95% CI % 0.86-1), NNEAVRScore: 0.65 (95% CI 0.33-0.97), OntarioScore: 0.93 (95% CI 0.84-1). Regarding calibration, we found that the P value for the Hosmer-Lemeshowed test was: EuroScore logistic: 0.85, EuroScore 2: 0.73, STSAVRScore: 0.93, NNEAVRscore: 0.37 and OntarioScore: 0. 62. Conclusions: The STSAVRScore presented the best discrimination for hospital mortality, although the Euroscores and the Ontario Score behaved well. The STSAVRScore was the scale that achieved the best calibration at the different levels of risk.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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 it