The comparison of the efficacy of three different risk-scoring systems on predicting the mortality rates of patients undergoing coronary artery bypass grafting
Bibliographic record
Abstract
Introduction: The importance of preoperative risk scoring in open-heart surgery has risen in the last decades. Many scoring systems for mortality prediction before coronary artery bypass grafting surgery (CABG) have been described in all over the world. We aimed to compare the efficacy of three different well-known and commonly used mortality risk-scoring systems and to provide a more suitable scoring system for our patient population.Material-Method: A total of 2120 patients who had undergone a CABG operation in Türkiye Yüksek İhtisas Hospital Cardiovascular Surgery Clinic between January 2003 – December 2004 included in this study. The patients who had concomitant surgery with CABG operation were excluded. The in-hospital deaths and the deaths in postoperative 30 days were accepted as mortality. The patients were divided into low, moderate and high-risk groups as the risk scoring systems prerequisites. The predicted mortality rates by the risk scoring systems and the observed mortality rates were compared. Results: The observed mortality rates and the predicted mortality rates by the European System for Cardiac Operative Risk Evaluation (EuroSCORE) were similar between the groups (p>0.05). The observed mortality rates of low and moderate risk groups were significantly lower than the predicted mortality rates with Parsonnet risk scoring system (p<0.001). In the high-risk group, the observed mortality rates were not significantly different from the predicted mortality rates with the same risk scoring system (p>0.05). The predicted mortality rates with Ontario Province Risk (OPR) scoring system and observed mortality rates in the low risk group were significantly different (p<0.001). But in the moderate and high risk groups, the observed mortality rates and predicted mortality rates with the OPR were not significantly different (p>0.05). In the receiver operating characteristic curve (ROC) analysis, the area under the curve (AUC) = 0.801 for EuroSCORE, AUC = 0.737 for Parsonnet and AUC = 0.677 for OPR risk scoring systems. According to these values, the accuracy of EuroSCORE was accepted as high, Parsonnet was accepted as moderate and OPR was accepted as non-significant. Conclusion: The EuroSCORE risk scoring system results were similar to the results in the literature. It is a reliable way of risk prediction for the patients undergoing CABG surgery in our region.
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".