Cross-Validation of Risk Scores for Patients Undergoing Transcatheter Edge-to-Edge Repair for Mitral Regurgitation
Bibliographic record
Abstract
Background: Risk scores may identify patients with mitral regurgitation (MR) who are at risk for adverse events, but who may still benefit from transcatheter edge-to-edge repair (TEER). We sought to cross-validate the MitraScore and COAPT risk score to predict adverse events in patients undergoing TEER. Methods: MitraScore validation was carried out in the COAPT population which included 614 patients with FMR who were randomized 1:1 to guideline-directed medical therapy (GDMT) with or without TEER and were followed for 2 years. Validation of the COAPT risk score was carried out in 1007 patients from the MIVNUT registry of TEER-treated patients with both FMR and degenerative MR who were followed for a mean of 2.1 years. The predictive value was assessed using the area under the receiver operating characteristic curve (AUC) plots. The primary outcome was all-cause mortality. Results: The MitraScore had fair to good predictive accuracy for mortality in the overall COAPT trial population (AUC, 0.67); its accuracy was higher in patients treated with TEER (AUC, 0.74) than GDMT alone (AUC, 0.65). The COAPT risk score had fair predictive accuracy for death in the overall MitraScore cohort (AUC, 0.64), which was similar in patients with FMR and degenerative MR (AUC, 0.64 and 0.66, respectively). There was a consistent benefit of treatment with TEER plus GDMT compared with GDMT alone in the COAPT trial population across all MitraScore risk strata. Conclusions: The COAPT risk score and MitraScore are simple tools that are useful for the prediction of 2-year mortality in patients eligible for or undergoing treatment with TEER.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.529 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".