Clinical Outcomes and Cost Analysis in Patients with Heart Failure Undergoing Transcatheter Edge-to-Edge Repair for Mitral Valve Regurgitation
Bibliographic record
Abstract
Objective: To analyze the clinical and cost outcomes of transcatheter edge-to-edge repair (TEER) for mitral regurgitation (MR) in heart failure (HF) patients. Methods: All 162 HF patients undergoing TEER for MR between January 2019 and March 2023 were included. A propensity-adjusted analysis was used to compare 32 systolic vs. 97 diastolic vs. 33 mixed (systolic + diastolic) HF patients. Systolic, diastolic, and mixed HF patients were defined according to AHA guidelines. The primary outcome was the long-term incidence of all-cause death and major adverse cardiovascular and cerebrovascular events (MACCEs, all-cause mortality + stroke + myocardial infarction + repeat intervention). Results: The mean age was 76.3 vs. 80.9 vs. 76 years old, and the mean ejection fraction (EF) was 39.5% vs. 59.8% vs. 39.7% in systolic vs. diastolic vs. mixed HF, respectively. Postoperatively, the diastolic vs. systolic HF group had a higher intensive care unit stay (21 vs. 0 h; HR 67.5 (23.7, 111.4)]; lower ventilation time [2 vs. 2.3 h; HR 49.4 (8.6, 90.2)]; lower EF [38% vs. 58.5%; HR 9.9 (3.7, 16.1)]. In addition, the diastolic vs. mixed HF groups had a lower incidence of EF < 50% (11 vs. 27 patients; HR 6.6 (1.6, 27.3) and a lower use of dialysis (one vs. three patients; HR 18.1 (1.1, 287.3), respectively. At a mean 1.6 years follow-up, all-cause death [HR 39.8 (26.2, 60.5)], MACCEs [HR 50.3 (33.7–75.1)], and new pacemaker implantations [HR 17.3 (8.7, 34.6)] were higher in the mixed group. There was no significant total hospital cost difference among the systolic (USD 106,859) vs. diastolic (USD 91,731) vs. mixed (USD 120,522) HF groups (p = 0.08). Conclusions: TEER for MR evidenced the worst postoperative and follow-up clinical outcomes in the mixed HF group compared to diastolic and systolic HF groups. No total hospital cost differences were observed.
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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) | 0.001 | 0.004 |
| Bibliometrics | 0.001 | 0.000 |
| 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".