Prognostic Value of NT-ProBNP in Patients with Primary Mitral Regurgitation Undergoing Transcatheter Edge-To-Edge Repair
Bibliographic record
Abstract
AIMS: The prognostic value of N-terminal pro-B-type natriuretic peptide (NT-proBNP) in patients undergoing mitral valve transcatheter edge-to-edge repair (M-TEER) for primary mitral regurgitation (PMR) is unclear. This study assessed the association between NT-proBNP and outcomes and explored its additive value to the Mitral Regurgitation International Database (MIDA) score. METHODS AND RESULTS: PRIME-MR, a retrospective, international, multicentre registry, includes 3083 consecutive PMR patients treated with M-TEER. This analysis focused on 1382 patients (median age 81 years, 47% female, 82% New York Heart Association [NYHA] functional class III/IV, median EuroSCORE II 4.1%) with available NT-proBNP levels and follow-up. The primary endpoint was death or heart failure hospitalization within 3 years. Median NT-proBNP level was 1991 pg/ml (T1: 578, T3: 6285), and 384 patients reached the primary endpoint (Kaplan-Meier estimate: 48.5%). Log-transformed NT-proBNP levels independently predicted the primary endpoint (adjusted hazard ratio [HR] 1.17, 95% confidence interval [CI] 1.07-1.28; p < 0.001) after adjusting for NYHA class, haemoglobin, creatinine, and atrial fibrillation. In 1041 patients with a modified MIDA score (median 9), the score was initially associated with the primary endpoint (HR 1.10, 95% CI 1.04-1.17; p = 0.002), but lost significance when adjusting for NT-proBNP levels, which remained independently predictive (adjusted HR 1.20, 95% CI 1.07-1.34; p = 0.002). CONCLUSIONS: NT-proBNP, but not the MIDA score, was independently associated with death or heart failure hospitalizations within 3 years in M-TEER-treated PMR patients. Incorporating NT-proBNP levels into clinical assessment may improve risk stratification and potentially supports earlier intervention at lower NT-proBNP levels to optimize outcomes.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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".