P5459MR-proANP and NT-proBNP as specific indicators of procedural success in patients with severe mitral regurgitation undergoing percutaneous mitral valve repair (MitraClip)
Bibliographic record
Abstract
Background: Percutaneous mitral valve repair (PMVR) is an interventional treatment option in patients with severe mitral regurgitation (MR) who have a high risk for open-heart surgery. Although PMVR is safe and feasible, there is currently limited information on predictors of clinical outcome and procedural success after the MitraClip procedure. Severe mitral valve regurgitation (MR) is associated with left atrial (LA) and ventricular (LV) pressure and volume overload that can lead to aggravation of heart failure and dyspnea. Elevated blood levels of mid-regional pro-atrial natriuretic peptide (MR-proANP) and N-terminal brain natriuretic peptide (NT-proBNP) were consistently found to be associated with atrial and ventricular volume overload in patients with severe MR. The aim of the present study was to examine the diagnostic value of MR-proANP and NT-proBNP as specific indicators of therapeutic success in high-risk patients undergoing PMVR using the MitraClip system. Methods: A total of 120 consecutive patients (age: 77.4 yrs [±7.5] years) undergoing PMVR were included in this study. PMVR was performed according to standard clinical practice using the MitraClip® system. Procedural success was defined as a reduction of MR by ≥2 grades after PMVR. Venous blood samples were collected for biomarker analysis prior to and 24 h after PMVR. Samples were processed immediately and frozen at -80 °C until assay.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.001 | 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".