Usefulness of NT-pro BNP monitoring to identify echocardiographic responders following cardiac resynchronization therapy
Bibliographic record
Abstract
BACKGROUND: Cardiac resynchronization therapy (CRT) improves left ventricular (LV) volumes, mitral regurgitation (MR) severity and symptoms of patients with heart failure (HF). However, >or= 30% of patients have no significant clinical or echocardiographic improvement following CRT. Reverse remodeling after CRT correlates with improved clinical outcomes. We hypothesized that in NT-pro BNP monitoring is accurate to identify responders following CRT. METHODS: 42 consecutive patients (mean age 66 +/- 12 years, male 68%) with HF undergoing CRT were prospectively enrolled. Responders at follow-up were defined by echocardiography (decrease in LV end systolic volume >or= 15%). Echocardiography and NT-pro BNP measurement were performed at baseline and repeated 3 to 6 month after CRT. RESULTS: There was no significant difference between responders (n = 29, 69%) and non-responders (n = 13, 31%) regarding baseline NT-pro BNP level. Responders had significantly higher decrease in NT-pro BNP levels during follow-up than non-responders (absolute: -1428 +/- 1333 pg x ml-1 vs. -61 +/- 959 pg x ml-1, p = 0.002; relative: -45 +/- 28% vs. 2 +/- 28%, p < 0.0001). A decrease of >or= 15% in NT-pro BNP 3-6 months after CRT identifies echocardiographic responders with a sensitivity of 90% and a specificity of 77%. CONCLUSION: NT-pro BNP monitoring can accurately identify echocardiographic responders after CRT.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.001 | 0.002 |
| 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".