Bone morphogenetic protein 10 as a predictor for recurrent atrial fibrillation after catheter ablation
Bibliographic record
Abstract
Abstract Funding Acknowledgements Type of funding sources: None. Background Atrial fibrillation (AF) recurrence after catheter ablation (CA) poses a major challenge. The novel atrial-specific biomarker, bone morphogenetic protein 10 (BMP10), might aid in the selection of appropriate patients for CA. Purpose We aimed to assess the predictive value BMP10 for AF recurrence after CA in a large cohort of AF patients. Methods We measured baseline BMP10 concentrations in AF patients who underwent elective CA for the first time. Patients were enrolled in a single-center prospective cohort study. The primary outcome variable was AF recurrence during 12 months’ follow-up using 2 x 24h and 1 x at least 4-day Holter. We constructed Cox proportional hazard models to determine the association of BMP10 and AF recurrence. The multivariable model was adjusted for age, sex, body mass index, and cardiovascular risk factors. Results A total of 1,112 AF patients (74% male) with a mean age of 61 ± 10 years were included in our analysis (60% paroxysmal AF, 40% persistent AF). The 12-month follow-up examination revealed that AF recurred in 374 (33.6%) patients. Kaplan-Meier curves for recurrent AF according to BMP10 quartiles are shown in the Figure (BMP10 quartile I: 0.76-1.50 ng/mL, quartile II: 1.50-1.72 ng/mL, quartile III: 1.72-1.99 ng/mL, quartile IV: 1.99-3.75 ng/mL). In the unadjusted Cox proportional hazard model, a per-unit increase in log transformed BMP10 was associated with a hazard ratio (HR) of 2.28 (95% CI 1.43, 3.62; p < 0.001) for AF recurrence. After multivariable adjustment, the HR of BMP10 was 1.98 (95% CI 1.14; 3.42, p = 0.01) for AF recurrence. Conclusion The novel atrial-specific biomarker BMP10 was associated with AF recurrence after CA in our large cohort of AF patients.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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".