Prognostic Value of Plasma B-Type Natriuretic Peptide in the Long-Term Follow-up of Patients With Transposition of the Great Arteries With Morphologic Right Systemic Ventricle After Atrial Switch Operation
Bibliographic record
Abstract
BACKGROUND: B-type natriuretic peptide (BNP) is an established marker for heart failure assessment, but the prognostic quality of BNP after atrial switch operation (ASO) has not yet been elucidated. METHODS AND RESULTS: In 89 patients (median age, 24 years; range, 15-35 years) after ASO, BNP was measured. During a 48-months follow-up we focused on critical cardiac events, defined as decompensation, sudden cardiac death or need for heart transplantation. BNP was considerably lower in 81 patients in functional class (FC) I/II (median, 35 pg/ml; range, 3-586 pg/ml) than in 6 patients in FC III/IV (median, 246 pg/ml; range, 14-1,150 pg/ml, P≤0.073). BNP was significantly higher after Mustard than after Senning procedure (P≤0.030). There was no significant difference in BNP between simple or complex transposition of the great arteries (TGA) (P≤0.44). Eleven subjects (13%, 95% CI: 7-22%) had a critical cardiac event within 48 months. On ROC analysis BNP had a high predictive value regarding discrimination of patients with and without critical events (area under the ROC curve, 0.90; 95% CI: 0.76 to >0.99, P<0.001). The cut-off was 85 pg/ml (sensitivity, 88%; specificity, 85%). Additionally, estimated event-free-survival was longer after Senning than after Mustard procedure (P≤0.017). There was no significant difference in outcome between patients with simple or complex TGA with regard to occurrence of critical events. CONCLUSIONS: BNP is a sensitive and specific prognostic marker for critical cardiac events after ASO.
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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 | 0.002 |
| 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 | 0.001 | 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".