Clinical utility of B‐type natriuretic peptide (<scp>NP</scp>) in pediatric cardiac surgery – a systematic review
Bibliographic record
Abstract
BACKGROUND: NP is a biomarker that has been used in the diagnosis, management, and prognostication of a number of cardiovascular disorders in the pediatric population. The physiological role of this hormone is to allow the myocardium to adapt to stress or strain imposed by a volume and/or pressure load. OBJECTIVE: The aim of this study was to determine the utility of preoperative and postoperative NP to predict outcome in pediatric patients undergoing cardiac surgery for structural congenital heart disease. METHOD: We conducted a systematic review by searching three electronic databases using the search terms 'paediatric' or 'pediatric' and 'B-type natriuretic peptide'. Twenty peer-reviewed papers were included in the study. RESULTS: Preoperative NP levels were associated with the severity of cardiac failure in several studies. Preoperative NPs also correlated with early postoperative outcome measures such as duration of cardiopulmonary bypass, duration of mechanical ventilation, presence of low cardiac output syndrome, length of stay in the intensive care unit and in one study, death. Early (within 24 h) postoperative NPs showed a stronger correlation than preoperative NPs to early postoperative adverse events. CONCLUSION: NPs provide a simple, noninvasive and complementary tool to echocardiography that can be used to assist clinicians in the assessment and management of pediatric patients with congenital heart disease in the perioperative period.
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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 | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".