B-Type Natriuretic Peptides and Cardiac Troponins for Diagnosis and Risk-Stratification of Syncope
Bibliographic record
Abstract
Background: The utility of BNP (B-type natriuretic peptide), NT-proBNP (N-terminal proBNP), and hs-cTn (high-sensitivity cardiac troponin) concentrations for diagnosis and risk-stratification of syncope is incompletely understood. Methods: We evaluated the diagnostic and prognostic accuracy of BNP, NT-proBNP, hs-cTnT, and hs-cTnI concentrations, alone and against those of clinical assessments, in patients >45-years old presenting with syncope to the emergency department in a prospective diagnostic multicenter study. BNP, NT-proBNP, hs-cTnT and hs-cTnI concentrations were measured in a blinded fashion. Cardiac syncope, as adjudicated by 2 physicians based on all information available including cardiac work-up and 1-year follow-up, was the diagnostic end point. EGSYS (Evaluation of Guidelines in Syncope Study), a syncope-specific diagnostic score, served as the diagnostic comparator. Death and major adverse cardiac events at 30 and 720 days were the prognostic end points. Major adverse cardiac events were defined as death, cardiopulmonary resuscitation, life-threatening arrhythmia, implantation of pacemaker/implantable cardioverter defibrillator, acute myocardial infarction, pulmonary embolism, stroke/transient ischemic attack, intracranial bleeding, or valvular surgery. ROSE (Risk Stratification of Syncope in the Emergency Department), OESIL (Osservatorio Epidemiologico della Sincope nel Lazio), SFSR (San Fransisco Syncope Rule), and CSRS (Canadian Syncope Risk Score) served as the prognostic comparators. Results: Among 1538 patients eligible for diagnostic assessment, cardiac syncope was the adjudicated diagnosis in 234 patients (15.2%). BNP, NT-proBNP, hs-cTnT, and hs-cTnI were significantly higher in cardiac syncope versus other causes ( P <0.01). The diagnostic accuracy for cardiac syncope, as quantified by the area under the curve, was 0.77 to 0.78 (95% CI, 0.74–0.81) for all 4 biomarkers, and superior to EGSYS (area under the curve, 0.68 [95%-CI 0.65–0.71], P <0.001). Combining BNP/NT-proBNP with hs-cTnT/hs-cTnI further improved diagnostic accuracy to an area under the curve of 0.81 ( P <0.01). BNP, NT-proBNP, hs-cTnT, and hs-cTnI cut-offs, achieving predefined thresholds for sensitivity and specificity (95%), allowed for rule-in or rule-out of ≈30% of all patients. A total of 450 major adverse cardiac events occurred during follow-up. The prognostic accuracy of BNP, NT-proBNP, hs-cTnI, and hs-cTnT for major adverse cardiac events was moderate-to-good (area under the curve, 0.75–0.79), superior to ROSE, OESIL, and SFSR, and inferior to CSRS. Conclusions: BNP, NT-proBNP, hs-cTnT, and hs-cTnI concentrations provide useful diagnostic and prognostic information in emergency department patients with syncope. Clinical Trial Registration: URL: https://www.clinicaltrials.gov . Unique identifier: NCT01548352.
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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 | 0.012 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".