Analysis of N-terminal pro-B-type natriuretic peptide in patients with acute coronary syndromes
Bibliographic record
Abstract
BACKGROUND: The N-terminal portion of brain natriuretic peptide (NT-proBNP) has been identified as an indicator of prognosis in different cardiovascular diseases. The objective of this study was to determine the utility of measuring plasma NT-proBNP levels in patients with acute coronary syndromes. METHODS AND RESULTS: We studied 66 patients admitted in our division for acute coronary syndromes. Patients underwent a venous blood sample within 24 h from the admission to determine NT-proBNP levels. Increasing plasma levels of NT-proBNP (in tertiles) was associated with a greater history of hypertension and current smoking, whereas biochemical parameters were associated with higher level of creatine kinase-MB mass, cardiac troponin I, and renal insufficiency. We detected correlations between the values of NT-proBNP and several variables; positive correlations were found between the values of NT-proBNP and creatinine (r=+0354; P=0.0024), cardiac troponin I levels (r=0320; P=0.0111), and creatine kinase-MB mass values (r=0261; P=0.035). An interesting result of our study was a significantly longer hospitalization in those patients belonging to the third tertile compared with those belonging to the first one (P=0.02). Finally, we showed a higher N-terminal brain natriuretic peptide level in patients with poor outcome during the hospitalization (left-ventricular systolic dysfunction, recurrent ischemic events, or death) compared with those who did not (3204+/-1841 vs. 836+/-1136, P=0.003). CONCLUSION: Measurement of B-type natriuretic peptide provides predictive information during the hospitalization in patients with acute coronary syndromes.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".