Incremental value of high-sensitivity C-reactive protein and N-terminal pro-B-type natriuretic peptide for the prediction of postoperative cardiac events in noncardiac vascular surgery patients
Bibliographic record
Abstract
OBJECTIVES: High-sensitivity C-reactive protein (hs-CRP) and N-terminal pro-B-type natriuretic peptide (NT-proBNP) are associated with the presence of coronary artery disease. The aim of this study was to assess the prognostic value of hs-CRP and NT-proBNP for postoperative cardiac events in noncardiac vascular surgery patients. METHODS: In 592 patients, cardiac history, hs-CRP, and NT-proBNP levels were assessed preoperatively. Levels of hs-CRP of at least 6.5 mg/l and NT-proBNP of at least 350 pg/ml were defined as the optimal cut-off values for the prediction of postoperative cardiac events. The end point was the composite of 30-day cardiovascular death, Q-wave myocardial infarction, and troponin T release. Multivariable regression analysis was used to evaluate the association between hs-CRP, NT-proBNP and the end point. The performance of the risk models based on cardiac risk factors alone and the addition of both biomarkers was determined using C statistics. RESULTS: After adjustment for cardiac risk factors, site of surgery and type of procedure, elevated levels of hs-CRP (odds ratio 2.54; 95% confidence interval 1.50-4.30) and NT-proBNP (odds ratio 4.78; 95% confidence interval 2.71-8.42) remained independent predictors for postoperative cardiac events. When hs-CRP and NT-proBNP were added to the cardiac risk score, the C statistic improved from 0.79 to 0.84. A combined elevation of hs-CRP and NT-proBNP provided a seven-fold higher risk for postoperative cardiac events. CONCLUSION: Both hs-CRP and NT-proBNP have additional value in the prediction of postoperative cardiac events in vascular surgery patients. Their integrated use improves cardiac risk stratification.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
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 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".