Elevated plasma levels of NT-proBNP in ambulatory patients with peripheral arterial disease
Bibliographic record
Abstract
N-terminal pro B-type natriuretic peptide (NT-proBNP), a cardiac disease biomarker, has been demonstrated to be a strong independent predictor of cardiovascular events in patients without heart failure. Patients with peripheral arterial disease (PAD) are at high risk of cardiovascular events and death. In this study, we investigated levels of NT-proBNP in patients with PAD compared to non-PAD controls. A total of 355 patients were recruited from outpatient clinics at a tertiary care hospital network. Plasma NT-proBNP levels were quantified using protein multiplex. There were 279 patients with both clinical and diagnostic features of PAD and 76 control patients without PAD (non-PAD cohort). Compared with non-PAD patients, median (IQR) NT-proBNP levels in PAD patients were significantly higher (225 ng/L (120-363) vs 285 ng/L (188-425), p- value = 0.001, respectively). Regression analysis demonstrated that NT-proBNP remained significantly higher in patients with PAD relative to non-PAD despite adjusting for age, sex, hypercholesterolemia, smoking and hypertension [odds ratio = 1.28 (1.07-1.54), p-value <0.05]. Subgroup analysis showed elevated NT-proBNP levels in patients with PAD regardless of prior history of CHF, CAD, diabetes and hypercholesteremia (p-value <0.05). Finally, spearmen's correlation analysis demonstrated a negative correlation between NT-proBNP and ABI (ρ = -0.242; p-value < 0.001). In conclusion, our data shows that patients with PAD in an ambulatory care setting have elevated levels of NT-proBNP compared to non-PAD patients in the absence of cardiac symptoms.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".