Urinary fatty acid binding protein 3 (uFABP3) is a potential biomarker for peripheral arterial disease
Bibliographic record
Abstract
Plasma levels of fatty acid binding protein 3 (pFABP3) are elevated in patients with peripheral artery disease (PAD). Since the kidney filters FABP3 from circulation, we investigated whether urinary fatty acid binding protein 3 (uFABP3) is associated with PAD, and also explored its potential as a diagnostic biomarker for this disease state. A total of 130 patients were recruited from outpatient clinics at St. Michael's Hospital, comprising of 65 patients with PAD and 65 patients without PAD (non-PAD). Levels of uFABP3 normalized for urine creatinine (uFABP3/uCr) were 1.7-folds higher in patients with PAD [median (IQR) 4.41 (2.79-8.08)] compared with non-PAD controls [median (IQR) 2.49 (1.78-3.12), p-value = 0.001]. Subgroup analysis demonstrated no significant effect of cardiovascular risk factors (age, sex, hypertension, hypercholesteremia, diabetes and smoking) on uFABP3/uCr in both PAD and non-PAD patients. Spearmen correlation studies demonstrated a significant negative correlation between uFABP3/uCr and ABI (ρ = - 0.436; p-value = 0.001). Regression analysis demonstrated that uFABP3/Cr levels were associated with PAD independently of age, sex, hypercholesterolemia, smoking, prior history of coronary arterial disease and Estimated Glomerular Filtration rate (eGFR) [odds ratio: 2.34 (95% confidence interval: 1.47-3.75) p-value < 0.001]. Lastly, receiver operator curve (ROC) analysis demonstrated unadjusted area under the curve (AUC) for uFABP3/Cr of 0.79, which improved to 0.86 after adjusting for eGFR, age, hypercholesteremia, smoking and diabetes. In conclusion, our results demonstrate a strong association between uFABP3/Cr and PAD and suggest the potential of uFABP3/Cr in identifying patients with PAD.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".