Fatty Acid Binding Protein 4—A Circulating Protein Associated with Peripheral Arterial Disease in Diabetic Patients
Bibliographic record
Abstract
Diabetic patients with peripheral arterial disease (PAD) often suffer from poor clinical outcomes such as limb-loss. Fatty acid binding protein 4 (FABP4) is mainly expressed by adipocytes and is known to play a significant role in the development of atherosclerosis. In this study, we sought to investigate whether FABP4 is associated with PAD in patients with type 2 diabetes mellitus (DM). FABP4 plasma levels were studied in 119 diabetic patients with PAD (DM-PAD) and 49 diabetic patients without PAD (DM-noPAD) presenting to St. Michael’s Hospital between October 2017 and September 2018. Levels of FABP4 in DM-PAD patients (23.34 ± 15.27 ng/mL) were found to be over two-fold higher than the levels in DM-noPAD patients (10.3 ± 7.59 ng/mL). Regression analysis demonstrated a significant association between FABP4 levels and DM-PAD after adjusting for age, sex, prior history of coronary arterial disease and white blood cells count (OR, 2.77; 95% CI, 1.81–4.31; p-value = 0.001). Relative to DM-noPAD controls, plasma FABP4 levels in DM-PAD patients were noted to be inversely correlated with the ankle brachial index (ABI; r= −0.374, p-value < 0.001). The diagnostic ability of FABP4 was investigated using receiver operator curves (ROC) and area under the curve (AUC) analysis. FABP4 had an AUC of 0.79, which improved to 0.86 after adjusting for age, sex and prior history of coronary arterial disease. This raises a possibility of utilizing FABP4 as a biomarker for diagnosing PAD in diabetic patients.
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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".