Urinary neutrophil gelatinase-associated lipocalin (NGAL) can potentially predict vascular complications and reliably risk stratify patients with peripheral arterial disease
Bibliographic record
Abstract
Neutrophil gelatinase-associated lipocalin (NGAL) is expressed in atherosclerotic plaques and implicated in the development of cardiovascular diseases. Peripheral arterial disease (PAD) is an atherosclerotic disease that often results in major cardiovascular events. This study aimed to prospectively examine the potential of urine NGAL (uNGAL) in predicting worsening PAD status and major adverse limb events (MALE). Baseline urine NGAL (uNGAL) and urine creatinine (uCr) concentrations were measured in PAD (n = 121) and non-PAD (n = 77) patients. Levels of uNGAL were normalized for urine creatinine (uNGAL/uCr). Outcomes included worsening PAD status, which was defined as a drop in ankle brachial index (ABI) > 0.15, and major adverse limb events (MALE), which was defined as a need for surgical revascularization or amputations. PAD patients had 2.30-fold higher levels of uNGAL/uCr [median (IQR) 31.8 (17.0-62.5) μg/g] in comparison to non-PAD patients [median (IQR) 73.3 (37.5-154.7) μg/g] (P = 0.011). Multivariate cox analysis showed that uNGAL/uCr levels were independently associated with predicting worsening PAD status and MALE outcomes. Cumulative survival analysis, over follow up period, demonstrated a direct correlation between elevated uNGAL/uCr levels and PAD disease progression and MALE outcomes. These data demonstrate an association between elevated uNGAL/uCr levels and worsening PAD disease status and MALE outcomes, indicating its potential for risk-stratification of PAD 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".