Comparative analysis of urinary biomarkers for early detection of acute kidney injury following cardiopulmonary bypass
Bibliographic record
Abstract
The purpose of this study was to compare the performance of six candidate urinary biomarkers, kidney injury molecule (KIM)-1, N-acetyl-beta-D-glucosaminidase (NAG), neutrophil gelatinase-associated lipocalin (NGAL), interleukin (IL)-18, cystatin C and alpha-1 microglobulin, measured 2 h following cardiopulmonary bypass (CPB) for the early detection of acute kidney injury (AKI) in a prospective cohort of patients undergoing cardiac surgery. A total of 103 subjects were enrolled; AKI developed in 13%. Urinary KIM-1 achieved the highest area under-the-receiver-operator-characteristic curve (AUC 0.78, 95% confidence interval 0.64-0.91), followed by IL-18 and NAG. Only urinary KIM-1 remained independently associated with AKI after adjustment for a preoperative AKI prediction score (Cleveland Clinic Foundation score; p = 0.02), or CPB perfusion time (p = 0.006). In this small pilot cohort, KIM-1 performed best as an early biomarker for AKI. Larger studies are needed to explore further the role of biomarkers for early detection of AKI following cardiac surgery.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".