Early Postoperative Serum Cystatin C Predicts Severe Acute Kidney Injury Following Pediatric Cardiac Surgery
Bibliographic record
Abstract
n this multicenter, prospective study of 288 children (half under 2 years of age) undergoing cardiac surgery, we evaluated whether the measurement of pre- and postoperative serum cystatin C (CysC) improves the prediction of acute kidney injury (AKI) over that obtained by serum creatinine (SCr). Higher preoperative SCr-based estimated glomerular filtration rates predicted higher risk of the postoperative primary outcomes of stage 1 and 2 AKI (adjusted odds ratios (ORs) 1.5 and 1.9, respectively). Preoperative CysC was not associated with AKI. The highest quintile of postoperative (within 6 h) CysC predicted stage 1 and 2 AKI (adjusted ORs of 6 and 17.2, respectively). The highest tertile of percent change in CysC independently predicted AKI, whereas the highest tertile of SCr predicted stage 1 but not stage 2 AKI. Postoperative CysC levels independently predicted longer duration of ventilation and intensive care unit length of stay, whereas the postoperative SCr change only predicted longer intensive care unit stay. Thus, postoperative serum CysC is useful to risk-stratify patients for AKI treatment trials. More research, however, is needed to understand the relation between preoperative renal function and the risk of AK
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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 | 0.003 |
| 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 | 0.001 |
| 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".