Biomarkers upon discontinuation of renal replacement therapy predict 60‐day survival and renal recovery in critically ill patients with acute kidney injury
Bibliographic record
Abstract
INTRODUCTION: There is no consensus on the specific indications for weaning critically ill patients with acute kidney injury (AKI) off renal replacement therapy (RRT). This study aimed to explore the prognostic value of several biomarkers measured upon discontinuation of RRT for their value in predicting 60-day survival and renal recovery in an effort to add knowledge to the decision-making process regarding RRT withdrawal. METHODS: We prospectively enrolled 102 patients with AKI who required RRT from the intensive care unit. Serum osteopontin (sOPN), serum interleukin 6 (sIL-6), serum cystatin C (sCysC), sIL-18, serum neutrophil gelatinase-associated lipocalin and urinary IL-18 and urinary neutrophil gelatinase-associated lipocalin were measured upon discontinuation of RRT. Patients were followed up at 60 days for survival and renal recovery. FINDINGS: Patients who survived showed lower levels of all serum and urinary biomarkers. Serum OPN (OR 1.029, 95% CI 1.013-1.047, P = 0.001), diabetes (OR 23.157, 95% CI 4.507-118.981, P < 0.001) and APACHE II score (OR 1.308, 95% CI 1.121-1.527, P = 0.001) were independent predictors of 60-day mortality. Patients whose sOPN values fell within the highest and middle tertiles showed 5.25- and 2.31-fold increased risks of mortality, respectively, compared with that of patients in the lowest tertile. The addition of sOPN to the clinical model resulted in significant net reclassification improvement of 0.453 (P = 0.026) and an integrated discriminative index of 0.155 (P = 0.032). Lower levels of sOPN and sIL-6 were associated with greater odds of 60-day survival (AUC 0.812 and 0.741). The AUC value for predicting survival reached its highest level when all biomarkers were combined with urine output (UO) and urinary and serum creatinine upon discontinuation of RRT (0.882). Lower sCysC performed as well as higher UO in predicting 60-day renal recovery with the greatest AUC of 0.743. DISCUSSION: Upon discontinuation of RRT, serum and urinary biomarkers, particularly sOPN, may predict 60-day survival and renal recovery in critically ill patients with AKI. The serum levels of OPN, IL-6 and CysC may be useful when considering withdrawal of RRT on the basis of conventional indicators.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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".