Serial Urinary C-C Motif Chemokine Ligand 14 and Risk of Persistent Severe Acute Kidney Injury
Bibliographic record
Abstract
OBJECTIVES: To assess the added prognostic value of serial monitoring of urinary C-C motif chemokine ligand 14 (uCCL14) over that of single measurements, which have been shown to be prognostic for development of persistent severe acute kidney injury (AKI) in critically ill patients. DESIGN: Retrospective observational study. SETTING: Data derived from two multinational ICU studies (Ruby and Sapphire). PATIENTS: Critically ill patients with early stage 2–3 AKI. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We analyzed three consecutive uCCL14 measurements at 12-hour intervals after diagnosis of stage 2–3 AKI by Kidney Disease Improving Global Outcomes criteria. Primary outcome was persistent severe AKI, defined as 72 consecutive hours of stage 3 AKI, death, or receipt of dialysis prior to 72 hours. uCCL14 was measured using the NEPHROCLEAR uCCL14 Test on the Astute 140 Meter (Astute Medical, San Diego, CA). Based on predefined, validated cutoffs, we categorized uCCL14 as: low (≤ 1.3 ng/mL), medium (> 1.3 to ≤ 13 ng/mL), or high (> 13 ng/mL). Seventy-five of 417 patients with three consecutive uCCL14 measurements developed persistent severe AKI. Initial uCCL14 category strongly correlated with primary endpoint and, in most cases (66%), uCCL14 category was unchanged over the first 24 hours. Compared with no change and accounting for baseline category, decrease in category was associated with decreased odds of persistent severe AKI (odds ratio [OR], 0.20; 95% CI, 0.08–0.45; p < 0.001) and an increase in category with increased odds (OR, 4.04; 95% CI, 1.75–9.46; p = 0.001). CONCLUSIONS: In one-third of patients with moderate to severe AKI uCCL14 risk category altered over three serial measurements and such changes were associated with altered risk for persistent severe AKI. Serial CCL-14 measurement may detect progression or resolution of underlying kidney pathology and help refine AKI prognosis.
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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 | 0.004 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".