The following is a summary of “Redefining urine output thresholds for acute kidney injury criteria in critically Ill patients: a derivation and validation study,” published in the August 2024 issue of Critical Care by Machado et al.

Acute Kidney Injury (AKI) is characterized by increased serum creatinine (sCr) concentration and reduced urinary output (UO). The standard UO threshold of 0.5 ml/kg/h was suboptimal.

Researchers conducted a retrospective study to design and validate a novel UO-based AKI classification system for improving mortality prediction and patient stratification.

They interpreted data from the MIMIC-IV and eICU databases. The development process involved evaluating UO as a continuous variable across 3-, 6-, 12-, and 24-hour periods; identifying three optimal UO cutoff points for each time window (stages 1, 2, and 3); comparing sensitivity and specificity to create a unified staging system; assessing average versus persistent hourly reduced UO; comparing the new UO-AKI system with the KDIGO UO-AKI system; integrating sCr criteria with both systems and comparing them; and validating the new classification with an independent cohort. The preliminary outcome was hospital mortality, and  90-day mortality was also analyzed. ROC curve analysis, net reclassification improvement (NRI), integrated discrimination improvement (IDI), and logistic and Cox regression analyses were evaluated. 

The results showed that 35,845 patients from the MIMIC-IV database were included in the development cohort. After comparing the sensitivity and specificity of 12 different UO thresholds in 4-time frames, 3 cutoff points were selected to create the proposed UO-AKI classification: stage 1 (0.2–0.3 mL/kg/h), stage 2 (0.1–0.2 mL/kg/h), and stage 3 (< 0.1 mL/kg/h) over 6 hours. The classification showed the average method compared to the persistent method. The adjusted odds ratio had a stepwise increase in in-hospital mortality with the advancing UO-AKI stage. The classification, whether combined with the sCr criterion or not, outperformed the KDIGO criteria in predictive accuracy—AUC-ROC 0.75 (0.74–0.76) versus 0.69 (0.68–0.70); NRI: 25.4% (95% CI: 23.3–27.6); and IDI: 4.0% (95% CI: 3.6–4.5). The eICU database confirmed the performance of the new classification system. 

They concluded that UO-AKI classification improves mortality prediction and patient stratification, furnishing a more realistic approach than KDIGO criteria.

Source: ccforum.biomedcentral.com/articles/10.1186/s13054-024-05054-3#Abs1