Background: Acute kidney injury (AKI) is one of the most common complications for critically ill patients with cirrhosis, but it has remained unclear whether urine output fluctuations are associated with the risk of AKI in such patients. Thus, we explored the influence of 24-h urine-output trajectory on AKI in patients with cirrhosis through latent category trajectory modeling.
Materials and methods: This retrospective cohort study examined patients with cirrhosis using the MIMIC-IV database. Changes in the trajectories of urine output within 24 h after admission to the intensive care unit (ICU) were categorized using latent category trajectory modeling. The outcome examined was the occurrence of AKI during ICU hospitalization. The risk of AKI in patients with different trajectory classes was explored using the cumulative incidence function (CIF) and the Fine-Gray model with the sub-distribution hazard ratio (SHR) and the 95% confidence interval (CI) as size effects.
Results: The study included 3,562 critically ill patients with cirrhosis, of which 2,467 (69.26%) developed AKI during ICU hospitalization. The 24-h urine-output trajectories were split into five classes (Classes 1-5). The CIF curves demonstrated that patients with continuously low urine output (Class 2), a rapid decline in urine output after initially high levels (Class 3), and urine output that decreased slowly and then stabilized at a lower level (Class 4) were at higher risk for AKI than those with consistently moderate urine output (Class 1). After fully adjusting for various confounders, Classes 2, 3, and 4 were associated with a higher risk of AKI compared with Class 1, and the respective SHRs (95% CIs) were 2.56 (1.87-3.51), 1.86 (1.34-2.59), and 1.83 1.29-2.59).
Conclusions: The 24-h urine-output trajectory is significantly associated with the risk of AKI in critically ill patients with cirrhosis. More attention should be paid to the dynamic nature of urine-output changes over time, which may help guide early intervention and improve patients' prognoses.
Keywords: Acute kidney injury; cirrhosis; latent category trajectory modeling; urine output.