Abstract
Genitourinary infections are common in female intensive care unit patients and are associated with acute kidney injury and sepsis, often becoming life-threatening. Although urine volume correlates with these adverse outcomes, the prognostic value of dynamic urine output trajectories remains unclear. This study investigates the relationship between early urine output trajectories and clinical outcomes in female with genitourinary infections. A retrospective cohort of 1289 patients were analyzed. Latent class growth modeling identified distinct urine output trajectories in the first 3 days after intensive care unit admission. The primary endpoint was 28-day mortality, and the secondary outcome was the incidence of acute kidney injury. Four trajectory classes were identified: Class 1-persistently low (65.7%), Class 2-high-to-low (13.7%), Class 3-persistently high (4.0%), and Class 4-low-to-high (16.7%). In multivariable analysis, compared to Class 4, the 28-day mortality risk showed a graded increase with hazard ratio of 4.329 for Class 1, 3.477 for Class 2, and 2.081 for Class 3. Additionally, Class 1 was associated with a significantly higher incidence of acute kidney injury compared to Class 4. The trajectory of urine output changes in female patients with genitourinary infections is a potential variable in predicting mortality and acute kidney injury outcomes.
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Data availability
The datasets generated and/or analysed during the current study are available in the MIMIC-IV Database, https://physionet.org/content/mimiciv/1.0/.
Abbreviations
- AIC:
-
Akaike Information Criterion
- AKI:
-
Acute kidney injury
- BIC:
-
Bayesian Information Criterion
- CRRT:
-
Continuous Renal Replacement Therapy
- DCA:
-
Decision curve analysis
- HR:
-
Hazard ratio
- ICU:
-
Intensive care unit
- KDIGO:
-
Kidney Disease: Improving Global Outcomes
- LCGM:
-
Latent Class Growth Modeling
- LOS:
-
Length of Stay
- OR:
-
Odds Ratio
- ROC:
-
Receiver Operating Characteristic
- SABIC:
-
Sample-Size Adjusted BIC
- SOFA:
-
Sequential Organ Failure Assessment
- UO:
-
Urine output
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Funding
This work was supported by the General Project of Qihang Fund of Fujian Medical University (Grant number 2024QH1120), the Science and Technology Project of Quan Zhou (Grant number 2025QZNG009).
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Wei-hong Chen and Jing Xu designed the study. Ling-tao Zheng extracted the data, performed the analysis. Hui-jie You drew the figure and table. Wei-hong Chen and Jing Xu wrote the paper. Yu-min Ke supervised the study.
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This study utilized data from the MIMIC-IV (Medical Information Mart for Intensive Care IV) database, a publicly available de-identified dataset approved by the Massachusetts Institute of Technology Institutional Review Board (MIT IRB). All protected health information was removed by the database administrators, and patients were assigned random identifiers to ensure privacy. The study complied with the Declaration of Helsinki and the MIMIC-IV Data Use Agreement.
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Chen, Wh., Xu, J., Zheng, Lt. et al. The impact of urine output trajectory on clinical outcomes in female patients with genitourinary infections in the intensive care unit. Sci Rep (2026). https://doi.org/10.1038/s41598-026-35926-3
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DOI: https://doi.org/10.1038/s41598-026-35926-3
