Risk factors for predicting acute kidney injury in children with septic shock: a retrospective cohort study.

BACKGROUND

Acute kidney injury (AKI) is a prevalent and severe complication of septic shock in children, yet data on its risk factors remain scarce. This study aims to identify key predictors for AKI in this population and develop a clinical model for early risk assessment.

METHODS

We conducted a retrospective analysis of clinical data from 180 children diagnosed with septic shock at a large tertiary hospital in China over 10 years. Multivariate analysis was performed to identify independent risk factors for AKI. Based on the results of the multivariate analysis, a clinical predictive nomogram for assessing the risk of sepsis-associated AKI (SA-AKI) in children with septic shock was established and validated using the "rms" package in R 4.3.0 software.

RESULTS

The incidence of AKI in children with septic shock was 44.4%, with significant predictors identified as greater height (95% CI 1.01-1.04), positive random proteinuria (95% CI 1.17-13.09), elevated procalcitonin levels (95% CI 1.00-1.04), base excess (95% CI 0.85-0.99), increased blood urea nitrogen levels (95% CI 1.03-1.22), and prolonged prothrombin time by ≥ 3 s (95% CI 1.13-11.43). Early use of antibiotics (95% CI 0.03-0.77) demonstrated a protective effect. The developed clinical predictive nomogram's ROC curve AUC was 0.895 (95% CI 0.836-0.955), with a sensitivity of 77.1% and specificity of 88.9%. It outperformed individual variables in predicting SA-AKI, and demonstrated good calibration and clinical utility as shown by the calibration and DCA curve. Internal validation by the bootstrap resampling method (1000 times) confirmed the model's accuracy with an AUC of 0.895 (95% CI 0.893-0.896).

CONCLUSIONS

Recognizing these risk factors facilitates timely interventions for pediatric patients with septic shock. The nomogram serves as a valuable tool for clinicians, improving the management of AKI and potentially enhancing patient outcomes.