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DOI 10.1007/s11255-025-04697-7

Медицинская библиотека · International urology and nephrology · 2025

Ultrasonic hemodynamic parameters for predicting acute kidney injury and establishment of a predictive model based on these parameters.

Wang Zhi-Ming, Chen Sheng-Jiang

СтатьяНаблюдательное исследованиеПеревод в очереди

Аннотация

BACKGROUND

This study was designed to explore the clinical utility of ultrasound hemodynamic parameters in predicting acute kidney injury (AKI) and assessing its severity.

METHODS

A total of 122 patients initially diagnosed with AKI were included in this prospective observational study. The ultrasound measurements were completed within 24 h of admission. Significant variables associated with AKI were identified through multivariable logistic regression. The discriminative power of the established model was evaluated using receiver operating characteristic (ROC) curve analysis.

RESULTS

Patients were stratified into the AKI group (AKI stages 1-3) and the non-AKI group (AKI stage 0). Serum creatinine (SCr) ≥ 111 μmol/L, renal resistive index (RRI) ≥ 0.70, and renal blood flow/cardiac output (RBF/CO) < 0.06 were identified as risk factors for AKI (P < 0.05) in the multivariate logistic regression analysis. The predictive model that was established to predict AKI incorporating these parameters demonstrated high accuracy. Patients were further categorized into the mild AKI group (AKI stages 0-1) and the severe AKI group (AKI stages 2-3). In the multivariate logistic regression analysis, SCr ≥ 210 μmol/L and RRI ≥ 0.73 emerged as risk factors for severe AKI (P < 0.05). Based on these two indicators, a corresponding predictive model was established to predict severe AKI.

CONCLUSION

In this study, it was found that early-stage AKI could be predicted using SCr, RRI, and RBF/CO, while SCr and RRI were effective in predicting the severity of AKI. These parameters may facilitate timely intervention in patients with AKI.

Для цитирования: Wang Zhi-Ming, Chen Sheng-Jiang. Ultrasonic hemodynamic parameters for predicting acute kidney injury and establishment of a predictive model based on these parameters.. International urology and nephrology. 2025. DOI: 10.1007/s11255-025-04697-7.

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