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Predicting Renal Replacement Therapy Requirement In Sepsis-Associated Acute Kidney Injury Using Furosemide Stress
Shujuan Ning1, Jingyan Chen2, Jinlan Ma3
1First Clinical Medical College, Ningxia Medical University; Department of Intensive Care Unit, Zhongwei People's Hospital.
A new model combining the furosemide stress test (FST) with urinary tissue inhibitor of metalloproteinase-2 (TIMP-2) and insulin-like growth factor-binding protein 7 (IGFBP-7) shows high accuracy in predicting the need for renal replacement therapy (RRT) in sepsis-associated acute kidney injury (SA-AKI) patients. This tool aids in early risk stratification for SA-AKI.
Area of Science:
- Nephrology
- Critical Care Medicine
- Biomarker Research
Background:
- Sepsis-associated acute kidney injury (SA-AKI) is a common and severe complication in intensive care units (ICUs).
- Early identification of SA-AKI patients requiring renal replacement therapy (RRT) is crucial for timely intervention and improved outcomes.
- Current predictive models for RRT in SA-AKI have limitations in accuracy and timeliness.
Purpose of the Study:
- To evaluate the predictive value of a combined model using the furosemide stress test (FST) and urinary biomarkers (tissue inhibitor of metalloproteinase-2 [TIMP-2] and insulin-like growth factor-binding protein 7 [IGFBP-7]) for RRT initiation within 7 days in SA-AKI patients.
- To assess the performance of this combined model compared to individual components.
Main Methods:
- A prospective study involving 63 SA-AKI patients admitted to ICUs.
- Patients were divided into RRT (n=20) and non-RRT (n=43) groups based on RRT initiation within 7 days.
- Urinary TIMP-2 and IGFBP-7 levels were measured using ELISA. The furosemide stress test (FST) was performed, and urinary biomarkers were re-measured 2 hours post-FST.
- Multivariate logistic regression and receiver operating characteristic (ROC) curve analysis were used to evaluate predictive performance.
Main Results:
- The combined model incorporating FST and urinary [TIMP-2] * [IGFBP-7] demonstrated a high area under the curve (AUC) of 0.966.
- Individual components also showed predictive value: FST (AUC=0.878), baseline TIMP-2*IGFBP-7 (AUC=0.820), and post-FST TIMP-2*IGFBP-7 (AUC=0.845).
- The combined model was identified as an independent predictor of RRT requirement in SA-AKI patients.
Conclusions:
- The combined model of FST and urinary TIMP-2*IGFBP-7 offers a robust and accurate tool for early risk stratification of SA-AKI patients.
- This model can help identify patients at high risk of requiring RRT, enabling prompt clinical decision-making.
- Further validation in larger cohorts is warranted to confirm its clinical utility.
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