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Plasma Insulin-Like Growth Factor-Binding Protein-2 Levels Predict Severe Septic Acute Kidney Injury: A Mendelian
Bozhi Zhao1, Zuyi Zhao1, Zhengkai Wang1
1Intensive Care Unit, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, CHN.
Cureus
|April 15, 2025
Summary
Plasma insulin-like growth factor-binding protein-2 (IGFBP-2) levels show promise in predicting sepsis-associated acute kidney injury (SA-AKI). However, Mendelian randomization analysis indicates no direct causal link between IGFBP-2 and septic kidney injury.
Area of Science:
- Nephrology
- Critical Care Medicine
- Biomarker Discovery
Background:
- Sepsis-associated acute kidney injury (SA-AKI) lacks sensitive early detection biomarkers, leading to delayed intervention and increased mortality.
- Early identification of SA-AKI is crucial for timely treatment and improved patient outcomes.
Purpose of the Study:
- To investigate the association between insulin-like growth factor-binding protein-2 (IGFBP-2) levels and the incidence of sepsis-induced kidney injury.
- To evaluate a potential causal relationship between IGFBP-2 and SA-AKI using Mendelian randomization (MR) analysis.
Main Methods:
- A prospective cohort study of 79 sepsis patients in the Intensive Care Unit (ICU).
- Patients were categorized into SA-AKI and non-SA-AKI groups based on development within 48 hours of admission.
- Mendelian randomization and sensitivity analyses were performed to assess causality.
Main Results:
- IGFBP-2 demonstrated high diagnostic value for SA-AKI prediction (AUC=0.8994).
- Combined prediction using IGFBP-2, APACHE II, SOFA scores, and vasopressor use yielded an AUC of 0.9604.
- MR analysis found no causal relationship between genetically predicted IGFBP-2 levels and AKI (p=0.2995).
Conclusions:
- Plasma IGFBP-2 levels are predictive of SA-AKI in sepsis patients.
- Despite predictive value, MR analysis suggests no direct causal link between IGFBP-2 and septic kidney injury.
- Further research, including randomized controlled trials, is needed to elucidate underlying mechanisms.

