Objective:

To develop and internally validate a prediction model using first serum laboratory indicators after hospital admission to predict the risk of sepsis-associated acute kidney injury (SA-AKI).

Approach:

Key Findings:

• LASSO regression identified 10 serum indicators; multivariate logistic regression confirmed 8 independent risk factors: MYO, ALT, PO4, Na, K, CO2-CP, PLT, and NEUT (all P 0.81).

Interpretation:

The study developed a predictive model for SA-AKI risk using initial serum biomarkers, providing a nomogram for risk estimation.

Limitations:

• The study was conducted at a single center, limiting generalizability.
• External validation in multi-center, diverse cohorts is necessary before broader clinical implementation.

Conclusion:

The predictive model supports early risk stratification of high-risk individuals for SA-AKI in sepsis patients.

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