To develop and validate a predictive model for the progression of chronic kidney disease (CKD) to end-stage kidney disease (ESKD) specifically incorporating serum bilirubin levels.
Key Findings:
Serum bilirubin levels were identified as strong predictors for the progression of CKD to ESKD, highlighting their significance alongside other predictors.
The developed model demonstrated excellent predictive performance with a 2-year AUC of 0.943 and a 5-year AUC of 0.935.
The model included 9 key variables: eGFR, serum bilirubin, proteinuria, age, diabetes, gender, hypertension, serum albumin, and hemoglobin.
Interpretation:
Incorporating serum bilirubin levels into CKD progression models significantly enhances predictive accuracy for ESKD, potentially transforming clinical decision-making.
Limitations:
The study was conducted in a single country, which may limit generalizability and introduce biases.
The cohort was limited to individuals aged 20-69, potentially excluding older populations and affecting the applicability of the findings.
Conclusion:
The novel prediction model effectively predicts ESKD in CKD patients by integrating serum bilirubin levels, which may improve clinical decision-making.
