Neutrophil Percentage-to-Albumin Ratio as a Predictor of Acute Kidney Injury in Cirrhotic Patients: A Novel Approach Utilizing Artificial Intelligence.

Introduction: Acute kidney injury (AKI) is common in cirrhotic patients and is associated with a poor prognosis. The neutrophil percentage-to-albumin ratio (NAR) is a novel marker of systemic inflammation. This study aimed to evaluate the predictive power of NAR for AKI in cirrhotic patients with ascites using AI tools such as Shapley Additive Explanations and a Random Forest (RF) model.

Methods: This study involved 322 patients with liver cirrhosis and ascites. AKI was defined based on the International Club of Ascites. The sensitivity and specificity of the NAR were evaluated using receiver operating characteristic curve analysis. Predictors of AKI were identified, and the significance of artificial intelligence features was determined using Shapley Additive Explanations. The RF model was utilized to rank all predictors for AKI.

Results: In our study, 130 patients (40.3%) developed AKI, with stages 2 and 3 analyzed for clinical relevance. The NAR at a cutoff of >23.2 revealed a substantial predictive value for AKI stages 2 and 3 (AUC = 0.893, sensitivity = 85.4%, specificity = 72.3%). The RF model identified serum albumin as the top predictor with an importance score of 0.350, followed by NAR with a score of 0.280, and chronic kidney disease ranked third with a score of 0.170. These factors are key drivers in predicting the outcome of AKI. Age, ischemic heart disease, diabetes mellitus, international normalized ratio, and hemoglobin had lower predictive power.

Conclusion: NAR could be a new, affordable, and non-invasive test demonstrating a strong discriminative ability to predict AKI in cirrhotic patients.