Development of Predisposition,Injury,Response,Organ failure model for predicting acute kidney injury in acute on chronic liver failure.

Background and Aim There is limited data on predictors of acute kidney injury(AKI) in ACLF. We developed a PIRO model (Predisposition, Injury, Response, Organ failure) for predicting AKI in a multi-centric cohort of ACLF patients. Patients and Methods Data of 2360 patients from APASL-ACLF Research Consortium (AARC) was analysed. Multivariate logistic regression model (PIRO score) was developed from a derivation cohort (n=1363) which was validated in another prospective multicentric cohort of ACLF patients (n=997) Results Factors significant for P component were serum creatinine[(≥2mg/dl)OR 4.52, 95% CI (3.67-5.30)], bilirubin [(/dL,OR 1) versus (12-30 mg/dL,OR 1.45, 95% 1.1-2.63) versus (≥30 mg/dL,OR 2.6, 95% CI 1.3-5.2)], serum potassium [(/LOR-1)versus (3-4.9 mmol/L,OR 2.7, 95% CI 1.05-1.97) versus (≥5 mmol/L,OR 4.34, 95% CI 1.67-11.3)] and blood urea (OR 3.73, 95% CI 2.5-5.5); for I component nephrotoxic medications (OR-9.86, 95% CI 3.2-30.8); for R component,Systemic Inflammatory Response Syndrome,(OR-2.14, 95% CI 1.4-3.3); for O component, Circulatory failure (OR-3.5, 95% CI 2.2-5.5). The PIRO score predicted AKI with C-index of 0.95 and 0.96 in the derivation and validation cohort.The increasing PIRO score was also associated with mortality (p \u3c 0.001) in both the derivation and validation cohorts. Conclusions The PIRO model identifies and stratifies ACLF patients at risk of developing AKI. It reliably predicts mortality in these patients, underscoring the prognostic significance of AKI in patients with ACLF