Abstrakt: |
Background/Aims Prognostic Nutritional Index (PNI) is an immunonutritional biomarker with established prognostic value in various malignant and non-malignant diseases. This study aimed to evaluate the PNI's ability to predict liver-related mortality and cirrhosis recompensation following decompensation. Methods Cirrhotic patients admitted for first liver decompensation between 2000 and 2021 were retrospectively analyzed. Decompensation events included ascites, variceal hemorrhage, and hepatic encephalopathy. PNI was calculated at admission as 10×serum albumin (g/dL)+0.005×lymphocyte count(/mm3). Cirrhosis recompensation was defined according to Baveno VII consensus. The discriminative performance of PNI was assessed using ROC analysis and area under the curve (AUC). Cox regression was employed to determine hazard ratios (HR). Results Ninety-nine patients (mean age 61±11 years, 56.6% female) were included. Ascites was the most common decompensation event (n=81), followed by variceal hemorrhage (n=13) and hepatic encephalopathy (n=11), with 10 patients presenting multiple concurrent events. Over a median follow-up of 22 months [13–88 months], 15 patients (15.2%) died from liver-related causes, and 45 patients (45.5%) achieved recompensation. PNI demonstrated excellent predictive performance for recompensation, with a HR of 1.14 (95%CI: 1.09–1.20, p<0.001) and an AUC of 0.96 (p<0.001). PNI of 33.38 or higher yielded 96% sensitivity, 93% specificity, 93% positive predictive value (PPV), 96% negative predictive value (NPV), and 94% diagnostic accuracy (DA). PNI also predicted liver-related mortality, yet with lower performance, with a HR of 0.86 (95%CI: 0.76–0.96, p=0.012) and an AUC of 0.78 (p=0.012). A score below 33.38 had 100% sensitivity, 61% specificity, 100% NPV, 32% PPV, and 67% DA. Conclusion PNI is a simple and effective prognostic indicator in decompensated cirrhosis, predicting both liver-related morality and cirrhosis recompensation. Its high sensitivity and NPV make it a valuable tool for risk stratification and patient management. [ABSTRACT FROM AUTHOR] |