• Heidi S Ahmed, Natalie Pedersen, Manju Bengaluru Jayanna, Patrick Ten Eyck, Antonio Sanchez, and Arvind R Murali.
• Department of Internal Medicine, University of Iowa Hospitals and Clinics, Iowa City, IA, USA. heidi.s.ahmed@gmail.com.
• J Gen Intern Med. 2020 May 1; 35 (5): 1523-1529.

BackgroundNon-alcoholic fatty liver disease (NAFLD) is one of the most common causes of cirrhosis in the USA.ObjectivesWe aimed to determine the time to develop hepatic events in patients with NAFLD and develop a simple model to identify patients at risk for hepatic decompensation.DesignRetrospective cohort study.PatientsSeven hundred patients with NAFLD met inclusion criteria for the study. Patients were divided into model construction (n = 450) and validation (n = 250) cohorts.Main MeasuresDemographic, clinical, and laboratory variables were gathered at the time of diagnosis of NAFLD. Kaplan-Meier analysis determined the time to development of hepatic events from initial diagnosis. A time-to-event prediction model was established in the model construction cohort using the multivariate Cox proportional hazards model and was then internally validated.Key ResultsForty-nine (7%) patients developed hepatic events at a mean duration of 6.2 ± 4.2 years from initial diagnosis. Kaplan-Meier probability of developing a hepatic event at 5-, 10-, and 12-year intervals was 4.8%, 10.6%, and 11.3%, respectively. Age, presence of diabetes, and platelet count were identified as significant variables to predict hepatic events. NAFLD decompensation risk score was developed as "age × 0.06335 + presence of diabetes (yes = 1, no = 0) × 0.92221 - platelet count × 0.01522" to predict the probability of hepatic decompensation. Risk score model had an area under the curve of 0.89 (95% CI = 0.92, 0.86) and it performed well in both the validation (0.91, 0.87-0.94) and the overall cohort (0.89, 0.87-0.91).ConclusionsA significant proportion of patients with NAFLD developed hepatic decompensation. We have provided a simple, objective model to help identify "at-risk" patients.

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