Predicting incident fatty liver using simple cardio-metabolic risk factors at baseline

Ki-Chul Sung*, Bum-Soo Kim, Yong-Kyun Cho, Dong-il Park, Sookyoung Woo, Seonwoo Kim, Sarah H. Wild, Christopher D. Byrne

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Background: Non alcoholic fatty liver disease (NAFLD) is associated with increased risk of type 2 diabetes and chronic liver disease but identifying patients who have NAFLD without resorting to expensive imaging tests is challenging. In order to help identify people for imaging investigation of the liver who are at high risk of NAFLD, our aim was to: a) identify easily measured risk factors at baseline that were independently associated with incident fatty liver at follow up, and then b) to test the diagnostic performance of thresholds of these factors at baseline, to predict or to exclude incident fatty liver at follow up.

Methods: 2589 people with absence of fatty liver on ultrasound examination at baseline were re-examined after a mean of 4.4 years in a Korean occupational cohort study. Multi-variable logistic regression analyses were used to identify baseline factors that were independently associated with incident fatty liver at follow up. The diagnostic performance of thresholds of these baseline factors to identify people with incident fatty liver at follow-up was assessed using receiver operating characteristic (ROC) curves.

Results: 430 incident cases of fatty liver were identified. Several factors were independently associated with incident fatty liver: increased triglyceride (per mmol/l increase) OR 1.378 [95% CIs 1.179, 1.611], p <0.0001; glucose (per mmol/l increase) OR 1.215 [95% CIs 1.042, 1.416], p = 0.013; waist (per cm increase) OR 1.078 [95% CIs 1.057, 1.099], p <0.001; ALT (per IU/L increase) OR 1.009 [95% CIs 1.002, 1.017], p = 0.016; and platelets (per 1x10(9)/L increase) OR 1.004 [1.001, 1.006], p = 0.001; were each independently associated with incident fatty liver. Binary thresholds of the five factors were applied and the area under the ROC curve for incident fatty liver was 0.75 (95% CI 0.72-0.78) for the combination of all five factors above these thresholds.

Conclusion: Simple risk factors that overlap considerably with risk factors for type 2 diabetes allow identification of people at high risk of incident fatty liver at who use of hepatic imaging could be targeted.

Original languageEnglish
Article numberARTN 84
Number of pages9
JournalBMC gastroenterology
Volume12
DOIs
Publication statusPublished - 6 Jul 2012

Keywords

  • HEPATIC STEATOSIS
  • Etiology
  • SPECTROSCOPY
  • ATHEROSCLEROSIS
  • INSULIN-RESISTANCE
  • PLATELETS
  • NONALCOHOLIC STEATOHEPATITIS
  • Risk prediction
  • INFLAMMATION
  • Metabolic syndrome
  • Fatty liver
  • DIAGNOSIS
  • DISEASE
  • POPULATION
  • Non alcoholic fatty liver disease

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