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

<p>Abstract</p> <p>Background</p> <p>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...

Full description

Bibliographic Details
Main Authors: Sung Ki-Chul, Kim Bum-Soo, Cho Yong-Kyun, Park Dong-il, Woo Sookyoung, Kim Seonwoo, Wild Sarah H, Byrne Christopher D
Format: Article
Language:English
Published: BMC 2012-07-01
Series:BMC Gastroenterology
Subjects:
Online Access:http://www.biomedcentral.com/1471-230X/12/84
id doaj-1ce369b2404a44fa8d9fba9aaff45002
record_format Article
spelling doaj-1ce369b2404a44fa8d9fba9aaff450022020-11-25T03:29:32ZengBMCBMC Gastroenterology1471-230X2012-07-011218410.1186/1471-230X-12-84Predicting incident fatty liver using simple cardio-metabolic risk factors at baselineSung Ki-ChulKim Bum-SooCho Yong-KyunPark Dong-ilWoo SookyoungKim SeonwooWild Sarah HByrne Christopher D<p>Abstract</p> <p>Background</p> <p>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.</p> <p>Methods</p> <p>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.</p> <p>Results</p> <p>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<sup>9</sup>/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.</p> <p>Conclusion</p> <p>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.</p> http://www.biomedcentral.com/1471-230X/12/84Non alcoholic fatty liver diseaseFatty liverEtiologyRisk predictionMetabolic syndrome
collection DOAJ
language English
format Article
sources DOAJ
author Sung Ki-Chul
Kim Bum-Soo
Cho Yong-Kyun
Park Dong-il
Woo Sookyoung
Kim Seonwoo
Wild Sarah H
Byrne Christopher D
spellingShingle Sung Ki-Chul
Kim Bum-Soo
Cho Yong-Kyun
Park Dong-il
Woo Sookyoung
Kim Seonwoo
Wild Sarah H
Byrne Christopher D
Predicting incident fatty liver using simple cardio-metabolic risk factors at baseline
BMC Gastroenterology
Non alcoholic fatty liver disease
Fatty liver
Etiology
Risk prediction
Metabolic syndrome
author_facet Sung Ki-Chul
Kim Bum-Soo
Cho Yong-Kyun
Park Dong-il
Woo Sookyoung
Kim Seonwoo
Wild Sarah H
Byrne Christopher D
author_sort Sung Ki-Chul
title Predicting incident fatty liver using simple cardio-metabolic risk factors at baseline
title_short Predicting incident fatty liver using simple cardio-metabolic risk factors at baseline
title_full Predicting incident fatty liver using simple cardio-metabolic risk factors at baseline
title_fullStr Predicting incident fatty liver using simple cardio-metabolic risk factors at baseline
title_full_unstemmed Predicting incident fatty liver using simple cardio-metabolic risk factors at baseline
title_sort predicting incident fatty liver using simple cardio-metabolic risk factors at baseline
publisher BMC
series BMC Gastroenterology
issn 1471-230X
publishDate 2012-07-01
description <p>Abstract</p> <p>Background</p> <p>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.</p> <p>Methods</p> <p>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.</p> <p>Results</p> <p>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<sup>9</sup>/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.</p> <p>Conclusion</p> <p>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.</p>
topic Non alcoholic fatty liver disease
Fatty liver
Etiology
Risk prediction
Metabolic syndrome
url http://www.biomedcentral.com/1471-230X/12/84
work_keys_str_mv AT sungkichul predictingincidentfattyliverusingsimplecardiometabolicriskfactorsatbaseline
AT kimbumsoo predictingincidentfattyliverusingsimplecardiometabolicriskfactorsatbaseline
AT choyongkyun predictingincidentfattyliverusingsimplecardiometabolicriskfactorsatbaseline
AT parkdongil predictingincidentfattyliverusingsimplecardiometabolicriskfactorsatbaseline
AT woosookyoung predictingincidentfattyliverusingsimplecardiometabolicriskfactorsatbaseline
AT kimseonwoo predictingincidentfattyliverusingsimplecardiometabolicriskfactorsatbaseline
AT wildsarahh predictingincidentfattyliverusingsimplecardiometabolicriskfactorsatbaseline
AT byrnechristopherd predictingincidentfattyliverusingsimplecardiometabolicriskfactorsatbaseline
_version_ 1724578642531450880