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A Nomogram for Predicting Non-Alcoholic Fatty Liver Disease in Obese Children

PURPOSE: Non-alcoholic fatty liver disease (NAFLD) ranges in severity from simple steatosis to steatohepatitis. Early detection of NAFLD is important for preventing the disease from progressing to become an irreversible end-stage liver disease. We developed a nomogram that allows for non-invasive sc...

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Autores principales: Kim, Ahlee, Yang, Hye Ran, Cho, Jin Min, Chang, Ju Young, Moon, Jin Soo, Ko, Jae Sung
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Korean Society of Pediatric Gastroenterology, Hepatology and Nutrition 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7231740/
https://www.ncbi.nlm.nih.gov/pubmed/32483549
http://dx.doi.org/10.5223/pghn.2020.23.3.276
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author Kim, Ahlee
Yang, Hye Ran
Cho, Jin Min
Chang, Ju Young
Moon, Jin Soo
Ko, Jae Sung
author_facet Kim, Ahlee
Yang, Hye Ran
Cho, Jin Min
Chang, Ju Young
Moon, Jin Soo
Ko, Jae Sung
author_sort Kim, Ahlee
collection PubMed
description PURPOSE: Non-alcoholic fatty liver disease (NAFLD) ranges in severity from simple steatosis to steatohepatitis. Early detection of NAFLD is important for preventing the disease from progressing to become an irreversible end-stage liver disease. We developed a nomogram that allows for non-invasive screening for NAFLD in obese children. METHODS: Anthropometric and laboratory data of 180 patients from our pediatric obesity clinic were collected. Diagnoses of NAFLD were based on abdominal ultrasonographic findings. The nomogram was constructed using predictors from a multivariate analysis of NAFLD risk factors. RESULTS: The subjects were divided into non-NAFLD (n=67) and NAFLD groups (n=113). Factors, including sex, body mass index, abdominal circumference, blood pressure, insulin resistance, and levels of aspartate aminotransferase, alanine aminotransferase (ALT), γ-glutamyl transpeptidase (γGT), uric acid, triglycerides, and insulin, were significantly different between the two groups (all p<0.05) as determined using homeostatis model assessment of insulin resistance (HOMA-IR). In our multivariate logistic regression analysis, elevated serum ALT, γGT, and triglyceride levels were significantly related to NAFLD development. The nomogram was established using γGT, uric acid, triglycerides, HOMA-IR, and ALT as predictors of NAFLD probability. CONCLUSION: The newly developed nomogram may help predict NAFLD risk in obese children. The nomogram may also allow for early NAFLD diagnosis without the need for invasive liver biopsy or expensive liver imaging, and may also allow clinicians to intervene early to prevent the progression of NAFLD to become a more advanced liver disease.
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spelling pubmed-72317402020-05-31 A Nomogram for Predicting Non-Alcoholic Fatty Liver Disease in Obese Children Kim, Ahlee Yang, Hye Ran Cho, Jin Min Chang, Ju Young Moon, Jin Soo Ko, Jae Sung Pediatr Gastroenterol Hepatol Nutr Original Article PURPOSE: Non-alcoholic fatty liver disease (NAFLD) ranges in severity from simple steatosis to steatohepatitis. Early detection of NAFLD is important for preventing the disease from progressing to become an irreversible end-stage liver disease. We developed a nomogram that allows for non-invasive screening for NAFLD in obese children. METHODS: Anthropometric and laboratory data of 180 patients from our pediatric obesity clinic were collected. Diagnoses of NAFLD were based on abdominal ultrasonographic findings. The nomogram was constructed using predictors from a multivariate analysis of NAFLD risk factors. RESULTS: The subjects were divided into non-NAFLD (n=67) and NAFLD groups (n=113). Factors, including sex, body mass index, abdominal circumference, blood pressure, insulin resistance, and levels of aspartate aminotransferase, alanine aminotransferase (ALT), γ-glutamyl transpeptidase (γGT), uric acid, triglycerides, and insulin, were significantly different between the two groups (all p<0.05) as determined using homeostatis model assessment of insulin resistance (HOMA-IR). In our multivariate logistic regression analysis, elevated serum ALT, γGT, and triglyceride levels were significantly related to NAFLD development. The nomogram was established using γGT, uric acid, triglycerides, HOMA-IR, and ALT as predictors of NAFLD probability. CONCLUSION: The newly developed nomogram may help predict NAFLD risk in obese children. The nomogram may also allow for early NAFLD diagnosis without the need for invasive liver biopsy or expensive liver imaging, and may also allow clinicians to intervene early to prevent the progression of NAFLD to become a more advanced liver disease. The Korean Society of Pediatric Gastroenterology, Hepatology and Nutrition 2020-05 2020-05-08 /pmc/articles/PMC7231740/ /pubmed/32483549 http://dx.doi.org/10.5223/pghn.2020.23.3.276 Text en Copyright © 2020 by The Korean Society of Pediatric Gastroenterology, Hepatology and Nutrition https://creativecommons.org/licenses/by-nc/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Kim, Ahlee
Yang, Hye Ran
Cho, Jin Min
Chang, Ju Young
Moon, Jin Soo
Ko, Jae Sung
A Nomogram for Predicting Non-Alcoholic Fatty Liver Disease in Obese Children
title A Nomogram for Predicting Non-Alcoholic Fatty Liver Disease in Obese Children
title_full A Nomogram for Predicting Non-Alcoholic Fatty Liver Disease in Obese Children
title_fullStr A Nomogram for Predicting Non-Alcoholic Fatty Liver Disease in Obese Children
title_full_unstemmed A Nomogram for Predicting Non-Alcoholic Fatty Liver Disease in Obese Children
title_short A Nomogram for Predicting Non-Alcoholic Fatty Liver Disease in Obese Children
title_sort nomogram for predicting non-alcoholic fatty liver disease in obese children
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7231740/
https://www.ncbi.nlm.nih.gov/pubmed/32483549
http://dx.doi.org/10.5223/pghn.2020.23.3.276
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