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Clinical and Biochemical Predictors of Nonalcoholic Fatty Liver Disease among Type 2 Diabetes Mellitus Patients at Primary Health Care Level in South Western Saudi Arabia

Objectives: To predict the role of different clinical and biochemical parameters in identifying nonalcoholic fatty liver disease (NAFLD) among patients with type 2 diabetes mellitus (T2DM) in Abha city, southwestern Saudi Arabia. Methods: A stratified random sample was selected. A detailed clinical...

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Autores principales: Al Humayed, Suliman M., Al Sabaani, Abdullah A., Mahfouz, Ahmed A., Awadalla, Nabil J., Musa, Mustafa Jafar, Patel, Ayyub
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7601804/
https://www.ncbi.nlm.nih.gov/pubmed/33053793
http://dx.doi.org/10.3390/diagnostics10100809
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author Al Humayed, Suliman M.
Al Sabaani, Abdullah A.
Mahfouz, Ahmed A.
Awadalla, Nabil J.
Musa, Mustafa Jafar
Patel, Ayyub
author_facet Al Humayed, Suliman M.
Al Sabaani, Abdullah A.
Mahfouz, Ahmed A.
Awadalla, Nabil J.
Musa, Mustafa Jafar
Patel, Ayyub
author_sort Al Humayed, Suliman M.
collection PubMed
description Objectives: To predict the role of different clinical and biochemical parameters in identifying nonalcoholic fatty liver disease (NAFLD) among patients with type 2 diabetes mellitus (T2DM) in Abha city, southwestern Saudi Arabia. Methods: A stratified random sample was selected. A detailed clinical and biochemical examinations were performed. Using portable abdominal ultrasound examination, NAFLD was identified. The study used receiver operating characteristic (ROC) analysis. Results: The study covered 237 T2DM patients. NAFLD was detected among 174 patients. Area under the curve (AUC) calculations showed that the ability of age, duration of DM in years, and body mass index to predict NAFLD was poor (AUC < 0.6). Similarly, biochemical factors like HbA1c%, AST, cholesterol, triglycerides, HDL, LDL, and VLDL were poor in discriminating between those with and without NAFLD among T2DM. On the other hand, the ability of ALT to predict NAFLD among T2DM was good (AUC = 0.701, 95% CI: 0.637–0.761). The analysis identified the optimal cutoff point of ALT to be ≤22.1 nmol/L. The corresponding sensitivity was 60.7% (95% CI: 53.0–68.0) and specificity was 62.5% (95% CI: 49.5–74.3). Conclusions: Early identification of NAFLD among T2DM is important. A threshold cutoff value of 22.1 nmol/L of ALT has been identified to predict NAFLD. They should be referred for ultrasound examination for NAFLD.
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spelling pubmed-76018042020-11-01 Clinical and Biochemical Predictors of Nonalcoholic Fatty Liver Disease among Type 2 Diabetes Mellitus Patients at Primary Health Care Level in South Western Saudi Arabia Al Humayed, Suliman M. Al Sabaani, Abdullah A. Mahfouz, Ahmed A. Awadalla, Nabil J. Musa, Mustafa Jafar Patel, Ayyub Diagnostics (Basel) Article Objectives: To predict the role of different clinical and biochemical parameters in identifying nonalcoholic fatty liver disease (NAFLD) among patients with type 2 diabetes mellitus (T2DM) in Abha city, southwestern Saudi Arabia. Methods: A stratified random sample was selected. A detailed clinical and biochemical examinations were performed. Using portable abdominal ultrasound examination, NAFLD was identified. The study used receiver operating characteristic (ROC) analysis. Results: The study covered 237 T2DM patients. NAFLD was detected among 174 patients. Area under the curve (AUC) calculations showed that the ability of age, duration of DM in years, and body mass index to predict NAFLD was poor (AUC < 0.6). Similarly, biochemical factors like HbA1c%, AST, cholesterol, triglycerides, HDL, LDL, and VLDL were poor in discriminating between those with and without NAFLD among T2DM. On the other hand, the ability of ALT to predict NAFLD among T2DM was good (AUC = 0.701, 95% CI: 0.637–0.761). The analysis identified the optimal cutoff point of ALT to be ≤22.1 nmol/L. The corresponding sensitivity was 60.7% (95% CI: 53.0–68.0) and specificity was 62.5% (95% CI: 49.5–74.3). Conclusions: Early identification of NAFLD among T2DM is important. A threshold cutoff value of 22.1 nmol/L of ALT has been identified to predict NAFLD. They should be referred for ultrasound examination for NAFLD. MDPI 2020-10-12 /pmc/articles/PMC7601804/ /pubmed/33053793 http://dx.doi.org/10.3390/diagnostics10100809 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Al Humayed, Suliman M.
Al Sabaani, Abdullah A.
Mahfouz, Ahmed A.
Awadalla, Nabil J.
Musa, Mustafa Jafar
Patel, Ayyub
Clinical and Biochemical Predictors of Nonalcoholic Fatty Liver Disease among Type 2 Diabetes Mellitus Patients at Primary Health Care Level in South Western Saudi Arabia
title Clinical and Biochemical Predictors of Nonalcoholic Fatty Liver Disease among Type 2 Diabetes Mellitus Patients at Primary Health Care Level in South Western Saudi Arabia
title_full Clinical and Biochemical Predictors of Nonalcoholic Fatty Liver Disease among Type 2 Diabetes Mellitus Patients at Primary Health Care Level in South Western Saudi Arabia
title_fullStr Clinical and Biochemical Predictors of Nonalcoholic Fatty Liver Disease among Type 2 Diabetes Mellitus Patients at Primary Health Care Level in South Western Saudi Arabia
title_full_unstemmed Clinical and Biochemical Predictors of Nonalcoholic Fatty Liver Disease among Type 2 Diabetes Mellitus Patients at Primary Health Care Level in South Western Saudi Arabia
title_short Clinical and Biochemical Predictors of Nonalcoholic Fatty Liver Disease among Type 2 Diabetes Mellitus Patients at Primary Health Care Level in South Western Saudi Arabia
title_sort clinical and biochemical predictors of nonalcoholic fatty liver disease among type 2 diabetes mellitus patients at primary health care level in south western saudi arabia
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7601804/
https://www.ncbi.nlm.nih.gov/pubmed/33053793
http://dx.doi.org/10.3390/diagnostics10100809
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