Prevalence and risk factor analysis for the nonalcoholic fatty liver disease in patients with type 2 diabetes mellitus.
Prevalence and risk factor analysis for the nonalcoholic fatty liver disease in patients with type 2 diabetes mellitus.
复制标题
2型糖尿病患者非酒精性脂肪肝患病率及危险因素分析。
DOI：
10.1097/md.0000000000024940
复制
发表时间：
2021-03-12
期刊：
影响因子：
1.6
通讯作者：
Huo X
中科院分区：
文献类型：
--
作者：
Zhou Q;Wang Y;Wang J;Liu Y;Qi D;Yao W;Jiang H;Li T;Huang K;Zhang W;Huo X
尽管非酒精性脂肪性肝病(NAFLD)与2型糖尿病(T2 DM)密切相关，但对T2 DM患者的NAFLD的诊断仍然是一个挑战。本研究旨在调查门诊2型糖尿病患者非酒精性脂肪肝的患病率及其危险因素。这是一项回顾性横断面研究，纳入2017年4月至2019年3月因血糖控制而入院的2405例T2 DM患者。采用严格的排除标准，筛选目标患者并将其分为两组：NAFLD患者组(研究组)和非NAFLD患者组(对照组)。随后，对两组间的34个因素进行比较。此外，对NAFLD的危险因素进行多因素Logistic回归分析。最后，通过受试者工作特征(ROC)曲线分析，评价单个生化指标以及组合预测指标(CPI)对NAFLD的诊断意义。在本研究中，T2 DM患者NAFLD的总患病率为58.67%。单因素分析发现17个因素与NAFLD相关，二元Logistic回归模型发现8个因素是NAFLD的显著预测因素。此外，CPI和C-肽对T2 DM患者的NAFLD具有较高的诊断价值。本研究为T2 DM患者NAFLD的危险因素分析提供了更为全面的依据。这些数据可用于NAFLD的及时诊断和有效治疗。
Although non-alcoholic fatty liver disease (NAFLD) is strongly associated with type 2 diabetes mellitus (T2DM), the diagnosis of NAFLD for T2DM patients remains a challenge. This study aimed to investigate the prevalence and risk factors for the NAFLD in T2DM outpatients. This is a retrospective, cross-sectional study that included 2405 T2DM patients treated and admitted for glucose control into the Endocrinology Department of our hospital from April 2017 to March 2019. Using strict exclusion criteria, the target patients were screened and divided into two groups: NAFLD patients (study group) and non-NAFLD patients (control group). Subsequently, 34 factors were compared between the two groups. Furthermore, multivariate analysis of the NAFLD risk factors was performed using logistic regression. Finally, the diagnostic significance of individual biochemical predictors, as well as the combined predictive indicator (CPI), for NAFLD was estimated using receiver operating characteristic (ROC) curve analysis. In this study, the overall prevalence of NAFLD in T2DM patients was 58.67%. Of the target patients, 17 factors were identified by univariate analysis to be associated with NAFLD, and 8 factors were found to be significant predictors for NAFLD using binary logistic regression modeling. Furthermore, the CPI and C-Peptide represent high diagnostic value for NAFLD in T2DM patients. This study provides a more comprehensive risk factor analysis for NAFLD in T2DM patients. These data can be used to provide timely diagnosis and effective management of NAFLD.