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| Prediction of non-alcoholic fatty liver in patients with type 2 diabetes mellitus |
| ZHENG Shuaiyin1,2, LI Lidan3, CHEN Peidi1, Xieerwaniguli·Abulimiti4, LI Di5,6,7
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1. School of Public Health, Xinjiang Second Medical College, Karamay, Xinjiang 834000, China;
2. Academic Affairs Office of Xinjiang Second Medical College, Karamay, Xinjiang 834000, China;
3. Xinjiang Second Medical University, Karamay, Xinjiang 834000, China;
4. Kashgar University School of Medicine, Kashgar, Xinjiang 844000, China;
5. Karamay Hospital of People′s Hospital of Xinjiang Uygur Autonomous Region, Karamay, Xinjiang 834000, China;
6. Xinjiang Digestive System Tumor Precision Medical Clinical Medical Research Center, Karamay, Xinjiang 834000, China;
7. Xinjiang Key Laboratory of Clinical Genetic Testing and Biomedical Information, Karamay, Xinjiang 834000, China |
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Abstract Objective To construct a prediction model of non-alcoholic fatty liver disease (NAFLD) in middle-aged and elderly patients with type 2 diabetes mellitus (T2DM), so as to provide basis for early screening and prevention of T2DM complicated with NAFLD. Methods Patients aged 45 years and above and diagnosed with T2DM in Karamay Hospital of People's Hospital of Xinjiang Uygur Autonomous Region in 2021 were collected as the study subjects. The data of general demographic characteristics and biochemical test results were collected. The patients were randomly divided into training group (n=3 241) and validation group (n=1 389) according to the ratio of 7∶3. LASSO regression and multivariable logistic regression model were used to select predictive factors. The nomograph model for prediction of NAFLD risk in T2DM patients was established. The predictive value of the model was evaluated using the receiver operating characteristic (ROC), adjusted curve and decision clinical analysis. Results Totally 4 630 T2DM cases were included, including 1 279 cases (27.62%) complicated with NAFLD. LASSO regression and multivariable logistic regression analysis identified gender, age, diastolic blood pressure, body mass index, alanine transaminase, triglycerides, low density lipoprotein cholesterol and platelet count as risk prediction factors for NAFLD in T2DM patients. The area under the ROC curve was 0.823 (95%CI: 0.814-0.832) for the training group and 0.809 (95%CI: 0.799-0.818) for the validation group, and Hosmer-Lemeshow test showed a good fitting effect (P>0.05). Decision curve analysis showed higher net clinical benefit of using the predictive model to predict NAFLD risk when the risk threshold probability was 0.27 to 0.85. Conclusion The nomogram model established has a good predictive value for the risk of NAFLD in T2DM patients aged 45 years and above.
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Received: 03 June 2024
Revised: 26 August 2024
Published: 18 September 2024
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[1] 唐英琪,李英,田坚.2型糖尿病患者合并非酒精性脂肪性肝病的影响因素分析[J].预防医学,2021,33(3):292-294,298.
[2] CHEN K,SNG W K,QUAH J H,et al.Clinical spectrum of non-alcoholic fatty liver disease in patients with diabetes mellitus[J/OL].PLoS One,2020,15(8)[2024-08-26].https://doi.org/10.1371/journal.pone.0236977.
[3] EN LI CHO E,ANG C Z,QUEK J,et al.Global prevalence of non-alcoholic fatty liver disease in type 2 diabetes mellitus:an updated systematic review and meta-analysis[J].Gut,2023,72(11):2138-2148.
[4] TAKYAR V,ETZION O,HELLER T,et al.Complications of percutaneous liver biopsy with Klatskin needles:a 36-year single-centre experience[J].Aliment Pharmacol Ther,2017,45(5):744-753.
[5] 周瑞芬,杜秋菊,姚国萍,等.杭州市45~69岁人群非酒精性脂肪性肝病与2型糖尿病相关性研究[J].预防医学,2020,32(8):809-812.
[6] 中华医学会糖尿病学分会.中国2型糖尿病防治指南(2017年版)[J].中国实用内科杂志,2018,38(4):292-344.
[7] 中华医学会肝病学分会脂肪肝和酒精性肝病学组,中国医师协会脂肪性肝病专家委员会.非酒精性脂肪性肝病防治指南(2018年更新版)[J].临床肝胆病杂志,2018,34(5):947-957.
[8] 陈芳,刘岚.上海某社区老年人肝胆超声体检结果分析[J].上海医药,2021,42(16):45-47.
[9] ROBEVA R,MLADENOVIĆ D,VESKOVIĆ M,et al.The interplay between metabolic dysregulations and non-alcoholic fatty liver disease in women after menopause[J].Maturitas,2021,151:22-30.
[10] MA J,HWANG S J,PEDLEY A,et al.Bi-directional analysis between fatty liver and cardiovascular disease risk factors[J].J Hepatol,2017,66(2):390-397.
[11] POLYZOS S A,KOUNTOURAS J,MANTZOROS C S.Obesity and nonalcoholic fatty liver disease:from pathophysiology to therapeutics[J].Metabolism,2019,92:82-97.
[12] ANGELICO F,BARATTA F,PASTORI D,et al.Statins and non-alcoholic fatty liver disease[J].Liver Int,2019,39(9):1787-1795.
[13] MARTIN A,LANG S,GOESER T,et al.Management of dyslipidemia in patients with non-alcoholic fatty liver disease[J].Curr Atheroscler Rep,2022,24(7):533-546.
[14] SUN D Q,WU S J,LIU W Y,et al.Association of low-density lipoprotein cholesterol within the normal range and NAFLD in the non-obese Chinese population:a cross-sectional and longitudinal study[J/OL].BMJ Open,2016,6(12)[2024-08-26].https://doi.org/10.1136/bmjopen-2016-013781.
[15] GIANNOPOULOS C K,TZIMA I G,TENTOLOURIS N K,et al.Common pathogenetic pathways of non-alcoholic fatty liver disease and type 2 diabetes mellitus[J/OL].Curr Diabetes Rev,2023,19(9)[2024-08-26].https://doi.org/10.2174/1573399819666230216112032.
[16] KORPIMÄKI S,ROVIO S P,JUONALA M,et al.Nonalcoholic fatty liver disease incidence and remission and their predictors during 7 years of follow-up among finns[J/OL].J Clin Endocrinol Metab,2023,109(1)[2024-08-26].https://doi.org/10.1210/clinem/dgad418.
[17] CHAO Y L,WU P Y,HUANG J C,et al.Hepatic steatosis is associated with high white blood cell and platelet counts[J].Biomedicines,2022,10(4):892-904.
[18] 张沥今,魏夏琰,陆嘉琦,等.Lasso回归:从解释到预测[J].心理科学进展,2020,28(10):1777-1788.
[19] 李永生,张学良,李丞,等. 2型糖尿病周围神经病变风险的列线图预测模型研究[J].中国全科医学,2022,25(6):675-681.
[20] 周梓萌,洪忻.心血管病高危人群预测模型研究[J].预防医学,2024,36(3):211-214,218. |
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