Prediction of Liver Steatosis Applying a New Score in Subjects from the Brazilian Longitudinal Study of Adult Health

被引:6
作者
Perazzo, Hugo [1 ]
Bensenor, Isabela [5 ]
Mill, Jose Geraldo [6 ]
Pacheco, Antonio G. [2 ]
Mendes da Fonseca, Maria de Jesus [3 ]
Griep, Rosane Haerter [4 ]
Lotufo, Paulo [5 ]
Chor, Dora [3 ]
机构
[1] Oswaldo Cruz Fdn FIOCRUZ, Evandro Chagas Natl Inst Infect Dis INI, Lab Clin Res STD AIDS, Rio De Janeiro, Brazil
[2] Oswaldo Cruz Fdn FIOCRUZ, Sci Comp Program PROCC, Rio De Janeiro, Brazil
[3] Oswaldo Cruz Fdn FIOCRUZ, Natl Sch Publ Hlth, R Leopoldo Bulhoes 1480, BR-21041210 Rio De Janeiro, RJ, Brazil
[4] Oswaldo Cruz Fdn FIOCRUZ, Inst Oswaldo Cruz, Lab Hlth & Environm Educ, Rio De Janeiro, Brazil
[5] Univ Sao Paulo, Ctr Clin & Epidemiol Res, Sao Paulo, SP, Brazil
[6] Univ Fed Espirito Santo, Dept Physiol Sci, Vitoria, ES, Brazil
关键词
liver steatosis; predictive model; noninvasive methods; fatty liver; NONALCOHOLIC FATTY LIVER; HOMEOSTASIS MODEL ASSESSMENT; INSULIN-RESISTANCE; DIAGNOSTIC-ACCURACY; RISK-FACTORS; MASS INDEX; DISEASE; EPIDEMIOLOGY; ASSOCIATION; BIOMARKERS;
D O I
10.1097/MCG.0000000000001007
中图分类号
R57 [消化系及腹部疾病];
学科分类号
摘要
Goals:To develop a noninvasive algorithm for diagnosis of liver steatosis and to compare its diagnostic value with available predictive models.Background:Liver steatosis represents the most frequent liver disease worldwide.Study:This cross-sectional study analyzed data from the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil). Patients were randomly divided into training (n=6571) and validation (n=3286) cohort. Abdominal ultrasound (US), used to grade steatosis, and overnight fasting blood tests were performed at the same day. Fatty Liver Index (FLI), Hepatic Steatosis Index, and Nonalcoholic Fatty Liver Disease-Liver Fat Score were calculated. A backward stepwise multivariate logistic regression analysis was used to develop the new predictive model, Steato-ELSA.Results:In total, 9857 subjects [58% female, age=51 (interquartile range, 45 to 58) years, body mass index=26.4 (23.9 to 29.6) Kg/m(2)] were included. Body mass index, waist circumference, homeostasis model of assessment of insulin resistance, transaminases, and triglycerides were independently associated with steatosis in the multivariate model (Hosmer-Lemeshow P=0.279). In the validation cohort, the area under the receiver-operator characteristics (95% confidence interval) for prediction of mild and moderate steatosis were: (i) 0.768 (0.751-0.784) and 0.829 (0.810-0.848) for Steato-ELSA; (ii) 0.762 (0.745-0.779) and 0.819 (0.799-0.838) for Fatty Liver Index; (iii) 0.743 (0.727-0.761) and 0.800 (0.779-0.822) for Hepatic Steatosis Index; and (iv) 0.719 (0.701-0.737) and 0.769 (0.747-0.791) for Nonalcoholic Fatty Liver Disease-Liver Fat Score. Steato-ELSA performed significantly better than other models and yielded sensitivity (Se)/specificity (Sp) (95% confidence interval): (i) for mild steatosis (score >= 0.386): Se=65.6% (63.0-68.3) and Sp=73.7% (71.8-75.6); (ii) for moderate steatosis (score >= 0.403): Se=83.5% (80.0-86.9) and Sp=68.7% (67.0-70.4).Conclusions:Steato-ELSA is an accurate and inexpensive tool that uses simple parameters to identify individuals at high risk of liver steatosis.
引用
收藏
页码:E1 / E10
页数:10
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