Predicting hepatic steatosis in a racially and ethnically diverse cohort of adolescent girls.
Predicting hepatic steatosis in a racially and ethnically diverse cohort of adolescent girls.
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预测不同种族和民族的青春期女孩的肝脂肪变性。
DOI：
10.1016/j.jpeds.2014.04.019
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发表时间：
2014
期刊：
影响因子：
--
通讯作者：
Allen,DavidB
中科院分区：
文献类型：
--
作者：
Rehm,JenniferL;Connor,EllenL;Wolfgram,PeterM;Eickhoff,JensC;Reeder,ScottB;Allen,DavidB
目的建立一个风险评估模型，用于早期发现肝脂肪变性使用常见的人体测量和代谢markers.Study designThis是一个横断面研究的134名青少年和年轻的成年女性，年龄11-22岁（平均13.3 ± 2岁），从中学和诊所在麦迪逊，威斯康星州。种族分布为27%西班牙裔和73%非西班牙裔;种族分布为64%高加索人、31%非洲裔美国人和5%亚洲人。评估空腹血糖、空腹胰岛素、丙氨酸氨基转移酶（ALT）、体重指数（BMI）、腰围（WC）和其他代谢标志物。使用磁共振成像质子密度脂肪分数（MR-PDFF）定量肝脏脂肪。肝脂肪变性定义为MR-PDFF > 5.5%。在风险评估模型中，结果指标为BMI、WC、ALT、空腹胰岛素和种族作为肝脂肪变性预测因子的敏感性、特异性和阳性预测值（PPV）。分类和回归树方法被用来构建一个决策树预测肝脂肪变性。ResultsMR-PDFF显示在16%的受试者（27%超重，3%非超重）肝脂肪变性。西班牙裔种族对肝脂肪变性的OR为4.26（95% CI，1.65-11.04;P= .003）。BMI和ALT不能独立预测肝脂肪变性。BMI >85%联合ALT >65 U/L的敏感性为9%，特异性为100%，PPV为100%。将ALT值降低至24 U/L，敏感性增加至68%，但PPV降低至47%。结合空腹胰岛素、总胆固醇、WC和种族的风险评估模型将敏感性提高至64%，特异性提高至99%，PPV提高至93%.Conclusion风险评估模型可提高识别肝脂肪变性风险的特异性、敏感性和PPV，并指导有效使用活检或影像学进行早期发现和干预。
ObjectiveTo develop a risk assessment model for early detection of hepatic steatosis using common anthropometric and metabolic markers.Study designThis was a cross-sectional study of 134 adolescent and young adult females, age 11-22 years (mean 13.3 ± 2 years) from a middle school and clinics in Madison, Wisconsin. The ethnic distribution was 27% Hispanic and 73% non-Hispanic; the racial distribution was 64% Caucasian, 31% African-American, and 5% Asian, Fasting glucose, fasting insulin, alanine aminotransferase (ALT), body mass index (BMI), waist circumference (WC), and other metabolic markers were assessed. Hepatic fat was quantified using magnetic resonance imaging proton density fat fraction (MR-PDFF). Hepatic steatosis was defined as MR-PDFF >5.5%. Outcome measures were sensitivity, specificity, and positive predictive value (PPV) of BMI, WC, ALT, fasting insulin, and ethnicity as predictors of hepatic steatosis, individually and combined, in a risk assessment model. Classification and regression tree methodology was used to construct a decision tree for predicting hepatic steatosis.ResultsMR-PDFF revealed hepatic steatosis in 16% of subjects (27% overweight, 3% nonoverweight). Hispanic ethnicity conferred an OR of 4.26 (95% CI, 1.65-11.04;P= .003) for hepatic steatosis. BMI and ALT did not independently predict hepatic steatosis. A BMI >85% combined with ALT >65 U/L had 9% sensitivity, 100% specificity, and 100% PPV. Lowering the ALT value to 24 U/L increased the sensitivity to 68%, but reduced the PPV to 47%. A risk assessment model incorporating fasting insulin, total cholesterol, WC, and ethnicity increased sensitivity to 64%, specificity to 99% and PPV to 93%.ConclusionA risk assessment model can increase specificity, sensitivity, and PPV for identifying the risk of hepatic steatosis and guide the efficient use of biopsy or imaging for early detection and intervention.
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影响因子：
5.8
作者：
Denzer, Christian;Thiere, Dorothee;Wabitsch, Martin
通讯作者：
Wabitsch, Martin
影响因子：
3.1
作者：
Ko, Jae Sung;Yoon, Jung Min;Seo, Jeong Kee
通讯作者：
Seo, Jeong Kee
DOI：
10.1152/ajpendo.00064.2004
发表时间：
2005-02-01
影响因子：
5.1
作者：
Szczepaniak, LS;Nurenberg, P;Dobbins, RL
通讯作者：
Dobbins, RL
DOI：
10.1210/jc.2007-2458
发表时间：
2008-12
期刊：
The Journal of clinical endocrinology and metabolism
影响因子：
--
作者：
August GP;Caprio S;Fennoy I;Freemark M;Kaufman FR;Lustig RH;Silverstein JH;Speiser PW;Styne DM;Montori VM;Endocrine Society
通讯作者：
Endocrine Society
影响因子：
5.1
作者：
Fernández, JR;Redden, DT;Allison, DB
通讯作者：
Allison, DB