Section of Gastroenterology, Department of Medicine, Boston University School of Medicine, Boston, MA, USA.
Framingham Heart Study, Framingham, MA, USA.
Liver Int. 2018 Aug;38(8):1495-1503. doi: 10.1111/liv.13709. Epub 2018 Mar 12.
The factors associated with incident hepatic steatosis are not definitively known. We sought to determine factors associated with incident hepatic steatosis, as measured on computed tomography, in the community.
We studied Framingham Heart Study participants without heavy alcohol use or baseline hepatic steatosis who underwent computed tomography scans between 2002-2005 (baseline) and 2008-2011 (follow-up). We performed a stepwise logistic regression procedure to determine the predictors associated with incident hepatic steatosis.
We included 685 participants (mean age: 45.0 ± 6.2 years, 46.8% women). The incidence of hepatic steatosis in our sample was 17.1% over a mean 6.3 years of follow-up. Participants who developed hepatic steatosis had more adverse cardiometabolic profiles at baseline compared to those free of hepatic steatosis at follow-up. Multivariable stepwise regression analysis showed that a simple clinical model including age, sex, body mass index, alcohol consumption and triglycerides was predictive of incident hepatic steatosis (C statistic = 0.791, 95% CI: 0.748-0.834). A complex clinical model, which included visceral adipose tissue volume and liver phantom ratio added to the simple clinical model, and had improved discrimination for predicting incident hepatic steatosis (C statistic = 0.826, 95% CI: 0.786-0.866, P < .0001).
The combination of demographic, clinical and imaging characteristics at baseline was predictive of incident hepatic steatosis. The use of our predictive model may help identify those at increased risk for developing hepatic steatosis who may benefit from risk factor modification although further investigation is warranted.
与肝脂肪变性事件相关的因素尚不完全清楚。我们旨在确定社区人群中,与 CT 测量的肝脂肪变性事件相关的因素。
我们研究了Framingham 心脏研究参与者,他们没有大量饮酒或基线肝脂肪变性,并且在 2002-2005 年(基线)和 2008-2011 年(随访)期间接受了 CT 扫描。我们进行了逐步逻辑回归程序,以确定与肝脂肪变性事件相关的预测因素。
我们纳入了 685 名参与者(平均年龄:45.0±6.2 岁,46.8%为女性)。在平均 6.3 年的随访中,我们样本中肝脂肪变性的发生率为 17.1%。与随访时无肝脂肪变性的参与者相比,发生肝脂肪变性的参与者在基线时具有更不利的心脏代谢特征。多变量逐步回归分析显示,包括年龄、性别、体重指数、饮酒和甘油三酯在内的简单临床模型可预测肝脂肪变性事件(C 统计量=0.791,95%CI:0.748-0.834)。一个复杂的临床模型,包括内脏脂肪组织体积和肝脏模拟比,添加到简单的临床模型中,提高了预测肝脂肪变性事件的区分度(C 统计量=0.826,95%CI:0.786-0.866,P<0.0001)。
基线时的人口统计学、临床和影像学特征的组合可预测肝脂肪变性事件。尽管需要进一步研究,但使用我们的预测模型可能有助于识别那些发生肝脂肪变性风险增加的患者,他们可能受益于危险因素的改变。