Singh Yuvaraj, Gogtay Maya, Gurung Susant, Trivedi Nitin, Abraham George M
Department of Medicine, Saint Vincent Hospital, Worcester, MA, USA.
J Community Hosp Intern Med Perspect. 2022 Jul 4;12(4):58-65. doi: 10.55729/2000-9666.1071. eCollection 2022.
This retrospective, cross-sectional study aimed to evaluate the predictive factors of moderate/severe hepatic steatosis diagnosed by vibration-controlled transient elastography (VCTE). It included 158 adult patients with suspected nonalcoholic fatty liver disease (NAFLD) evaluated by VCTE in an outpatient setting of a community-based teaching hospital. Patients with significant alcohol consumption, oral contraceptive use, hepatitis B disease, autoimmune hepatitis, and primary biliary cirrhosis were excluded. Steatosis was categorized as S0-S1 (mild) and S2-S3 (moderate/severe) based on the controlled attenuation parameter (CAP) score. Results demonstrated the mean values of BMI (p = 0.001), kiloPascals [kPa] (fibrosis) raw score (p = 0.009), obesity (p = 0.001), diabetes mellitus [DM] (p = 0.014), and comorbidities status [chronic hepatitis C(HCV), DM, obesity, HCV+DM] (p = 0.028) were significantly different between the two arms of the study . S0-S1 (mild) and S2-S3 (moderate/severe). A multinomial logistic regression analysis of the comorbidities associated with hepatic steatosis revealed a good level of prediction (R-0.584) for hepatic steatosis. Of all the variables analyzed, obesity was the most impactful vavriable. Furthermore, the -2 log-likelihood of the regressed model in patients with HCV and hepatic steatosis did not show a significant correlation when adjusted for obesity. Obesity had a significant independent association with steatosis (chi-square value = 52, df = 12). Interestingly, DM independently predicted a weak association with steatosis (chi-square value = 0.825, df = 3). In conclusion, our study demonstrates that hepatic steatosis is independently associated with metabolic parameters like obesity and DM. Management of these risk factors in patients with HCV may be vital to reducing the risk of steatosis and progression to fibrosis.
这项回顾性横断面研究旨在评估通过振动控制瞬时弹性成像（VCTE）诊断的中度/重度肝脂肪变性的预测因素。该研究纳入了158例在社区教学医院门诊接受VCTE评估的疑似非酒精性脂肪性肝病（NAFLD）的成年患者。排除有大量饮酒、使用口服避孕药、患有乙型肝炎、自身免疫性肝炎和原发性胆汁性肝硬化的患者。根据控制衰减参数（CAP）评分，将脂肪变性分为S0-S1（轻度）和S2-S3（中度/重度）。结果显示，研究的两组之间，体重指数（BMI）的平均值（p = 0.001）、千帕斯卡[kPa]（纤维化）原始评分（p = 0.009）、肥胖（p = 0.001）、糖尿病[DM]（p = 0.014）以及合并症状态[慢性丙型肝炎（HCV）、DM、肥胖、HCV+DM]（p = 0.028）存在显著差异。S0-S1（轻度）和S2-S3（中度/重度）。对与肝脂肪变性相关的合并症进行的多项逻辑回归分析显示，对肝脂肪变性有良好的预测水平（R = 0.584）。在所有分析的变量中，肥胖是影响最大的变量。此外，在对肥胖进行校正后，HCV和肝脂肪变性患者回归模型的-2对数似然值未显示出显著相关性。肥胖与脂肪变性有显著的独立关联（卡方值 = 52，自由度 = 12）。有趣的是，DM独立预测与脂肪变性有较弱的关联（卡方值 = 0.825，自由度 = 3）。总之，我们的研究表明，肝脂肪变性与肥胖和DM等代谢参数独立相关。对HCV患者管理这些风险因素对于降低脂肪变性风险和进展为纤维化可能至关重要。
