医学
内科学
减肥
血脂异常
置信区间
体质指数
优势比
2型糖尿病
脂肪肝
糖尿病
胃肠病学
肥胖
疾病
内分泌学
作者
Nicola Pugliese,Ivan Arcari,Federica Cerini,Rosa Lombardi,Federica Turati,Grazia Pennisi,Matteo Soleri,Simone Rocchetto,Diletta De Deo,Michele Sagasta,Chiara Masetti,Anna Ludovica Fracanzani,Salvatore Petta,Carlo La Vecchia,Mauro Viganò,Alessio Aghemo
摘要
ABSTRACT Background and Aims Weight loss is an effective therapeutic strategy for patients with metabolic dysfunction‐associated steatotic liver disease (MASLD). This study aimed to identify factors that predict relevant weight loss, defined as at least 7% of initial body weight, in MASLD outpatients. Method We retrospectively included all MASLD patients referred to four Italian tertiary centers between January 2019 and December 2021. Patients received lifestyle modification advice according to current guidelines, with reassessment of anthropometric measures after 18–24 months. Results A total of 897 patients were included. The majority were male (57%) with a mean age of 61.6 ± 13.3 years and a mean baseline body mass index (BMI) of 30.3 ± 4.5 kg/m 2 . Comorbidities included type 2 diabetes (T2D; 36%), arterial hypertension (54.7%) and dyslipidemia (55.2%). Over a median observation period of 21 months, 164 (18.3%) patients achieved relevant weight loss. Multiple adjusted regression analysis identified baseline BMI between 30 and 34.9 kg/m 2 (odds ratio, OR = 1.95, 95% confidence interval, CI: 1.30–2.95) or ≥ 35 kg/m 2 (OR = 2.08, 95% CI: 1.21–3.57), use of GLP‐1 agonists for T2D (OR 1.85, 95% CI: 1.19–3.80), bilirubin levels ≥ 1.2 mg/dL (OR 2.12, 95% CI: 1.29–3.51) nutritionist support (OR 2.04, 95% CI: 1.12–3.71) and liver stiffness measurement (LSM) ≥ 10 kPa (OR 1.70, 95% CI: 1.07–2.70) as independent predictors of relevant weight loss. Conclusions Baseline BMI ≥ 30 kg/m 2 , use of GLP‐1 agonists, elevated bilirubin levels, support from a nutritionist and LSM ≥ 10 kPa are significant predictors of relevant weight loss in MASLD patients. These findings underscore the importance of personalized interventions in MASLD management.
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