Jiang Deyue, Wang Shengjie, Xiao Yan, Zhi Peng, Zheng Erhan, Lyu Zhaohui, Guo Qinghua
Graduate School of The PLA General Hospital, No.28 Fuxing Road, Haidian District, Beijing, 100853, China.
Department of Endocrinology, Chinese PLA General Hospital, No.28 Fuxing Road, Haidian District, Beijing, 100853, China.
Sci Rep. 2025 Mar 5;15(1):7740. doi: 10.1038/s41598-025-91461-7.
Pituitary stalk interruption syndrome (PSIS) is an infrequently occurring congenital condition, and there exists a dearth of systematic investigative work focusing on the clinical features and long-term outcomes in adult patients. Individuals who have reached adulthood with PSIS are at an increased risk of developing metabolic disorders, including metabolic syndrome (MS) and non-alcoholic fatty liver disease (NAFLD) or metabolic dysfunction associated fatty liver disease (MAFLD), which are also one of the main factors for the poor prognosis of these patients. An analysis was conducted on the clinical data of adult PSIS patients who visited the endocrinology department of the First Medical Center of the People's Liberation Army General Hospital from January 2005 to August 2023. Patients were grouped based on their MAFLD and MS status, and the differences in clinical characteristics and risk factors between the groups were analyzed. Machine learning models were used to construct a prediction model for the occurrence of MAFLD in adult PSIS patients and to analyze high-risk predictors. Out of 136 PSIS adult patients, 93.3% were male. The prevalence of MAFLD was 55.5%, and MS was 22.3%. Patients with a history of growth hormone (GH) treatment were less likely to develop MAFLD (P = 0.032). MAFLD patients exhibited higher rates of hypertension, hyperuricemia, obesity, MS, and dyslipidemia. Multiple risk factors may contribute to MS, while no significant link was found between MS and hormone replacement. However, GH non-treatment may serve as the notable predictor of MAFLD in PSIS patients revealed by the Ridge regression model of machine learning model with the highest predictive performance of a mean area under the curve (AUC) of 0.82. The prevalence of MS and MAFLD is high among adult patients with PSIS. Multiple risk factors may contribute to these two diseases, and after constructing a predictive model, we found that MAFLD may be closely linked to the previous lack of GH treatment.
垂体柄阻断综合征（PSIS）是一种罕见的先天性疾病，目前针对成年患者临床特征和长期预后的系统性研究工作较少。成年后患有PSIS的个体发生代谢紊乱的风险增加，包括代谢综合征（MS）和非酒精性脂肪性肝病（NAFLD）或代谢功能障碍相关脂肪性肝病（MAFLD），这些也是这些患者预后不良的主要因素之一。对2005年1月至2023年8月期间就诊于中国人民解放军总医院第一医学中心内分泌科的成年PSIS患者的临床资料进行了分析。根据患者的MAFLD和MS状态进行分组，并分析了各组之间的临床特征和危险因素差异。使用机器学习模型构建成年PSIS患者MAFLD发生的预测模型，并分析高危预测因素。在136例成年PSIS患者中，93.3%为男性。MAFLD的患病率为55.5%，MS为22.3%。有生长激素（GH）治疗史的患者发生MAFLD的可能性较小（P = 0.032）。MAFLD患者的高血压、高尿酸血症、肥胖、MS和血脂异常发生率较高。多种危险因素可能导致MS，而未发现MS与激素替代之间存在显著关联。然而，机器学习模型的岭回归模型显示，GH未治疗可能是PSIS患者MAFLD的显著预测因素，其平均曲线下面积（AUC）为0.82，预测性能最高。成年PSIS患者中MS和MAFLD的患病率较高。多种危险因素可能导致这两种疾病，构建预测模型后，我们发现MAFLD可能与既往缺乏GH治疗密切相关。
