Department of Critical Care Medicine, Affiliated Hospital of Putian University, Putian, China.
Department of Critical Care Medicine, Fujian Medical University Union Hospital, Fuzhou, China.
Biomol Biomed. 2024 Mar 19;24(4):1004-1015. doi: 10.17305/bb.2024.10222.
Increasing evidence suggests that body composition is associated with the development of acute pancreatitis (AP). This study aimed to investigate the applicability of body composition in predicting AP severity. Data of 213 patients with AP from Affiliated Hospital of Putian University (AHOPTU) were included in this study, whilst data of 173 patients with AP from Fujian Medical University Union Hospital (FMUUH) were used for external validation. Patients were classified into the non-severe and severe groups according to AP severity. After seven days of treatment, in patients from AHOPTU, the difference in skeletal muscle index before and after treatment (ΔSMI) was significantly higher (P = 0.002), while the skeletal muscle radiodensity before treatment (PreSMR) was significantly lower (P = 0.042) in the non-severe group than in the severe group. The multivariate logistic regression model also revealed that the ΔSMI and PreSMR were independent risk factors for AP severity. The optimal cut-off values of ΔSMI and PreSMR were 1.0 and 43.7, respectively. The following metabolic score (SMS) was established to predict AP severity: 0: ΔSMI < 1.0 and PreSMR < 43.7; 1: ΔSMI ≥ 1.0 and PreSMR < 43.7 or ΔSMI < 1.0 and PreSMR ≥ 43.7; 3: ΔSMI ≥ 1.0 and PreSMR ≥ 43.7. In patients from AHOPTU and FMUUH, the areas under the curves (AUC) for this model were 0.764 and 0.741, respectively. ΔSMI and PreSMR can accurately predict AP severity. It is recommended to routinely evaluate the statuses of patients with AP using the predictive model presented in this study for individualized treatment.
越来越多的证据表明，人体成分与急性胰腺炎（AP）的发展有关。本研究旨在探讨人体成分在预测 AP 严重程度中的适用性。本研究纳入了来自莆田学院附属医院（AHOPTU）的 213 例 AP 患者的数据，同时纳入了来自福建医科大学附属协和医院（FMUUH）的 173 例 AP 患者的数据进行外部验证。根据 AP 严重程度将患者分为非重症组和重症组。在 AHOPTU 的患者中，治疗 7 天后，非重症组患者治疗前后骨骼肌指数的差值（ΔSMI）显著更高（P = 0.002），而治疗前骨骼肌辐射密度（PreSMR）显著更低（P = 0.042）。多变量逻辑回归模型还表明，ΔSMI 和 PreSMR 是 AP 严重程度的独立危险因素。ΔSMI 和 PreSMR 的最佳截断值分别为 1.0 和 43.7。建立了以下代谢评分（SMS）来预测 AP 严重程度：0：ΔSMI < 1.0 且 PreSMR < 43.7；1：ΔSMI ≥ 1.0 且 PreSMR < 43.7 或 ΔSMI < 1.0 且 PreSMR ≥ 43.7；3：ΔSMI ≥ 1.0 且 PreSMR ≥ 43.7。在 AHOPTU 和 FMUUH 的患者中，该模型的曲线下面积（AUC）分别为 0.764 和 0.741。ΔSMI 和 PreSMR 可准确预测 AP 严重程度。建议常规使用本研究提出的预测模型评估 AP 患者的状态，以便进行个体化治疗。
