高脂血症胰腺炎复发危险因素分析及预测模型的构建

丁媛媛; 周丙梅; 王银娥; 张雪坤; 杨从艳

高脂血症胰腺炎复发危险因素分析及预测模型的构建

Analysis of the risk factors for recurrence of hyperlipidemic pancreatitis and construction of a prediction model

摘要

摘要:
目的： 探讨高脂血症胰腺炎（HLAP）复发危险因素，构建HLAP病人复发风险预测模型。
方法： 回顾性收集2020年7月至2023年8月于蚌埠医科大学第一附属医院确诊为HLAP的114例病人的临床资料，分为复发组和非复发组，分析复发组3 ~ 6个月、6 ~ 12个月、1年以上复发率及复发诱因，筛选HLAP复发危险因素，构建 logistic 回归预测模型，并绘制列线图，采用ROC曲线评估HLAP病人复发危险因素预测价值。
结果： 114例HLAP病人中复发43例，复发率37.7%，出院后3 ~ 6个月、6 ~ 12月、1年以上复发率分别为11.4%、18.4%、7.9%。复发诱因主要有油腻饮食、暴饮暴食、饮酒、受凉。单因素分析结果显示病人体质量指数、住院时间、糖尿病、脂肪肝、三酰甘油、总胆固醇、葡萄糖、尿酸、肌酐、C–反应蛋白水平对HLAP复发的影响均有统计学意义（P ＜ 0.01）。多因素logistic 回归分析发现糖尿病、脂肪肝、三酰甘油、尿酸和住院时间均为影响HLAP病人复发的独立危险因素（P ＜ 0.01），将糖尿病、脂肪肝、三酰甘油、尿酸、住院时间构建HLAP复发风险列线图预测模型，ROC曲线验证预测HLAP病人复发的AUC为0.794（95%CI：0.718 ~ 0.871）、0.761（95%CI：0.692 ~ 0.830）、0.815（95%CI：0.734 ~ 0.896）、0.798（95%CI：0.711 ~ 0.884）、0.754（95%CI：0.660 ~ 0.848），5个危险因素联合预测HLAP病人复发的AUC为0.988（95%CI：0.792 ~ 1.000），灵敏度为95.35%，特异度为97.18%。
结论： 本研究通过对HLAP复发的危险因素分析及预测模型的构建，可为临床上预防和管理HLAP复发提供相关依据。

Abstract:
Objective To explore the risk factors for recurrence of hyperlipidemic pancreatitis (HLAP), and establish a predictive model for HLAP recurrence.
Methods The clinical data of 114 patients diagnosed with HLAP in the First Affiliated Hospital of Bengbu Medical University from July 2020 to August 2023 were retrospectively collected, and divided into the recurrence group and non-recurrence group. The recurrence rates and recurrence triggers in the recurrence group within 3–6 months, 6–12 months and over 1 year were analyzed, and the risk factors for HLAP recurrence were screened. A logistic regression prediction model was constructed, and a nomogram was drawn. The ROC curve was used to evaluate the predictive value of risk factors for recurrence in patients with HLAP.
Results Among 114 patients with HLAP, 43 cases relapsed, with a recurrence rate of 37.7%. The recurrence rates at 3–6 months, 6–12 months, and over 1 year after discharge were 11.4%, 18.4%and 7.9%, respectively. The main triggers for recurrence included the greasy diet, overeating, drinking alcohol and catching a cold. The results of univariate analysis showed that the differences of the effects of body mass index of patients, hospital stay, diabetes, fatty liver, triglycerides, total cholesterol, glucose, uric acid, creatinine and C-reactive protein on the recurrence of HLAP levels were statistically significant (P ＜ 0.01). The results of multivariate logistic regression analysis showed that the diabetes, fatty liver, triglycerides, uric acid and hospital stay were the independent risk factors affecting the recurrence of HLAP patients (P ＜ 0.01). A nomogram prediction model for the recurrence risk of HLAP was constructed by using diabetes, fatty liver, triglycerides, uric acid and hospital stay. The AUC for predicting recurrence in HLAP patients verified by the ROC curve were 0.794 (95%CI: 0.718–0.871), 0.761 (95%CI: 0.692–0.830) and 0.815 (95%CI), respectively. The AUC for the combined prediction of recurrence in HLAP patients by five risk factors was 0.988 (95%CI: 0.792–1.000), with a sensitivity of 95.35% and a specificity of 97.18%.
Conclusions This study can provide the relevant clinical evidence for the prevention and management of HLAP recurrence through risk factor analysis and predictive model construction.

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