探究发生结肠憩室病的危险因素，并构建风险预警模型。

回顾性选取2022年1月至2024年1月亳州市人民医院诊治的结肠憩室病患者163例为发生组，同期选取163例行肠镜检查，且检查结果排除结肠憩室病、炎症性肠病及肠道肿瘤的个体为未发生组。对两组临床资料，采用单因素、多因素Logistic回归分析筛选结肠憩室病的独立危险因素，构建并建立风险预警模型，采用Bootstrap内部验证评估模型性能，并按7∶3比例划分训练集与测试集进行验证。

单因素分析结果显示，两组患者在性别、年龄、饮食习惯、家族史、便秘、炎性息肉、C反应蛋白（CRP）和粪便钙卫蛋白（FC）水平比较上，均存在统计学差异（P<0.05）。多因素分析结果显示，男性、高龄、炎性息肉和高FC水平为结肠憩室病的独立危险因素（均P<0.01）。基于上述因素构建列线图模型，训练集与测试集的C指数分别为0.835和0.808，ROC分析显示，模型在训练集的AUC为0.918，测试集为0.904。模型校准度良好，决策曲线显示在较宽阈值范围内具有正向净收益。

男性、高龄、炎性息肉是结肠憩室病发生的独立危险因素，FC可作为识别相关亚临床炎症活动或预测并发症风险的潜在标志物，基于此构建的风险预警模型具有良好的区分度和校准度，具备一定的临床风险分层潜力，但需进一步在前瞻性队列中验证其适用性。

To explore the risk factors for colonic diverticular disease and construct a risk early warning model.

A retrospective selection was made of 163 patients with colonic diverticular disease diagnosed and treated in Bozhou People's Hospital from January 2022 to January 2024 as the occurrence group. During the same period, 163 individuals who underwent colonoscopy and whose examination results excluded colonic diverticular disease, inflammatory bowel disease and intestinal tumors were selected as the non-occurrence group. For the two groups of clinical data, univariate and multivariate Logistic regression analyses were used to screen for independent risk factors of colonic diverticular disease, and a risk early warning model was constructed. Bootstrap internal validation was used to evaluate the model performance, and the training set and test set were divided in a 7∶3 ratio for validation.

The results of univariate analysis showed that there were significant differences between the two groups of patients in terms of gender, age, dietary habits, family history, constipation, inflammatory polyps, C-reactive protein (CRP), and fecal calprotectin (FC) levels (all P<0.05). The results of multivariate analysis showed that male gender, advanced age, inflammatory polyps and high FC levels were independent risk factors for colonic diverticular disease (all P<0.001). Based on the above factors, a nomogram model was constructed. The C-indices of the training set and the test set were 0.835 and 0.808 respectively. ROC analysis showed that the AUC of the model in the training set was 0.918 and that in the test set was 0.904. The model has good calibration, and the decision curve showed a positive net gain within a wide threshold range.

Male gender, advanced age, and inflammatory polyps are independent risk factors for the occurrence of colonic diverticular disease. FC can serve as a potential biomarker for identifying related subclinical inflammatory activities or predicting the risk of complications. The risk early warning model constructed based on this has good discrimination and calibration, and has certain potential for clinical risk stratification. However, its applicability needs to be further verified in prospective cohorts.