基于炎症指标及肠道菌群指标的活动性溃疡性结肠炎病情严重程度预测模型构建  

Prediction model construction of disease severity in patients with active ulcerative colitis based on inflammatory indicators and intestinal flora indicators

作　　者：刘磊[1] 韩海涛[1] 张浩 LIU Lei;HAN Hai-tao;ZHANG Hao(Department of Proctology,the First Affiliated Hospital of Henan University of Traditional Chinese Medicine,Zhengzhou 450000,China)

机构地区：[1]河南中医药大学第一附属医院肛肠科,郑州450000

出　　处：《医药论坛杂志》2024年第23期2508-2513,共6页Journal of Medical Forum

摘　　要：目的构建基于炎症指标及肠道菌群指标的活动性溃疡性结肠炎病情严重程度预测模型,旨在为后续临床诊断及个体化治疗方案制定提供更多参考。方法回顾性纳入2018年1月—2024年1月于河南中医药大学第一附属医院诊治活动性溃疡性结肠炎患者共361例,根据病情严重程度分为轻度组(158例)、中度组(104例)及重度组(99例)。活动性溃疡性结肠炎病情严重程度预测因子行单因素以及多因素分析。进行活动性溃疡性结肠炎病情严重程度预测模型构建及预测效能分析。结果各病情严重程度亚组肿瘤坏死因子α[(107.53±20.30)ng/L vs(125.82±31.37)ng/L vs(159.23±44.60)ng/L]、白细胞介素1β[(34.77±12.04)ng/L vs(48.83±14.10)ng/L vs(75.99±18.57)ng/L]、白细胞介素6[(26.39±5.05)ng/L vs(32.42±7.33)ng/L vs(53.03±12.68)ng/L]、中性粒细胞/血小板比值[(13.95±1.39)vs(18.29±1.90)vs(23.07±2.26)]、大肠埃希菌[(3.53±0.60)CFU/g vs(4.17±0.85)CFU/g vs(4.85±1.07)CFU/g]、双歧杆菌[(1.79±0.65)CFU/g vs(1.22±0.43)CFU/g vs(0.49±0.10)CFU/g]、乳酸杆菌[(6.53±1.40)CFU/g vs(5.67±1.15)CFU/g vs(3.79±0.87)CFU/g]水平比较差异有统计学意义(P<0.05)。有序logistic回归模型的结果显示:肿瘤坏死因子α、白细胞介素1β、白细胞介素6、中性粒细胞/血小板比值、大肠埃希菌、双歧杆菌及乳酸杆菌均是活动性溃疡性结肠炎病情严重程度独立影响因素(OR=1.012、1.057、1.064、1.072、2.950、0.471、0.651、P<0.05)。利用肿瘤坏死因子α、白细胞介素1β、白细胞介素6、中性粒细胞/血小板比值、大肠埃希菌、双歧杆菌、乳酸杆菌以及P值预测概率对活动性溃疡性结肠炎病情严重程度进行ROC曲线的预测,曲线下面积分别为0.632,0.632,0.593,0.589,0.764,0.607,0.595,0.845。结论炎症相关实验室指标及肠道菌群特征均可用于活动性溃疡性结肠炎病情严重程度预测;利用以上因素构建的数据模型对于患者的病Objective To construct the prediction model of disease severity in patients with active ulcerative colitis based on inflammatory indicators and intestinal flora indicators to provide more reference for follow-up clinical diagnosis and individualized treatment plan.Methods Totally 361 patients with active ulcerative colitis diagnosed and treated in our hospital from January 2018 to January 2024 were retrospectively included and were divided into mild group(158 cases),moderate group(104 cases)and severe group(99 cases)according to the disease severity.Univariate and multivariate analyses of predictors of severity of active ulcerative colitis.Construction of prediction model for severity of active ulcerative colitis and analysis of prediction efficacy.Results Tumor necrosis factor-α[(107.53±20.30)ng/L vs(125.82±31.37)ng/L vs(159.23±44.60)ng/L]and interleukin-1β[(34.77±12.04)ng/L vs(48.83±14.10)ng/L vs(75.99±18.57)ng/L],interleukin-6[(26.39±5.05)ng/L vs(32.42±7.33)ng/L vs(53.03±12.68)ng/L],neutrophil/platelet ratio[(13.95±1.39)vs(18.29±1.90)vs(23.07±2.26)],Escherichia coli[(3.53±0.60)CFU/g vs(4.17±0.85)CFU/g vs.(4.85±1.07)CFU/g],Bifidobacterium[(1.79±0.65)CFU/g vs(1.22±0.43)CFU/g vs(0.49±0.10)CFU/g],Lactobacillus[(6.53±1.40)CFU/g vs(5.67±1.15)CFU/g vs(3.79±0.87)CFU/g]levels were significantly different(P<0.05).The results of the ordered logistic regression model show:Tumor necrosis factor-α,interleukin-1β,interleukin-6,neutrophil/platelet ratio,Escherichia coli,bifidobacterium and Lactobacillus were all independent factors influencing the severity of active ulcerative colitis(OR=1.012,1.057,1.064,1.072,2.950,0.471,0.651,P<0.05).Tumor necrosis factorα,interleukin1β,interleukin6,neutrophil/platelet ratio,Escherichia coli,bifidobacterium,lactobacillus and P-value prediction probability were used to predict the severity of active ulcerative colitis.The area under the curve was 0.632,0.632,0.593,0.589,0.764,0.607,0.595,0.845.Conclusion Both inflammatory laboratory indicators and intestinal flora

关 键 词：溃疡性结肠炎 炎症 肠道菌群 病情严重程度 模型 

分 类 号：R574.62[医药卫生—消化系统]