摘要
目的:探究影响消化性溃疡(PU)的多元Logistic回归分析及防治措施。方法:回顾性分析某院于2019年1月~2021年6月接收的200例PU患者的临床资料,按照PU治愈后有无复发分为复发组(n=55)和未复发组(n=145),对PU复发的影响因素进行单因素分析与Logistic回归分析。结果:单因素分析显示,饮食、遵医用药、睡眠、运动、溃疡数目、大直径溃疡、吸烟、酗酒、终末期幽门螺杆菌(Hp)感染及非甾体类消炎药(NSAIDs)可能为影响PU复发的相关因素(P<0.05);Logistic回归分析结果显示,大直径溃疡(OR=2.054,P=0.015)、吸烟(OR=1.791,P=0.018)、酗酒(OR=2.323,P=0.002)、终末期Hp感染(OR=1.640,P=0.037)及NSAIDs应用史(OR=2.751,P=0.001)为影响PU复发的独立危险因素。结论:吸烟、终末期Hp感染、大直径溃疡、酗酒、NSAIDs应用史均为影响PU治愈后复发的独立危险因素,临床可采取相关措施进行干预,降低治愈后复发风险。
Objective:To explore the multiple logistic regression analysis and prevention measures of peptic ulcer(PU).Methods:The clinical data of 200 patients with PU in a hospital from January 2019 to June 2021 were analyzed retrospectively.According to whether there was recurrence after cure,they were divided into recurrence group(n=55)and non recurrence group(n=145).The influencing factors of PU recurrence were analyzed by univariate analysis and Logistic regression analysis.Results:Univariate analysis showed that diet,medication compliance,sleep,exercise,number of ulcers,large-diameter ulcers,smoking,alcoholism,end-stage Helicobacter pylori(HP)infection and non steroidal anti-inflammatory drugs(NSAIDs)may be the related factors affecting the recurrence of PU(P<0.05);Logistic regression analysis showed that large diameter ulcers(OR=2.054,P=0.015),smoking(OR=1.791,P=0.018),alcoholism(OR=2.323,P=0.002),end-stage HP infection(OR=1.640,P=0.037)and application history of NSAIDs(OR=2.751,P=0.001)were independent risk factors for PU recurrence.Conclusion:Smoking,end-stage HP infection,large-diameter ulcers,alcoholism and application history of NSAIDs are independent risk factors affecting the recurrence of PU after cure.Relevant clinical measures can be taken to reduce the risk of recurrence after cure.
作者
邹毅玲
黄永华
Zou Yiling;Huang Yonghua(Department of Gastroenterology,Huidong County People's Hospital,Guangdong Province,Huizhou 516300)
出处
《数理医药学杂志》
CAS
2022年第3期379-382,共4页
Journal of Mathematical Medicine
关键词
消化性溃疡
复发
影响因素
防治措施
回归分析
peptic ulcer
recurrence
influencing factors
prevention and control measures
regression analysis