摘要
目的:探讨剖宫产患者术后感染的影响因素,构建其列线图预测模型。方法:回顾性分析2021年1—12月于山西白求恩医院行剖宫产手术患者的临床资料,根据术后是否发生感染分为感染组(n=60)和未感染组(n=1086),筛选剖宫产患者术后感染的影响因素纳入列线图风险预测模型,评价列线图预测模型的区分度、校准度及预测效能。结果:多因素Logistic回归分析结果显示,有稳定的工作是剖宫产患者术后感染的保护因素(OR=0.570,95%CI:0.331~0.983,P=0.043),妊娠期高血压疾病(OR=2.356,95%CI:1.324~4.192,P=0.004)、B族链球菌(group B Streptococcus,GBS)定植(OR=3.154,95%CI:1.118~8.897,P=0.030)、阴道检查次数>5次(OR=2.470,95%CI:1.146~5.324,P=0.021)以及缩宫素引产(OR=2.457,95%CI:1.230~4.907,P=0.011)是剖宫产患者术后感染的危险因素。基于以上因素建立列线图预测模型,一致性指数(consistency index,C-index)为0.721(95%CI:0.651~0.791),以0.051为截断值,敏感度为66.7%,特异度为72.5%。Homer-Lemeshow拟合优度检验提示预测模型有较好的校准能力(χ^(2)=2.169,P=0.825)。结论:基于工作、妊娠期高血压疾病、GBS定植、阴道检查次数及缩宫素引产构建的列线图预测模型可根据预测风险值早期识别剖宫产术后感染高危人群,采取对应的预防措施,减少感染发生。但仍需进一步行外部验证及前瞻性比较试验证实模型预测能力的可靠性。
Objective:To investigate the influencing factors of postoperative infection in cesarean section patients and construct a nomogram prediction model.Methods:The clinical data of patients undergoing cesarean section in Shanxi Bethune Hospital from January 2021 to December 2021 were retroanalyzed and devided into infection group(n=60)and no infection group(n=1086).The influencing factors of postoperative infection in cesarean section patients were selected into the nomogram risk prediction model.The discrimination,calibration,and prediction efficacy of the nomograms prediction model were evaluated.Results:The results of the multivariate Logistic regression analysis showed that having stable work was a protective factor for postoperative infection in cesarean section patients(OR=0.570,95%CI:0.331-0.983,P=0.043).Hypertensive disorders in pregnancy(OR=2.356,95%CI:1.324-4.192,P=0.004),GBS colonization(OR=3.154,95%CI:1.118-8.897,P=0.030),times of vaginal examinations>5(OR=2.470,95%CI:1.146-5.324,P=0.021)and oxytocin induction(OR=2.457,95%CI:1.230-4.907,P=0.011)were independent risk factors of postoperative infection in cesarean section patients.The nomogram prediction model was established based on the above factors,whose consistency index(C-index)was 0.721(95%CI:0.651-0.791),and 0.051 was selected as the cut-off value,with a sensitivity of 66.7%and a specificity of 72.5%.The Homer-Lemeshow goodness-of-fit test suggested that the prediction model had a better calibration ability(χ^(2)=2.169,P=0.825).Conclusions:The nomogram prediction model constructed based on work,gestational hypertensive diseases,GBS colonization,times of vaginal examinations,and oxytocin labor induction has good accuracy and differentiation.It can identify the high-risk group after cesarean section to be infected in the early stage according to the predicted risk value,and corresponding preventive measures should be taken to reduce the occurrence of infection.However,further external verification and prospective comparative trials are needed to confirm the reliability of the predictive ability of the model.
作者
张燕飞
王艺璇
张韶华
褚莹
王赞宏
ZHANG Yan-fei;WANG Yi-xuan;ZHANG Shao-hua;CHU Ying;WANG Zan-hong(Department of Obstetrics and Gynecology,Shanxi Bethune Hospital,Taiyuan 030032,China)
出处
《国际妇产科学杂志》
CAS
2023年第4期421-427,共7页
Journal of International Obstetrics and Gynecology
关键词
剖宫产术
手术后并发症
感染
影响因素分析
列线图
预测
Cesarean section
Postoperative complications
Infections
Root cause analysis
Nomograms
Forecasting
作者简介
通信作者:王赞宏,E-mail:wangzanhong@126.com。
