Risk factors analysis and preliminary study on risk prediction model of adverse events in pregnancy complicated with heart disease
Objective To investigate the risk factors associated with adverse events in pregnant women with heart disease,and to make a preliminary study on the related risk prediction model.Methods Clinical data of 146 pregnant patients with heart disease treated in the Second Affiliated Hospital of Dalian Medical University from January 2016 to December 2022 were collected.With the occurrence of maternal-fetal adverse events as outcome variables,logistic regression analysis was adopted to explore the independent influencing factors for outcome variables,and the risk prediction model was preliminarily explored based on machine learning.Results The number of pregnancies,BMI,cardiac function grade,type of heart disease and whether assisted reproductive technology was used were independent risk factors for adverse events.Based on the results of binary logistic regression,the nomogram of the risk prediction model for adverse maternal and fetal outcomes was drawn,and the risk prediction value of adverse events in pregnant women with different high-risk factors was calculated.The nomogram and the multi-indicator combined ROC curve were drawn,and the area under ROC curve was 0.90.Conclusion The management of pregnant women with heart disease through real-time data monitoring and analysis,as well as the establishment of predictive models,can provide more accurate and real-time decision support for clinical practice.
pregnancy complicated with heart diseaseadverse maternal-fetal outcomesrisk prediction model
国家科技期刊平台
NSTL
万方数据
