Predictive Value of Logistic Regression Model Based on Uterine Artery Blood Flow Parameters on Adverse Delivery Outcomes in Patients with Hypertensive Disorder of Pregnancy
Objective:To explore the predictive value of Logistic regression model of uterine artery blood flow parameters on the adverse delivery outcomes in patients with hypertensive disorder of pregnancy(HDP).Methods:A total of 203 HDP patients who received prenatal examination in the hospital from April 2022 to June 2023 were selected as the study subjects(HDP group),and 100 pregnant women without abortion histo-ry were included in control group.All pregnant women were tested for uterine artery blood flow parameters in the second trimester.The pulsatility index(PI),resistance index(RI),and the ratio of peak systolic velocity to diastolic velocity(S/D)were assessed.Independent predictors of adverse delivery outcomes were identified using logistic regression analysis.The effectiveness of the logistic model in predicting outcomes was evaluated through receiver operating characteristic(ROC)curve analysis.Results:The PI,RI and S/D in HDP group were significantly higher than those in control group(P<0.05).Among the 203 patients with HDP,135 cases had adverse pregnancy outcomes,with the incidence rate of 66.50%.Logistic regression model showed that PI,RI,S/D ratio were independent risk factors for adverse delivery outcomes in HDP patients(P<0.05).The AUC,SE and 95%CI of logistic regression model based on uterine artery blood flow parameters were 0.952,0.324 and 0.913-0.977 in predicting the adverse delivery outcomes(P<0.001),and the sensitivity,specificity and Youden indexes were 0.896,0.956 and 0.852.Conclusion:Uterine artery blood flow param-eters are of great significance in predicting the risk of adverse delivery outcomes in patients with HDP,and can be used as an effective tool for clinical risk assessment.
Hypertensive disorder of pregnancyUterine artery blood flow parametersLogistic regression modelAdverse delivery outcomesPrediction model
万方数据
维普
