Published online Sep 19, 2023. doi: 10.5498/wjp.v13.i9.654
Peer-review started: June 30, 2023
First decision: July 18, 2023
Revised: July 25, 2023
Accepted: August 21, 2023
Article in press: August 21, 2023
Published online: September 19, 2023
The clinical prediction of postpartum depression in patients with pregnancy-induced hypertension is still insufficient, and the application of the nomogram model in predicting postpartum depression in patients with pregnancy-induced hypertension is rarely reported.
Compared with normal pregnant, pregnancy-induced hypertension patients have a higher risk of postpartum depression, which is related to several factors. By integrating risk factors of postpartum depression in pregnancy-induced hypertension and constructing predictive models, this study guides identifying high-risk patients and early clinical intervention.
The study's purpose was to integrate the risk factors of postpartum depression in patients with pregnancy-induced hypertension, construct a graph prediction model, and evaluate the predictive effect of the model.
Multivariate logistic regression analysis and LASSO regression were used to analyze the factors related to postpartum depression in pregnancy-induced hypertension. R version 4.0.3 was used to construct a line graph risk predictive model. The area under the receiver operating curve was used to evaluate effectiveness.
Vitamin A deficiency (VAD) during pregnancy and puerperium, eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) are independent risk factors for postpartum depression in pregnancy-induced hypertension. The histogram model established by this method had good predictive efficacy and could guide clinical prevention and intervention.
Postpartum depression in pregnancy-induced hypertension is related to VAD during pregnancy and puerperium, family history of hypertension, intestinal flora disorders during pregnancy and perinatal period, EPA, and DHA. The predictive efficacy of the risk model established by this method has clinical application value.
Future research directions should increase the sample size or multicenter study to verify the results, enhance the reliability of the conclusions, and better carry out clinical prevention interventions.