Influencing factors of fetal growth restriction in patients with preeclampsia and the establishment of a Nomogram prediction model
10.3760/cma.j.cn115807-20231107-00132
- VernacularTitle:子痫前期并发胎儿生长受限的影响因素及其Nomogram预测模型建立
- Author:
Lu QIAN
1
;
Huifeng GU
;
Weihui YANG
Author Information
1. 湖州市妇幼保健院妇产科，湖州 313000
- Keywords:
Preeclampsia;
Fetal growth restriction;
Nomogram prediction model
- From:
Chinese Journal of Endocrine Surgery
2024;18(3):434-439
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To explore the influencing factors of fetal growth restriction (FGR) in patients with preeclampsia (PE) and construct a Nomogram prediction model.Methods:From Aug. 2021 to May. 2023, 273 PE patients admitted to our hospital were regarded as the study subjects, and grouped into a modeling group (n=191) and a validation group (n=82). Multivariate logistic regression analysis was applied to determine the influencing factors of FGR in PE patients. R4.3.1 was applied to construct a Nomogram model for predicting FGR in PE patients. Receiver operating characteristic (ROC) curve and the Hosmer Lemeshoe (H-L) goodness of fit test were applied to evaluate the discrimination and consistency of the Nomogram model in predicting FGR in PE patients.Results:There was no statistically obvious difference in gestational age, blood pressure, hemoglobin, urinary protein (UP), uric acid, umbilical artery systolic/diastolic blood pressure (S/D), D-dimer (D-D), or birth frequency between the modeling group and the validation group ( P>0.05). Compared with no concurrent FGR group, the onset of pregnancy in the concurrent FGR group was earlier, the levels of UP, S/D, and D-D, and the proportion of oligohydramnios were obviously higher, and the platelet count (PLT) was obviously lower ( t/χ 2=2.588, 1.437, 6.262, 5.464, 9.881, 3.326, P<0.05). Multivariate Logistic regression analysis showed that UP, S/D, D-D, and oligohydramnios were risk factors for FGR in PE patients ( OR=1.004, 3.807, 1.006, 4.348, P<0.05), while PLT was a protective factor ( OR=0.980, P<0.05). Nomogram model showed that when the total score of the above 5 influencing factors in PE patients was 149, the probability of concurrent FGR was 60%; when the total score was 167, the probability of concurrent FGR was 90%, and the probability of exceeding 167 was over 90%. Modeling group H-L test χ 2=6.736, P=0.565, validation group χ 2=5.812, P=0.668. The area under the ROC curve (AUC) of the modeling group and the validation group was 0.924 (95% CI: 0.883-0.965) and 0.932 (95% CI: 0.880-0.984), respectively. The sensitivity was 83.93% and 90.48%, and the specificity was 89.63% and 81.97%, respectively. Decision curve analysis (DCA) was applied to evaluate the clinical application value of the Nomogram model in predicting FGR in PE patients. Conclusion:The Nomogram model constructed based on the five indicators of UP, S/D, D-D, PLT, and oligohydramnios for predicting the risk of FGR in PE patients has high discrimination and consistency.
