Identification of risk factors and development of a predictive model for foetal growth restriction: a retrospective case-control study.
The study identifies several risk factors for fetal growth restriction and presents a predictive model with moderate capability, but external validation is needed before it can be applied clinically.
Where it sits
this study against the rest of the hcg (human chorionic gonadotropin) corpusSummary and findings
This study aimed to identify risk factors associated with fetal growth restriction (FGR) and develop a predictive model based on a retrospective case-control analysis of 490 pregnant women. The study found significant differences in maternal-neonatal outcomes between FGR cases and controls, with a predictive model showing an area under the ROC curve of 0.722. No therapeutic claims are made.
Abstract
<h4>Objective</h4>To identify risk factors associated with foetal growth restriction (FGR) and develop a predictive model to support early diagnosis and individualized clinical management strategies.<h4>Methods</h4>A retrospective case-control study was conducted at Wusibei Campus of Fujian Maternity and Child Health Hospital, Fuzhou, China involving 490 pregnant women (196 FGR cases and 294 controls) who delivered between January and December 2024. Participants were categorized into two groups: a control group with normal foetal growth and an FGR group with confirmed FGR (This retrospective case-control study selected participants according to pregnancy outcomes and analysed clinical data retrospectively). Clinical characteristics and maternal-neonatal outcomes were compared. Univariate and multivariate logistic regression analyses were performed using SPSS 26.0 to determine independent risk factors for FGR. A predictive nomogram was constructed using R software (version 4.1.0) with the rms package. Model performance was evaluated <i>via</i> bootstrap internal validation, and discrimination and calibration were assessed using receiver operating characteristic (ROC) curve analysis and calibration plots.<h4>Results</h4>The FGR group demonstrated significantly higher incidences of foetal distress, caesarean delivery, preterm birth, and neonatal hospitalization compared to the control group (all <i>p</i> < 0.001). Multivariate analysis identified the following independent risk factors for FGR: reduced placental thickness on first-trimester nuchal translucency ultrasound, low pregnancy-associated plasma protein A levels, hypertensive disorders of pregnancy, gestational hypothyroidism, oligohydramnios, and absence of gestational diabetes mellitus. The resulting nomogram demonstrated moderate predictive capability with an area under the ROC curve of 0.722.<h4>Conclusion</h4>The predictive model developed in this study may facilitate the early identification of high-risk pregnancies, enabling timely intervention to improve maternal and neonatal outcomes. However, external validation of this model is needed before clinical implementation.
Background
Fetal growth restriction (FGR) is a significant concern in obstetrics, associated with adverse perinatal outcomes. Previous studies have identified various maternal and placental factors contributing to FGR, but a comprehensive predictive model remains elusive. This study addresses the gap by examining risk factors and developing a predictive model based on a case-control design.
Methods
The study employed a retrospective case-control design, but specific details regarding the population size (n), selection criteria, and the exact nature of the data collected were not reported in the abstract. The study aimed to identify risk factors and develop a predictive model, though the methodology for these analyses was not detailed.
Results
Not reported in abstract.
Interpretation
Without specific results or effect sizes reported, it is challenging to compare this study's findings to existing literature on FGR. The lack of detailed outcomes limits the ability to determine whether any identified risk factors are clinically meaningful or if the predictive model has practical applications. Potential confounding factors and the retrospective nature of the study may also limit the conclusions drawn.
Key findings
- Not reported in abstract.
Limitations
- Not reported in abstract.
- Retrospective design may introduce biases.
- Lack of specific numeric findings limits assessment.
- No details on sample size or population characteristics.