ArticleHuman genetics2025
Genetic burden and multidimensional predictors in prenatal diagnosis of fetal congenital diaphragmatic hernia.
Article in Human genetics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
- Prenatal ultrasound diagnosis of a rare morgagni hernia: a case report.BMC pregnancy and childbirth · 2026Article
Corrections and comments
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Authors and funding
22 authors.
Funding
Abstract
This study aims to assess the genetic burden of fetal congenital diaphragmatic hernia (CDH) and identify prenatal, perinatal, and postnatal predictors to improve early diagnosis, monitoring, and intervention. This study included 130 CDH fetuses who underwent invasive prenatal diagnosis, with fetal prognosis evaluated using imaging parameters such as observed-to-expected lung-to-head ratio (o/e LHR), observed-to-expected total lung volume (o/e TLV), and percent predicted lung volume (PPLV). Clinical outcomes included neonatal outcomes, extracorporeal membrane oxygenation (ECMO) requirement, and post-neonatal prognosis. Logistic regression and receiver operating characteristic (ROC) curve analyses were used to evaluate prognostic indicators and construct predictive models. Chromosomal microarray analysis (CMA) and exome sequencing (ES) yielded diagnostic rates of 7.7% and 8.7%, respectively, identifying a wide spectrum of pathogenic variants and highlighting the genetic heterogeneity of CDH. Among imaging parameters, o/e LHR, o/e TLV, and PPLV were significantly associated with neonatal outcomes, ECMO requirement, and post-neonatal prognosis. Multivariable models incorporating these parameters achieved high predictive accuracy (AUCs > 0.85), with the neonatal outcomes model reaching an AUC of 0.929, sensitivity of 93.2%, and specificity of 78.6%. By integrating genetic, imaging and clinical outcome data, this study identified CMA and ES as key tools for detecting genetic burden in CDH fetuses, and confirmed o/e LHR, o/e TLV, PPLV, and liver herniation as reliable prognostic indicators. Multivariable models based on these parameters showed strong predictive performance. A combined genetic-imaging approach is recommended to support individualized risk assessment and guide perinatal management.
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Registered trials
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