Evidence map›Paper›PMID 40567897›Full record

SynthesisFrontiers in genetics2025

Exome sequencing and prenatal skeletal abnormalities: comprehensive review and meta-analysis and way forward.

Mengting Jiang, Bin Zhang, Jing Wang, Cui Wei, Xiuzhen Mao, Bin Yu

Abstract readSystematic Review
In one paragraph

Synthesis in Frontiers in genetics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Mengting JiangDepartment of Medical Genetics, Changzhou Maternal and Child Healthcare Hospital, Changzhou Medical Center of Nanjing Medical University, Changzhou, Jiangsu, China.
Bin ZhangDepartment of Medical Genetics, Changzhou Maternal and Child Healthcare Hospital, Changzhou Medical Center of Nanjing Medical University, Changzhou, Jiangsu, China.
Jing WangDepartment of Medical Genetics, Changzhou Maternal and Child Healthcare Hospital, Changzhou Medical Center of Nanjing Medical University, Changzhou, Jiangsu, China.
Cui WeiThe Affiliated Suqian First People's Hospital of Nanjing Medical University, Suqian First People's Hospital, Suqian, Jiangsu, China.
Xiuzhen MaoThe Affiliated Suqian First People's Hospital of Nanjing Medical University, Suqian First People's Hospital, Suqian, Jiangsu, China.
Bin YuDepartment of Medical Genetics, Changzhou Maternal and Child Healthcare Hospital, Changzhou Medical Center of Nanjing Medical University, Changzhou, Jiangsu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To assess the detection rate of exome sequencing (ES) in fetuses diagnosed as skeletal abnormalities (SKA) with normal karyotype or chromosomal microarray analysis (CMA) results. Methods: We conducted electronic searches in four databases, focusing on studies involving ES in fetuses with SKA. Additional detection rate of ES compared to karyotype/CMA was calculated, followed by a meta-analysis. Subgroup analyses explored the influence of fetal phenotype on diagnostic outcomes. Results: From 2,393 studies, 21 reports covering 476 fetuses were analyzed. Key findings include: (1) an additional detection rate of ES of 63.2% (Risk Difference (RD), 0.68 [95% CI, 0.60-0.76], p < 0.00001); (2) identification of 76 genes across 304 types of variants, with Conclusion: The meta-analysis indicates that genetic variation significantly contributes to fetal SKA, primarily due to single-gene variants. Consequently, ES should be used in the prenatal diagnosis of SKA fetuses in clinical practice.

Indexed as

chromosomal microarray analysisexome sequencingkaryotypingprenatal diagnosisskeletal abnormalities

Identifiers

PMID40567897
PMCPMC12188644

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.