Evidence map›Paper›PMID 41982947›Full record

ReviewTranslational pediatrics2026

Current status and prospects of prenatal ultrasound diagnosis of congenital heart disease in fetuses: a narrative review.

Hui Xin, Lei Wang, Guifeng Ding, Guilan Ding, Lingqian Meng, Hong'e Wan

Abstract readReview
In one paragraph

Review in Translational pediatrics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Hui XinSchool of Public Health, Xinjiang Medical University, Urumqi, China.
Lei WangXinjiang Clinical Research Center for Perinatal Diseases, Urumqi Maternal and Child Health Hospital, Urumqi, China.
Guifeng DingXinjiang Clinical Research Center for Perinatal Diseases, Urumqi Maternal and Child Health Hospital, Urumqi, China.
Guilan DingXinjiang Clinical Research Center for Perinatal Diseases, Urumqi Maternal and Child Health Hospital, Urumqi, China.
Lingqian MengXinjiang Clinical Research Center for Perinatal Diseases, Urumqi Maternal and Child Health Hospital, Urumqi, China.
Hong'e WanXinjiang Clinical Research Center for Perinatal Diseases, Urumqi Maternal and Child Health Hospital, Urumqi, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and Objective: Congenital heart disease (CHD) is the most common congenital anomaly and a leading cause of infant mortality. Fetal echocardiography (FE) serves as the cornerstone of prenatal screening, yet significant heterogeneity exists in its diagnostic performance. This review aims to critically appraise the current status, technological advancements, and persistent challenges in FE for diagnosing CHD. Focusing on the central issue of improving detection rates, it outlines a future direction toward an integrated, intelligent screening ecosystem. Methods: Following a narrative review methodology, a systematic literature search was conducted in PubMed, Web of Science for articles and CNKI (China National Knowledge Infrastructure) published from January 2019 to May 2025. Search terms incorporated fetal echocardiography, CHD, screening/diagnosis, and related advanced technologies. Inclusion criteria covered relevant original studies, reviews, and guidelines, while editorials and articles with unavailable full texts were excluded. Literature screening, data extraction, and bias risk assessment were performed independently by two researchers. Key Content and Findings: Standardized acquisition of key views (e.g., four-chamber, outflow tracts) forms the foundation of screening. Technology-enhanced modalities such as three-dimensional/four-dimensional spatiotemporal image correlation (3D/4D STIC) and speckle tracking offer incremental diagnostic value for specific defects. Artificial intelligence (AI) demonstrates transformative potential in automating view identification, anomaly detection, and even community-based screening. However, diagnostic efficacy remains significantly hampered by operator dependency, limitations of screening protocols, and the inherent complexity of certain CHD types, resulting in a wide variation in detection rates ranging from 60% to 90%. Conclusions: FE, particularly comprehensive FE, is indispensable for the prenatal diagnosis of CHD. Future success hinges on constructing a tiered, integrated intelligent ecosystem. This involves leveraging AI tools to standardize basic screening, combining specialized training with targeted use of advanced modalities, and precisely directing complex cases to regional diagnostic and care centers.

Indexed as

Congenital heart disease (CHD)echocardiographyprenatal diagnosisultrasound screening

Identifiers

PMID41982947
PMCPMC13071520

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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 Socratic graph.