Evidence map›Paper›PMID 38033683›Full record

ArticleClinical case reports2023

Prenatal sirenomelia diagnosis in the first trimester: A case report and literature review.

Xiaqing Shi, Fengbei Kong, Guoru Wu, Yu Shi

Open access · goldAbstract readCase Reports
In one paragraph

Article in Clinical case reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.6field-weighted citation impact, top 28% of its field
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

3 citing papers in PubMed, 2 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
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

4 authors at 2 institutions in 1 country.

Xiaqing ShiDepartment of Ultrasound Anhui Medical University Hefei Anhui China.ORCID https://orcid.org/0009-0000-5046-8806
Fengbei KongDepartment of Ultrasound Peking University Shenzhen Hospital Shenzhen Guangdong China.
Guoru WuDepartment of Ultrasound Peking University Shenzhen Hospital Shenzhen Guangdong China.
Yu ShiDepartment of Ultrasound Peking University Shenzhen Hospital Shenzhen Guangdong China.
Peking University Shenzhen Hospital · CNAnhui Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Key Clinical Message: Sirenomelia is a lethal condition in the perinatal period. The sonographic examination in the first trimester can effectively detect sirenomelia with a high degree of accuracy. Furthermore, vascular examinations using color flow imaging and augmented imaging techniques such as 3D sonography can improve diagnostic accuracy. Parents should get advice from a multidisciplinary team concerning sirenomelia care and prognosis as soon as possible. Abstract: Sirenomelia is a rare condition with an uncommon congenital malformation; its most remarkable feature is lower extremity fusion with multiple visceral anomalies. Accordingly, the appearance resembles a mermaid's tail, hence mermaid syndrome. Sirenomelia has an incidence rate of 1.5-4.2 per 100,000 births, a male-to-female 2.7:1 ratio, and shows no differences across races. The condition is generally associated with renal agenesis, exterior genitalia defects, a single umbilical artery, and an imperforate anus. Here, we describe the first sirenomelia case in our hospital; a 13-week-old fetus with conjoined lower limbs was identified by ultrasound in the first trimester. We discuss this rare case with reference to the literature and provide insights on diagnosing this condition by ultrasound.

Indexed as

caudal regressionfetal malformationliterature reviewmermaid syndromesirenomelia

Identifiers

PMID38033683
PMCPMC10683041
OpenAlexW4389099675

What OpenQuestion 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 OpenQuestion graph.