Evidence map›Paper›PMID 32571459›Full record

ArticleZhongguo dang dai er ke za zhi = Chinese journal of contemporary pediatrics2020

[A predictive analysis of the association between clinical phenotypes and genotypes in children with Becker muscular dystrophy/Duchenne muscular dystrophy].

Huan-Hong Niu, Dong-Ying Tao, Sheng-Quan Cheng

Open access · greenAbstract read
In one paragraph

Article in Zhongguo dang dai er ke za zhi = Chinese journal of contemporary pediatrics, 2020. 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
0.3field-weighted citation impact, top 43% 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, 6 citations in OpenAlex.

  1. Article
  2. [Magnetic resonance imaging for the diagnosis of muscular dystrophy].Zhongguo dang dai er ke za zhi = Chinese journal of contemporary pediatrics · 2022
    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

3 authors at 1 institution in 1 country.

Huan-Hong NiuDepartment of Pediatrics, First Affiliated Hospital of Air Force Medical University, Xi'an 710032, China. quanyi@fmmu.edu.cn.
Dong-Ying Tao
Sheng-Quan Cheng
Xi'an Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo study the association between clinical phenotypes and genotypes in children with Becker muscular dystrophy (BMD)/Duchenne muscular dystrophy (DMD) so as to provide a theoretical basis for disease management, gene therapy, and prenatal diagnosis.

methodsA retrospective analysis was performed for the clinical data and gene detection results of 52 children with BMD/DMD. Multiplex ligation-dependent probe amplification (MLPA) was used to detect the DMD gene. The children with negative results of MLPA were further screened by exon chip capture combined with next-generation sequencing (NGS). The mothers of 20 probands were validated by sequencing.

resultsThe pathogenic genes for BMD/DMD were detected in 50 children by MLPA and NGS, with a detection rate of 96%. Among the 52 children, 36 (69%) had gene deletion, 7 (13%) had duplication, and 7 (13%) had micromutation. Among the 43 children with deletion/duplication, 32 had DMD and 11 had BMD; 37 children (86%) met the reading frame rule, among whom 27 (96%) had DMD and 10 (67%) had BMD. All 7 children with micromutation had DMD.

conclusionsThe reading frame rule has an extremely high predictive value for DMD but a limited predictive value for BMD.

Indexed as

Muscular Dystrophy, DuchenneChildDystrophinFemaleGene DeletionGenotypeHumansMultiplex Polymerase Chain ReactionMutationPhenotypePregnancyRetrospective StudiesDystrophin

Identifiers

PMID32571459
PMCPMC7390220
OpenAlexW3036524552

What OpenQuestion holds

Textmetadata
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.