Evidence map›Paper›PMID 36034570›Full record

ArticleFrontiers in pediatrics2022

Walking alone milestone combined reading-frame rule improves early prediction of Duchenne muscular dystrophy.

Yan-Li Ma, Wei-Hua Zhang, Guo-Hong Chen, Li-Fang Song, Yuan Wang, Rui-Li Yuan, Ying Wang, Xiu-Yong Cheng

Abstract read
In one paragraph

Article in Frontiers in pediatrics, 2022. 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
–field-weighted citation impact
1 · What the graph read from it

What it found

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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.

2 · The registry

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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.

  1. Incidental finding of aFrontiers in pediatrics · 2025
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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

8 authors.

Yan-Li MaDepartment of Neonatology, The First Affiliated Hospital of Zheng Zhou University, Zhengzhou, China.
Wei-Hua ZhangDepartment of Neurology, Beijing Children's Hospital, Beijing, China.
Guo-Hong ChenDepartment of Neurology, Children's Hospital Affiliated to Zhengzhou University, Henan Children's Hospital, Zhengzhou Children's Hospital, Zhengzhou, China.
Li-Fang SongDepartment of Neurology, Children's Hospital Affiliated to Zhengzhou University, Henan Children's Hospital, Zhengzhou Children's Hospital, Zhengzhou, China.
Yuan WangDepartment of Neurology, Children's Hospital Affiliated to Zhengzhou University, Henan Children's Hospital, Zhengzhou Children's Hospital, Zhengzhou, China.
Rui-Li YuanDepartment of Neurology, Children's Hospital Affiliated to Zhengzhou University, Henan Children's Hospital, Zhengzhou Children's Hospital, Zhengzhou, China.
Ying WangDepartment of Neurology, Children's Hospital Affiliated to Zhengzhou University, Henan Children's Hospital, Zhengzhou Children's Hospital, Zhengzhou, China.
Xiu-Yong ChengDepartment of Neonatology, The First Affiliated Hospital of Zheng Zhou University, Zhengzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To explore the potential of walking alone milestone combined reading-frame rule to improve the early diagnosis of Duchenne muscular dystrophy (DMD). Method: To retrospectively describe the genotype and phenotype of Duchenne and Becker muscular dystrophies (BMD) patients with deletions and duplicates in the dystrophin gene. The sensitivity and specificity of the reading frame rule were calculated and compared to that of the combined reading frame rule and walking alone milestone. The diagnostic coincidence rate of two different methods was analyzed. Result: One hundred sixty-nine male DMD/BMD patients were enrolled, including 17 cases of BMD and 152 cases of DMD. The diagnostic coincidence rate, diagnostic sensitivity, and specificity of the reading-frame rule for DMD/BMD were 85.2, 86.8, and 70.59%, respectively. The sensitivity and specificity of the reading frame principle combined with the walking alone milestone for DMD/BMD were 96.05 and 70.59%, respectively. The diagnostic coincidence rate increased to 93.49%, significantly different from that predicted by reading- frame rule ( Conclusion: The reading-frame rule combined with the walking alone milestone significantly improved the early diagnosis rate of DMD.

Indexed as

childrenDuchenne muscular dystrophymotor milestonepredictionreading-frame

Identifiers

PMID36034570
PMCPMC9417149

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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.