Evidence map›Paper›PMID 23456025›Full record

ArticleJournal of neurology2013

An algorithm for candidate sequencing in non-dystrophic skeletal muscle channelopathies.

Tai-Seung Nam, Christoph Lossin, Dong-Uk Kim, Myeong-Kyu Kim, Young-Ok Kim, Kang-Ho Choi, Seok-Yong Choi, Sang-Cheol Park, In-Seop Na

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Article in Journal of neurology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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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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3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Tai-Seung NamDepartment of Neurology, The Brain Korea 21 Project, Chonnam National University Medical School, 8 Hakdong, Donggu, Gwangju 501-757, Korea.
Christoph Lossin
Dong-Uk Kim
Myeong-Kyu Kim
Young-Ok Kim
Kang-Ho Choi
Seok-Yong Choi
Sang-Cheol Park
In-Seop Na

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Human skeletal muscle channelopathies (HSMCs) are a group of heritable conditions with ion channel-related etiology and similar presentation. To create a comprehensive picture of the phenotypic spectrum for each condition and to devise a strategy that facilitates the differential diagnosis, we collected the genotype and phenotype information from more than 500 previously published HSMC studies. Using these records, we were able to identify clear correlations between particular clinical features and the underlying alteration(s) in the genes SCN4A, CACNA1S, KCNJ2, and CLCN1. This allowed us to develop a clinical, symptom-based, binary decision flow algorithm that predicts the proper genetic origin with high accuracy (0.88-0.93). The algorithm was implemented in a stand-alone online tool ("CGPS"- http://cgps.ddd.co.kr ) to assist with HSCM diagnosis in the clinical practice. The CGPS provides simple, symptom-oriented navigation that guides the user to the most likely molecular basis of the presentation, which permits highly targeted genetic screens and, upon confirmation, tailored pharmacotherapy based on the molecular origin.

Indexed as

AlgorithmsArtificial IntelligenceChannelopathiesGenetic TestingGenotypeHumansMuscle, SkeletalMuscular DiseasesMutationPhenotype

Identifiers

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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.