Evidence map›Paper›PMID 39666128›Full record

ArticleJournal of neurology2024

The diagnostic journey of patients being investigated for myopathy in a tertiary centre in England.

Zekai Qiang, Laura Barnett, Georgia Bingham, Oscar Han, Annabel Walsh, Martin Conwill, Harry E McDonough, Christopher J McDermott, Pamela J Shaw, James J P Alix

Abstract read
In one paragraph

Article in Journal of neurology, 2024. 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

10 authors.

Zekai Qiang *Sheffield Institute for Translational Neuroscience, Division of Neuroscience, University of Sheffield, Sheffield, UK.
Laura Barnett *Sheffield Institute for Translational Neuroscience, Division of Neuroscience, University of Sheffield, Sheffield, UK.
Georgia Bingham *Sheffield Institute for Translational Neuroscience, Division of Neuroscience, University of Sheffield, Sheffield, UK.
Oscar Han *Sheffield Institute for Translational Neuroscience, Division of Neuroscience, University of Sheffield, Sheffield, UK.
Annabel Walsh *Sheffield Institute for Translational Neuroscience, Division of Neuroscience, University of Sheffield, Sheffield, UK.
Martin ConwillDepartment of Clinical Neurophysiology, Royal Hallamshire Hospital, Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield, UK.
Harry E McDonoughSheffield Institute for Translational Neuroscience, Division of Neuroscience, University of Sheffield, Sheffield, UK.
Christopher J McDermottSheffield Institute for Translational Neuroscience, Division of Neuroscience, University of Sheffield, Sheffield, UK.
Pamela J ShawSheffield Institute for Translational Neuroscience, Division of Neuroscience, University of Sheffield, Sheffield, UK.
James J P AlixSheffield Institute for Translational Neuroscience, Division of Neuroscience, University of Sheffield, Sheffield, UK. j.alix@sheffield.ac.uk.ORCID http://orcid.org/0000-0001-8391-9749

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Myopathies are heterogenous and can provide a diagnostic puzzle. Many patients investigated for myopathy will go on to other diagnoses. An overall understanding of how patients are investigated for suspected myopathy is lacking. Our aim was to understand how patients were investigated for myopathy in our tertiary centre and the timeline of their diagnostic journey. Through local database searches over a 5-year period (2015-2019), we identified a final total of 770 patients investigated for myopathy. Of these, 29.7% went on to a diagnosis of myopathy. The top non-myopathy diagnoses were neuropathy, spinal pathology and ataxia. Both the myopathy and non-myopathy groups had symptoms for an extended period before reaching specialist services (both groups 104 weeks). Following a first hospital visit, median time to diagnosis was not significantly different (myopathy 46.9 weeks, non-myopathy 40.7 weeks, p > 0.05). Data on the diagnostic journey for specific myopathies was also collected, with inflammatory myopathies diagnosed most quickly and muscular dystrophies most slowly. Muscle MRI and biopsy had the best positive predictive values (82.7% and 83.1%, respectively), while EMG had the best negative predictive value (89.3%). A combination of CK, EMG and neuroaxis MRI (brain and spinal cord) yielded at least one correct test result with respect to final diagnosis in 98.9% of cases. In conclusion, patients in whom a muscle disease is considered experience significant diagnostic delay. The first step in the diagnostic journey should be able to identify both myopathy and non-myopathy cases.

Indexed as

Muscular DiseasesTertiary Care CentersAdolescentAdultAgedAged, 80 and overDelayed DiagnosisElectromyographyEnglandFemaleHumansMagnetic Resonance ImagingMaleMiddle AgedRetrospective StudiesYoung AdultBiopsyDiagnosisEMGMuscleMyopathy

Identifiers

PMID39666128
PMCPMC11638302

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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.