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Record W3009065377 · doi:10.1159/000506193

Myofibrillar Myopathy Mimicking Polyneuropathy

2020· article· en· W3009065377 on OpenAlexaff
Pierre R. Bourque, Ari Breiner, Jodi Warman‐Chardon

Bibliographic record

VenueCase Reports in Neurology · 2020
Typearticle
Languageen
FieldNeuroscience
TopicHereditary Neurological Disorders
Canadian institutionsChildren's Hospital of Eastern OntarioOttawa Hospital
Fundersnot available
KeywordsMedicineMyopathyPolyneuropathyMyofibrilPhysical medicine and rehabilitationInternal medicine

Abstract

fetched live from OpenAlex

A 76-year-old man with a 5-year history of gait difficulties was suspected to have length-dependent sensorimotor polyneuropathy. Electrodiagnostic results pointed to a foot drop of neurogenic etiology, except for the prominence of myotonic discharges on needle EMG. Tests for acquired and genetic causes of polyneuropathy were unrevealing. The patient's first-degree cousin, with a much different clinical phenotype had been diagnosed with myofibrillar myopathy. Our patient was eventually found to carry the same myotilin c.179C>T p.Ser60Phe mutation. Muscle MRI was helpful in delineating clinically unsuspected involvement of paraspinal and pelvi-femoral muscles, as well as showing marked myopathic fatty infiltration of distal leg muscles. The association of neuropathy and myopathy is a recognized feature of myofibrillar myopathy. In some patients with unexplained foot drop, whole-body muscle MRI and a dedicated genetic mutation testing strategy may help reveal a diagnosis of genetic myopathy.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.051
GPT teacher head0.259
Teacher spread0.208 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2020
Admission routes1
Has abstractyes

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