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Record W4407250368 · doi:10.1016/j.jns.2025.123420

Awareness of bone strength in patients with neuromuscular disorders: ERN EURO-NMD clinician survey and European patient survey

2025· article· en· W4407250368 on OpenAlexaff
Marie Kruse, B.A.S. Olde Dubbelink, Madelon Kroneman, I. de Groot, Sabrina Schlüter, M. de Visser, Teresinha Evangelista, Antimo Moretti, David R. Weber, Leanne M. Ward, Nicol C. Voermans

Bibliographic record

VenueJournal of the Neurological Sciences · 2025
Typearticle
Languageen
FieldMedicine
TopicNeurogenetic and Muscular Disorders Research
Canadian institutionsChildren's Hospital of Eastern OntarioUniversity of Ottawa
FundersEuropean Neuromuscular Centre
KeywordsMedicineSurvey researchPhysical medicine and rehabilitationPhysical therapyPsychologyApplied psychology

Abstract

fetched live from OpenAlex

Bone strength is reduced In various neuromuscular disorders (NMDs). We aimed to assess the awareness and practice of bone strength management in NDMs among clinicians and patients. We performed two online surveys; among health care providers (HCPs) of the European Reference Network for Neuromuscular Disorders (ERN EURO-NMD) and among patients. The survey among 52 HCPs showed that awareness of potentially impaired bone strength in people with NMDs was reasonable to good: the vast majority of HCPs asked often or almost always about bone fractures during history-taking (81 %). Bone strength was less often assessed: often or almost always at diagnosis (50 %) and at follow-up (58 %). Medical training on this topic was considered poor to very poor in 50 % of HCPs. Prevention and treatment of reduced bone strength was variable and multidisciplinary care was sub-optimal. The survey among 581 patients provided important additional insights. Many patients were followed-up outside ERN EURO-NMD centers and treatment was variable. These parallel surveys provided a broad view on the awareness and management of bone strength in people with NMDs. The findings are expected to increase the appreciation of this important aspect of NMD care, and direct future research foci and care guidelines.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.267

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.031
GPT teacher head0.307
Teacher spread0.276 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2025
Admission routes1
Has abstractyes

Explore more

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