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Record W4315780166 · doi:10.1136/rmdopen-2022-002591

Pain in autoimmune inflammatory myopathies: a scoping review

2023· review· en· W4315780166 on OpenAlexaff
Valérie Leclair, Harmony Tsui, Marie Hudson

Bibliographic record

VenueRMD Open · 2023
Typereview
Languageen
FieldMedicine
TopicInflammatory Myopathies and Dermatomyositis
Canadian institutionsMcGill UniversityJewish General Hospital
Fundersnot available
KeywordsMedicineInflammationImmunologyPhysical therapyBioinformatics

Abstract

fetched live from OpenAlex

BACKGROUND: Pain is considered a priority for research by adult patients with autoimmune inflammatory myopathy (AIM) and their families. Our aim was to review the literature for studies reporting on pain in adult AIM and to summarise their findings. METHODS: A scoping review was conducted searching for studies in PubMed and MEDLINE including more than five adult patients with AIM and assessing pain using a patient-reported outcome measure. Study population characteristics, pain measurement and clinical correlates of pain were extracted using a standardised protocol. RESULTS: The search strategy identified 2831 studies with 33 meeting inclusion criteria. Most studies used visual analogue scales (n=14) and/or the Medical Outcomes Study 36-Item Short Form Bodily Pain Scale (n=17). Frequency of pain and/or myalgias ranged from 64% to 100%. Subjects with AIM had significantly more pain than the general population and comparable pain to other chronic rheumatic diseases. Insufficient results were available to identify significant clinical correlates of pain in AIM. CONCLUSION: This review suggests that the burden of pain in AIM is considerable. Still, due to the heterogeneity and low quality of the evidence, significant knowledge gaps persist. Studies are needed to characterise pain trajectories of patients with AIM.

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)0.006
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.487
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0060.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.002

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 head0.084
GPT teacher head0.404
Teacher spread0.320 · 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.

Study designSystematic review
Domainnot available
GenreReview

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

Citations11
Published2023
Admission routes1
Has abstractyes

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