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Record W3109891099 · doi:10.1186/s13063-020-04892-0

A randomised controlled trial of heavy shoulder strengthening exercise in patients with hypermobility spectrum disorder or hypermobile Ehlers-Danlos syndrome and long-lasting shoulder complaints: study protocol for the Shoulder-MOBILEX study

2020· article· en· W3109891099 on OpenAlexaboutno aff
Behnam Liaghat, Søren Thorgaard Skou, Jens Søndergaard, Eleanor Boyle, Karen Søgaard, Birgit Juul‐Kristensen

Bibliographic record

VenueTrials · 2020
Typearticle
Languageen
FieldMedicine
TopicShoulder Injury and Treatment
Canadian institutionsnot available
FundersOdense UniversitetshospitalSyddansk UniversitetGigtforeningenRegion Syddanmark
KeywordsMedicineEhlers–Danlos syndromeHypermobility (travel)Physical therapyJoint hypermobilityRandomized controlled trialPhysical medicine and rehabilitationSurgery

Abstract

fetched live from OpenAlex

BACKGROUND: Four out of five patients with hypermobility spectrum disorder (HSD) or hypermobile Ehlers-Danlos syndrome (hEDS) experience shoulder complaints including persistent pain and instability. Evidence suggests that patients with HSD/hEDS who experience knee and back complaints improve with exercise-based therapy. However, no study has focused on exercise-based treatment for the shoulder in this patient group. The potential benefits of strengthening the shoulder muscles, such as increased muscle-tendon stiffness, may be effective for patients with HSD/hEDS who often display decreased strength and increased shoulder laxity/instability. The primary aim is to investigate the short-term effectiveness of a 16-week progressive heavy shoulder strengthening programme and general advice (HEAVY) compared with low-load training and general advice (LIGHT), on self-reported shoulder symptoms, function, and quality of life. METHODS: A superiority, parallel group, randomised controlled trial will be conducted with 100 patients from primary care with HSD/hEDS and shoulder complaints (persistent pain and/or instability) for more than 3 months. Participants will be randomised to receive HEAVY (full range of motion, high load) or LIGHT (neutral to midrange of motion, low load) strengthening programme three times weekly with exercises targeting scapular and rotator cuff muscles. HEAVY will be supervised twice weekly, and LIGHT three times during the 16 weeks. The primary outcome will be between-group difference in change from baseline to 16-week follow-up in the Western Ontario Shoulder Instability Index (WOSI, 0-2100 better to worse). Secondary outcomes will include a range of self-reported outcomes covering symptoms, function, and quality of life, besides clinical tests for shoulder strength, laxity/instability, and proprioception. Outcome assessors will be blinded to group allocation. Participants will be kept blind to treatment allocation through minimal information about the intervention content and hypotheses. Primary analyses will be performed by a blinded epidemiologist. DISCUSSION: If effective, the current heavy shoulder strengthening programme will challenge the general understanding of prescribing low-load exercise interventions for patients with HSD/hEDS and provide a new treatment strategy. The study will address an important and severe condition using transparent, detailed, and high-quality methods to potentially support a future implementation. TRIAL REGISTRATION: ClinicalTrials.gov NCT03869307 . Registered on 11 March 2019.

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)0.007
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.027
Threshold uncertainty score0.090

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.008
Meta-epidemiology (narrow)0.0040.002
Meta-epidemiology (broad)0.0090.004
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.0270.004

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 head0.109
GPT teacher head0.395
Teacher spread0.285 · 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 designRandomized trial
Domainnot available
GenreProtocol

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

Citations13
Published2020
Admission routes1
Has abstractyes

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