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Record W2957616815 · doi:10.1002/msc.1408

A multi‐centre study to explore the feasibility and acceptability of collecting data for complex regional pain syndrome clinical studies using a core measurement set: Study protocol

2019· article· en· W2957616815 on OpenAlexaff
Sharon Grieve, Florian Brunner, Lisa Buckle, François Gobeil, Hitoshi Hirata, Norimasa Iwasaki, G. Lorimer Moseley, Gudson Sousa, Jean‐Jacques Vatine, Nicole Vaughan‐Spickers, Jijun Xu

Bibliographic record

VenueMusculoskeletal Care · 2019
Typearticle
Languageen
FieldMedicine
TopicPain Management and Treatment
Canadian institutionsCentre de Santé et de Services Sociaux CavendishDéveloppement Economique Longueuil
Fundersnot available
KeywordsProtocol (science)Data collectionMedicineTest (biology)Set (abstract data type)Core (optical fiber)Electronic data captureMedical physicsPhysical therapyFamily medicineClinical trialAlternative medicineComputer sciencePathology

Abstract

fetched live from OpenAlex

OBJECTIVES: This international, multicentre study will inform the final data collection tools and processes which will comprise the first international, clinical research registry for complex regional pain syndrome (CRPS). This study will: (a) test the feasibility and acceptability of collecting outcome measurement data using a patient reported, questionnaire core measurement set (COMPACT [Core Outcome Measurement set for complex regional PAin syndrome Clinical sTudies]); and (b) test and refine an electronic data management system to collect and manage the data. METHODS: A maximum of 240 adults, meeting the Budapest diagnostic clinical criteria for CRPS type I or II, will be recruited across eight countries. The COMPACT questionnaire will be completed on two occasions: at baseline (T1) and 6 months later (T2). At T2, participants will choose to complete COMPACT using a paper or electronic version. Participants will be asked to feed back on their experience of completing COMPACT via a questionnaire. A separate questionnaire will ask clinicians to feed back their experience of data collection. ANALYSIS: The study is not aiming to derive statistically significant data but to ascertain the practicalities of collecting data, using the COMPACT questionnaire set, across a range of different cultures and populations. At the end of the study, a single workshop will be convened to review the findings and agree the final documents and processes for the international registry.

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)0.002
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 score0.254
Threshold uncertainty score0.799

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.649
GPT teacher head0.527
Teacher spread0.122 · 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

Citations6
Published2019
Admission routes1
Has abstractyes

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