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Record W2473113688

Understanding the physical and mental functioning of those with persistent and resolved Complex Regional Pain Syndrome to help inform treatment approaches

2016· article· en· W2473113688 on OpenAlexaboutno aff
Candy McCabe, Alison Llewellyn, Yvette Hibberd, Paul M. White, Lindsay Davies, Johan Marinus, R. Perez, Ilona Thomassen, Florian Brunner, Carol Sontheim, Frank Birklein, Andreas Göebel, Richard Haigh, Robyn Connett, Christian Maihöfner, Lone Knudsen, Norman Harden, Andrzej Żyluk, David H. Shulman, Helen Small, François Gobeil, Peter A. Moskovitz

Bibliographic record

VenueUWE Research Repository (UWE Bristol) · 2016
Typearticle
Languageen
FieldMedicine
TopicPain Management and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsPsychosocialComplex regional pain syndromeQuality of life (healthcare)MedicineAnxietyPopulationMental healthChronic painInformed consentPhysical therapyClinical psychologyPsychiatryAlternative medicineNursingEnvironmental health
DOInot available

Abstract

fetched live from OpenAlex

Background Pain is bio-psychosocial in nature. Recognising the inter-relationship of physical and psychological factors in Complex Regional Pain Syndrome (CRPS) has clinical implications for treating this often poorly understood chronic pain condition. Whilst there is little evidence suggesting psychosocial factors have a prognostic role in the development of CRPS, research suggests CRPS has significant consequences for patients, such as poor psychological health, poor functional ability and reduced quality of life (QoL). It is also known that anxiety, pain-related fear, and disability in the early stages of CRPS are associated with poorer outcomes in the first year. However, little is known about how demographic and bio-psychosocial factors may vary and relate to patient-defined recovery and other individual characteristics (including duration of the condition and upper- versus lower-limb CRPS). Understanding self-reported symptoms and psychosocial factors within these contexts may be important in helping healthcare professionals design and evaluate future treatments.Aims To undertake a cross-sectional study, describing the self-reported physical and psychological function of people with CRPS (with varying disease duration), and those who had recovered. Using an international sample to ensure population diversity, to identify variances and/or relationships between recovered and non-recovered populations and condition characteristics (upper/lower limb affected). Methods Following ethical and institutional approvals at study sites, potential participants ≥18yrs, who met, or previously met, Budapest CRPS criteria, were identified from 8 country-specific databases (UK, Germany, USA, Canada, Switzerland, Denmark, Netherlands, Poland) and sent postal questionnaires (translated from English as required). Consent was implied by return of completed questionnaires. Data collected within countries was anonymised and pooled on a single common database (lead centre Bath). Self-reported data included: patient demographics, limb affected, disease stage (early, intermediate, late, recovered/non-recovered); knowing CRPS type (I or II); date of CRPS onset; trigger (trauma or spontaneous); and symptoms (from a provided list) in the prior 48 hours. Participants also completed: McGill Pain Questionnaire (MPQ); EQ-5D; Acceptance and Action Questionnaire (AAQ-II); Radboud Skills Questionnaire (RSQ) for upper-limb CRPS; and Measuring Activity Limitations in Walking Questionnaire (WAQ) for lower-limb. Chi-squared, Welch’s t-tests, odds ratios and regression analyses were used to explore the data.Results N=347 participants (80.4% female; mean age=53yrs; 52.7% disease duration ≥ 3yrs. N=310 reported recovery status: 280 (90.3%) non-recovered. Self-reported recovery and number of symptoms were strongly associated (χ2 = 124.94, df = 15, p

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)0.002
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.018
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0170.002

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 head0.293
GPT teacher head0.331
Teacher spread0.037 · 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 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

Citations0
Published2016
Admission routes1
Has abstractyes

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