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Record W4364354742

Placebo response in neuropathic pain after spinal cord injury: a meta-analysis of individual participant data

2018· article· en· W4364354742 on OpenAlexaboutno aff
Jutzeler CR, Warner FM, Cragg JJ, J Haefeli, Richards JS, Andresen SR, Finnerup NB, C Mercier, Kramer JLK

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2018
Typearticle
Languageen
FieldNeuroscience
TopicPain Management and Placebo Effect
Canadian institutionsnot available
Fundersnot available
KeywordsPlacebo responsePlaceboNeuropathic painSpinal cord injuryMeta-analysisMedicinePhysical medicine and rehabilitationAnesthesiaPhysical therapySpinal cordPsychologyInternal medicineAlternative medicinePsychiatry
DOInot available

Abstract

fetched live from OpenAlex

Catherine R Jutzeler,1–3 Freda M Warner,1,2 Jacquelyn J Cragg,1,3 Jenny Haefeli,4 J Scott Richards,5 Sven R Andresen,6 Nanna B Finnerup,7,8 Catherine Mercier,9 John LK Kramer1,2 1Faculty of Medicine, ICORD, University of British Columbia, Vancouver, BC, Canada; 2Faculty of Education, School of Kinesiology, University of BC, Vancouver, BC, Canada; 3Faculty of Medicine, Spinal Cord Injury Center, University Hospital Balgrist, University of Zurich, Zurich, Switzerland; 4Weill Institute for Neurosciences, Department of Neurological Surgery, Brain and Spinal Injury Center, University of California, San Francisco, CA, USA; 5Department of Physical Medicine and Rehabilitation, University of Alabama at Birmingham, Birmingham, AL, USA; 6Spinal Cord Injury Centre of Western Denmark, Department of Neurology, Regional Hospital of Viborg, Viborg, Denmark; 7Danish Pain Research Centre, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark; 8Department of Neurology, Aarhus University Hospital, Aarhus, Denmark; 9Center for Interdisciplinary Research in Rehabilitation and Social Integration, Québec, QC, Canada Background: Understanding factors associated with high placebo responses in clinical trials increases the likelihood of detecting a meaningful treatment effect. The aim of the present study was to identify subject-level factors that contribute to placebo variability in patients with neuropathic pain due to spinal cord injury (SCI).Methods: Multiple regression analysis of patient data from randomized, double-blind, placebo-controlled trials (duration >4 weeks) involving individuals with SCI was performed. Patient demographics, as well as injury and pain characteristics were examined for their association with changes in pain rating from baseline to the end of the trial (i.e., placebo response). The overall effect of individual predictors was quantified with meta-analysis statistics.Results: A total of 276 patients with SCI from six studies were included in the analysis. Based on the meta-analysis of subject-level predictors, larger placebo responses were associated with male subjects (β=0.635; standard error [SE]=0.262; p=0.016) and higher baseline pain (β=−0.146; SE=0.073; p=0.044). There were no significant effects for injury characteristics (i.e., severity, level, and time since injury) or pain characteristics (i.e., location and evoked). No significant publication bias was detected.Conclusion: The current meta-analysis of individual patient data demonstrated the importance of sex and baseline pain intensity on changes in pain ratings in the placebo arm of SCI central neuropathic pain randomized controlled clinical trials. Overall, our findings indicate that placebo responses occur independent of injury characteristics. Keywords: placebo response, clinical trial, spinal cord injury, neuropathic pain

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)0.038
metaresearch head score (Gemma)0.073
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.038
Threshold uncertainty score0.201

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0380.073
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0120.033
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0020.000

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 head0.636
GPT teacher head0.591
Teacher spread0.045 · 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 designMeta-analysis
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
Published2018
Admission routes1
Has abstractyes

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