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Record W4389266167 · doi:10.1016/j.eclinm.2023.102340

Developing consensus on core outcome sets of domains for acute, the transition from acute to chronic, recurrent/episodic, and chronic pain: results of the INTEGRATE-pain Delphi process

2023· article· en· W4389266167 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEClinicalMedicine · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicDelphi Technique in Research
Canadian institutionsUniversity of Ottawa
FundersNational Institutes of HealthInnovative Medicines InitiativeInnovative Health InitiativeSaluda MedicalMerz PharmaceuticalsEuropean Federation of Pharmaceutical Industries and AssociationsVertex PharmaceuticalsAsahi Kasei Pharma CorporationStowers Institute for Medical ResearchF. Hoffmann-La RocheEli Lilly and CompanyPfizerHexal AGAlnylam PharmaceuticalsBundesministerium für Bildung und ForschungNational Institute for Health and Care ResearchTeva Pharmaceutical IndustriesBayer HealthCareEuropean CommissionGemeinsame BundesausschussEsteve PharmaceuticalsSanofiDeutsche ForschungsgemeinschaftGlaxoSmithKlineGedeon RichterBayer
KeywordsHarmonizationDelphi methodMedicineMultidisciplinary approachChronic painDelphiQuality of life (healthcare)Physical therapyNursingArtificial intelligenceComputer science

Abstract

fetched live from OpenAlex

Background: Pain is the leading cause of disability worldwide among adults and effective treatment options remain elusive. Data harmonization efforts, such as through core outcome sets (COS), could improve care by highlighting cross-cutting pain mechanisms and treatments. Existing pain-related COS often focus on specific conditions, which can hamper data harmonization across various pain states. Methods: to measure) that transcend pain conditions within different pain categories. We hosted a meeting to assess the need for these four COS in pain research and clinical practice. Potential COS domains/subdomains were identified via a systematic literature review (SLR), meeting attendees, and Delphi participants. We conducted an online, three step Delphi process to reach a consensus on domains to be included in the four final COS. Survey respondents were identified from the SLR and pain-related social networks, including multidisciplinary health care professionals, researchers, and people with lived experience (PWLE) of pain. Advisory boards consisting of COS experts and PWLE provided advice throughout the process. Findings: Domains in final COS were generally related to aspects of pain, quality of life, and physical function/activity limitations, with some differences among pain categories. This effort was the first to generate four separate, overarching COS to encourage international data harmonization within and across different pain categories. Interpretation: The adoption of the COS in research and clinical practice will facilitate comparisons and data integration around the world and across pain studies to optimize resources, expedite therapeutic discovery, and improve pain care. Funding: Innovative Medicines Initiative 2 Join Undertaking; European Union Horizon 2020 research innovation program, European Federation of Pharmaceutical Industries and Associations (EFPIA) provided funding for IMI-PainCare. RDT acknowledges grants from Esteve and TEVA.

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.

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)0.015
metaresearch head score (Gemma)0.013
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.526
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0150.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.265
GPT teacher head0.531
Teacher spread0.266 · 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