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Record W4401742697 · doi:10.1371/journal.pmed.1004447

A minimum data set—Core outcome set, core data elements, and core measurement set—For degenerative cervical myelopathy research (AO Spine RECODE DCM): A consensus study

2024· article· en· W4401742697 on OpenAlexaff
Benjamin M. Davies, Xiaoyu Yang, Danyal Z. Khan, Oliver Mowforth, Alvaro Yanez Touzet, Aria Nouri, James S. Harrop, Bizhan Aarabi, Vafa Rahimi‐Movaghar, Shekar N. Kurpad, James D. Guest, Lindsay Tetreault, Brian Kwon, Timothy F. Boerger, Ricardo Rodrigues‐Pinto, Julio C. Furlan, Robert Chen, Carl Moritz Zipser, Armin Curt, James Milligan, Sukhivinder Kalsi-Rayn, Ellen Sarewitz, Iwan Sadler, Tammy Blizzard, Caroline Treanor, David Anderson, Nader Fallah, Olesja Hazenbiller, Carla Salzman, Zachary Zimmerman, Anne M. Wandycz, Shirley Widdop, Margaret Reeves, Rye Raine, Sukvinder K. Ryan, Ailish Malone, Ali Gharooni, Jefferson R. Wilson, Allan R. Martin, Michael G. Fehlings, Angus McNair, Mark Kotter

Bibliographic record

VenuePLoS Medicine · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicDelphi Technique in Research
Canadian institutionsPraxis Spinal Cord InstituteMcMaster UniversityToronto Rehabilitation InstituteUniversity Health NetworkUniversity of TorontoInternational Collaboration On Repair DiscoveriesUniversity of British Columbia
FundersCambridge University HospitalsAOSpineAO FoundationUniversity of CambridgeDepartment of Health and Social CareNational Institute for Health and Care Research
KeywordsMedicineDelphi methodSystematic reviewData extractionData setSet (abstract data type)Computer scienceData miningMEDLINEArtificial intelligence

Abstract

fetched live from OpenAlex

BACKGROUND: Degenerative cervical myelopathy (DCM) is a progressive chronic spinal cord injury estimated to affect 1 in 50 adults. Without standardised guidance, clinical research studies have selected outcomes at their discretion, often underrepresenting the disease and limiting comparability between studies. Utilising a standard minimum data set formed via multi-stakeholder consensus can address these issues. This combines processes to define a core outcome set (COS)-a list of key outcomes-and core data elements (CDEs), a list of key sampling characteristics required to interpret the outcomes. Further "how" these outcomes should be measured and/or reported is then defined in a core measurement set (CMS). This can include a recommendation of a standardised time point at which outcome data should be reported. This study defines a COS, CDE, and CMS for DCM research. METHODS AND FINDINGS: A minimum data set was developed using a series of modified Delphi processes. Phase 1 involved the setup of an international DCM stakeholder group. Phase 2 involved the development of a longlist of outcomes, data elements, and formation into domains. Phase 3 prioritised the outcomes and CDEs using a two-stage Delphi process. Phase 4 determined the final DCM minimal data set using a consensus meeting. Using the COS, Phase 5 finalised definitions of the measurement construct for each outcome. In Phase 6, a systematic review of the literature was performed, to scope and define the psychometric properties of measurement tools. Phase 7 used a modified Delphi process to inform the short-listing of candidate measurement tools. The final measurement set was then formed through a consensus meeting (Phase 8). To support implementation, the data set was then integrated into template clinical research forms (CRFs) for use in future clinical trials (Phase 9). In total, 28 outcomes and 6 domains (Pain, Neurological Function, Life Impact, Radiology, Economic Impact, and Adverse Events) were entered into the final COS. Thirty two outcomes and 4 domains (Individual, Disease, Investigation, and Intervention) were entered into the final CDE. Finally, 4 outcome instruments (mJOA, NDI, SF-36v2, and SAVES2) were identified for the CMS, with a recommendation for trials evaluating outcomes after surgery, to include baseline measurement and at 6 months from surgery. CONCLUSIONS: The AO Spine RECODE-DCM has produced a minimum data set for use in DCM clinical trials today. These are available at https://myelopathy.org/minimum-dataset/. While it is anticipated the CDE and COS have strong and durable relevance, it is acknowledged that new measurement tools, alongside an increasing transition to study patients not undergoing surgery, may necessitate updates and adaptation, particularly with respect to the CMS.

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)0.030
metaresearch head score (Gemma)0.018
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.333
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0300.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0030.003
Research integrity0.0000.001
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 head0.883
GPT teacher head0.620
Teacher spread0.263 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations15
Published2024
Admission routes1
Has abstractyes

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