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Record W2892145935 · doi:10.1097/htr.0000000000000427

Why Do We Need a New Clinical Practice Guideline for Moderate to Severe Traumatic Brain Injury?

2018· article· en· W2892145935 on OpenAlexaffabout
Bonnie Swaine, Mark Bayley, Shawn Marshall, Ailene Kua, Pascale Marier-Deschênes, Anne-Sophie Allaire, Corinne Kagan, Catherine Truchon, Shannon Janzen, Robert Teasell, Marie‐Ève Lamontagne

Bibliographic record

VenueJournal of Head Trauma Rehabilitation · 2018
Typearticle
Languageen
FieldMedicine
TopicClinical practice guidelines implementation
Canadian institutionsUniversité de MontréalUniversité LavalInstitut National d'Excellence en Santé et en Services SociauxOntario Neurotrauma FoundationUniversity Health NetworkOttawa HospitalUniversity of OttawaSt Joseph's Health CareUniversity of TorontoToronto Rehabilitation InstituteLawson Health Research InstituteCentre for Interdisciplinary Research in Rehabilitation
Fundersnot available
KeywordsGuidelineRehabilitationConsistency (knowledge bases)Acquired brain injuryImplementationProcess (computing)Traumatic brain injuryHealth careMedicinePerceptionClinical PracticeQuality (philosophy)Process managementNursingPsychologyMedical educationComputer sciencePhysical therapyBusinessPsychiatryPolitical sciencePathology

Abstract

fetched live from OpenAlex

OBJECTIVE: Clinical practice guidelines (CPGs) aim to improve quality and consistency of healthcare services. A Canadian group of researchers, clinicians, and policy makers developed/adapted a CPG for rehabilitation post-moderate to severe traumatic brain injury (MSTBI) to respond to end users' needs in acute care and rehabilitation settings. METHODS: The rigorous CPG development process began assessing needs and expectations of end users, then appraised existing CPGs, and, during a consensus conference, produced fundamental and priority recommendations. We also surveyed end users' perceptions of implementation gaps to determine future implementation strategies to optimize adherence to the CPG. RESULTS: The unique bilingual (French and English) CPG consists of 266 recommendations (of which 126 are new recommendations), addressing top priorities for MSTBI, rationale, process indicators, and implementations tools (eg, algorithms and benchmarks). CONCLUSION: The novel approach of consulting and working with end users to develop a CPG for MSTBI should influence knowledge uptake for clinicians wanting to provide evidence-based care.

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)0.011
metaresearch head score (Gemma)0.122
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: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.553
Threshold uncertainty score0.898

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.122
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.213
GPT teacher head0.549
Teacher spread0.336 · 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.

Study designNot applicable
Domainnot available
GenreMethods

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

Citations3
Published2018
Admission routes2
Has abstractyes

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