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Record W4385214936 · doi:10.1002/ana.26740

Feasibility and Validity of the Coma Recovery Scale‐Revised for Accelerated Standardized Testing: A Practical Assessment Tool for Detecting Consciousness in the Intensive Care Unit

2023· article· en· W4385214936 on OpenAlexaff
Yelena G. Bodien, Isha Vora, Alice Barra, Kevin C.H. Chiang, Camille Chatelle, Kelsey Goostrey, Géraldine Martens, Christopher Malone, Jennifer Mello, Kristin Parlman, Jessica Ranford, Ally Sterling, Abigail B. Waters, Ronald E. Hirschberg, Douglas I. Katz, Nicole Mazwi, Pengsheng Ni, George C. Velmahos, Karen Waak, Brian L. Edlow, Joseph T. Giacino

Bibliographic record

VenueAnnals of Neurology · 2023
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsUniversité de Montréal
FundersHORIZON EUROPE Marie Sklodowska-Curie ActionsNational Center for Chronic Disease Prevention and Health PromotionNational Institute of Neurological Disorders and StrokeWallonie-Bruxelles InternationalAdministration for Community LivingFédération Wallonie-BruxellesEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentU.S. Department of DefenseEuropean CommissionNational Institute on Disability, Independent Living, and Rehabilitation ResearchNational Metal and Materials Technology CenterTiny Blue Dot FoundationGE FoundationAustralian GovernmentU.S. Department of Health and Human ServicesNational Institutes of HealthHorizon 2020 Framework ProgrammeJames S. McDonnell Foundation
KeywordsGlasgow Coma ScaleComa (optics)Intensive care unitScale (ratio)MedicinePsychologyIntensive care medicinePsychiatry

Abstract

fetched live from OpenAlex

We developed and validated an abbreviated version of the Coma Recovery Scale-Revised (CRS-R), the CRS-R For Accelerated Standardized Testing (CRSR-FAST), to detect conscious awareness in patients with severe traumatic brain injury in the intensive care unit. In 45 consecutively enrolled patients, CRSR-FAST administration time was approximately one-third of the full-length CRS-R (mean [SD] 6.5 [3.3] vs 20.1 [7.2] minutes, p < 0.0001). Concurrent validity (simple kappa 0.68), test-retest (Mak's ρ = 0.76), and interrater (Mak's ρ = 0.91) reliability were substantial. Sensitivity, specificity, and accuracy for detecting consciousness were 81%, 89%, and 84%, respectively. The CRSR-FAST facilitates serial assessment of consciousness, which is essential for diagnostic and prognostic accuracy. ANN NEUROL 2023;94:919-924.

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)0.010
metaresearch head score (Gemma)0.043
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.043
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.505
GPT teacher head0.508
Teacher spread0.003 · 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

Citations51
Published2023
Admission routes1
Has abstractyes

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