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Record W2747858746 · doi:10.1177/1747493017727338

Where to now? AVERT answered an important question, but raised many more

2017· review· en· W2747858746 on OpenAlexaff
Mark Bayley, Audrey Bowen, Coralie English, Robert Teasell, Janice J. Eng

Bibliographic record

VenueInternational Journal of Stroke · 2017
Typereview
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsGF Strong Rehabilitation CentreUniversity of British ColumbiaWestern UniversityLawson Health Research InstituteToronto Rehabilitation InstituteUniversity of TorontoUniversity Health Network
FundersNational Institute for Health and Care Research
KeywordsMedicineStroke (engine)Randomized controlled trialRehabilitationClinical trialMobilizationPhysical therapyStroke recoveryAcute strokePhysical medicine and rehabilitationIntensive care medicineNursingSurgery

Abstract

fetched live from OpenAlex

A Very Early Rehabilitation Trial (AVERT) was a Phase 3 randomized trial with over 2100 subjects post stroke that had unexpected results with better outcomes for usual care than those receiving very early mobilization. This review of published stroke clinical practice guidelines highlights that recommendations for mobilization have changed after publication of AVERT but also that developers have struggled to provide recommendations for appropriate dose, duration and intensity of mobilization in the acute post stroke period with available analyses from AVERT and other literature. This review highlights the priority research questions about early rehabilitation post stroke that need to be addressed through future large scale randomized controlled trials.

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)0.006
metaresearch head score (Gemma)0.030
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.008
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.030
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0020.005
Open science0.0010.001
Research integrity0.0040.008
Insufficient payload (model declined to judge)0.0080.002

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 head0.048
GPT teacher head0.396
Teacher spread0.347 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations11
Published2017
Admission routes1
Has abstractyes

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