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Record W2609084689 · doi:10.1177/1747493017706239

Canadian Stroke Best Practice Recommendations: Telestroke Best Practice Guidelines Update 2017

2017· article· en· W2609084689 on OpenAlexaffabout
Dylan Blacquière, M. Patrice Lindsay, Norine Foley, Colleen Taralson, Susan Alcock, Catherine Balg, Sanjit K. Bhogal, Julie Cole, Marsha Eustace, Patricia M. Gallagher, Antoinette Ghanem, Alexander Hoechsmann, Gary Hunter, Khurshid Khan, Alier Marrero, Brian Moses, Kelley Rayner, Andrew J. W. Samis, Elisabeth Smitko, Marilyn Vibe, Gord Gubitz, Dar Dowlatshahi, Stephen Phillips, Frank L. Silver

Bibliographic record

VenueInternational Journal of Stroke · 2017
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsUniversity of TorontoUniversity of SaskatchewanQueen Elizabeth II Health Sciences CentreOntario Stroke NetworkCARE CanadaQueen's UniversitySt. John’s Health Sciences CentreDr. Georges-L.-Dumont University Hospital CentreUniversity Health NetworkUniversity of AlbertaDalhousie UniversityUniversity of OttawaHealth PEIMcGill UniversityManitoba HealthUniversité LavalOttawa HospitalCapital District Health AuthorityUniversity of Alberta HospitalYukon UniversityIsland HealthWestern UniversityNova Scotia HospitalHeart and Stroke FoundationSaint John Regional Hospital
Fundersnot available
KeywordsMedicineTelemedicineRehabilitationStroke (engine)GuidelineBest practiceMedical emergencyHealth careAcute strokeMEDLINETelehealthMultidisciplinary approachIntensive care medicinePhysical therapyNursingEmergency department

Abstract

fetched live from OpenAlex

Every year, approximately 62,000 people with stroke and transient ischemic attack are treated in Canadian hospitals. The 2016 update of the Canadian Stroke Best Practice Recommendations Telestroke guideline is a comprehensive summary of current evidence-based and consensus-based recommendations appropriate for use by all healthcare providers and system planners who organize and provide care to patients following stroke across a broad range of settings. These recommendations focus on the use of telemedicine technologies to rapidly identify and treat appropriate patients with acute thrombolytic therapies in hospitals without stroke specialized expertise; select patients who require to immediate transfer to stroke centers for Endovascular Therapy; and for the patients who remain in community hospitals to facilitate their care on a stroke unit and provide remote access to stroke prevention and rehabilitation services. While these latter areas of Telestroke application are newer, they are rapidly developing, with new opportunities that are yet unrealized. Virtual rehabilitation therapies offer patients the opportunity to participate in rehabilitation therapies, supervised by physical and occupational therapists. While not without its limitations (e.g., access to telecommunications in remote areas, fragmentation of care), the evidence-to-date sets the foundation for improving access to care and management for patients during both the acute phase and now through post stroke recovery.

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)0.001
metaresearch head score (Gemma)0.025
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: Empirical · Consensus signal: none
Teacher disagreement score0.731
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.025
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0000.001
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 head0.052
GPT teacher head0.415
Teacher spread0.363 · 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
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

Citations80
Published2017
Admission routes2
Has abstractyes

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