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Record W3170865046 · doi:10.1017/cjn.2021.127

Canadian Stroke Best Practice Recommendations: Secondary Prevention of Stroke Update 2020

2021· review· en· W3170865046 on OpenAlexafffundvenueabout
David J. Gladstone, M. Patrice Lindsay, James D. Douketis, Eric E. Smith, Dar Dowlatshahi, Theodore Wein, Aline Bourgoin, Jafna L. Cox, John Falconer, Brett Graham, Marilyn Labrie, Lena McDonald, Jennifer Mandzia, Daniel Ngui, Paul Pageau, Amanda Rodgerson, William Semchuk, Tammy Tebbutt, Carmen Tuchak, Stephen van Gaal, Karina Villaluna, Norine Foley, Shelagh B. Coutts, Anita Mountain, Gord Gubitz, Jacob A. Udell, Rebecca McGuff, Manraj K.S. Heran, Pascale Lavoie, Alexandre Y. Poppe

Bibliographic record

VenueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques · 2021
Typereview
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsHôpital de l'Enfant-JésusUniversity of AlbertaRegional Municipality of WaterlooQueen Elizabeth II Health Sciences CentreUniversity of TorontoWestern UniversityCentre Hospitalier de l’Université de MontréalUniversité LavalUniversity of SaskatchewanHeart and Stroke FoundationUniversity of British Columbia, Okanagan CampusYukon UniversityUniversity of British ColumbiaDalhousie UniversityMcGill University Health CentreUniversity of OttawaSt Martha's Regional HospitalUniversity of CalgaryMcMaster UniversityOntario Stroke NetworkSunnybrook Health Science CentreOttawa HospitalHealth Sciences Centre
FundersAllerganIpsenNova Scotia Health Research FoundationCanadian Association of Emergency PhysiciansBiogenPfizerCanadian Stroke ConsortiumResearch Nova ScotiaUniversity of PennsylvaniaSanofiServierCanadian Institutes of Health ResearchWomen's College Hospital
KeywordsMedicineStroke (engine)Intensive care medicinePatent foramen ovaleAtrial fibrillationTriageGuidelineAntithromboticPhysical therapyMedical emergencyInternal medicineMigraine

Abstract

fetched live from OpenAlex

The 2020 update of the Canadian Stroke Best Practice Recommendations (CSBPR) for the Secondary Prevention of Stroke includes current evidence-based recommendations and expert opinions intended for use by clinicians across a broad range of settings. They provide guidance for the prevention of ischemic stroke recurrence through the identification and management of modifiable vascular risk factors. Recommendations address triage, diagnostic testing, lifestyle behaviors, vaping, hypertension, hyperlipidemia, diabetes, atrial fibrillation, other cardiac conditions, antiplatelet and anticoagulant therapies, and carotid and vertebral artery disease. This update of the previous 2017 guideline contains several new or revised recommendations. Recommendations regarding triage and initial assessment of acute transient ischemic attack (TIA) and minor stroke have been simplified, and selected aspects of the etiological stroke workup are revised. Updated treatment recommendations based on new evidence have been made for dual antiplatelet therapy for TIA and minor stroke; anticoagulant therapy for atrial fibrillation; embolic strokes of undetermined source; low-density lipoprotein lowering; hypertriglyceridemia; diabetes treatment; and patent foramen ovale management. A new section has been added to provide practical guidance regarding temporary interruption of antithrombotic therapy for surgical procedures. Cancer-associated ischemic stroke is addressed. A section on virtual care delivery of secondary stroke prevention services in included to highlight a shifting paradigm of care delivery made more urgent by the global pandemic. In addition, where appropriate, sex differences as they pertain to treatments have been addressed. The CSBPR include supporting materials such as implementation resources to facilitate the adoption of evidence into practice and performance measures to enable monitoring of uptake and effectiveness of recommendations.

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)0.054
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: Not applicable
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.140
Threshold uncertainty score0.305

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.054
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.004
Bibliometrics0.0070.009
Science and technology studies0.0040.001
Scholarly communication0.0050.003
Open science0.0070.003
Research integrity0.0070.010
Insufficient payload (model declined to judge)0.0530.027

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 head0.055
GPT teacher head0.346
Teacher spread0.291 · 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

Citations162
Published2021
Admission routes4
Has abstractyes

Explore more

Same venueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences NeurologiquesSame topicAcute Ischemic Stroke ManagementFrench-language works237,207