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Record W3203561161 · doi:10.4088/pcc.21nr02919

The Emerging Role of Telestroke in the Middle East and North Africa Region in the Era of COVID-19

2021· article· en· W3203561161 on OpenAlex
Rizwana Shahid, Hosam Al-Jehani, Azra Zafar, Maher Saqqur

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe Primary Care Companion For CNS Disorders · 2021
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsUniversity of AlbertaMcGill UniversityMontreal Neurological Institute and Hospital
Fundersnot available
KeywordsPandemicCoronavirus disease 2019 (COVID-19)Stroke (engine)Middle EastTelemedicineMedicineMedical emergencyAcute strokeIntensive care medicineDiseaseHealth careGeographyEmergency departmentInfectious disease (medical specialty)Economic growthNursingInternal medicineEngineering

Abstract

fetched live from OpenAlex

Stroke is the second most common cause of death worldwide. It is a medical emergency demanding immediate recognition to provide time-sensitive acute management. The coronavirus disease 2019 (COVID-19) pandemic has challenged acute stroke care, and alternate models of treatment are needed. Telestroke is well proven as a valid tool for acute stroke assessment and has been utilized successfully to manage patients remotely in many parts of the world, though it is underutilized in the Middle East and North Africa region. Given the challenges associated with the COVID-19 pandemic, such as risk of physician exposure to infection, implementation of a telestroke system is critical to provide consultant stroke physician coverage. This article provides a proposed model for coordinated telestroke. Implementation of telestroke in the Middle East and North Africa region and other underdeveloped areas will optimize stroke management, especially during the COVID-19 era.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.182
Threshold uncertainty score0.282

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.037
GPT teacher head0.246
Teacher spread0.210 · 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