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Record W4408370625 · doi:10.1177/23969873251323171

Feasibility of telephone and computerized cognitive testing as a secondary outcome in an acute stroke clinical trial: A mixed methods sub-study of the AcT Trial

2025· article· en· W4408370625 on OpenAlex
Sajeevan Sujanthan, Pugaliya Puveendrakumaran, Katie N. Dainty, Morgan D. Barense, Krista L. Lanctôt, Adrian M. Owen, Nishita Singh, Brian Buck, Houman Khosravani, Shelagh B. Coutts, Mohammed Almekhlafi, Ramana Appireddy, Aleksander Tkach, Jennifer Mandzia, Heather Williams, Thalia S. Field, Alejandro Manosalva, Muzaffar Siddiqui, Gary R. Hunter, MacKenzie Horn, Fouzi Bala, Michael D. Hill, Michel Shamy, Aravind Ganesh, Tolulope T. Sajobi, Bijoy K. Menon, Richard H. Swartz

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.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueEuropean Stroke Journal · 2025
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsUniversity of OttawaUniversity of SaskatchewanMedicine Hat Regional HospitalUniversity of British ColumbiaLondon Health Sciences CentreInstitute of Health Services and Policy ResearchQueen's UniversityInstitute for Work & HealthUniversity of CalgaryGrey Nuns Community HospitalUniversity of AlbertaUniversity of TorontoWestern UniversityBaycrest HospitalSunnybrook Health Science CentreKelowna General HospitalUniversity of Manitoba
FundersCanadian Institutes of Health Research
KeywordsMontreal Cognitive AssessmentMedicineConfidence intervalTelephone interviewLogistic regressionQuality of life (healthcare)Stroke (engine)CognitionPhysical therapyCognitive testGerontologyCognitive impairmentInternal medicinePsychiatry

Abstract

fetched live from OpenAlex

Abstract Introduction Post-stroke cognitive impairment is associated with impaired quality of life. Remote testing provides a potential avenue to measure cognitive outcomes efficiently. Patients and Methods Prospective cognitive outcomes were collected at 90–180 days using both telephone MoCA (T-MoCA; range 0–22; <17 impairment) and Creyos, a computerized cognitive battery. Key variables associated with completion were assessed using logistic regressions. Mixed methods brief structured interviews and exit survey were performed to explore barriers to completing computer testing. Results Of 791 potentially eligible patients (mean age 70 ± 14 years), there was low feasibility of remote cognitive testing, with only 401 (51%) completing the T-MoCA, and 242 (31%) completing Creyos. Our regression models show that age (ORT-MoCA: 0.95 (95% Confidence Interval (CI): 0.94–0.97); ORCreyos: 0.95 (95% CI: 0.94–0.96)), functional impairment (mRS 2–5; ORT-MoCA: 0.55 (95% CI: 0.37–0.81); ORCreyos: 0.66 (95% CI: 0.44–0.98)), quality of life (EQ-VAS; ORT-MoCA: 1.02 (95% CI: 1.01–1.03); ORCreyos: OR:1.02 (95% CI: 1.01–1.03)) and length of hospital stay (ORT-MoCA: 0.98 (95% CI: 0.96–0.99); ORCreyos: 0.97 (95% CI: 0.94–0.99)) predicted both telephone and computer cognitive test completion; computer literacy predicted computer test completion (ORCreyos: 1.12 (95% CI: 1.04–1.21)). In interviews, a preference for accessibility of computerized testing was reported. Discussion Remote cognitive testing has limited feasibility as a secondary outcome in large acute stroke trials. Patients who are older, with worse quality of life, or severe functional impairment post-stroke are less likely to complete remote cognitive outcomes. Conclusion Innovative approaches to post-stroke cognitive outcomes in acute stroke trials are needed. Data Access Data available upon request.

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)0.009
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation 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 score0.154
Threshold uncertainty score0.872

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.138
GPT teacher head0.459
Teacher spread0.321 · 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