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Record W3111139944 · doi:10.1002/alz.045709

Stroke memory rehabilitation (SMaRT) programme for mild ischemic stroke: Preliminary findings

2020· article· en· W3111139944 on OpenAlexaboutno aff
Angeline Ong, Fennie Wong, Sheng Chun Ng, Man Qing Leong, Esther Vanessa Chua, Nagaendran Kandiah

Bibliographic record

VenueAlzheimer s & Dementia · 2020
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsnot available
Fundersnot available
KeywordsStroke (engine)Cognitive rehabilitation therapyRehabilitationMoodMedicineCognitionPhysical therapyMontreal Cognitive AssessmentNeuropsychologyBonferroni correctionQuality of life (healthcare)Physical medicine and rehabilitationCognitive impairmentClinical psychologyPsychiatry

Abstract

fetched live from OpenAlex

Abstract Background There are 6000‐7000 stroke survivors yearly in Singapore with about 40% being at risk for post‐stroke cognitive impairment (PSCI). Stroke Memory Rehabilitation (SMaRT) programme was designed to reduce the incidence of PSCI, facilitate transition back to the community, improve the mood and quality of life of patients with mild ischemic strokes. We report the preliminary outcomes of the program. Method Participants who attended the programme from April 2018 to Dec 2019 were included in this study. Each patient attended 8 two‐hour sessions over 8 weeks, focusing on cognitive processes (episodic memory, executive function and visuospatial function); healthy lifestyle habits, relaxation techniques and goal setting. All patients were administered neuropsychological assessments and questionnaires pre‐programme, 8 weeks and 6 months post‐programme. Paired sample t‐tests were applied to evaluate the changes in scores over the four time points on each outcome measure, subject to Bonferroni correction for family‐wise errors. Result 156 participants (mean age=63.53 years, SD=9.63; mean education=9.95 years SD=4.18, 65.4 % male). Significant improvements in all outcome measures were observed from pre‐programme to all other time points. Cognitive scores significantly improved from pre to post‐programme and pre to 6 months post‐programme on the Montreal Cognitive Assessment (24.52 to 25.36; p<.001 and 25.05 to 25.98; p<.001 respectively); Visual Cognitive Assessment Test (VCAT) Score (22.67 to 24.14; p<.001 and 22.63 to 24.92; p<.001). Scores for Trail Making Test‐A only significantly shortened from pre‐ to 6 months post‐programme (52.00 to 45.52; p<.001). Depression levels significantly reduced on the Geriatric Depression Scale (4.01 to 3.29; p=.001 and 3.46 to 2.33; p<.001). Activities of daily living measured on the NEADL significantly improved (52.24 to 55.15; p<.001 and 52.48 to 56.27; p<.001). Quality of life (DemQOL) also significantly improved (88.77 to 91.88; p=.006 and 91.83 to 95.52; p<.001). Conclusion Preliminary findings demonstrate encouraging improvement in global cognition, executive function, quality of life, depression and activities of daily living from pre‐programme to 8 weeks and 6 months post‐programme. A multi‐approach structured cognitive rehabilitation programme for stroke survivors may thus be useful in preventing post‐stroke dementia.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.032
GPT teacher head0.284
Teacher spread0.252 · 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 designObservational
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

Citations0
Published2020
Admission routes1
Has abstractyes

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