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Record W4390201418 · doi:10.1002/alz.080413

Baseline Cognitive Performance Is a Determinant of Prospective Health Resource Utilization Among Adults with Chronic Stroke: A Secondary Analysis

2023· article· en· W4390201418 on OpenAlexaffabout
Jennifer C. Davis, Cassandra Adjetey, Janice J. Eng, Ryan S. Falck, Elizabeth Dao, John R. Best, Kimberly Bennett, Katherine McGuire, Ging‐Yuek Robin Hsiung, Laura E. Middleton, Peter A. Hall, Teresa Liu‐Ambrose

Bibliographic record

VenueAlzheimer s & Dementia · 2023
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsCenter for Diagnosis and Research on Alzheimer's DiseaseUniversity of WaterlooOkanagan University CollegeVancouver Coastal HealthUniversity of British Columbia, Okanagan CampusSimon Fraser UniversityKelowna General HospitalInternational Collaboration On Repair DiscoveriesUniversity of British Columbia
Fundersnot available
KeywordsRandomized controlled trialMedicineGerontologyCognitive declineCognitionStroke (engine)Quality of life (healthcare)Physical therapyEffects of sleep deprivation on cognitive performanceProspective cohort studyDementiaPhysical medicine and rehabilitationDiseasePsychiatryInternal medicine

Abstract

fetched live from OpenAlex

Abstract Background Cognitive impairment is a costly public health problem globally. Among older adults with chronic stroke, the literature is devoid of prospective data that identify factors responsible for driving health care resource utilization. This study aimed to ascertain key determinants of health resource utilization (HRU) at 6 and 12 months among older adults with chronic stroke. Method This study was a secondary prospective analysis of an economic evaluation conducted alongside the Vitality study, a 6‐month randomized controlled trial with a 6‐month follow‐up which included 120 community‐dwelling adults with chronic stroke, aged 55 years and older. Participants were randomized into 1) exercise (EX) or 2) cognitive and social enrichment activities (ENRICH), or 3) stretching and toning program (BAT) (i.e., control group/ comparator). The primary outcome measure of the randomized controlled trial was the Alzheimer’s Disease Assessment Scale‐Cognitive‐Plus (ADAS‐Cog‐Plus), a global measure of cognitive performance using multidimensional item response theory. We constructed two linear regression models with HRU at 6 and 12 months as the dependent variables for each model, respectively. Predictors relating to mobility, quality of life, global cognition and executive functions were examined. Age, sex, comorbidities, and group allocation (i.e., EX, ENRICH or BAT) were included regardless of statistical significance. Costs were reported in 2022 Canadian Dollars. Result The ADAS‐Cog Plus was a significant determinant of total HRU at 6 months (intervention cessation; p = 0.001) and 12‐months (6‐month followup; p = 0.004). Conclusion The ADAS‐Cog Plus, a measure of cognitive performance, was a significant determinant of HRU at 6 and 12 months among older adults with chronic stroke. This highlights the importance of interventions aimed at combating cognitive decline to minimize health care resource among individuals with chronic stroke.

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)0.004
metaresearch head score (Gemma)0.007
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.006
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
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 head0.018
GPT teacher head0.288
Teacher spread0.270 · 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
Published2023
Admission routes2
Has abstractyes

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