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Record W1955624635 · doi:10.5770/cgj.18.166

Is Cardiac Rehabilitation Exercise Feasible for People with Mild Cognitive Impairment?

2015· article· en· W1955624635 on OpenAlexafffundvenue
Brittany Intzandt, Sandra E. Black, Krista L. Lanctôt, Nathan Herrmann, Paul Oh, Laura E. Middleton

Bibliographic record

VenueCanadian Geriatrics Journal · 2015
Typearticle
Languageen
FieldMedicine
TopicCardiac Health and Mental Health
Canadian institutionsSunnybrook Health Science CentreSunnybrook HospitalUniversity of Waterloo
FundersUniversity of Waterloo
KeywordsMedicineRehabilitationPhysical therapyCognitive impairmentDementiaPhysical medicine and rehabilitationCognitionPsychiatryDiseaseInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Exercise is a promising strategy to prevent dementia, but no clinically supervised exercise program is widely available to people with mild cognitive impairment (MCI). The objective was to survey health professionals to assess the feasibility of using cardiac rehabilitation exercise programs for MCI populations. METHODS: We distributed surveys to: 1) health professionals working in cardiac rehabilitation exercise programs (36/72 responded); and 2) physicians who treat MCI (22/32 responded). Questions addressed clinician and clinic characteristics and feasibility of referring and accommodating people with MCI. RESULTS: Most cardiac rehabilitation exercise programs currently treat people with MCI (61.1%). Nearly all were willing and able to accept people with MCI and comorbid vascular risk (91.7%), though only a minority could accept MCI without vascular risk (16.7%). Although most physicians recommend exercise to people with MCI (63.6%), few referred patients with MCI to programs or people to guide exercise (27.3%). However, all physicians (100%) would refer patients with MCI to a cardiac rehabilitation exercise program. CONCLUSIONS: Our study supports cardiac rehabilitation exercise programs as a feasible model of exercise for patients with MCI with vascular risk. Patients with and without vascular risk could likely be accommodated if program mandates were expanded.

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 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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.271
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.025
GPT teacher head0.314
Teacher spread0.289 · 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 teacher head, 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

Citations15
Published2015
Admission routes3
Has abstractyes

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