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Record W2896150264 · doi:10.1161/str.49.suppl_1.wp142

Abstract WP142: Baseline and Demographic Factors Associated With Improvements in Physical Activity, Cognition and Mood: Preliminary Data from the Bugher Foundation’s Stroke and Exercise Study

2018· article· en· W2896150264 on OpenAlexaboutno aff
Barbara Junco, Eduard Tiozzo, Marti Flothmann, Lucas C. Lages, Andrew Yu, Nathalie Chang, Frank De La Cruz, Anabel Ruiz, Marialaura Simonetto, Carolina M Gutierrez, Chunhai Dong, Tatjana Rundek, David Loewenstein, Ralph L. Sacco, Sebastian Koch

Bibliographic record

VenueStroke · 2018
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePhysical therapyStroke (engine)WaistMontreal Cognitive AssessmentMoodCognitionInternal medicineBody mass indexPhysical medicine and rehabilitationCognitive impairmentClinical psychologyPsychiatry

Abstract

fetched live from OpenAlex

Background: The Bugher Stroke and Exercise Study examines the impact of a structured exercise and cognitive training program after stroke. In this preliminary analysis we investigated baseline predictors and demographics related to physical, cognitive and affective improvements. Methods: Participants with recent stroke and limited physical activity ≥ 3 months prior to enrollment were randomized to one of two arms of a 3-month intervention. Arm 1 (N=62) received exercise (strength & cardiovascular) and cognitive training. Arm 2 (N=35) received light stretching and sham cognitive training. Outcome measures included depression (CES-D), cognition (MoCA), stroke impact scale (SIS), impairment (NIHSS), degree of disability (mRS), and physical measures of hand grip (HG), time up and go (TUG), 30-second chair stand test, 6-minute walk, waist circumference, BMI and blood pressure (BP). The trial is ongoing, therefore treatment group comparisons were not available. T-tests evaluated change in outcome measures among all participants. Regression analyses evaluated demographic variables and baseline factors (i.e., time-since-stroke, ischemic vs. hemorrhagic, & pre-stroke physical activity) associated with change in outcome measures. Results: To date, 97 participants were enrolled ( M age 59±11 years; 34% women; 53% white, 49% Hispanic, 39% black & 7% other). Participants demonstrated significant improvement on the CES-D (p=.005), MoCA (p=.005), NIHSS (p<.001), SIS (p=.015), mRS (p<.001), HG (p=.002), TUG (p=.004), 30-second chair (p<.001), 6-minute walk (p=.001), waist circumference (p=.010), and both systolic (p=.009) and diastolic (p<.001) BP. Regression analyses revealed that older adults were less likely to improve in MoCA scores (p=.010), 6-minute walk (p=.041), and systolic BP (p=.032). Participants with more pre-stroke physical activity demonstrated greater improvement in 6-minute walk (p=.024). Black participants saw less decline in systolic BP (p=.033) while participants with hemorrhagic (vs. ischemic) stroke saw less decline in diastolic BP (p=.039). Conclusions: Participation in an exercise and cognitive training intervention benefit stroke survivors; however, improvement may depend on baseline and demographic factors.

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)0.003
metaresearch head score (Gemma)0.004
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 score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.039
GPT teacher head0.311
Teacher spread0.271 · 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
Published2018
Admission routes1
Has abstractyes

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