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Record W2727852128 · doi:10.1093/geroni/igx004.1678

MOTOR-COGNITIVE TRAINING IMPROVES BALANCE AND COGNITION OF PATIENTS WITH PARKINSON’S DISEASE

2017· article· en· W2727852128 on OpenAlexaboutno aff
J.R. Bacha, K.G. Silva, Tatiana Beline de Freitas, Grace Angélica de Oliveira Gomes, Larissa Alamino Pereira de Viveiro, Eliana Maria Varise, Camila Torriani‐Pasin, José Eduardo Pompeu

Bibliographic record

VenueInnovation in Aging · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicPhysical Education and Gymnastics
Canadian institutionsnot available
Fundersnot available
KeywordsBalance (ability)Montreal Cognitive AssessmentCognitionGaitPhysical therapyTimed Up and Go testMedicineBerg Balance ScaleDynamic balanceTest (biology)Physical medicine and rehabilitationAerobic exercisePsychologyCognitive impairmentPsychiatry

Abstract

fetched live from OpenAlex

Objective: To investigate the effects of motor-cognitive training on individuals with Parkinson disease (PD) compared with community dwelling elderly. Method: This is a randomized clinical trial, in which participated five elderly people [mean age 68.3 (2.03) years] and five patients with idiopathic PD [mean age 67.7 (2.1) years, stages 1–3 in the Hoehn and Yahr scale]. Participants underwent 14 training sessions of one hour of duration each one, twice a week. Training was conducted in groups with a maximum of five elderlies. The program included challenging exercises for balance and cognition, including warming up, strengthening, flexibility, aerobic training, gait, balance and transfer training. Participants were assessed pre and post-test and after 30 days [follow-up (FU)]. Cognition and balance were assessed by the Montreal Cognitive Assessment (MoCA) and Mini-Balance Evaluation Systems Test (Mini-BESTest), respectively. Study was registered in Brazilian Registry of Clinical Trials (RBR-27kqv5). Results: Both groups showed improvement on balance and cognition post-test with maintenance of its effects on the FU. However, this improvement was substantial in the elderly group, but there was is not difference between groups. The mean (SD) scores in scales evaluated in the elderly were: Mini-BESTest were: 26.9 ± 3.4 (pre-test), 29.4 ± 3.7 (post-test) and 28.7 ± 2.8 (FU); MoCA were 24.0 ± 5.2 (pre-test), 26.7 ± 3.3 (post-test) and 26.9 ± 4.4 (FU). The mean (SD) scores of PD patients on Mini-BESTest were: 24.0 ± 3.9 (pre-test), 24.4 ± 4.1 (post-test) and 26.3 ± 3.7 (FU); MoCA were 21.3 ± 4.5 (pre-test), 23.6 ± 5.5 (post-test) and 23.4 ± 4.5 (FU). Conclusion: The proposed intervention promoted improvement on balance and cognition in PD patients and community dwelling elderly.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.082
Threshold uncertainty score0.187

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0000.000
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 head0.031
GPT teacher head0.328
Teacher spread0.297 · 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

Citations0
Published2017
Admission routes1
Has abstractyes

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