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Abstract 16684: Cardiovascular Responses of Persons With ABI to Computerized Motor-Cognitive Assessments

2018· article· en· W4395037266 on OpenAlexaboutno aff
Denise Gobert, Sarah E. Edmiston

Bibliographic record

VenueCirculation · 2018
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Syncope and Autonomic Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCognitionPhysical medicine and rehabilitationPsychiatry

Abstract

fetched live from OpenAlex

Introduction: Recent evidence suggests that a traumatic brain injury is associated with a higher risk for cardiovascular pathology and impaired responses to activities of daily living. However, limited standardized testing is available to document cardiovascular responses during motor-cognitive function after acquired brain injury (ABI). Our study aimed to compare cardiovascular responses in persons with and without ABI during motor-cognitive assessments in virtual-reality gaming environments. Hypothesis: We hypothesized that there would be a significant difference in participant effort as defined by cardiovascular response specific to each activity. Methods: 50 participants (M/F = 16/34) age 29.31 (+/-11.667) years with and without ABI (9/41) performed a timed, 4-square stepping task to test dynamic balance (4SST) and the standardized Montreal Cognitive Assessment (MoCA).Testing included polar heart monitoring of participant effort via heart rate (HR) while performing five standardized, virtual-reality games to test motor-cognitive skills. Variables included HR, 4SST time, MoCA score, and computerized Cognitive Scores (ICOG). Descriptive statistics explored group performance using SPSS 24.0 (IBM) and an alpha level of 0.05. Results: results Indicated similar performance in MoCA and ICOG scores (26.78 +/- 2.188, 28.043 +/- 2.230 respectively) but ICOG effort ratings were significantly higher in the ABI group compared to without ABI (2.60 +/- 1.140 vs. 1.60 +/- 1.095 respectively). Also, the ABI group took significantly longer to complete each ICOG activity (34.056 +/- 24.461 vs. 29.964 +/- 25.727 respectively) with significantly delayed reaction times (3.598+/- 1.542 vs. 2.825 +/- 1.630 respectively). Significant relationships occurred between the ICOG activity score and the associated HR (r = - 0.512, p = 0.030) and 4SST and AGE (r = 0.526, p = 0.025). Multiple regression analysis indicated history of concussion, previous night hours of sleep, MoCA scores, gender, and HR significantly explained 61.2% of the ICOG variance (p = 0. 005). Discussion: Results indicate significant differences in cardiovascular responses to motor-cognitive activities however similar performance in MoCA and ICOG scores. There was also a significant difference in effort and reaction time scores. This trend appeared to explain overall ICOG performance as presented by the regression analysis. Conclusions: Preliminary findings warrant further research of cardiovascular responses during specific motor-cognitive tasks common to ADL’s.

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)0.000
metaresearch head score (Gemma)0.002
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 score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
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)0.0040.001

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 head0.025
GPT teacher head0.291
Teacher spread0.267 · 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".

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Citations0
Published2018
Admission routes1
Has abstractyes

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