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The Effect Of Bodyweight Exercise On Glycemic Variability Using Continuous Glucose Monitoring In Inactive Adults.

2023· article· en· W4387053320 on OpenAlexaff
Fiona J. Powley, Michael C. Riddell, Larissa M. Adamo, Douglas L. Richards, Martin J. Gibala

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2023
Typearticle
Languageen
FieldMedicine
TopicCardiovascular and exercise physiology
Canadian institutionsYork UniversityMcMaster University
Fundersnot available
KeywordsGlycemicMedicineCoefficient of variationHeart rateContinuous glucose monitoringSittingRandomized controlled trialSample size determinationInternal medicinePhysical therapyAnimal scienceInsulinBlood pressureMathematicsStatisticsBiology

Abstract

fetched live from OpenAlex

Brief vigorous exercise can enhance indices of glycemic control. Limited work has investigated the effect of simple, practical activities that do not require specialized equipment. PURPOSE: To determine the acute effect of brief bodyweight exercise (BWE) on glycemic variability over 24 h using continuous glucose monitoring (CGM) under controlled dietary conditions in healthy inactive adults. METHODS: A sample size of 27 was estimated to detect a medium effect size (dz = 0.5) in 24 h mean glucose with 80% power at an alpha level of 0.05 for a one-tailed (matched pairs) t-test. Participants (8 males, 19 females; age: 23 ± 3 y) completed two virtually supervised trials in a randomized order after familiarization. The trials involved either an 11-min BWE protocol or an equivalent non-exercise sitting control period (CON). BWE consisted of five, 1-min bouts performed at a self-selected pace interspersed with 1-min active recovery periods. Individualized pre-packaged meals were provided to each participant to standardize food intake during the 24 hours following each trial. Measures of GV included the mean amplitude of glycemic excursions (MAGE), coefficient of variation (CV), and mean standard deviation (SD) of the 24 h glucose means. This study was registered prior to data collection (ClinicalTrials.gov NCT05144490). RESULTS: Mean heart rate (HR) over the 11-min BWE protocol was 147 ± 14 beats/min (~75% of age-predicted HR maximum). Mean 24 h glucose following BWE and CON were not different (5.0 ± 0.4 mM vs 5.0 ± 0.5 mM, respectively; p = 0.39). Similarly, indices of GV were not different after BWE vs CON [MAGE: 2.20 ± 0.67 mM vs 2.37 ± 0.63 mM (p = 0.06), CV: 19 ± 5% vs 20 ± 5% (p = 0.21), mean SD: 0.97 ± 0.26 mM vs 0.99 ± 0.24 mM (p = 0.30), respectively]. CONCLUSIONS: An 11-min BWE protocol did not alter acute glycemic control in previously inactive adults who were otherwise young and healthy. These data nonetheless highlight the feasibility of completing remotely supervised BWE combined with CGM under free-living conditions. Future studies should investigate the effects of BWE in people with impaired glycemic control as well as the impact of repeated sessions of BWE training.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
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)0.0010.000

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 head0.010
GPT teacher head0.287
Teacher spread0.277 · 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 routes1
Has abstractyes

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