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Influence Of Remotely-Delivered Exercise On Glycemia In Women With Or At-Risk For Type 2 Diabetes

2023· article· en· W4387061959 on OpenAlexaffabout
Alexa Govette, Alexandra Dojutrek, Elia Rishis, Stephanie Small, Rebecca Christensen, Olivia Lee, Sarah Neil‐Sztramko, Catherine M. Sabiston, Sasha High, Amy A. Kirkham, Jenna B. Gillen

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2023
Typearticle
Languageen
FieldMedicine
TopicCardiovascular and exercise physiology
Canadian institutionsSTART ClinicMcMaster UniversityUniversity of Toronto
Fundersnot available
KeywordsPostprandialMedicineGlycemicInterquartile rangeType 2 diabetesPrediabetesDiabetes mellitusMealHeart rateInternal medicinePhysical therapyEndocrinologyBlood pressure

Abstract

fetched live from OpenAlex

Exaggerated increases in blood glucose concentration following meals is a risk factor for the development of cardiovascular disease in women with or at risk for type 2 diabetes (T2D). Previous laboratory-based research has demonstrated that performing exercise after a meal can lower postprandial glycemic excursions; however, exercise is often performed at a pre-determined intensity with specialized exercise equipment, which may not reflect exercise performed at home. Whether unsupervised exercise performed following a meal at home can lower postprandial glycemia is not well characterized. PURPOSE: To investigate the effects of performing unsupervised exercise at a self-selected pace following dinner on postprandial glycemia in women with or at risk for T2D. METHODS: 65 women (age: 60 ± 6 yr, BMI: 32 ± 7 kg/m2) diagnosed with prediabetes, T2D, or a moderate-to-high Canadian Diabetes Risk score (≥21) were recruited across Ontario, Canada. Participants were mailed a continuous glucose monitor and activity tracker to measure blood glucose and heart rate. In a randomized and counterbalanced order, participants consumed a habitual dinner meal on 3 occasions (640 ± 273 kcal, 66 ± 35 g carbohydrate) and initiated the following interventions 30 min thereafter independently: no exercise (CTL), 15 min of video-guided bodyweight interval exercise (BWI; 8 x 1-min intervals, 1-min recovery) or 30 min of walking (WALK). Participants were instructed to walk at a moderate pace for WALK and complete as many repetitions as possible during the BWI exercise intervals. Mean ± standard deviation of heart rate during exercise and median (interquartile range) of 3 h glucose mean, peak and iAUC following dinner were calculated. RESULTS: At-home BWI and WALK elicited self-selected intensities of 76 ± 8% and 73 ± 7% HRmax, respectively. Compared to CTL, WALK reduced 3 h glucose mean (6.3 (1.2) vs. 6.9 (1.3) mmol/L, p = 0.002), peak (7.9 (1.9) vs. 8.3 (1.7) mmol/L, p = 0.029) and iAUC (106 (160) vs. 159 (174) mmol/L x 3 h, p = 0.044). 3 h glucose mean (6.7 (1.3) mmol/L), peak (8.0 (1.7) mmol/L) and iAUC (166 (175) mmol/L x 3 h) in BWI were not different from CTL. CONCLUSION: An unsupervised 30-minute walk performed at home after dinner reduced postprandial glycemia in women with or at risk for T2D. Supported by CCS and CIHR.

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)0.001
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 score0.008
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

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)0.0020.000

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 head0.015
GPT teacher head0.280
Teacher spread0.265 · 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 routes2
Has abstractyes

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