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Record W3102317263 · doi:10.1139/apnm-2020-0785

Effect of exercise-heat acclimation on cardiac autonomic modulation in type 2 diabetes: a pilot study

2020· article· en· W3102317263 on OpenAlexaffvenue
Michael J. Macartney, Sean R. Notley, Christophe L. Herry, Ronald J. Sigal, Pierre Boulay, Glen P. Kenny

Bibliographic record

VenueApplied Physiology Nutrition and Metabolism · 2020
Typearticle
Languageen
FieldMedicine
TopicHeart Rate Variability and Autonomic Control
Canadian institutionsUniversité de SherbrookeUniversity of CalgaryOttawa HospitalUniversity of Ottawa
Fundersnot available
KeywordsHeart rate variabilityType 2 diabetesHeart rateAcclimatizationMedicineInternal medicineCardiologyDiabetes mellitusNoveltyAutonomic nervous systemPhysical therapyPhysical medicine and rehabilitationEndocrinologyPsychologyBlood pressureBiology

Abstract

fetched live from OpenAlex

The effects of exercise-heat acclimation on heart rate variability (HRV) in individuals with type 2 diabetes (T2D) remains unclear. We assessed electrocardiogram recordings during exercise-heat stress in middle-aged-to-older individuals (50–70 years) with (n = 6) and without (control; n = 8;) T2D, before and after 7 days of exercise-heat acclimation. Exercising heart rate was reduced (control, −9 ± 5 bpm; T2D, −14 ± 9 bpm) yet HRV was not significantly different. Given the negative correlations between diminished HRV and cardiac risk observed in the scientific literature, further research is warranted. Novelty: Our observations indicate that 7 days exercise-heat acclimation may not effectively attenuate the deviation toward reduced overall HRV and unfavourable cardiac autonomic modulation in individuals with T2D.

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)0.001
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: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.016
GPT teacher head0.259
Teacher spread0.243 · 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 designNon-randomized trial
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

Citations7
Published2020
Admission routes2
Has abstractyes

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