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Record W4410483051 · doi:10.1093/eurjpc/zwaf236.379

The effects of high-intensity interval training on glucose variability and symptom severity in patients with atrial fibrillation and diabetes: a pilot randomized controlled trial

2025· article· en· W4410483051 on OpenAlexafffund
Tasuku Terada, Matheus Mistura, Jennifer L. Reed

Bibliographic record

VenueEuropean Journal of Preventive Cardiology · 2025
Typearticle
Languageen
FieldMedicine
TopicCardiovascular and exercise physiology
Canadian institutionsUniversity of Ottawa
FundersUniversity of Ottawa
KeywordsMedicineHigh-intensity interval trainingAtrial fibrillationDiabetes mellitusRandomized controlled trialInternal medicineConfidence intervalPhysical therapyIntensity (physics)CardiologyEndocrinology

Abstract

fetched live from OpenAlex

Abstract Background Atrial fibrillation (AF) is the most common heart rhythm disorder. Type 2 diabetes (T2D) increases a risk of developing AF and is present in approximately 20% of patients with non-permanent AF (paroxysmal and persistent AF). Many patients with T2D have high blood glucose levels and high glucose variability (GV). Greater GV is independently associated with inflammation, oxidative stress, and autonomic nervous system dysfunction, all of which contribute to the underlying pathophysiology of AF and AF symptom severity. GV has also been associated with poorer quality of life (QoL) in patients with T2D. Exercise improves GV, and high-intensity interval training (HIIT) has emerged as a superior and time-efficient approach to improve GV. However, the effects of HIIT on GV, AF symptom severity, and AF-related QoL in patients with AF living with T2D remain unknown. Purposes This pilot randomized controlled trial compared the impact of HIIT and no exercise training (Control) on GV (primary outcome), AF symptom severity, and AF-related QoL in patients with non-permanent AF living with T2D. The associations between GV and AF symptom severity and QoL were also examined. Methods Eligible patients had diagnosed non-permanent AF and T2D, and were ≥40 years of age, non-smokers, with resting heart rates ≤110 bpm, and no contraindications to performing high-intensity exercise. Included participants were randomized to a 4-week supervised HIIT program or Control. The HIIT group exercised thrice weekly for 12 weeks. Each HIIT session included 16x30-seconds high-intensity intervals at 80-100% of peak power output interspersed with 30-seconds active recovery. At baseline (prior to randomization) and follow-up (after the intervention), participants’ glucose concentrations were measured over three days using a continuous glucose monitoring system, on which percent coefficient of variation (%CV) was calculated for GV. Participants also completed the AF Severity Scale (AFSS) and AF Effect on Quality of Life (AEFQT) questionnaires. Results Due to recruitment challenges imposed by the COVID-19 pandemic, fewer than anticipated participants (N=11 vs. N=36, age: 70±6 years, 25% females) were randomised into HIIT (n=6) or Control (n=5). There were no differences between HIIT and Control in changes in GV (Baseline [B] 20.0±2.5 to follow-up [FU] 18.9±7.9 % vs. B: 21.9±5.5 to FU: 21.5±6.8 %, time x group interaction effect: p=0.988), AFEQT (B: 87.7±7.4 to FU: 88.8±11.5 points vs. B: 68.6±9.9 to FU: 80.5±9.6 points, interaction effect: p=0.123), or AFSS (B: 9.1±2.9 to FU: 9.3±2.1 vs. B: 18.2±6.1 vs. FU: 18.2±6.6 points, interaction effect: p=0.801). No significant correlations were found between GV and AF symptom severity or AF-related QoL. Conclusions Four weeks of HIIT did not improve GV, AF symptom severity or AF-related QoL in patients with non-permanent AF and T2D. However, these findings should be interpreted with caution given the smaller than desired sample size.

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)0.006
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.377
Threshold uncertainty score0.577

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
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 head0.005
GPT teacher head0.220
Teacher spread0.215 · 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 designRandomized 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".

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Citations0
Published2025
Admission routes2
Has abstractyes

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