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Record W4410500203 · doi:10.1093/eurjpc/zwaf236.166

The long-term follow-up of atrial fibrillation-specific quality of life following moderate-to-vigorous intensity continuous and high-intensity interval training programs

2025· article· en· W4410500203 on OpenAlexafffund
M. Hausen, Isabela Roque Marçal, Matheus Mistura, Jennifer L. Reed

Bibliographic record

VenueEuropean Journal of Preventive Cardiology · 2025
Typearticle
Languageen
FieldMedicine
TopicCardiovascular and exercise physiology
Canadian institutionsUniversity of Ottawa
FundersCanadian Institutes of Health Research
KeywordsMedicineIntensity (physics)High-intensity interval trainingAtrial fibrillationTerm (time)CardiologyInterval (graph theory)Interval trainingInternal medicineQuality of life (healthcare)

Abstract

fetched live from OpenAlex

Abstract Background High-intensity interval training (HIIT) has been shown to produce similar improvements in functional capacity and general quality of life (QoL), and a decrease in the Atrial Fibrillation Severity Scale (AFSS) symptom scores of patients with atrial fibrillation (AF), when compared with standard care moderate-to-vigorous intensity continuous training (MICT). However, the long-term effects of exercise programs on disease-specific QoL of patients with AF are unclear. Understanding the long-term effect of exercise programs on symptoms and quality of life is essential to improve the management of the unique needs of patients with AF. Purpose To assess the long-term effects of 12 weeks of HIIT- and MICT-based cardiovascular rehabilitation (CR) on disease-specific QoL in patients with persistent and permanent AF. Methods A randomized clinical trial with patients with persistent and permanent AF randomized (1:1) to either 12 weeks of MICT or HIIT. Disease-specific QoL was assessed using the AFSS, a 19-item self-report validated questionnaire with the following subscales: (1) global well-being, (2) AF total burden (comprising frequency, duration, and severity of AF), and (3) AF symptom score in the previous four weeks. A linear mixed-effect model with repeated measures over time (i.e., baseline, week 12, week 26, 1-year, and 2-year) was used to examine the main effects of time, group, and time by group interactions. The maximum likelihood estimation method was used to address missingness. A p-value of < 0.05 was set for statistical significance. Results The study included 86 participants (mean [SD] age, 69[8] years; 57[66.3%] males). The global well-being scores varied significantly (Time F=17.4, p<0.001) across the two years, irrespective of the exercise program, with a significant decrease at week 26, when compared to week 12 (p<0.001, mean difference[MD]=-5.0 pts) and baseline (p<0.001, MD=-4.6 pts). Next, global well-being increased in years 1 and 2 to similar values from week 12. The frequency of AF was significantly lower (Time F=23.6, p<0.001) at week 26 when compared to week 12 (p<0.001, MD = -0.9 pts), but increased at year 1 (p<0.001, MD=2.4 pts). AF symptom score (Time F=5.0, p=0.004) was lower at week 26 when compared to baseline (p=0.03, MD=-2.6 pts). A significant time by group interaction was observed for AF total burden (F=3.1, p=0.01). Both groups presented a decrease in AF total burden from week 12 to week 26 (p<0.001 both, HIIT MD=-6.4 points; MICT MD=-7.8 pts), followed by an increase to year 1 (p<0.001 both, HIIT MD=6.6 pts; MICT MD=8.0 pts). From year 1 to 2, AF total burden decreased only in HIIT (p<0.001, MD=-5.6 pts). There were no significant changes in the severity and duration of AF. Conclusion No long-term decreases in global well-being or AF symptoms for both groups, although a more pronounced reduction in AF total burden was observed in the HIIT group.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.764
Threshold uncertainty score0.608

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.002
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 head0.039
GPT teacher head0.293
Teacher spread0.254 · 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 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
Published2025
Admission routes2
Has abstractyes

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