<p>Quality of Life and Frailty Syndrome in Patients with Atrial Fibrillation</p>
Bibliographic record
Abstract
Introduction: Atrial fibrillation (AF) and frailty syndrome (FS) are a part of the aging process. Both are still of great importance in the assessment of quality of life (QoL). There is definitely a lack of research clarifying the association between FS and QoL in AF patients. Objective: The aim of this study was to evaluate the influence of FS on QoL in AF patients. Materials and Methods: The retrospective and observational study included 158 inpatients with mean age 69.8± 7.1 years, treated for AF in the cardiac department from 1 April 2019 to 31 June 2019. The following instruments were used: the Arrhythmia-Specific Questionnaire in Tachycardia and Arrhythmia (ASTA) and the Edmonton Frail Scale (EFS). Results: The mean level of frailty in the study group was 8.5± 5.0. In 25.9% of patients, the level of frailty was mild, in 10.1% moderate, and in 17.1% severe. Patients were divided into two groups based on their frailty status. In comparative analysis of the QoL, there were significant differences between the groups: the frail group had more intense symptoms of arrhythmia than the non-frail group (14.9± 4.1 vs 11.9± 4.9; p < 0.001). In the analysis of the total score impact of arrhythmia on QoL, the frail group had a significantly higher score than the non-frail group (23.5± 5.2 vs 14.5± 5.5), which confirmed the stronger negative impact of arrhythmia on QoL. In the regression coefficient analysis, the independent predictor of symptom severity and QoL was FS. However, we observed a negative impact of diabetes, which increased the impact of arrhythmia on QoL, and physical activity, which improved QoL and decreased the impact of symptoms on everyday life. Conclusion: Patients in the frail group have worse QoL and higher impact of arrhythmia on QoL in comparison to patients in the non-frail group. Frailty is an independent predictor of higher intensity of symptoms of arrhythmia and worse QoL. Diabetes and physical activity are predictors of QoL for patients with AF. Keywords: atrial fibrillation, frailty, older age
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".