Paroxysmal atrial fibrillation and health-related quality of life: the importance of keeping score
Bibliographic record
Abstract
This editorial refers to ‘Impact of the control of symptomatic paroxysmal atrial fibrillation on health-related quality of life’ by L. Guédon-Moreau et al ., on page 634. Atrial fibrillation (AF) causes more impairment of health-related quality of life (QOL) than many physicians appreciate. Although rarely a life-threatening disease, the distress caused by the onset of AF symptoms can be severe. For patients with paroxysmal atrial fibrillation (PAF), QOL as measured by a generic scale (SF-36) has been found to be comparable to that of post-MI patients. 1 Poorer QOL can be mostly attributed to AF symptoms; however, QOL is also influenced by patient factors and side effects of AF therapies. 2 In the absence of a gold standard method to treat AF patients, relief of symptoms and improving QOL are often the primary goals of therapeutic management. 3 In the study conducted by Guédon-Moreau et al ., 4 217 symptomatic PAF patients were classified into two groups (‘controlled’ vs. ‘uncontrolled’) and treated with an antiarrhythmic drug. ‘Controlled’ PAF was defined as no more than one self-reported episode of AF over the prior 6 months. Patients with controlled PAF had similar or better SF-36 scores for all subscales when compared to an age- and sex-matched reference population. Surprisingly, those with ‘uncontrolled’ PAF (two or more episodes of AF in the past 6 months) also had similar scores for ‘role physical’ and ‘bodily pain’ subscales of the SF-36 and the physical component summary when compared to the reference population. However, these patients reported a very high level of symptom severity (Part C of the AFSS symptoms score) at baseline compared to controlled PAF individuals. Symptom severity improved over time in uncontrolled PAF patients, whereas those with controlled PAF had consistent symptom severity scores and general QOL scores for the duration of the study. Interpreting the results of this study is not straightforward, as there is a discrepancy between patient-reported AF symptoms and physical functioning in the uncontrolled PAF group. Previous studies have shown that symptoms in AF are inversely correlated to physical functioning, suggesting symptoms are predictive of general well-being in this population. 5 Findings by Guédon-Moreau et al. imply that uncontrolled PAF patients were not as physically impaired by their symptoms as one might expect. Disease severity in AF patients can be assessed using objective measures of AF frequency and duration (as recorded by ECG monitoring), or subjective measures of the consequences of AF on patient well-being. The terms ‘controlled’ and ‘uncontrolled’ in this study are measures of subjective patient self-assessment rather than objective assessments of ‘true’ AF burden. It is reasonable to assume that patients who report having many episodes of AF will likely report more symptoms and worse QOL. Therefore, it is not unexpected that uncontrolled PAF patients had more severe symptoms than those who were controlled. The authors conclude that following treatment with an antiarrhythmic drug, QOL improved in the uncontrolled group comparable to controlled patients. However, antiarrhythmic therapy may not be the only reason for improvement, as there are factors influencing QOL, independent of specific drug effects. It is noteworthy that the majority of individuals in the uncontrolled PAF group (54.1%) had AF diagnosed <1 month prior to study entry, whereas few patients in the controlled group (4%) had AF diagnosed within the prior month. More recent onset of AF in the uncontrolled group may have influenced QOL scores at baseline since symptoms at the first onset of AF are often more severe than with subsequent episodes. 6 Quality of life improvement in uncontrolled PAF patients may have been due to adjustment to AF, decrease in the number of AF episodes, decrease in the severity of AF episodes that did occur, and/or non-specific benefits from following a treatment programme. It is not only important from a clinician's perspective to assess and improve QOL, but also to understand the causes of improvement to better manage these patients. The study conducted by Guédon-Moreau et al . reinforces the importance of QOL in this particular population, as PAF patients have varying levels of AF symptom severity. Although objective measures are often necessary to diagnose the disease, subjective patient reports and self-assessment of QOL should play a significant role in how physicians determine the best treatments for their patients. Just as there is no gold standard for AF treatment, there is no gold standard to measure QOL in AF patients. Most available QOL questionnaires are cumbersome and time consuming to complete. A simple, objective bedside measurement such as the CCS-SAF scale 5 or disease-specific AF-6 7 may be useful for determining the impact of symptoms on QOL and assisting in decision-making regarding AF treatments. Conflict of interest: P.D. has received consulting fees and research support from Sanofi-aventis and St. Jude Medical.
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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 | 0.002 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".