Paroxysmal atrial fibrillation and health-related quality of life: the importance of keeping score
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,018 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,005 | 0,008 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,002 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».