Abstract P136: Assessing the Impact of Atrial Fibrillation Symptoms: Whose Perspective Should Be Used to Develop a Health Status Questionnaire?
Notice bibliographique
Résumé
Background Knowledge on how patients experience atrial fibrilliation (AF) and the effect of AF on their life is needed. While generic health status tools are used in clinical trials where the aim is to get a general picture of how patients rate their health, an AF disease-specific tool is missing. In development of disease-specific tools it is important that both patients and physicians are asked to describe the impact of symptoms of AF, when the goal is to elucidate patients' perspectives on the impact of the symptoms on their life with AF. By means of a systematic literature search, we identified five AF disease-specific self-reported instruments: The Canadian Cardiovascular Society Severity in AF (CCS-SAF); the specific questionnaire for Quality of Life in AF patients (QLAF); the Short Symptom Scale for patients with AF (SSS-AF); The Quality of Life questionnaire for patients with AF (AF-QOL); and finally the Atrial Fibrillation Effect on QualiTy-of-life (AFEQT). Aim The aim of this study was to compare five disease-specific AF self-reported instruments in order to elucidate which one is preferable to validate in a Danish context. The preferable tool is expected to be used in a prospective study on the evaluation of ablation and mini-maze operation due to AF and in a study on the development of a rehabilitation solution for patients with AF. Method A literature study comparing the five tools by text analysis was conducted as suggested by the Danish scholar Leif Becker Jensen. Criteria to determine which tool to validate in a Danish cohort included: a) Purpose of tool, b) Perspective captured in development of the tool, d) Content of the tool including length and type of questions, items, domains, e) Validation of the tool. Results a) Purpose of tool b) Perspective captured in development of the tool c) Content of the tool d) Validation of the tool CCS-SAF - Canada Designed for use in clinical practice. Not well designed for clinical trials to elucidate patients' perspective on the impact of symptoms on their life. Expert perspective only Consists of three steps; symptoms, association, functionality, and finally rating of the patients in Five classes (0-4). à designed for doctors to fill out Short Form 36, University of Toronto Atrial Fibrillation Severity Scale QLAF - Brazil Designed for clinical trials. Can also be used in the clinical practice context. Expert perspective only Consists of seven domains and 22 questions and is to be filled out by patients. Short Form 36 SSS-AF - Sweden Designed for use in clinical practice. Not well designed for clinical trials to elucidate patients' perspective on symptoms impact on their life. Expert perspective only Consists of six items which the patient rates on a scale from 0-100 Toronto AF symptom checklist, Short Form 36. AF-QOL - Spain Designed for clinical trials. Can also be used in the clinical practice context. Both patient and expert perspective were involved. Patients were involved during the process by focus group interviews Consists of 18 questions divided into three domains and is designed to be filled out by the patients Short Form 36 AFEQT - US Designed for clinical trials. Can also be used in the clinical practice context. Both patient and expert perspectives were involved. Patients were involved during the process by personal interviews and by having patients' rate relevant items. Consists of 21 questions divided into two sections and is also designed for the patients to fill out Short Form 36, EuroQOL - 5D, Symptom Checklist: Frequency and Severity, University of Toronto Atrial Fibrillation Severity Scale. Generalized Anxiety Disorder (GAD-7), Atrial Fibrillation Patients and Physician Global Change Forms Conclusion AFEQT and AF-QOL meet the criteria specified and by the fact that AFEQT is validated against more tools than AF-QOL it is preferred and will be translated into a Danish context for use in future Danish studies mentioned in the aim section of this study.
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 | 0,033 | 0,080 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,008 | 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 ».