The Impact of Acute Worsening Events on Daily Lives and Healthcare Seeking Behaviour in Patients With COPD: An International Qualitative Study
Notice bibliographique
Résumé
Abstract Background: In patients with COPD, acute worsening events (AWEs), i.e., clinically relevant deteriorations of peak expiratory flow, reliever use and/or symptoms, are often underreported in both clinical trials as in the real-world. Yet, little is known about the patients’ perception of, and healthcare seeking behaviour during or after, such events. Objective: (1) to create more insights into the impact of an AWE on daily lives of patients with COPD and (2) to identify and explain AWE associated behaviour. Methods: A qualitative international sub-study was performed in the Netherlands, Spain, the United States, Canada, and the United Kingdom during 2023-2024. Interviews were audio-recorded, transcribed and analysed using the grounded-theory approach. Nine-teen patients, with moderate-to-severe COPD, were recruited while they participated in a randomised controlled trial. The first interview was triggered by the occurrence of an AWE, and the second interview took place 6 weeks after the first. Results: Patients identification of bad days showed large variability (e.g., attributed to inability to perform physical activity, worsening of symptoms, add-on treatment). About half of the AWEs were recognized based on patients’ evaluation of recent days. Most of the 2-days AWEs were not noticed by patients, whereas longer (>2 days) AWE events were often recognized. The majority of patients were seeking help in case they felt the need to. Difficulties in getting an appointment with a clinician on a short notice was mentioned as an important external barrier, whereas a reactive stance to worsenings seemed to be a key internal barrier – both influencing the decision to consult a healthcare professional. Conclusions: AWEs impact the daily life of patients with COPD. Patients differ widely in terms of how they perceive and recognise (previous) worsenings and their threshold for seeking healthcare. A lack of recognition of day-to-day variations in disease stability may lead to underreporting of the frequency and impact of worsening events to healthcare professionals. The patient's experience of identifying and managing (previous) worsenings should not be overlooked when integrating this into COPD action plans. The variation in duration and frequency of AWEs should be considered when implementing this as endpoint in clinical trials for COPD
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 tête enseignante, 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 ».