P075 Evaluation of the impact of the COVID-19 pandemic on patients with rheumatic diseases in the UK: results from the REUMAVID study
Notice bibliographique
Résumé
Abstract Background/Aims This study presents the impact of the COVID-19 pandemic on health care, access to treatment, daily activities, well-being and mental health and the role of patient organisations from the perspective of the patient with rheumatic disease in the UK. Methods REUMAVID is an international collaboration led by HTR of the University of Seville, together with a multidisciplinary team of rheumatologists and patient organisations from 7 European countries (in the UK: NASS, NRAS and Arthritis Action). The study consists of an online survey, including the following instruments: Self-Perceived Health, WHO-5 Well-Being Index and Hospital Anxiety and Depression Scale (HADS). Data are collected in two phases: the first wave of the pandemic (from May 14th to July 18th 2020) and the second wave (to be conducted in winter 2020). Results 558 patients with rheumatic diseases participated in REUMAVID UK. The most frequently reported diagnoses were axial spondyloarthritis (44.6%), rheumatoid arthritis (44.1%) and osteoarthritis (25.6%). The mean age was 58.5±13.4 years, 78.7% women, 70.8% married or in a relationship and 54.1% having university studies. 45.8% perceived their health status being "fair to very poor" with 38.4% reporting a worsening during lockdown. 48.8% had their rheumatology appointment cancelled. Of these, 46.9% were offered either online or telephone follow-up, while the remaining 50.6% were not given any alternative. 15.6% changed their medication, of which 66.3% were indicated to do so by the medical team and 21.7% did so out of concern with COVID-19 with the major fear being that their treatment would lead to serious illness if they contracted SARS-CoV-2, while the greater hope was to be able to continue with their treatment as usual. 10.3% smoked more than before, 59.4% quit smoking and 36.3% drank more alcohol than before. 20.7% were unable to physically exercise at home and 39.2% reported weight gain. According to the WHO-5 scale, 52.5% declared poor well-being (≤50). A total of 43.6% were at risk of anxiety and 33.6% at risk of depression according to the HADS scale. During the lockdown, 54.3% were able to continue their psychological therapy. The main source of COVID-19 information was the patient organisations (reaching 63.6% of members), compared to 45.3% of non-members who did not receive any information. Conclusion The REUMAVID study has allowed us to measure and quantify the experience of British patients with rheumatic disease during an unprecedented public health crisis. A reduction in healthcare access, concern about treatment, changes in daily life habits and worsening of well-being and mental health were reported during the first wave. Patient organisations were the main source of COVID-19-related information. Further data will be gathered during the second wave. Disclosure M. Garrido-Cumbrera: None. V. Navarro-Compán: Honoraria; Abbvie, BMS, Lilly, MSD, Novartis, Pfizer, Roche, UCB. D. Webb: Grants/research support; AbbVie, Biogen, Janssen, Lilly, Novartis, UCB. C. Jacklin: Grants/research support; Abbvie, Amgen, Biogen, Eli, Lilly, Gilead, Janssen, Pfizer, Roche, Sanofi, UCB. S. Irwin: Other; Coronavirus Community Support Fund. L. Christen: Other; Novartis employee. J. Correa-Fernández: None. S. Sanz-Gómez: None. H. Marzo-Ortega: Honoraria; Abbvie, Celgene, Eli-Lilly, Janssen, Novartis, Pfizer, Takeda, UCB. Grants/research support; Janssen, Novartis.
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 | 0,012 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,001 |
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 ».