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Enregistrement W4411432923 · doi:10.1016/j.ard.2025.05.801

POS0415-HPR DEVELOPING A REHABILITATION REGISTRY IN RHEUMATOLOGY: FROM CORE SET SELECTION TO FUTURE APPLICATIONS

2025· article· en· W4411432923 sur OpenAlexaboutno aff
Alice Christiansen, Brian Clausen, Jannie Laursen, Karen Schreiber, Ann Bremander

Notice bibliographique

RevueAnnals of the Rheumatic Diseases · 2025
Typearticle
Langueen
DomaineMedicine
ThématiqueRheumatoid Arthritis Research and Therapies
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésMedicineRheumatologyRehabilitationCore (optical fiber)Selection (genetic algorithm)Internal medicinePhysical therapyFamily medicineMedical physicsArtificial intelligence

Résumé

récupéré en direct d'OpenAlex

Background: Evaluation of effectiveness in rheumatologic rehabilitation requires a systematic approach to collecting and utilizing patient data. Our previous efforts to establish a rehabilitation registry failed due to both limited clinical application, restricted accessibility for clinicians, and lack of relevance to the patients, resulting in limited follow-up data. Moreover, the application of multiple questionnaires covering the same domains or subdomains often proved to be time-consuming for the patients. There is currently no consensus or international recommendation for a rehabilitation core set in rheumatology. Herein we present the development of our online registry, which both emphasizes utility in clinical practice and quality monitoring while paving the way for cross-sectoral coordination and rehabilitation research. Objectives: The primary objectives of this initiative are to 1Identify a rheumatologic-specific core set of rehabilitation measures. 2Select reliable, valid and generically applicable instruments suitable for measuring effectiveness over time that minimize respondent burden while covering multiple domains within the core set of rehabilitation measures. 3Design a comprehensive platform for visualization of clinical patient-reported outcomes that supports interdisciplinary work flows and facilitates real-time decision making. Methods: Guided by international standards, existing core sets [1] and clinical expertise, a core set of domains essential to rheumatology care were identified by an expert panel, consisting of health professionals with expertise in rehabilitation and patient representatives. Assessment tools were selected based on their capacity to address multiple domains within the core set using minimal questions, while ensuring reliability and validity. Priority was given to generic instruments to ensure applicability across inflammatory and degenerative inflammatory disorders. Questions and forms addressing personal circumstances, comorbidities and lifestyle factors were incorporated to provide a comprehensive evaluation framework. The registry underwent pilot testing with a focus on the data entry component, during which adjustments were made to enhance usability and functionality. This testing involved 10 clinicians from various professional disciplines, followed by evaluations by two patient representatives and two layperson prior to its launch. Data collection began January 2025. The core set domains were organized to enhance clarity and usability on a registry dashboard. The dashboard functionality is still under development. Results: The identified core set measures comprised pain, fatigue, activity, quality of life, mental health, work, self-management and goal setting. The selected assessment tools were the Fatigue Visual Analogue Scale (VAS-fatigue), the Euroquol 5-dimension-5 level questionnaire (EQ-5D-5L) including the EurQuol VAS (EQVAS) [2], the Self-Efficacy for Managing Chronic Disease 6-item Scale (SES6G) [3], the Workability Index single item (WAI-question 1) [4] and the Patient Specific Functional Scale (PSFS) [5]. A preliminary grouping of questionnaire items according to the core measures for dashboard-use is visualized in Table 1. Conclusion: We were able to identify eight rehabilitation core domains essential to rheumatology care effectively covered by five validated questionnaires comprising 17 items. Further validation and real-world implementation of the core set, and implementation and testing of the dashboard are required to assess the registry's impact and refine its functionality. Looking ahead, the registry holds potential for enhancing cross-sectoral collaboration, supporting patient-centered care, and advancing research in rheumatologic rehabilitation, ultimately contributing to the development of an international rehabilitation core set. REFERENCES: [1] Oude Voshaar, M.A.H., et al., International Consortium for Health Outcome Measurement Set of Outcomes That Matter to People Living With Inflammatory Arthritis: Consensus From an International Working Group. Arthritis Care & Research, 2019. 71 (12): p. 1556-1565. [2] Kreimeier, S., et al., EQ-5D-Y-5L: developing a revised EQ-5D-Y with increased response categories. Quality of Life Research, 2019. 28 (7): p. 1951-1961. [3] Lorig, K.R., et al., Effect of a self-management program on patients with chronic disease. Eff Clin Pract, 2001. 4 (6): p. 256-62. [4] Tuomi, K., et al., Work ability index. Helsinki: Finnish Institute of Occupational Health ICOH, 2003. [5] Stratford, P., et al., Assessing Disability and Change on Individual Patients: A Report of a Patient Specific Measure. Physiotherapy Canada, 1995. 47 (4): p. 258-263. Table 1Overview of the selected instruments, instrument entities and the alignment with core domainsInstrumentEntityCore domainVAS-fatigueFatigueFatigueEQ-5D-5LMobilityActivitySelf-careSelf-managementUsual activitiesActivityPain/discomfortPainAnxiety/depressionMental healthEQ-VASQuality of lifeSES6GFatigueFatiguePain/discomfortPainEmotional stressMental healthSymptoms/ health problemsSelf-managementTasks/activitiesSelf-managementOtherSelf-managementWAI question 1Work capacityWorkPSFSActivity 1Goal settingPSFSActivity 2Goal settingPSFSActivity 3Goal settingVAS, visual analogue scale; EQ, Euroquol; 5D-5L, 5 dimensions-5-level; SES6G, Self-Efficacy for Managing Chronic Disease 6-item Scale; WAI, Workability Index; PSFS, Patient Specific Functional Scale. Acknowledgements: NIL . Disclosure of Interests: None declared . © The Authors 2025. This abstract is an open access article published in Annals of Rheumatic Diseases under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Neither EULAR nor the publisher make any representation as to the accuracy of the content. The authors are solely responsible for the content in their abstract including accuracy of the facts, statements, results, conclusion, citing resources etc.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,206
score de la tête « metaresearch » (Gemma)0,192
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche
Catégories consensuellesMétarecherche
DomaineSignal candidat: Méthodes · Signal consensuel: aucune
Devis d'étudeSignal candidat: Théorique ou conceptuel · Signal consensuel: aucune
GenreSignal candidat: Méthodes · Signal consensuel: Méthodes
Score de désaccord entre enseignants0,794
Score d'incertitude au seuil0,979

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,2060,192
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0020,002
Bibliométrie0,0070,005
Études des sciences et des technologies0,0020,002
Communication savante0,0080,008
Science ouverte0,0050,014
Intégrité de la recherche0,0020,004
Charge utile insuffisante (le modèle a refusé de juger)0,0150,012

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.

Tête enseignante Opus0,027
Tête enseignante GPT0,352
Écart entre enseignants0,326 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; l’étiquette directe de Gemma et le classifieur distillé Codex s’accordent sur ce qui est montré ici.

Devis d'étudeThéorique ou conceptuel
DomaineMéthodes
GenreMéthodes

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2025
Routes d'admission1
Résumé présentoui

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