Development of a novel clinimetric tool: PAtient Reported Disease Activity Index in Rheumatoid Arthritis (PARDAI-RA) by PANLAR, for the assessment of patients living with rheumatoid arthritis.
Daniel Gerardo Fernández-ÁvilaDaniela Patiño-HernándezSocorro MorenoMaría Gabriela Ávila PedrettiÁlvaro ArbeláezAntonio Cachafeiro VilarCarlos LozadaCarlos RíosCarlos ToroClaudia RamírezGuillermo J Pons-EstelManuel Francisco Ugarte-GilMaría NarváezMiguel AlbaneseOrlando RoaOscar RuizPaula I BurgosRicardo XavierYurilis J Fuentes-SilvaEnrique Roberto SorianoPublished in: Clinical rheumatology (2024)
In this article, we present a new clinimetric tool developed based on expert consensus and on data retrieved from our search. Disease activity can be better assessed by combining various data sources, such as clinical, laboratory, and self-reported outcomes. These variables were included in our novel clinimetric tool. Key Points • The goal of treatment of RA is to achieve the best possible control of inflammation, or even remission; therefore, disease management should include systematic and regular evaluation of inflammation and health status. • Clinimetric tools evaluate a series of variables (e.g., symptoms, functional capacity, disease severity, quality of life, disease progression) and can reveal substantial prognostic and therapeutic differences between patients. • Our clinimetric tool, which is based on a combination of data (e.g., clinical variables, laboratory results, PROMs), can play a relevant role in patient assessment and care.
Keyphrases
- disease activity
- rheumatoid arthritis
- systemic lupus erythematosus
- ankylosing spondylitis
- rheumatoid arthritis patients
- patient reported
- end stage renal disease
- juvenile idiopathic arthritis
- newly diagnosed
- chronic kidney disease
- patient reported outcomes
- ejection fraction
- healthcare
- interstitial lung disease
- prognostic factors
- electronic health record
- palliative care
- insulin resistance
- adipose tissue
- genome wide
- dna methylation
- single cell
- depressive symptoms
- pain management
- machine learning
- smoking cessation
- deep learning
- replacement therapy