Prevalence and clinical characteristics of patients with rheumatoid arthritis with interstitial lung disease using unstructured healthcare data and machine learning.
Jose A Román IvorraErnesto Trallero-AraguasMaria Lopez LasantaLaura CebriánLeticia LojoBelén López-MuñízJulia Fernández-MelonBelén NúñezLucia Silva-FernándezRaúl Veiga CabelloPilar AhijadoIsabel De la Morena BarrioNerea Costas TorrijoBelén SafontEnrique OrnillaJuliana RestrepoArantxa CampoJose L AndreuElvira DíezAlejandra López RoblesElena BolloDiego BenaventDavid VilanovaSara Luján ValdésRaul Castellanos-MoreiraPublished in: RMD open (2024)
We found an estimated age-adjusted prevalence of RA and RAILD by analysing real-world data through NLP. RAILD patients were more vulnerable at the time of inclusion with higher comorbidity and inflammatory burden than RAnonILD, which correlated with higher mortality.
Keyphrases
- interstitial lung disease
- risk factors
- systemic sclerosis
- healthcare
- machine learning
- end stage renal disease
- rheumatoid arthritis
- big data
- electronic health record
- ejection fraction
- newly diagnosed
- idiopathic pulmonary fibrosis
- chronic kidney disease
- oxidative stress
- prognostic factors
- peritoneal dialysis
- artificial intelligence
- type diabetes
- systemic lupus erythematosus
- coronary artery disease
- deep learning
- social media
- health information