OP0288 MACHINE LEARNING ALGORITHMS TO PREDICT COVID-19 ACUTE RESPIRATORY DISTRESS SYNDROME IN PATIENTS WITH RHEUMATIC DISEASES: RESULTS FROM THE GLOBAL RHEUMATOLOGY ALLIANCE PROVIDER REGISTRY
Izadi Z, Gianfrancesco M, Hyrich K, Strangfeld A, Gossec L, Carmona L, Mateus E, Lawson-Tovey S, Trupin L, Rush S, Schmajuk G, Jacobsohn L, Katz P, Al Emadi S, Wise L, Gilbert E, Valenzuela-Almada M, Duarte-Garcia A, Sparks J, Hsu T, D’silva K, Serling-Boyd N, Bhana S, Costello W, Grainger R, Hausmann J, Liew J, Sirotich E, Sufka P, Wallace Z, Machado P, Robinson P, Yazdany J. OP0288 MACHINE LEARNING ALGORITHMS TO PREDICT COVID-19 ACUTE RESPIRATORY DISTRESS SYNDROME IN PATIENTS WITH RHEUMATIC DISEASES: RESULTS FROM THE GLOBAL RHEUMATOLOGY ALLIANCE PROVIDER REGISTRY. Annals Of The Rheumatic Diseases 2021, 80: 175.2-176. DOI: 10.1136/annrheumdis-2021-eular.446.Peer-Reviewed Original ResearchAcute respiratory distress syndromeDevelopment of acute respiratory distress syndromeTime of COVID-19 diagnosisNegative predictive valuePositive predictive valueGlobal Rheumatology AllianceRheumatic diseasesBristol-Myers SquibbGrant/research supportPredictive valueArea under curveCOVID-19 Global Rheumatology AllianceRisk factors associated with acute respiratory distress syndromeGlobal cohort of patientsPre-existing rheumatic diseaseRisk of acute respiratory distress syndromeAnti-CD20 monoclonal antibodyAcute respiratory distress syndrome diagnosisTumor necrosis factor inhibitorsBristol-MyersCOVID-19 diagnosisRespiratory distress syndromeCohort of patientsInterstitial lung diseaseLife-threatening complications