Results 161 to 170 of about 3,530,899 (245)

Discordance Between Systemic Lupus Erythematosus Disease Activity Index Domain Weights and Their Association With Organ Damage Accrual

Arthritis Care &Research, EarlyView.
Objective Studies of damage accrual in patients with systemic lupus erythematosus (SLE) show associations with disease activity measured by the SLE Disease Activity Index 2000 (SLEDAI‐2K), but these associations are imperfect. SLEDAI scores are powerfully influenced by weightings (1–8) assigned to each domain.
Kevin Zhang, Eric F. Morand, Sarah E. Boyd, François Petitjean, Alberta Hoi, Rachel Koelmeyer, Iolanda Miceli, Julie A. Monk, Hieu T. Nim   +8 more
wiley   +1 more source

An Eulerian Approach to the Analysis of Krause's Consensus Models [PDF]

, 2012
Canuto, Claudio, Tilli, Paolo, Fagnani, Fabio   +2 more
core   +1 more source

Health Care Use Among Patients Presenting to Emergency Department for Gout Flares in Ontario, Canada: A Population‐Based Health Systems Analysis

Arthritis Care &Research, EarlyView.
Objective We characterized emergency department (ED) gout visits and identified patient characteristics and health services patterns contributing to ED presentations. Methods We conducted a population‐based study of ED gout visits in Ontario, Canada, between 2014 and 2023.
Timothy S. H. Kwok, Samantha Morais, William K. Silverstein, Clare L. Atzema, Gregory Choy, Priyanka Chandratre, Ping Li, Jessica Widdifield   +7 more
wiley   +1 more source

Artificial Intelligence–Based Online Symptom Assessment Tools for Systemic Lupus Erythematosus Diagnosis: Patient Perspectives

Arthritis Care &Research, EarlyView.
Objective The objective of this article is to identify perceptions of patients with systemic lupus erythematosus (SLE) regarding artificial intelligence (AI)–based online symptom assessment tools, and the potential of these tools to address diagnostic barriers.
Olivia A. Stein, Jennifer L. F. Lee, Evelyne Vinet, Arielle Mendel, Christian A. Pineau, Fares Kalache, Louis‐Pierre Grenier, Sasha Bernatsky   +7 more
wiley   +1 more source

The Lupus Damage Index Revision Program: Results From the Item Generation and Reduction Phases

Arthritis Care &Research, EarlyView.
Objective A data‐driven and expert/patient consensus‐based project to develop a revised Systemic Lupus International Collaborating Clinics (SLICC)/American College of Rheumatology (ACR) Damage Index (SDI) is under way supported by SLICC, ACR, and the Lupus Foundation of America. Our objective is to report the item generation and reduction phase results
Burak Kundakci, Megan R. W. Barber, Ann E. Clarke, Sindhu R. Johnson, Anselm Mak, Hermine I. Brunner, Murat Inanc, Rosalind Ramsey‐Goldman, Guillermo Ruiz‐Irastorza, Ellen M. Ginzler, John G. Hanly, Alexandra Legge, Cynthia Aranow, Laurent Arnaud, Nathalie Costedoat‐Chalumeau, Dafna D. Gladman, Søren Jacobsen, Michelle Petri, Clovis A. Silva, Évelyne Vinet, Alexandre E. Voskuyl, SDI Revision Literature Review Groups, SDI Revision Delphi Panel, SDI Revision Item Reduction Committee, SDI Revision Clinical Domain Groups, Ian N. Bruce   +25 more
wiley   +1 more source

Anorectal Dysfunction in Systemic Sclerosis: Clinical Phenotypes and Functional Patterns

Arthritis Care &Research, EarlyView.
Objective The aim of this study was to characterize specific physiologic defects in anorectal dysfunction in systemic sclerosis (SSc) using anorectal manometry (ARM), evaluate associations with gastrointestinal (GI) and extraintestinal clinical phenotypes, and explore potential serologic markers for risk stratification.
Timothy Kaniecki, Alireza Amindarolzarbi, Tsion Abdi, John Clarke, Michael Hughes, Ami A. Shah, Zsuzsanna H. McMahan   +6 more
wiley   +1 more source

Engagement Patterns With an Artificial Intelligence Health Coach for Systemic Sclerosis Self‐Management: A Mixed Methods Study

Arthritis Care &Research, EarlyView.
Objective To evaluate utility of an artificial intelligence (AI) health coach for systemic sclerosis (SSc) self‐management and identify patterns associated with participant engagement. Methods We conducted a mixed methods study in which an AI health coach, powered by a large language model (LLM), was used to support self‐management for SSc.
Nirali Shah, Melanie Morris, Cristina Daraban, Sophia Johnson, Susan L. Murphy   +4 more
wiley   +1 more source

Development of a Disease Activity Index for the Assessment of VEXAS Syndrome (VEXAS‐DAI)

Arthritis Care &Research, EarlyView.
Objective Vacuoles, E1 enzyme, X‐linked, autoinflammatory, somatic syndrome (VEXAS) syndrome is characterized by a complex spectrum of inflammatory and hematologic manifestations. Clinical research to identify effective therapies is urgently needed but is hindered by the lack of validated outcome measures.
Kevin Byram, Heřman Mann, Danielle Hammond, Onima Chowdhury, Sinisa Savic, Yohei Kirino, Carmelo Gurnari, Maël Heiblig, Thibault Comont, Arsène Mekinian, Mrinal M. Patnaik, Lachelle D. Weeks, Gary Ho, Adam Al‐Hakim, Scott Goldberg, Marcela A. Ferrada, Sophie Georgin‐Lavialle, Peter C. Grayson, Emma M. Groarke, Bhavisha Patel, Megan Sullivan, Sarah A. Buckley, Bryan G. Harder, Raman Garcha, David B. Beck, Matthew J. Koster   +25 more
wiley   +1 more source

The Development of Rheumatoid Arthritis–Specific Ambulatory Care–Sensitive Conditions: Results of a Consensus Process

Arthritis Care &Research, EarlyView.
Objective Ambulatory care–sensitive conditions (ACSCs) serve as indicators of access, quality, and performance of the health system. This study aimed to determine rheumatoid arthritis (RA)‐specific ACSCs for use in the evaluation of care system access and quality.
Kara Irwin, Candace H. Feldman, Claire E. H. Barber, Gabriel Fabreau, Jake Jennings, Scott Patten, Cheryl Barnabe, Inflammatory Arthritis‐Specific ACSC Consensus Process Working Group   +7 more
wiley   +1 more source

Clinical Validation of Artificial Intelligence (AI)‐based Cartilage Segmentation Predicting Knee Replacement

Arthritis Care &Research, Accepted Article.
Objective For cartilage morphology to serve as a scalable endpoint in clinical trials, analyses should be performed automatically without human interaction. To clinically validate artificial intelligence (AI)‐based analysis, we studied cartilage loss from MRI prior to knee replacement.
Felix Eckstein, David J. Hunter, C. Kent Kwoh, Wolfgang Wirth   +3 more
wiley   +1 more source