Results 211 to 220 of about 1,081,470 (322)

Metabolic Consequences of Rheumatoid Arthritis

open access: yesArthritis Care &Research, EarlyView.
Patients with rheumatoid arthritis (RA) may have metabolic disruption, which can contribute to adverse long‐term outcomes, for multiple reasons. Patients with RA appear to have a higher risk of sarcopenia, type 1 and type 2 diabetes mellitus, metabolic syndrome, and hypertension. Systemic inflammation in RA can cause a “lipid paradox,” with reduced low‐
Stevie Barry   +2 more
wiley   +1 more source

Moderators and Mediators of Pain and Function Outcomes in a New Service Delivery Model for Management of Knee Osteoarthritis in Primary Care: Secondary Exploratory Analysis of a Randomized Controlled Trial

open access: yesArthritis Care &Research, EarlyView.
Objective Our objective was to explore moderators and mediators influenced changes in pain and function in people with knee osteoarthritis (OA) receiving a new model of primary care service delivery (Optimizing Primary Care Management of Knee Osteoarthritis [PARTNER]), at 12 months (ACTRN: 12617001595303).
Abdolhay Farivar   +12 more
wiley   +1 more source

Development of a simplified smell test to identify Parkinson's disease using multiple cohorts, machine learning and item response theory. [PDF]

open access: yesNPJ Parkinsons Dis
Li J   +17 more
europepmc   +1 more source

Association Between Sleep Disturbance and Subsequent Pain Interference in Patients With Early Rheumatoid Arthritis

open access: yesArthritis Care &Research, EarlyView.
Objective This study investigated whether sleep disturbance can predict the extent to which pain interferes with daily functioning in patients with early rheumatoid arthritis (RA). Methods Data were from adults with early RA (joint symptoms ≤12 months) enrolled in the Canadian Early Arthritis Cohort between 2016 and 2023.
Burcu Aydemir   +16 more
wiley   +1 more source

Capturing Abnormal Personality With Normal Personality Inventories: An Item Response Theory Approach [PDF]

open access: green, 2008
Kate E. Walton   +4 more
openalex   +1 more source

Data‐driven forecasting of ship motions in waves using machine learning and dynamic mode decomposition

open access: yesInternational Journal of Adaptive Control and Signal Processing, EarlyView.
Summary Data‐driven forecasting of ship motions in waves is investigated through feedforward and recurrent neural networks as well as dynamic mode decomposition. The goal is to predict future ship motion variables based on past data collected on the field, using equation‐free approaches.
Matteo Diez   +2 more
wiley   +1 more source

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