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Currently, diagnosing a patient with systemic lupus erythematosus (SLE) is a complex process that compares potential lupus with other conditions. It can be challenging and delayed by a period of time, which increases patient uncertainty, referrals, healthcare utilization, increased flares, and organ dysfunction. In this study, machine learning (ML) via artificial intelligence tools based on patient data was used to develop an algorithm to help with SLE diagnosis.

Guselkumab is the first and only approved IL-23 inhibitor therapy used to treat adults with active PsA and moderate to severe plaque psoriasis (PsO). The medication showed efficacy in skin clearance and joint symptom relief and passed safety measures. Additionally, physical function, health-related quality of life, and resolution of enthesitis and dactylitis were confirmed through week 100.

The diagnosis of psoriatic arthritis (PsA) may be delayed by more than 2 years in half of patients, especially those of younger age at symptom onset, or with a higher body mass index (BMI) or enthesitis before diagnosis.

Pegloticase (pegylated uricase) is medication approved by the US Food and Drug Administration (FDA) designed to lower sUA in patients with uncontrolled gout. However, 26% of patients have infusion-related reactions (IRs), which may be indicative of the development of antidrug antibodies (ADAs). Due to this, physicians often administer immunomodulators in addition to pegloticase in order to prevent ADAs as well as increase the effectiveness of the therapy.

There were no differences in the occurrence of clinical characteristics between the subset of patients with and without neurological involvement, however disease activity was slightly higher in patients with neurological involvement than those without. Additionally, anti-SSA antibody was significantly higher in patients with neurological involvement and anti-SSB autoantibody was lower.