Results 151 to 160 of about 15,450 (266)

Impact of Six‐Month Monitoring Compared to Three‐Month Monitoring of Laboratories During Methotrexate Therapy

open access: yesArthritis Care &Research, EarlyView.
Objective To evaluate whether extending the American College of Rheumatology–recommended monitoring interval for complete blood count and liver function tests in patients receiving methotrexate (MTX) affects timely detection of medication‐related toxicity.
Spencer Simko   +4 more
wiley   +1 more source

Caregiver Perspectives on the Burden of Disease and Treatment in Uncontrolled Gout

open access: yesArthritis Care &Research, EarlyView.
Objective Uncontrolled gout (UG) refers to persistently elevated serum urate (SU) levels >6 mg/dL and ongoing gout symptoms despite use of urate‐lowering therapy (ULT). The objective of this study was to evaluate the burden associated with informal caregiving for individuals with UG.
Angelo Gaffo   +6 more
wiley   +1 more source

Optimizing Hydroxychloroquine Blood Levels and Long‐Term Hydroxychloroquine Intake Could Lower Atherosclerotic Cardiovascular Disease Risk and Prevent Polypharmacy in Systemic Lupus Erythematosus

open access: yesArthritis Care &Research, EarlyView.
Objective Hydroxychloroquine (HCQ) is the cornerstone of systemic lupus erythematosus (SLE) management with benefits extending beyond SLE control, including protection against atherosclerotic cardiovascular disease (ASCVD). Although HCQ blood levels reflect recent exposure and long‐term intake reflects medication adherence, the impact of longitudinal ...
Shivani Garg   +5 more
wiley   +1 more source

Medical School Admissions After the Supreme Court's 2023 Affirmative Action Ruling.

open access: yesJAMA Netw Open
Nguyen M   +13 more
europepmc   +1 more source

Affirmative action, minorities, and public services in India: Charting a future research and practice agenda. [PDF]

open access: yesIndian J Med Ethics, 2019
Bhojani U   +6 more
europepmc   +1 more source

Machine Learning‐Supported Analysis for Predicting and Visualizing Nonlinear Relationships Between Material Properties in Electroplated Chromium Layers

open access: yesAdvanced Engineering Materials, EarlyView.
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer   +4 more
wiley   +1 more source

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