Results 201 to 210 of about 1,979,548 (395)
Effect of captopril on mortality and morbidity in patients with left ventricular dysfunction after myocardial infarction. Results of the survival and ventricular enlargement trial. The SAVE Investigators.
New England Journal of Medicine, 1992 M. Pfeffer, E. Braunwald, L. Moye, L. Basta, E. Brown, T. Cuddy, B. Davis, E. Geltman, S. Goldman, G. Flaker, M. Klein, G. Lamas, M. Packer, Jacques R. Rouleau, Jean L. Rouleau, J. Rutherford, J. Wertheimer, C. Hawkins +17 moresemanticscholar +1 more sourcePerformance of the Predicting Risk of Cardiovascular Disease Events Calculator in Rheumatoid Arthritis
Arthritis &Rheumatology, EarlyView.Objective
Evaluate performance of the Predicting Risk of Cardiovascular Disease Events (PREVENT) calculator in rheumatoid arthritis (RA). Methods
Patients with RA were matched up to 10 controls on age, sex, and enrollment year using National Veterans Health Administration, Medicare, and National Death Index data (2006–2020).Tate M. Johnson, Halie Frideres, Punyasha Roul, Joshua F. Baker, Brian C. Sauer, Grant W. Cannon, Isaac D. Smith, Gary A. Kunkel, Beth I. Wallace, Thomas R. Porter, Kaveh R. Bookani, Amarnath R. Annapureddy, Ted R. Mikuls, Bryant R. England +13 morewiley +1 more sourceEfficacy and Safety of Guselkumab in Participants With Active Psoriatic Arthritis After Inadequate Response to One Prior Tumor Necrosis Factor Inhibitor: Week‐24 Results of a Phase 3, Randomized, Placebo‐Controlled Study
Arthritis &Rheumatology, EarlyView.Objective
To evaluate the efficacy and safety of guselkumab, an interleukin‐23p19 subunit inhibitor, in participants with active psoriatic arthritis (PsA) and inadequate response (inadequate efficacy and/or intolerance) to one prior tumor necrosis factor (TNF) inhibitor.Alexis Ogdie, Joseph F. Merola, Philip J. Mease, Christopher T. Ritchlin, Jose U. Scher, Kimberly Parnell Lafferty, Daphne Chan, Soumya D. Chakravarty, Wayne Langholff, Yanli Wang, Jie Shao, Yevgeniy Krol, Alice B. Gottlieb +12 morewiley +1 more sourceA Metabolomic Signature Predicts Gout Flare Clinical Outcome Associated With Colchicine Prophylaxis
Arthritis &Rheumatology, EarlyView.Objective
This study investigated that serum metabolomics, before urate‐lowering therapy (ULT) initiation, could serve as a biomarker for responsiveness to colchicine prophylaxis in patients with gout commencing treat‐to‐target ULT. Methods
We studied a multicenter prospective cohort (n = 409) initiating treat‐to‐target ULT plus colchicine prophylaxis. Wenyan Sun, Lingfang Xu, Haibing Chen, Mingshu Sun, Zhiqiang Li, Rui Li, Lidan Ma, Hui Zhang, Aichang Ji, Yuwei He, Na Wu, Le Yan, Robert Terkeltaub, Changgui Li +13 morewiley +1 more sourceMachine Learning to Predict Remission Between Six and 24 Months in Rheumatoid Arthritis: Insights from the JAK‐pot Collaboration
Arthritis &Rheumatology, Accepted Article.Objective
To develop, externally validate, and simplify a machine‐learning (ML) model to predict remission between six and 24 months in rheumatoid arthritis (RA) patients initiating TNF inhibitors, JAK inhibitors, IL‐6 inhibitors, abatacept, or rituximab, using data from 11 international registries in the JAK‐pot collaboration.Zubeyir Salis, Denis Mongin, Denis Choquette, Louis Coupal, Catalin Codreanu, Florenzo Iannone, Roberto Caporali, Tore K Kvien, Sella Provan, Ruth Fritsch‐Stork, Dan Nordström, Nina Trokovic, Karel Pavelka, Jakub Závada, Ana Rodrigues, Ziga Rotar, Prodromos Sidiropoulos, Irini Flouri, Céline Lamacchia, Michele Iudici, Delphine Courvoisier, Kim Lauper, Axel Finckh +22 morewiley +1 more sourceInferring rheumatoid arthritis disease activity status from the electronic health records across health systems
Arthritis &Rheumatology, Accepted Article.Objective
Disease activity plays a central role in rheumatoid arthritis (RA) clinical studies. The inconsistent availability of data on disease activity in real‐world electronic health records (EHR) data has limited the ability to generate real‐world evidence (RWE). This study aimed to develop and validate scalable machine learning (ML) models to infer David Cheng, Xuan Wang, Gregory C. McDermott, Jennifer S. Hanberg, Zoe Love, Katherine Zhong, Mary Jeffway, Jue Hou, Vidul Panickan, Rahul Sangar, Ying Qi, Connor Melley, Lauren Costa, Dakota Feil, Rachael Matty, Dana Weisenfeld, Abisayo Animashaun, Aimee Schreiner, Sara Morini, Lauren Rusnak, Andrew Cagan, Misti Paudel, J. Michael Gaziano, Brian Sauer, Michael Weinblatt, Joshua Baker, Bryant England, Yuk‐Lam Ho, Kelly Cho, Paul Monach, Grant W. Cannon, Nancy Shadick, Ted R. Mikuls, Tianxi Cai, Katherine P. Liao +34 morewiley +1 more source
