Results 81 to 90 of about 60,840 (277)

Machine Learning to Predict Remission Between 6 and 24 Months in Rheumatoid Arthritis: Insights From JAK, an International Registry Collaboration

Arthritis &Rheumatology, EarlyView.
Objective To develop, externally validate, and simplify a machine learning model to predict remission between 6 and 24 months in patients with rheumatoid arthritis (RA) initiating tumor necrosis factor inhibitors, JAK inhibitors, interleukin‐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 more
wiley   +1 more source

Extremely elevated erythrocyte sedimentation rates: Associations with patients’ diagnoses and clinical characteristics

Romanian Journal of Internal Medicine
The aim of the study was to assess the etiological distribution of patients with an erythrocyte sedimentation rate (ESR) over 100 mm/hour and to evaluate differences in demographic, comorbidity, laboratory characteristics, and clinical outcomes.
Holoğlu Esen Nur, Uzunlulu Mehmet, Torun Cundullah   +2 more
doaj   +1 more source

Giant cell arteritis with low erythrocyte sedimentation rate: frequency of occurence in a population-based study

, 2001
To determine the frequency of a low erythrocyte sedimentation rate (ESR) in patients with giant cell arteritis (GCA) and evaluate their clinical features in a defined ...
SALVARANI, CARLO, Hunder, G. G.
core   +1 more source

Inferring Rheumatoid Arthritis Disease Activity Status From the Electronic Health Records Across Health Systems

Arthritis &Rheumatology, EarlyView.
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 (EHRs) data has limited the ability to generate real‐world evidence (RWE).
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 more
wiley   +1 more source

Integrated Clinical and Proteomic Profiling of CD19 Chimeric Antigen Receptor T Cell Therapy in Progressive Systemic Sclerosis

Arthritis &Rheumatology, EarlyView.
Objective To characterize the clinical, immunologic, and proteomic changes associated with CD19 chimeric antigen receptor T cell therapy in patients with progressive systemic sclerosis (SSc). Methods Patients with progressive SSc received CD19 chimeric antigen receptor (CAR)‐T cell therapy and were observed longitudinally for safety, clinical efficacy,
Chenhan Jia, Wanyi Lin, Zhangyi Zhao, Fenglin Wu, Chaoyu Gu, Yuankai Sun, Zhe Ding, Chang Wei, Xinyu Li, Cuiwei Xie, Peng Xia, Zhen Xia, Xuesong Liu, Shaoying Yang, Chunyan Zhang, Hanlin Yin, Liangjing Lu   +16 more
wiley   +1 more source

From Interferon Signature to the Clinical Landscape: Type I Interferonopathies

Arthritis &Rheumatology, Accepted Article.
Background Type I interferonopathies are heterogeneous diseases driven by dysregulated IFN‐I signaling. Diagnosis is challenging due to clinical/molecular variability and the need for IFN‐I quantification. Objective To characterize the clinical, immunological, genetic, molecular profiles of patients with suspected enhanced IFN‐I signaling, and assess ...
Ismail Yaz, Seza Ozen, Hacer N. Bildik, Canberk Ipsir, Dilara Unal, Saliha Esenboga, Begum Cicek, Mehmet E. Seker, Fatima Aerts‐Kaya, Seher Sener, Mehmet O. Erkan, Hanife Avci, Deniz Cagdas, Ilhan Tezcan   +13 more
wiley   +1 more source

IMPACT OF SMOKING ON ERYTHROCYTE SEDIMENTATION RATE (ESR) AND LIPID PROFILE IN ADULTS

, 2020
Objective: The aim of the study was to understand the changes in ESR and serum lipid profile in adult smokers and non-smokers and the risk of developing atherosclerosis. Study design: This is a comparative and non-interventional study. Study period: In the Medicine Unit-II of Nishat Hospital Multan for one-year duration from May 2019 to May 2020 ...
openaire   +2 more sources

ERYTHROCYTE SEDIMENTATION RATE

, 2005
Inflammatory responses to tissue injury (the acute phase response) include alteration in serum protein concentration, especially increases in fibrinogen, serum amyloid A protein and C-reactive protein, and decrease in albumin.
Besisik, Sevgi
core  

Flowchart prospective study (ESR = Erythrocyte Sedimentation Rate; FUO = Fever of Unknown Origin, PMR  =  Polymyalgia rheumatica). ‡chronic tonsillitis (diagnosed by ear-nose-throat specialist).

, 2013
Flowchart prospective study (ESR = Erythrocyte Sedimentation Rate; FUO = Fever of Unknown Origin, PMR  =  Polymyalgia rheumatica). ‡chronic tonsillitis (diagnosed by ear-nose-throat specialist).
Emile F. I. Comans (391573), Alex B. Arntzenius (391574), Dirkjan van Schaardenburg (91650), Friso M. v.d. Zant (391578), Frank Stam (391576), Frits Smit (391581), Conny J. van der Laken (391572), Michelle Gompelman (391577), Sander Anten (391582), Bert J. Voerman (391580), Anneke Q. A. van Paassen (391579), Yvo M. Smulders (284308), Ton Zwijnenburg (391575), Arjen Binnerts (391584), Karel-Jan D. F. Lensen (391571), Alexandre E. Voskuyl (213961), Carl E. Siegert (391583)   +16 more
core   +1 more source

Clinical Model‐Informed Precision Dosing Consult Service for Accelerating Personalized Medication in Pediatric Patients

Clinical Pharmacology &Therapeutics, EarlyView.
Traditional dosing strategies often rely on a “one‐size‐fits‐all” paradigm, assuming an “average” patient with typical demographic and pharmacological characteristics. In reality, this often overlooks existing between‐patient variability and can lead to suboptimal drug exposure or toxicity. This issue is especially pronounced in pediatric patients, who
Zachary L. Taylor, Takanobu Nadai, Kei Irie, Wen Rui Tan, Sanjana Parikh, Anhar Hosawi, Matthijs W. van Hoogdalem, Ronaldo Morales Junior, Sonya Tang Girdwood, Abbie D. Leino, Kana Mizuno, Alexander A. Vinks, Tomoyuki Mizuno   +12 more
wiley   +1 more source