Results 161 to 170 of about 10,653 (287)

Subjective Cognitive Concerns and Cognitive Trajectories in Parkinson's Disease: Biomarker Impact

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To examine the relationship of subjective cognitive concerns (SCC) with biomarkers of Alzheimer's disease (AD), neurodegeneration, and Parkinson's disease (PD) and domain‐specific cognitive trajectories among cognitively unimpaired persons with de novo PD. Method Cognitively unimpaired participants with SCC (n = 294) and without SCC (
Francesca V. Lopez, Fareshte Erani, Katherine J. Bangen, David G. Coughlin, Douglas Galasko, Kelsey R. Thomas   +5 more
wiley   +1 more source

External Validation Cannot Participate in Selecting a Rheumatoid Arthritis Diagnostic Model [Letter]. [PDF]

J Inflamm Res
Chen Q.
europepmc   +1 more source

microRNA‐7‐5p and α‐Synuclein SAA Predict Parkinson's Disease Phenoconversion

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Corroborate blood neuron‐derived extracellular vesicle (NDEV) alpha‐synuclein (αSyn), the CSF αSyn seed amplification assay (αSyn‐SAA), and blood microRNA‐7‐5p (miR‐7‐5p) as markers for Parkinson's disease (PD) phenoconversion and determine if combining these markers would help select subjects who would be more likely to phenoconvert.
Shayan Zadegan, Praveen Velammal, Kanmani Muthiah, Madhu Jatty, Christopher Adams   +4 more
wiley   +1 more source

Neighborhood Socioeconomic Status and Short‐Term Functional Outcomes in Systemic Lupus Erythematosus

Arthritis Care &Research, EarlyView.
Objective Individuals with systemic lupus erythematosus (SLE) can accumulate functional status (FS) impairment. We evaluated the association between neighborhood socioeconomic disadvantage, as measured by the Area Deprivation Index (ADI), and FS in a national SLE sample.
Baljeet Rai, Jessica Fitzpatrick, Jing Li, Eric Roberts, Patricia Katz, Laura Plantinga, Gabriela Schmajuk, Jinoos Yazdany   +7 more
wiley   +1 more source

Leveraging machine learning models to forecast pediatric allergic rhinitis exacerbation risk based on environmental exposure data. [PDF]

Front Pediatr
Li Z, Huang S, Xia Z.
europepmc   +1 more source

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

Arthritis 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, Ray Zhang, Sohini Mukherjee, Puneet Bajaj, Bonnie L. Bermas   +4 more
wiley   +1 more source

Toward universal representations of the living: Physiological invariance for transportable medical AI. [PDF]

PLOS Digit Health
Vallée A.
europepmc   +1 more source

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

Arthritis 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, Bhavisha Desai, Abiola Oladapo, Nana Kragh, Rebekah Zincavage, Brad Padilla, Naomi Schlesinger   +6 more
wiley   +1 more source

Estimating the Effects of MTEER in U.S. Practice: A Transportability Analysis of the COAPT Trial. [PDF]

J Am Coll Cardiol
Lalani C, Butala N, Dong H, Song Y, Stone GW, Mack MJ, Shahim B, Kazi DS, Cohen DJ, Dahabreh IJ, Yeh RW.   +10 more
europepmc   +1 more source

Unsupervised Machine Learning Identifies Shared Biomechanical and Clinical Variation in Individuals with Knee Osteoarthritis and High BMI: A Secondary Analysis of the IDEA Trial

Arthritis Care &Research, Accepted Article.
Objective High body mass index (BMI≥27 kg/m2) and aberrant gait biomechanics are primary risk factors for knee osteoarthritis (KOA), yet the specific loading patterns linked to clinical disease features remain unclear. Unsupervised machine learning (ML) was used to identify vertical ground reaction force (vGRF) waveform modes of variation and ...
Ashley N. Buck, J. Elyse Borgert, Hyeon Lee, Liubov Arbeeva, Yvonne M. Golightly, Richard F. Loeser, Leigh F. Callahan, Stephen P. Messier, Brian Pietrosimone, Amanda E. Nelson, James S. Marron   +10 more
wiley   +1 more source