Results 41 to 50 of about 97,178 (217)

A Two‐Stage Questionnaire and Actigraphy Screening for iRBD in a Multicenter Retrospective Cohort

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Isolated rapid‐eye‐movement sleep behavior disorder is a prodromal marker of synucleinopathies. However, most cases remain undiagnosed due to the insufficient predictive value of questionnaires and limited access to confirmatory video‐polysomnography. We assessed a two‐stage screening strategy combining a brief questionnaire on rapid‐
Caleb A. Massimi, Giorgio Ricciardiello Mejia, Andre Metzger, Kang Hyun Ryu, Salonee Marwaha, Eva Grzegorczyk, Li Zhou, Eliana Jacobs, Boris Gilyadov, Claudia Kunney, Liqhwa Ncube, Ankit Parekh, Emmanuel Mignot, Fanny M. Elahi, Joseph Winer, Kathleen Poston, Andreas Brink‐Kjaer, Emmanuel H. During   +17 more
wiley   +1 more source

Adding bias to reduce variance in psychological results: A tutorial on penalized regression [PDF]

Tutorials in Quantitative Methods for Psychology, 2017
Regression models are commonly used in psychological research. In most studies, regression coefficients are estimated via maximum likelihood (ML) estimation.
Helwig, Nathaniel E.
doaj   +1 more source

Neurochemical Endpoints to Inform Early‐Stage Trials of Spinocerebellar Ataxia 2 and 3 in a Multisite Setting

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Neurochemical levels measured by brain MR spectroscopy (MRS) have been proposed as endpoints for clinical trials in early‐stage spinocerebellar ataxia (SCA) trials. We tested their trial‐readiness by quantifying neurochemicals in three affected brain regions in early‐stage cohorts of SCA2 and SCA3, examining their reproducibility in ...
James M. Joers, Yaqiao Wei, Dinesh K. Deelchand, Adam Berrington, Young Woo Park, Guita Banan, Michal Povazan, Jens T. Rosenberg, André J. W. van der Kouwe, Tetsuo Ashizawa, Khalaf O. Bushara, Chiadi U. Onyike, Sub H. Subramony, Jeremy D. Schmahmann, Brian J. Soher, Peter B. Barker, Thomas H. Mareci, Eva‐Maria Ratai, Lynn E. Eberly, Gülin Öz   +19 more
wiley   +1 more source

Integrated PANoptosis Profiling Identifies Immunosuppressive Subtypes and a Prognostic Signature With Functional Validation of MLKL in Glioblastoma

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective The prognosis of glioblastoma (GBM) remains highly unfavorable, largely due to high tumor heterogeneity and an immunosuppressive microenvironment. However, the functional role of PANoptosis in this context is poorly understood. Methods Patients were stratified via K‐means clustering. A risk score model was constructed using prognosis‐
Langfei Tian, Minghui Zhao, Yuanbo Hu, Kaiyue Wang, Haiguang Liu, Zetong Bai, Kebin Zheng   +6 more
wiley   +1 more source

A Lasso approach to covariate selection and average treatment effect estimation for clustered RCTs using design-based methods

Journal of Causal Inference, 2022
Statistical power is often a concern for clustered randomized control trials (RCTs) due to variance inflation from design effects and the high cost of adding study clusters (such as hospitals, schools, or communities).
Schochet Peter Z.
doaj   +1 more source

Arterial Spin‐Labeling MRI at the Cortical‐CSF Interface: A Novel Biomarker in Alzheimer Disease

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background/Objective Arterial spin‐labeling (ASL) MRI can measure perfusion signal adjacent to CSF spaces and may provide information regarding CSF‐adjacent water transport physiology. We developed an automated pipeline to extract cortical‐CSF interface (IF) perfusion for comparison between Alzheimer disease (AD) and cognitively normal ...
Mona Asghariahmadabad, Pouya Metanat, Michael Thomas, Luke W. Bonham, Tyson Lam, Mehmet Kurt, Hong Nguyen, Tara Ellingson, Mauro Zucchelli, Stefano Casagranda, Quin Lu, Andreas M. Rauschecker, Leo Sugrue, Luis E. Savastano, Christopher P. Hess, Kamalini Ranasinghe, S. Andrew Josephson, Bruce L. Miller, Jennifer S. Yokoyama, Gil D. Rabinovici, Peter A. Ljubenkov, Lawren VandeVrede, Kambiz Nael   +22 more
wiley   +1 more source

Prevalence of Systemic Lupus Erythematosus in Australia, 2010–2022: A Population‐Based Study Using Linked National Administrative Health Data

Arthritis Care &Research, EarlyView.
Objective Systemic lupus erythematosus (SLE) is a heterogenous inflammatory condition with widely varying global prevalence estimates. The frequency of SLE in the general population of Australia has been reported to be notably lower than contemporary estimates in countries such as the United States or United Kingdom, at 19 to 39 per 100,000 as opposed ...
Lucinda Roper, Rachel Black, Joanna Tieu, Winnie Chen, Matthew Parker, Catherine Hill, Natasha Nassar, Mandana Nikpour   +7 more
wiley   +1 more source

A Novel Clinical Prognostic Model for Breast Cancer Patients with Malignant Pleural Effusion: Avoiding Chemotherapy in Low-Risk Groups?

Cancer Management and Research, 2023
Yichen Wang,1,* Tao Zhou,2,* Shanshan Zhao,1,* Ning Li,3 Siwen Sun,1 Man Li1 1Department of Oncology, The Second Affiliated Hospital of Dalian Medical University, Dalian, 116023, People’s Republic of China; 2Department of Oncology, The First ...
Wang Y, Zhou T, Zhao S, Li N, Sun S, Li M   +5 more
doaj  

Mucocutaneous Disease Activity and Damage Accrual in Systemic Lupus Erythematosus: Analyses From the Asia‐Pacific Lupus Collaboration Longitudinal Cohort Study

Arthritis Care &Research, EarlyView.
Objective This research article aims to describe the prevalence, associations, and health‐related quality of life (HRQoL) impact of mucocutaneous features of systemic lupus erythematosus (SLE). Methods Data from the Asia‐Pacific Lupus Collaboration cohort were analyzed (2013–2021).
Amanda M. Saracino, Yanjie Hao, Dylan Hansen, Yi‐Hsing Chen, Alberta Hoi, Vera Golder, Jiacai Cho, Aisha Lateef, Worawit Louthrenoo, Laniyati Hamijoyo, Shue Fen Luo, Yeong‐Jian Jan Wu, Sandra Navarra, Leonid Zamora, Chak Sing Lau, Shirley Chan, Zhanguo Li, Hai‐hong Yao, Sargunan Sockalingam, B. M. D. B. Basnayake, Yasuhiro Katsumata, Masayoshi Harigai, Zhuoli Zhang, Jun Kikuchi, Yuko Kaneko, Tsutomu Takeuchi, Madelynn Chan, Sang‐Cheol Bae, Fiona Goldblatt, Sean O'Neill, Geraldine Hassett, Kristine Ng, Nicola Tugnet, Mark Sapsford, Yih Jia Poh, Michael Tee, Cherica Tee, Naoaki Ohkubo, Yoshiya Tanaka, Rangi Kandane‐Rathnayake, Eric Morand, Shereen Oon, Mandana Nikpour   +42 more
wiley   +1 more source

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

Advanced 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, Christopher Mai, Luca Eisentraut, Andreas Bund, Ricardo Buettner   +4 more
wiley   +1 more source