Results 131 to 140 of about 263,464 (354)

Effect of sevoflurane-based or propofol-based anesthesia on acute kidney injury after surgery for gastric cancer: a retrospective propensity score-matched analysis

BMC Anesthesiology
Background Acute kidney injury (AKI) is a common complication of major abdominal surgery that is associated with adverse patient outcomes including death.
Yang Song, Si Liang, Ming Wei, Hong Chen, Liping Wang, Yu Wang   +5 more
doaj   +1 more source

Onasemnogene Abeparvovec in Patients With SMA: Interim Results of the RESTORE Registry in Japan

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective There are limited real‐world data regarding the safety and effectiveness of onasemnogene abeparvovec (OA; Zolgensma) infusion, a one‐time gene replacement therapy, for Japanese patients with spinal muscular atrophy (SMA). We aimed to improve understanding of the real‐world outcomes for OA in Japan.
Kayoko Saito, Kamal Benguerba, Ken Tsuchida, Kazushige Yazawa, Isao Tsumiyama, Hiromitsu Kayama, Sandra P. Reyna, Farid Khan, Richard S. Finkel   +8 more
wiley   +1 more source

The Returns to Continuous Training in Germany: New Evidence from Propensity Score Matching Estimators [PDF]

The present paper examines the wage effects of continuous training programs using individual-level data from the German Socio Economic Panel (GSOEP). In order to account for selectivity in training participation we estimate average treatment effects (ATE
Muehler, Grit, Schauenberg, Bernd, Beckmann, Michael   +2 more
core  

Clinical Practice Guideline for Evaluation and Management of Peripheral Nervous System Manifestations in Sjögren's Disease

Arthritis Care &Research, EarlyView.
Objective Sjögren's disease is an autoimmune disorder that can impact multiple organ systems, including the peripheral nervous system (PNS). PNS manifestations, which can exist concurrently, include mononeuropathies, polyneuropathies, and autonomic nervous system neuropathies.
Anahita Deboo, Robert Fox, Katherine M. Hammitt, Julie Frantsve‐Hawley, Matthew C. Baker, Stamatina Danielides, Eduardo De Sousa, Brent P. Goodman, Jennifer K. King, Steven Mandel, Ghaith Noaiseh, Pantelis P. Pavlakis, George Sarka, R. Hal Scofield, Arun Varadhachary, Daniel J. Wallace, Matt Makara, Nancy Carteron, Steven Carsons, in collaboration with the Consensus Expert Panel (CEP) members, G. Alden Adkins, Brittany Adler, Hossein Ansari, Senada Arabelovic, Alan Baer, Denis Balaban, Shamik Bhattacharyya, Evelyn Bromet, Krishna Chaganti, Kamal Chemali, Melissa Cortez, Schartess Culpepper, Paul Dellaripa, Dana Direnzo, Daniel El Bogdadi, Robert Fearon, Mehrnez Fischbach, Judi Furlong, Christopher Gibbons, Rachael Gordon, Thomas Grader Beck, Syed Haider, Larry Hollenbeck, Chadwick R. Johr, Stuart S. Kassan, Brian King, Octavia Kincaid, Eugene Kissin, Vasileios Kyttaris, Lindsay Lally, Brandon M. Law, Janet Lewis, Scott M. Lieberman, Amanda Lusa, Joseph Lutt, Rashmi Maganti, Arthur M. Mandelin, Sara McCoy, Kerry Neall, Timothy Niewold, Anne Louise Oaklander, Ruben A. Peredo‐Wende, Lynn Petruzzi, Mark A. Porter, Guada Respicio Duque, Tania Reyna, Nathaniel M. Robbins, Elliot D. Rosenstein, Laura Rosow, Breanna Ruthrauff, Amit Sachdev, Nora Sandorfi, Sarah Schafer, Elena Schiopu, Chokkalingam Siva, Daniel Small, Sara M. Stern, Lauren Stiles, Susan Stoddard, Jinny Tavee, Donald Thomas, Edward L. Treadwell, Nagagopal Venna, Steven Vernino, Frederick B. Vivino, Brittany Weber, Sepideh Yadollahi, Huiying Yu, Scott Zashin   +88 more
wiley   +1 more source

Multivariate and Propensity Score Matching Software with Automated Balance Optimization: The Matching package for R

Matching is an R package which provides functions for multivariate and propensity score matching and for finding optimal covariate balance based on a genetic search algorithm.
Jasjeet S. Sekhon
core  

Estimating propensity scores with missing covariate data using general location mixture models

, 2009
In many observational studies, researchers estimate causal effects using propensity scores, e.g., by matching or sub-classifying on the scores. Estimation of propensity scores is complicated when some values of the covariates aremissing.
Reiter, Jerome P., Jerome P. Reiter, Mitra, Robin, Robin Mitra   +3 more
core   +1 more source

Temporal Trends and Short‐ and Long‐Term Mortality of People With Acute Myocardial Infarction and Rheumatoid Arthritis: A Nationwide Cohort Study

Arthritis Care &Research, EarlyView.
Objective We investigated whether a diagnosis of rheumatoid arthritis (RA) affects the quality of inpatient acute myocardial infarction (AMI) care and long‐term mortality post‐AMI. Methods We analyzed data from 784,091 adults, 6,047 with a diagnosis of RA, from England and Wales hospitalized with AMI between 2005 and 2019 from the Myocardial Ischaemia ...
Megan Butler, Nicholas Weight, Muhammad Rashid, Rodrigo Bagur, Purvi Parwani, Samantha Hider, Edward Roddy, Robert Butler, Mamas A. Mamas   +8 more
wiley   +1 more source

Evaluating the Effects of Farm Programs: Results from Propensity Score Matching

The paper applies a non-parametric propensity score matching approach to evaluate the effects of two types of farm programs (agri-environment (AE) programs and the less favoured area (LFA) scheme) on input use and farm output of individual farms in ...
Weiss, Christoph R., Pufahl, Andrea
core  

Mycophenolate Mofetil Treatment Reduces the Risk of Treatment Escalation Due to Vascular Complications in Limited Cutaneous Systemic Sclerosis: Emulation of a Target Trial From the Italian Rheumatology Society SPRING Registry

Arthritis Care &Research, EarlyView.
Objective Mycophenolate mofetil (MMF) use in limited cutaneous systemic sclerosis (lcSSc) is relatively uncommon because of the lower fibrotic burden and the predominance of vascular complications. In vitro observations and clinical data from transplanted patients suggest a protective effect of MMF on endothelial function.
Enrico De Lorenzis, Gerlando Natalello, Rossella De Angelis, Lucrezia Verardi, Dilia Giuggioli, Gianluigi Bajocchi, Lorenzo Dagna, Silvia Bellando‐Randone, Giovanni Zanframundo, Rosario Foti, Fabio Cacciapaglia, Giovanna Cuomo, Alarico Ariani, Edoardo Rosato, Gemma Lepri, Francesco Girelli, Valeria Riccieri, Elisabetta Zanatta, Ilaria Cavazzana, Francesca Ingegnoli, Maria De Santis, Giuseppe Murdaca, Giuseppina Abignano, Giorgio Pettiti, Alessandra Della Rossa, Maurizio Caminiti, Annamaria Iuliano, Giovanni Ciano, Lorenzo Beretta, Gianluca Bagnato, Ennio Lubrano, Maria Ilenia De Andres, Alessandro Giollo, Cosimo Bruni, Martina Orlandi, Marco Fornaro, Marta Saracco, Cecilia Agnes, Pier Giacomo Cerasuolo, Gabriella Alonzi, Edoardo Cipolletta, Federica Lumetti, Amelia Spinella, Luca Magnani, Corrado Campochiaro, Giacomo De Luca, Veronica Codullo, Elisa Visalli, Carlo Iandoli, Antonietta Gigante, Greta Pellegrino, Erika Pigatto, Maria‐Grazia Lazzaroni, Franco Franceschini, Elena Generali, Gianna Mennillo, Simone Barsotti, Giuseppa Pagano Mariano, Federica Furini, Licia Vultaggio, Simone Parisi, Clara Lisa Peroni, Gerolamo Bianchi, Enrico Fusaro, Gian Domenico Sebastiani, Marcello Govoni, Salvatore D'Angelo, Franco Cozzi, Fabrizio Conti, Serena Guiducci, Andrea Doria, Carlo Salvarani, Florenzo Iannone, Maria Antonietta D'Agostino, Clodoveo Ferri, Marco Matucci Cerinic, Silvia Laura Bosello, on behalf of the SPRING Italian Registry Collaborators   +77 more
wiley   +1 more source

Can nutritional label use influence body weight outcomes? [PDF]

Nutritional labeling has been of much interest to policy makers and health advocates due to rising obesity trends. So can nutritional label use really help reduce body weight outcomes?
Andreas Drichoutis, Panagiotis Lazaridis, Rodolfo M. Nayga, Jr.   +2 more
core