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http://dx.doi.org/10.1371/journal.pntd.0013351 | DOI Listing |
JAMA Surg
September 2025
Department of Surgery, Meander Medical Center, Amersfoort, the Netherlands.
Importance: Stoma reversal is associated with few complications. However, recent studies show that 1 in 3 patients develop an incisional hernia, for which half of the patients receive surgical correction.
Objective: To investigate whether prophylactic synthetic mesh placement in the retromuscular space during stoma reversal reduces the rate of stomal site incisional hernias.
Matern Child Health J
September 2025
Department of Nursing, New Taipei Municipal TuCheng Hospital (Built and Operated By Chang Gung Medical Foundation), New Taipei, Taiwan.
Resusc Plus
November 2025
Department of Anaesthesiology and Intensive Care Medicine, Innsbruck Medical University Hospital, Medical University of Innsbruck, Anichstrasse 35, 6020 Innsbruck, Austria.
Background: The aim of this study was to analyse the influence of voice navigation in a new generation of transceivers on the time and success rate of transceiver search in a simulated avalanche rescue scenario.
Methods: Fifty participants performed two randomized test runs, using two different transmitters with and without voice navigation. Primary outcome was success rate, total transceiver search and total location time, secondary outcome parameters comprised predefined time intervals (coarse search time, fine search time, probing time) and deviations from the recommended standard search procedure.
Clin Ophthalmol
September 2025
Faculty of Biomedical Engineering, Czech Technical University in Prague, Kladno, Czech Republic.
Aim: The objective of this study was to evaluate the efficacy of DIMS (Defocus Incorporated Multiple Segments) in comparison to control group (CTRL) in a wide age group of European progressive myopes (6-26 years).
Methods: In this prospective, non-randomised observational study, 78 myopes with progression myopia to -0.25 to -8.
Alpha Psychiatry
August 2025
Information Sciences and Technology, George Mason University, Fairfax, VA 22030, USA.
Background: Herein, we report on the initial development, progress, and future plans for an autonomous artificial intelligence (AI) system designed to manage major depressive disorder (MDD). The system is a web-based, patient-facing conversational AI that collects medical history, provides presumed diagnosis, recommends treatment, and coordinates care for patients with MDD.
Methods: The system includes seven components, five of which are complete and two are in development.