Purpose: We analyzed studies validating the effectiveness and deficiencies of simulation for training and assessment in urology. We documented simulation types (synthetic, virtual reality and animal models), participant experience level and tasks performed. The feasibility, validity, cost-effectiveness, reliability and educational impact of the simulators were also evaluated.
Materials And Methods: The MEDLINE®, EMBASE™ and PsycINFO® databases were systematically searched until September 2010. References from retrieved articles were reviewed to broaden the search.
Results: The study included case reports, case series and empirical studies of training and assessment in urology using procedural simulation. The model name, training tasks, participant level, training duration and evaluation scoring were extracted from each study. We also extracted data on face, content and construct validity. Most studies suitably addressed content, construct and face validation as well as the feasibility, educational impact and cost-effectiveness of simulation models. Synthetic, animal and virtual reality models were demonstrated to be effective training and assessment tools for junior trainees. Few investigators looked at the transferability of skills from simulation to real patients.
Conclusions: Current simulation models are valid and reliable for the initial phase of training and assessment. For advanced and specialist level skill acquisition animal models can be used but availability is limited due to supply shortages and ethical restrictions. More research is needed to validate simulated environments for senior trainees and specialists.
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http://dx.doi.org/10.1016/j.juro.2011.02.2684 | DOI Listing |
Front Biosci (Landmark Ed)
January 2025
Division of Biochemistry and Molecular Biology, Federal State Budgetary Educational Institution of Higher Education "Siberian State Medical University" of the Ministry of Health of Russia, 634050 Tomsk, Russia.
Background: Over the past five years, the pregnancy rate in assisted reproductive technology (ART) programs in Russia has remained relatively stable. The aim of this study was to assess the distribution of monocyte and macrophage subsets in the blood and follicular fluid of infertile women undergoing assisted reproductive technology.
Methods: The study involved 45 women with a mean age of 35 ± 4.
Pharm Biol
December 2025
The Affiliated Hospital, Changchun University of Chinese Medicine, Changchun, China.
Context: The decline in ovarian reserve is a major concern in female reproductive health, often associated with oxidative stress and mitochondrial dysfunction. Although ginsenoside Rg1 is known to modulate mitophagy, its effectiveness in mitigating ovarian reserve decline remains unclear.
Objective: To investigate the role of ginsenoside Rg1 in promoting mitophagy to preserve ovarian reserve.
Aesthet Surg J
January 2025
Department of Plastic, Reconstructive and Aesthetic Surgery, Faculty of Medicine, Altınbas University, Istanbul, Turkey.
Background: Artificial intelligence (AI)-driven technologies offer transformative potential in plastic surgery, spanning pre-operative planning, surgical procedures, and post-operative care, with the promise of improved patient outcomes.
Objectives: To compare the web-based ChatGPT-4o (omni; OpenAI, San Francisco, CA) and Gemini Advanced (Alphabet Inc., Mountain View, CA), focusing on their data upload feature and examining outcomes before and after exposure to CME articles, particularly regarding their efficacy relative to human participants.
Br J Hosp Med (Lond)
January 2025
Nursing Department, Zhang Ye People's Hospital Affiliated to Hexi University, Zhangye, Gansu, China.
Diabetes is a chronic lifelong condition that requires consistent self-care and daily lifestyle adjustments. Effective disease management involves regular blood glucose monitoring and ongoing nursing support. Inadequate education and poor self-management are key factors contributing to increased mortality among diabetic individuals.
View Article and Find Full Text PDFBr J Hosp Med (Lond)
January 2025
Speech and Language Rehabilitation Department, Beijing Rehabilitation Hospital Affiliated with Capital Medical University, Beijing, China.
The background for establishing and verifying a dehydration prediction model for elderly patients with post-stroke dysphagia (PSD) based on General Utility for Latent Process (GULP) is as follows: For elderly patients with PSD, GULP technology is utilized to build a dehydration prediction model. This aims to improve the accuracy of dehydration risk assessment and provide clinical intervention, thereby offering a scientific basis and enhancing patient prognosis. This research highlights the innovative application of GULP technology in constructing complex medical prediction models and addresses the special health needs of elderly stroke patients.
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