AI Article Synopsis
- A new, cost-effective abscess model was developed using common materials for use in medical training, costing less than $1 per use.
- The model was tested with 25 pre-clinical medical students, showing significant improvement in their skills before and after training.
- This innovative approach facilitates realistic practice for treating subcutaneous abscesses and can be easily integrated into cadaver labs for multi-procedural resident training.
Article Abstract
Background: Treatment of a subcutaneous abscess is a commonly encountered scenario across multiple specialties. Prior simulation models for abscess incision and drainage have been limited by their cost and reproducibility.
Methods: We developed a realistic abscess model with commonly available materials that can be utilized in fresh cadaver labs at a cost of less than $1 USD per use. The model was evaluated for content validity with pre- and post-measures by 25 pre-clinical medical students.
Results: The model described herein successfully simulates commonly encountered subcutaneous abscesses. Pre and post-training surveys demonstrated a significant increase in all outcomes measures.
Conclusions: The model presented in this manuscript can be easily incorporated into training programs that utilize a fresh cadaver lab for multi-procedural resident training. It provides a realistic abscess that can be placed in almost any anatomical location at a fraction of the cost, and significantly reduced preparation time compared to previously described models.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1016/j.amjsurg.2019.06.011 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Task Offloading with LLM-Enhanced Multi-Agent Reinforcement Learning in UAV-Assisted Edge Computing.
Sensors (Basel)
December 2024
School of Microelectronics and Communication Engineering, Chongqing University, Chongqing 400044, China.
Unmanned aerial vehicles (UAVs) furnished with computational servers enable user equipment (UE) to offload complex computational tasks, thereby addressing the limitations of edge computing in remote or resource-constrained environments. The application of value decomposition algorithms for UAV trajectory planning has drawn considerable research attention. However, existing value decomposition algorithms commonly encounter obstacles in effectively associating local observations with the global state of UAV clusters, which hinders their task-solving capabilities and gives rise to reduced task completion rates and prolonged convergence times.
View Article and Find Full Text PDFToward one-step As(III) removal in ultrafiltration with in situ BioMnO cake layer: Mechanism and feasibility insights.
Water Res
January 2025
School of Civil Engineering, Wuhan University, Wuhan, 430072, PR China. Electronic address:
Inorganic arsenic (As) is one of the most significant chemical contaminants in drinking water worldwide. Although membrane-based technologies are commonly used for As removal, they often encounter challenges including complex operation, high energy consumption, and the need for chemical addition. To address these challenges, we proposed a one-step ultrafiltration (UF) process empowered by in situ biogenic manganese oxides (BioMnO) cake layers without any additional chemicals, to treat source water contaminated with both As and manganese (Mn).
View Article and Find Full Text PDFDiscitis: A Rare Presentation and Review of Literature.
HCA Healthc J Med
December 2024
University of Florida College of Medicine, Gainesville, FL.
Background: is an anaerobic gram-negative coccus found as a commensal organism in the oral, respiratory, gastrointestinal, and genitourinary tract of humans. Rarely, it can cause serious infections by the production of lipopolysaccharide, an endotoxin. Although most infections occur in immunocompromised individuals, we herein describe cases of discitis, a rare presentation of , in immunocompetent patients.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!