Ex-vivo and live animal models are equally effective training for the management of a penetrating cardiac injury.

World J Emerg Surg

Center of Development for Advanced Medical Technology, Jichi Medical University, 3311-1 Yakushiji, Shimotsukeshi, Tochigiken 329-0498 Japan ; Department of Digestive Surgery, Jichi Medical University, 3311-1 Yakushiji, Shimotsukeshi, Tochigiken 329-0498 Japan.

Published: September 2016

Background: Live tissue models are considered the most useful simulation for training in the management for hemostasis of penetrating injuries. However, these models are expensive, with limited opportunities for repetitive training. Ex-vivo models using tissue and a fluid pump are less expensive, allow repetitive training and respect ethical principles in animal research. The purpose of this study is to objectively evaluate the effectiveness of ex-vivo training with a pump, compared to live animal model training. Staff surgeons and residents were divided into live tissue training and ex-vivo training groups. Training in the management of a penetrating cardiac injury was conducted for each group, separately. One week later, all participants were formally evaluated in the management of a penetrating cardiac injury in a live animal.

Results: There are no differences between the two groups regarding average years of experience or previous trauma surgery experience. All participants achieved hemostasis, with no difference between the two groups in the Global Rating Scale score (ex-vivo: 25.2 ± 6.3, live: 24.7 ± 6.3, p = 0.646), blood loss (1.6 ± 0.7, 2.0 ± 0.6, p = 0.051), checklist score (3.7 ± 0.6, 3.6 ± 0.9, p = 0.189), or time required for repair (101 s ± 31, 107 s ± 15, p = 0.163), except overall evaluation (3.8 ± 0.9, 3.4 ± 0.9, p = 0.037). The internal consistency reliability and inter-rater reliability in the Global Rating Scale were excellent (0.966 and 0.953 / 0.719 and 0.784, respectively), and for the checklist were moderate (0.570 and 0.636 / 0.651 and 0.607, respectively). The validity is rated good for both the Global Rating Scale (Residents: 21.7 ± 5.6, Staff: 28.9 ± 4.7, p = 0.000) and checklist (Residents: 3.4 ± 0.9, Staff Surgeons: 3.9 ± 0.3, p = 0.003). The results of self-assessment questionnaires were similarly high (4.2-4.9) with scores in self-efficacy increased after training (pre: 1.7 ± 0.8, post: 3.2 ± 1.0, p = 0.000 in ex-vivo, pre: 1.9 ± 1.0, post: 3.7 ± 0.7, p = 0.000 in live). Scores comparing pre-training and post-evaluation (pre: 1.7 ± 0.8, post: 3.7 ± 0.9, p = 0.000 in ex-vivo, pre: 1.9 ± 1.0, post: 3.8 ± 0.7, p = 0.000 in live) were increased.

Conclusion: Training with an ex-vivo model and live tissue training are similar for the management of a penetrating cardiac injury, with increased self-efficacy of participants in both groups. The ex-vivo model is useful to learn hemostatic skills in trauma surgery.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5007845PMC
http://dx.doi.org/10.1186/s13017-016-0104-3DOI Listing

Publication Analysis

Top Keywords

training management
16
management penetrating
16
penetrating cardiac
16
cardiac injury
16
training
12
live tissue
12
training ex-vivo
12
global rating
12
rating scale
12
ex-vivo
9

Similar Publications

Importance: Dual-eligible older adults rely on Medicaid to pay for Medicare premiums and cost sharing in addition to supplemental services including dental and long-term care. However, the unique experiences of dual-eligible older adults with Medicaid unwinding remain unknown.

Objective: To assess the awareness and experiences of dual-eligible older adults with Medicaid redetermination.

View Article and Find Full Text PDF

Introduction: Screening diabetic retinopathy (DR) for timely management can reduce global blindness. Many existing DR screening programs worldwide are non-digital, standalone, and deployed with grading retinal photographs by trained personnel. To integrate the screening programs, with or without artificial intelligence (AI), into hospital information systems to improve their effectiveness, the non-digital workflow must be transformed into digital.

View Article and Find Full Text PDF

[Management of acute coronary syndrome].

Herz

January 2025

Herzzentrum Leipzig, Universitätsklinik für Kardiologie, Strümpellstr. 39, 04289, Leipzig, Deutschland.

Coronary artery disease (CAD) is the leading cause of death worldwide. Acute coronary syndrome (ACS) encompasses a spectrum of diagnoses ranging from unstable angina pectoris to myocardial infarction with and without ST-segment elevation and frequently presents as the first clinical manifestation. It is crucial in this scenario to perform a timely and comprehensive assessment of patients by evaluating the clinical presentation, electrocardiogram and laboratory diagnostics using highly sensitivity cardiac troponin in order to initiate a timely and risk-adapted continuing treatment with immediate or early invasive coronary angiography.

View Article and Find Full Text PDF

Purpose Of Review: This article discusses a tailored approach to managing cardiogenic shock and temporary mechanical circulatory support (tMCS). We also outline specific mobilization strategies for patients with different tMCS devices and configurations, which can be enabled by this tailored approach to cardiogenic shock management.

Recent Findings: Safe and effective mobilization of patients with cardiogenic shock receiving tMCS can be accomplished.

View Article and Find Full Text PDF

Purpose: To develop a deep learning (DL) model based on primary tumor tissue to predict the lymph node metastasis (LNM) status of muscle invasive bladder cancer (MIBC), while validating the prognostic value of the predicted aiN score in MIBC patients.

Methods: A total of 323 patients from The Cancer Genome Atlas (TCGA) were used as the training and internal validation set, with image features extracted using a visual encoder called UNI. We investigated the ability to predict LNM status while assessing the prognostic value of aiN score.

View Article and Find Full Text PDF

Want 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!