基于虚拟教研室的公共卫生安全素养培育课程构建及实践

目的:探讨基于虚拟教研室的公共卫生安全素养培育课程构建及实践。方法:选取某医学院校专科护理专业学生(护生)为研究对象,将护理1班45人作为试验组,将护理2班43人作为对照组,对照组对公共卫生安全知识实施线上与线下的常规教学,试验组实施基于虚拟教研室的公共卫生安全素养培育课程。比较两组护生内容掌握情况及学习满意度。结果:试验组护生的学习成绩明显高于对照组(P<0.01),试验组护生对教学的满意度为95.6%(43/45),明显高于对照组(P<0.05)。结论:基于虚拟教研室的公共卫生安全素养培育课程构建既可以广泛促进不同专业教师进行教学研究交流,全面提高教师教书育人能力,又可以使护生在学习过程中接触不同专业、不同领域的知识与技能,注重护生主体作用,提高学习效果和学习满意度。     

The scope of computerized simulation in competency-based maxillofacial training: a systematic review

Oral and maxillofacial surgery (OMS) teaching is set to undergo a paradigm shift towards competency-based training. With increasing focus on resident skill development and patient safety, computerized simulators are likely to play a more mainstream role in OMS training. A systematic review of the available literature was conducted, in accordance with the PRISMA guidelines, to highlight the scope of computerized simulation in OMS teaching. A PubMed search was performed by two independent reviewers, and 35 articles published in English between 2010 and 2021 that reported the use of computerized simulation for teaching maxillofacial procedures were included in the analysis. Eight articles on minor oral surgery, seven on orthognathic surgery, five on maxillofacial trauma, five on cleft lip and palate surgery, three articles each on nerve block techniques, endoscopic procedures, and reconstructive surgery, and one article on fibre-optic intubation reported the use of computerized simulation that can be applied to OMS training. Ten randomized controlled trials were identified in the search. However there was marked heterogeneity among the studies. Simulator training for skill acquisition mentored by an expert OMS educator could offer holistic resident training; however more studies that test common themes of resident training such as knowledge acquisition and skill development are necessary.     

Clinical Simulation Augments Traditional Interviewing of Advanced Practice Provider Candidates

An essential role of critical care advanced practice providers—advanced practice registered nurses and physician assistants—is to have knowledge and competency to make accurate and efficient decisions. The ability to manage clinical scenarios involving medically deteriorating patients requires higher-order cognitive thinking and leadership skills that are challenging to extrapolate in traditional interviews. In critical care, advanced practice providers must make rapid clinical assessments and implement appropriate medical interventions to deter progression of life-threatening illnesses. Adding clinical simulation to the traditional interview allows interviewers to evaluate applicants’ crisis resource management skills, leadership, and clinical competency.     

外柱细胞软化对Corti器感音影响的生物力学研究

Corti器的感音过程容易受到内部结构属性变化的影响。外柱细胞血管舒张刺激磷蛋白缺失会减缓肌动蛋白丝的形成,从而产生听力延迟。本研究运用COMSOL建立三维有限元模型研究肌动蛋白缺失导致外柱细胞软化时,Corti器感音过程中基底膜和外毛细胞与Deiters细胞结合点的力学行为变化。结果表明,外柱细胞软化会削弱外毛细胞主动力对基底膜位移增益的放大作用,但削弱作用并不会立即产生,Corti器存在维持正常功能的"缓冲"阶段。在100 dB和120 dB之间可能存在一个声压级临界值,在该临界值两侧外柱细胞软化对基底膜应力变化的影响是截然相反的。另外外柱细胞软化对不同外毛细胞与Deiters细胞结合点力学行为的影响也不同,位移增益优先级会因此产生改变。     

Design and validation of a virtual reality trainer for ultrasound-guided regional anaesthesia

Virtual reality is a form of high-fidelity simulation that may be used to enhance the quality of medical education. We created a bespoke virtual reality trainer software using high resolution motion capture and ultrasound imagery to teach cognitive-motor needling skills necessary for the performance of ultrasound-guided regional anaesthesia. The primary objective of this study was to determine the construct validity between novice and experienced regional anaesthetists. Secondary objectives were: to create learning curves for needling performance; compare the virtual environment immersion with other high-fidelity virtual reality software; and compare cognitive task loads imposed by the virtual trainer compared with real-life medical procedures. We recruited 21 novice and 15 experienced participants, each of whom performed 40 needling attempts on four different virtual nerve targets. Performance scores for each attempt were calculated based on measured metrics (needle angulation, withdrawals, time taken) and compared between the groups. The degree of virtual reality immersion was measured using the Presence Questionnaire, and cognitive burden was measured using the NASA-Task Load Index. Scores by experienced participants were significantly higher than novices (p = 0.002) and for each nerve target (84% vs. 77%, p = 0.002; 86% vs. 79%, p = 0.003; 87% vs. 81%, p = 0.002; 87% vs. 80%, p = 0.003). Log–log transformed learning curves demonstrated individual variability in performance over time. The virtual reality trainer was rated as being comparably immersive to other high-fidelity virtual reality software in the realism, possibility to act and quality of interface subscales (all p > 0.06) but not in the possibility to examine and self-performance subscales (all p < 0.009). The virtual reality trainer created workloads similar to those reported in real-life procedural medicine (p = 0.53). This study achieved initial validation of our new virtual reality trainer and allows progression to a planned definitive trial that will compare the effectiveness of virtual reality training on real-life regional anaesthesia performance.     

Modeling the Recovery of Elective Waiting Lists Following COVID-19: Scenario Projections for England

ObjectivesA significant indirect impact of COVID-19 has been the increasing elective waiting times observed in many countries. In England’s National Health Service, the waiting list has grown from 4.4 million in February 2020 to 5.7 million by August 2021. The objective of this study was to estimate the trajectory of future waiting list size and waiting times up to December 2025.MethodsA scenario analysis was performed using computer simulation and publicly available data as of November 2021. Future demand assumed a phased return of various proportions (0%, 25%, 50%, and 75%) of the estimated 7.1 million referrals “missed” during the pandemic. Future capacity assumed 90%, 100%, and 110% of that provided in the 12 months immediately before the pandemic.ResultsAs a worst-case scenario, the waiting list would reach 13.6 million (95% confidence interval 12.4-15.6 million) by Autumn 2022, if 75% of missed referrals returned and only 90% of prepandemic capacity could be achieved. The proportion of patients waiting under 18 weeks would reduce from 67.6% in August 2021 to 42.2% (37.4%-46.2%) with the number waiting over 52 weeks reaching 1.6 million (0.8-3.1 million) by Summer 2023. At this time, 29.0% (21.3%-36.8%) of patients would be leaving the waiting list before treatment. Waiting lists would remain pressured under even the most optimistic of scenarios considered, with 18-week performance struggling to maintain 60%.ConclusionsThis study reveals the long-term challenge for the National Health Service in recovering elective waiting lists and potential implications for patient outcomes and experience.     

Molecular modeling in cardiovascular pharmacology: Current state of the art and perspectives

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Assessment of the Benefits of Targeted Interventions for Pandemic Control in China Based on Machine Learning Method and Web Service for COVID-19 Policy Simulation

Taking the Chinese city of Xiamen as an example, simulation and quantitative analysis were performed on the transmissions of the Coronavirus Disease 2019(COVID-19) and the influence of intervention combinations to assist policymakers in the preparation of targeted response measures. A machine learning model was built to estimate the effectiveness of interventions and simulate transmission in different scenarios. The comparison was conducted between simulated and real cases in Xiamen. A web inter...