<p>Participant’s surgical specialty.</p>

Misidentification of dermatologic manifestations of systemic infection can lead to life-threatening developments including sepsis. Training medical providers to accurately identify and respond to infections using simulation could reduce these rates. Moulage of infections are static and require a manual “scene change” during simulation scenarios. A high-fidelity, automated physiology-driven dynamic infection model was developed using the Modular Healthcare Simulation and Education platform that physically changes to simulate the progression of an infected wound. The silicone model was designed using resistive wire, wax actuators, and thermochromic powder. The resistive wire heats the wax, resulting in focal edema, skin warmth, and erythema that reverses with proper recognition and treatment. Without external treatment, purulence is released, and the patient will develop septic physiology. To evaluate the physiological realism and training value of the model, a survey of physicians was conducted using a five-point Likert scale of agreement with 5 being the highest rating. When asked to rate the realism of the model, the mean response was 4.1 ± 0.7. When asked if they thought the model had value for training infection identification, the mean response was 4.3 ± 0.9. Finally, when asked if the dynamic aspect would improve the simulation, the mean response was 4.7 ± 0.6. The dynamic infection model is functional and appealing for practitioners to assist in the early detection of infection. The use of a dynamic training model could potentially be used to replicate other dermatologic manifestations of systemic disease processes and improve medical training.全身性感染的皮肤表现识别失误，可引发脓毒症等致命性并发症。采用模拟训练方式培训医护人员精准识别并处置感染，可有效降低此类不良事件的发生率。现有感染病灶模拟模具均为静态结构，在模拟演练场景中需手动完成「场景切换」。基于模块化医疗模拟与教育（Modular Healthcare Simulation and Education）平台，本研究研发了一款高保真、自动化生理驱动的动态感染模型，可通过物理形态变化模拟感染伤口的病程进展。该硅基模型采用电阻丝、蜡质驱动器与热致变色粉末设计构建：电阻丝加热蜡质驱动器后，可诱发局部水肿、皮肤温热感与红斑；若医护人员能正确识别病灶并给予针对性治疗，上述症状可自行消退。若未接受及时外部干预，病灶将释放脓液，模拟患者出现脓毒症相关生理紊乱。为评估该模型的生理逼真度与训练价值，研究团队采用5级李克特同意量表（5分为最高评分）对医师群体开展问卷调查。当被要求对模型的逼真度进行评分时，受访者平均评分为4.1±0.7；当被问及是否认为该模型对感染识别训练具有应用价值时，平均评分为4.3±0.9；最后，当被问及动态化设计是否能够提升模拟训练效果时，平均评分为4.7±0.6。该动态感染模型具备良好实用性与吸引力，可助力临床从业者提升感染早期识别能力。该动态训练模型的应用思路，或可推广至其他全身性疾病的皮肤表现模拟场景，进一步提升医学培训质量。