A COVID-19 Airway Management Innovation with Pragmatic Efficacy Evaluation: The Patient Particle Containment Chamber

Use of a Negative Pressure Containment Pod Within Ambulance-Workspace During Pandemic Response

Emergency medical service (EMS) providers have a higher potential exposure to infectious agents than the general public (Nguyen et al., 2020, "Risk of COVID-19 Among Frontline Healthcare Workers and the General Community: A Prospective Cohort Study," Lancet Pub. Health, 5(9), pp. e475-e483; Brown et al., 2021, "Risk for Acquiring Coronavirus Disease Illness Among Emergency Medical Service Personnel Exposed to Aerosol-Generating Procedures," Emer. Infect. Disease J., 27(9), p. 2340). The use of protective equipment may reduce, but does not eliminate their risk of becoming infected as a result of these exposures. Prehospital environments have a high risk of disease transmission exposing EMS providers to bioaerosols and droplets from infectious patients. Field intubation procedures may be performed causing the generation of bioaerosols, thereby increasing the exposure of EMS workers to pathogens. Additionally, ambulances have a reduced volume compared to a hospital treatment space, often without an air filtration system, and no control mechanism to reduce exposure. This study evaluated a containment plus filtration intervention for reducing aerosol concentrations in the patient module of an ambulance. Aerosol concentration measurements were taken in an unoccupied research ambulance at National Institute for Occupational Safety and Health (NIOSH) Cincinnati using a tracer aerosol and optical particle counters (OPCs). The evaluated filtration intervention was a containment pod with a high efficiency particulate air (HEPA)-filtered extraction system that was developed and tested based on its ability to contain, capture, and remove aerosols during the intubation procedure. Three conditions were tested (1) baseline (without intervention), (2) containment pod with HEPA-1, and (3) containment pod with HEPA-2. The containment pod with HEPA-filtered extraction intervention provided containment of 95% of the total generated particle concentration during aerosol generation relative to the baseline condition, followed by rapid air cleaning within the containment pod. This intervention can help reduce aerosol concentrations within ambulance patient modules while performing aerosol-generating procedures.

Aerosol containment device design considerations and performance evaluation metrics

BACKGROUND

Spurred by the Coronavirus infectious disease 2019 pandemic, aerosol containment devices (ACDs) were developed to capture infectious respiratory aerosols generated by patients at their source. Prior reviews indicated that such devices had low evidence of effectiveness, but did not address how ACDs should be evaluated, how well they should perform, nor have clearly defined performance standards. Towards developing design criteria for ACDs, two questions were posed: 1) What characteristics have guided the design of ACDs? 2) How have these characteristics been evaluated?

METHODS

A scoping review was performed consistent with PRISMA guidelines. Data were extracted with respect to general study information, intended use of the device, device design characteristics and evaluation.

RESULTS

Fifty-four articles were included. Evaluation was most commonly performed with respect to device aerosol containment (n = 31, 61%), with only 5 (9%), 3 (6%) and 8 (15%) formally assessing providing experience, patient experience and procedure impact, respectively. Nearly all of the studies that explored provider experience and procedure impact studied intubation. Few studies provided a priori performance criteria for any evaluation metric, or referenced any external guidelines by which to bench mark performance.

CONCLUSION

With respect to aerosol containment, ACDs should reduce exposure among HCP with the device compared with the absence of the device, and provide ≥90% reduction in respirable aerosols, equivalent in performance to N95 filtering facepiece respirators, if the goal is to reduce reliance on personal protective equipment. The ACD should not increase awkward or uncomfortable postures, or adversely impact biomechanics of the procedure itself as this could have implications for procedure outcomes. A variety of standardized instruments exist to assess the experience of patients and healthcare personnel. Integration of ACDs into routine clinical practice requires rigorous studies of aerosol containment and the user experience.

A Narrative Review of Innovative Responses During the COVID-19 Pandemic in 2020

Objectives: The coronavirus disease 2019 (COVID-19) pandemic presented unprecedented challenges to healthcare systems worldwide. While existing studies on innovation have typically focused on technology, health providers still only have a vague understanding of the features of emergency responses during resource exhaustion in the early stage of a pandemic. Thus, a better understanding of innovative responses by healthcare systems during a crisis is urgently needed. Methods: Using content analysis, this narrative review examined articles on innovative responses during the COVID-19 pandemic that were published in 2020. Results: A total of 613 statements about innovative responses were identified from 296 articles and were grouped under the following thematic categories: medical care (n = 273), workforce education (n = 144), COVID-19 surveillance (n = 84), medical equipment (n = 59), prediction and management (n = 34), and governance (n = 19). From the four types of innovative responses extracted, technological innovation was identified as the major type of innovation during the COVID-19 pandemic, followed by process innovations, frugal innovation, and repurposing. Conclusion: Our review provides insights into the features, types, and evolution of innovative responses during the COVID-19 pandemic. This review can help health providers and society show better and quicker responses in resource-constrained conditions in future pandemics.

Learning the Language of Medical Device Innovation: A Longitudinal Interdisciplinary Elective for Medical Students

PROBLEM

Physicians are playing a growing role as clinician-innovators. Academic physicians are well positioned to contribute to the medical device innovation process, yet few medical school curricula provide students opportunities to learn the conceptual framework for clinical needs finding, needs screening, concept generation and iterative prototyping, and intellectual property management. This framework supports innovation and encourages the development of valuable interdisciplinary communication skills and collaborative learning strategies.

APPROACH

Our university offers a novel 3-year-long medical student Longitudinal Interdisciplinary Elective in Biodesign (MSLIEB) that teaches medical device innovation in 4 stages: (1) seminars and small-group work, (2) shared clinical experiences for needs finding, (3) concept generation and product development by serving as consultants for biomedical engineering capstone projects, and (4) reflection and mentorship. The MSLIEB objectives are to: create a longitudinal interdisciplinary peer mentorship relationship between undergraduate biomedical engineering students and medical students, and encourage codevelopment of professional identities in relation to medical device innovation.

OUTCOMES

The MSLIEB enrolled 5 entering cohorts from 2017 to 2021 with a total of 37 medical student participants. The first full entering cohort of 12 medical students produced 8 mentored biomedical engineering capstone projects, 7 of which were based on clinical needs statements derived from earlier in the elective. Medical student participants have coauthored poster and oral presentations; contributed to projects that won WolfieTank, a university-wide competition modeled after the television show Shark Tank; and participated in the filing of provisional patents. Students reflecting on the course reported a change in their attitude towards existing medical problems, felt better-equipped to collaboratively design solutions for clinical needs, and considered a potential career path in device design.

NEXT STEPS

The MSLIEB will be scaled up by recruiting additional faculty, broadening clinical opportunities to include the outpatient setting, and increasing medical student access to rapid prototyping equipment.

Detection of COVID-19 from CT and Chest X-ray Images Using Deep Learning Models

Coronavirus 2019 (COVID-19) is a highly transmissible and pathogenic virus caused by severe respiratory syndrome coronavirus 2 (SARS-CoV-2), which first appeared in Wuhan, China, and has since spread in the whole world. This pathology has caused a major health crisis in the world. However, the early detection of this anomaly is a key task to minimize their spread. Artificial intelligence is one of the approaches commonly used by researchers to discover the problems it causes and provide solutions. These estimates would help enable health systems to take the necessary steps to diagnose and track cases of COVID. In this review, we intend to offer a novel method of automatic detection of COVID-19 using tomographic images (CT) and radiographic images (Chest X-ray). In order to improve the performance of the detection system for this outbreak, we used two deep learning models: the VGG and ResNet. The results of the experiments show that our proposed models achieved the best accuracy of 99.35 and 96.77% respectively for VGG19 and ResNet50 with all the chest X-ray images.

3D Printed N-95 Masks During the COVID-19 Pandemic: Lessons Learned

Early in 2020, the pandemic resulted in an enormous demand for personal protective equipment (PPE), which consists of face masks, face shields, respirators, and gowns. At our institution, at the request of hospital administration, the Lifespan 3D Printing Laboratory spearheaded an initiative to produce reusable N95 masks for use in the hospital setting. Through this article, we seek to detail our experience designing and 3D printing an N95 mask, highlighting the most important lessons learned throughout the process. Foremost among these, we were successful in producing a non-commercial N95 alternative mask which could be used in an era when N95 materials were extremely limited in supply. We identified five key lessons related to design software, 3D printed material airtightness, breathability and humidity dispersal, and ability for communication. By sharing our experience and the most valuable lessons we learned through this process, we hope to provide a helpful foundation for future 3D-printed N95 endeavors.

Active Versus Passive Flow Control in UVC FILTERs for COVID-19 Containment

Ultraviolet radiation as a germicide is widely used in the health field and even in domestic hygiene. Here, we propose an improvement in low-cost portable units of filtration for indoor air, which is based on ultraviolet radiation. In the current technology, to carry out an air filtration with a suspension of aerosols in which there is a likely concentration of pathogens, whether viral, bacterial or molds, the air is forced to pass as close as possible to the ionizing radiation source (near field). Since the optical mass is very small, the desired effect can be achieved in a considerably short time, deactivating the infective potential of these biological agents. The proposal of this work is the regulation of the flow or speed control of passage through these filters by passive elements instead of by electronic control systems. For this, two devices have been designed, simulated, and built, obtaining similar net pathogen inactivation rates under different flow rates. The passive flow control device has demonstrated higher performance in terms of flow rate and lower cost of production since they do not require electronics and are produced with fewer diodes. This passive device has also shown a lower projection of maintenance cost, lower energy consumption rate (higher efficiency), and longer projection of useful life.

A Fully-Automated Method to Evaluate Coronavirus Disease Progression with COVID-19 Cough Sounds Using Minimal Phase Information

This paper focuses on an important issue of disease progression of COVID-19 (coronavirus disease 2019) through processing COVID-19 cough sounds by proposing a fully-automated method. The new method is based on time-domain exploiting only phase 1 data which is always available for any cough events. The proposed approach generates plausible click sequences consist of clicks for various cough samples from covid-19 patients. The click sequence, which is extracted from the phase slope function of an input signal, is used to calculate inter-click intervals (ICIs), and thereby a scoring index (SI) is derived based on coefficient of variation(CV) of the extracted ICIs. Moreover, probability density function (pdf) of the output click sequence is obtained. The method does not need to adjust any parameters. The experimental results achieved from real-recorded COVID-19 cough data using the medically annotated Novel Coronavirus Cough Database (NoCoCoDa) reveal that the proposed time-domain method can be a very useful tool for automatic cough sound processing to determine the disease progression of coronavirus patients.

The barrier techniques for airway management in covid-19 patients - review of literature

The coronavirus disease 2019 (COVID-19) has emerged as a pandemic and shall prevail for some time around the globe. The disease can manifest from asymptomatic to severe respiratory compromise requiring airway intervention. Transmission of COVID-19 has been reported to be by droplets, fomites, and aerosols, and airway management is an aerosol-generating procedure. The high viral load in the patient's airway puts the clinician performing intubation at a very high risk of viral load exposure. So, the need for barrier devices was considered and led to reporting of various such devices. All these devices have been reported individually and have not been compared. We present a review of all the information on these devices based on the reported literature.