Concept and Prelimnary Design of an Economical Bag Valve Mask Compressor as a Prototype for Simple Ventilator During COVID-19

COVID-19 Lessons Learned: Response to the Anticipated Ventilator Shortage

Early in the COVID-19 pandemic predictions of a worldwide ventilator shortage prompted a worldwide search for solutions. The impetus for the scramble for ventilators was spurred on by inaccurate and often unrealistic predictions of ventilator requirements. Initial efforts looked simply at acquiring as many ventilators as possible from national and international sources. Ventilators from the Strategic National Stockpile were distributed to early hotspots in the Northeast and Northwest United States. In a triumph of emotion over logic, well-intended experts from other industries turned their time, talent, and treasure toward making a ventilator for the first time. Interest in shared ventilation (more than one patient per ventilator) was ignited by an ill-advised video on social media that ignored the principles of gas delivery in deference to social media notoriety. With shared ventilation, a number of groups mistook a physiologic problem for a plumbing problem. The United States government invoked the Defense Production Act to push automotive manufacturers to partner with existing ventilator manufacturers to speed production. The FDA granted emergency use authorization for "splitters" to allow shared ventilation as well as for ventilators and ancillary equipment. Rationing of ventilators was discussed in the lay press and medical literature but was never necessary in the US. Finally, planners realized that staff with expertise in providing mechanical ventilation were the most important shortage. Over 200,000 ventilators were purchased by the United States government, states, cities, health systems, and individuals. Most had little value in caring for patients with COVID-19 ARDS. This paper attempts to look at where miscalculations were made, with an eye toward what we can do better in the future.

Experimental validation of a portable tidal volume indicator for bag valve mask ventilation

INTRODUCTION

Short-term emergency ventilation is most typically accomplished through bag valve mask (BVM) techniques. BVMs like the AMBU® bag are cost-effective and highly portable but are also highly prone to user error, especially in high-stress emergent situations. Inaccurate and inappropriate ventilation has the potential to inflict great injury to patients through hyper- and hypoventilation. Here, we present the BVM Emergency Narration-Guided Instrument (BENGI) - a tidal volume feedback monitoring device that provides instantaneous visual and audio feedback on delivered tidal volumes, respiratory rates, and inspiratory/expiratory times. Providing feedback on the depth and regularity of respirations enables providers to deliver more consistent and accurate tidal volumes and rates. We describe the design, assembly, and validation of the BENGI as a practical tool to reduce manual ventilation-induced lung injury.

METHODS

The prototype BENGI was assembled with custom 3D-printed housing and commercially available electronic components. A mass flow sensor in the central channel of the device measures air flow, which is used to calculate tidal volume. Tidal volumes are displayed via an LED ring affixed to the top of the BENGI. Additional feedback is provided through a speaker in the device. Central processing is accomplished through an Arduino microcontroller. Validation of the BENGI was accomplished using benchtop simulation with a clinical ventilator, BVM, and manikin test lung. Known respiratory quantities were delivered by the ventilator which were then compared to measurements from the BENGI to validate the accuracy of flow measurements, tidal volume calculations, and audio cue triggers.

RESULTS

BENGI tidal volume measurements were found to lie within 4% of true delivered tidal volume values (95% CI of 0.53 to 3.7%) when breaths were delivered with 1-s inspiratory times, with similar performance for breaths delivered with 0.5-s inspiratory times (95% CI of 1.1 to 6.7%) and 2-s inspiratory times (95% CI of -1.1 to 2.3%). Audio cues "Bag faster" (1.84 to 2.03 s), "Bag slower" (0.35 to 0.41 s), and "Leak detected" (43 to 50%) were triggered close to target trigger values (2.00 s, 0.50 s, and 50%, respectively) across varying tidal volumes.

CONCLUSIONS

The BENGI achieved its proposed goals of accurately measuring and reporting tidal volumes delivered through BVM systems, providing immediate feedback on the quality of respiratory performance through audio and visual cues. The BENGI has the potential to reduce manual ventilation-induced lung injury and improve patient outcomes by providing accurate feedback on ventilatory parameters.