Trends in mechanical ventilation: are we ventilating our patients in the best possible way?

Mechanical Ventilation, Past, Present, and Future

Mechanical ventilation (MV) has played a crucial role in the medical field, particularly in anesthesia and in critical care medicine (CCM) settings. MV has evolved significantly since its inception over 70 years ago and the future promises even more advanced technology. In the past, ventilation was provided manually, intermittently, and it was primarily used for resuscitation or as a last resort for patients with severe respiratory or cardiovascular failure. The earliest MV machines for prolonged ventilatory support and oxygenation were large and cumbersome. They required a significant amount of skills and expertise to operate. These early devices had limited capabilities, battery, power, safety features, alarms, and therefore these often caused harm to patients. Moreover, the physiology of MV was modified when mechanical ventilators moved from negative pressure to positive pressure mechanisms. Monitoring systems were also very limited and therefore the risks related to MV support were difficult to quantify, predict and timely detect for individual patients who were necessarily young with few comorbidities. Technology and devices designed to use tracheostomies versus endotracheal intubation evolved in the last century too and these are currently much more reliable. In the present, positive pressure MV is more sophisticated and widely used for extensive period of time. Modern ventilators use mostly positive pressure systems and are much smaller, more portable than their predecessors, and they are much easier to operate. They can also be programmed to provide different levels of support based on evolving physiological concepts allowing lung-protective ventilation. Monitoring systems are more sophisticated and knowledge related to the physiology of MV is improved. Patients are also more complex and elderly compared to the past. MV experts are informed about risks related to prolonged or aggressive ventilation modalities and settings. One of the most significant advances in MV has been protective lung ventilation, diaphragm protective ventilation including noninvasive ventilation (NIV). Health care professionals are familiar with the use of MV and in many countries, respiratory therapists have been trained for the exclusive purpose of providing safe and professional respiratory support to critically ill patients. Analgo-sedation drugs and techniques are improved, and more sedative drugs are available and this has an impact on recovery, weaning, and overall patients' outcome. Looking toward the future, MV is likely to continue to evolve and improve alongside monitoring techniques and sedatives. There is increasing precision in monitoring global "patient-ventilator" interactions: structure and analysis (asynchrony, desynchrony, etc). One area of development is the use of artificial intelligence (AI) in ventilator technology. AI can be used to monitor patients in real-time, and it can predict when a patient is likely to experience respiratory distress. This allows medical professionals to intervene before a crisis occurs, improving patient outcomes and reducing the need for emergency intervention. This specific area of development is intended as "personalized ventilation." It involves tailoring the ventilator settings to the individual patient, based on their physiology and the specific condition they are being treated for. This approach has the potential to improve patient outcomes by optimizing ventilation and reducing the risk of harm. In conclusion, MV has come a long way since its inception, and it continues to play a critical role in anesthesia and in CCM settings. Advances in technology have made MV safer, more effective, affordable, and more widely available. As technology continues to improve, more advanced and personalized MV will become available, leading to better patients' outcomes and quality of life for those in need.

1-year survival rate of SARS-CoV-2 infected patients with acute respiratory distress syndrome based on ventilator types: a multi-center study

The aim of this study was to evaluate the association between types of ventilator and the one-year survival rate of patients with acute respiratory distress syndrome (ARDS) due to SARS‑CoV-2 infection. This multi-center, retrospective observational study was conducted on 1078 adult patients admitted to five university-affiliated hospitals in Iran who underwent mechanical ventilator (MV) due to ARDS. Of the 1078 patients, 781 (72.4%) were managed with ICU ventilators and 297 (27.6%) with transport ventilators. Overall mortality was significantly higher in patients supported with transport ventilator compared to patients supported with ICU ventilator (16.5% vs. 9.3% P = 0.001). Regression analysis revealed that the expected hazard overall increased with age (HR: 1.525, 95% CI 1.112-1.938, P = 0.001), opacity score (HR: 1.448, 95% CI 1.122-2.074, P = 0.001) and transport ventilator versus ICU ventilator (HR: 1.511, 95% CI 1.143-2.187, P = 0.029). The Kaplan-Meier curves of survival analysis showed that patients supported with ICU ventilator had a significantly higher 1-year survival rate (P = 0.001). In MV patients with ARDS due to COVID-19, management with non-ICU sophisticated ventilators was associated with a higher mortality rate compared to standard ICU ventilators. However, more studies are needed to determine the exact effect of ventilator types on the outcome of critically ill patients.

Respiratory Monitoring During Mechanical Ventilation: The Present and the Future

The increased application of mechanical ventilation, the recognition of its harms and the interest in individualization raised the need for an effective monitoring. An increasing number of monitoring tools and modalities were introduced over the past 2 decades with growing insight into asynchrony, lung and chest wall mechanics, respiratory effort and drive. They should be used in a complementary rather than a standalone way. A sound strategy can guide a reduction in adverse effects like ventilator-induced lung injury, ventilator-induced diaphragm dysfunction, patient-ventilator asynchrony and helps early weaning from the ventilator. However, the diversity, complexity, lack of expertise, and associated cost make formulating the appropriate monitoring strategy a challenge for clinicians. Most often, a big amount of data is fed to the clinicians making interpretation difficult. Therefore, it is fundamental for intensivists to be aware of the principle, advantages, and limits of each tool. This analytic review includes a simplified narrative of the commonly used basic and advanced respiratory monitors along with their limits and future prospective.

Nutrition management of critically ill adult patients requiring non-invasive ventilation: a scoping review protocol

OBJECTIVE

This scoping review will identify the current available literature and key concepts in the nutrition management of critically ill adult patients requiring non-invasive ventilation.

INTRODUCTION

Current international nutrition guidelines include recommendations for the nutrition management of critically ill patients who are receiving invasive mechanical ventilation; however, these guidelines do not address nutrition management of patients receiving non-invasive ventilation. This scoping review aims to explore and describe the existing available literature on the nutrition management of critically ill adults requiring non-invasive ventilation.

INCLUSION CRITERIA

This review will consider original research (qualitative, quantitative, or mixed methods studies) reporting on any nutrition parameter for critically ill adult patients (≥16 years) requiring non-invasive ventilation in the intensive care unit. Concepts of interest based on the general intensive care nutrition literature include route of nutrition, recommendations related to macro- or micro-nutrients, nutrition provision, barriers to nutrition provision, and strategies for nutrition management.

METHODS

This review will be conducted in accordance with JBI methodology for scoping reviews using a three-step search strategy. MEDLINE, Embase, Scopus, and Web of Science will be searched to obtain original research available in English and published after 1990. Google Scholar will be searched for gray literature. Duplicates will be removed and studies will be selected by two independent reviewers based on the inclusion criteria. The same two reviewers will extract data in duplicate using a data extraction tool. Any disagreements will be resolved via consensus with a third reviewer. Data extraction will be synthesized in tabular and diagrammatic format.

What the American Journal of Critical Care Junior Peer Reviewers Were Reading During the First Year of the Program: Caring for Patients With COVID-19

The Junior Peer Reviewer program of the American Journal of Critical Care provides mentorship in the peer review process to novice reviewers. The program includes discussion sessions in which participants review articles published in other journals to practice and improve their critical appraisal skills. The articles reviewed during the first year of the program focused on caring for patients with COVID-19. The global pandemic has placed a heavy burden on nursing practice. Prone positioning of patients with acute respiratory failure is likely to improve their outcomes. Hospitals caring for patients needing prolonged ventilation should use evidence-based, standardized care practices to reduce mortality. The burden on uncompensated caregivers of COVID-19 survivors is also high, and such caregivers are likely to require assistance with their efforts. Reviewing these articles was helpful for building the peer review skills of program participants and identifying actionable research to improve the lives of critically ill patients.

Air–Oxygen Blenders for Mechanical Ventilators: A Literature Review

Respiratory diseases are one of the most common causes of death in the world and this recent COVID-19 pandemic is a key example. Problems such as infections, in general, affect many people and depending on the form of transmission they can spread throughout the world and weaken thousands of people. Two examples are severe acute respiratory syndrome and the recent coronavirus disease. These diseases have mild and severe forms, in which patients gravely affected need ventilatory support. The equipment that serves as a basis for operation of the mechanical ventilator is the air–oxygen blender, responsible for carrying out the air–oxygen mixture in the proper proportions ensuring constant supply. New blender models are described in the literature together with applications of control techniques, such as Proportional, Integrative and Derivative (PID); Fuzzy; and Adaptive. The results obtained from the literature show a significant improvement in patient care when using automatic controls instead of manual adjustment, increasing the safety and accuracy of the treatment. This study presents a deep review of the state of the art in air–oxygen benders, identifies the most relevant characteristics, performs a comparison study considering the most relevant available solutions, and identifies open research directions in the topic.

Causes of use errors in ventilation devices - Systematic review

A systematic review according to the PRISMA reporting standard was performed to identify causes of use errors in mechanical ventilators described in the literature. The PubMed search resulted in the inclusion of 16 papers. The errors described were systematically analyzed with regard to their causes and categorized in an adapted cause-and-effect diagram. The causes of use errors were related to specific usability issues and to the general condition that medical staff often work with different ventilators. When many devices are used, the different user interfaces are a source of use errors, since, for example, the same ventilation modes have different names. In order to avoid the identified causes for use errors in the future, this work offers manufacturers of ventilation devices design recommendations and the possibility to include the results in their risk management. In addition, standardizing user interface content across all ventilators, as in ISO 19223, can help reduce use errors.

Impact of the modification of a cleaning and disinfection method of mechanical ventilators of COVID-19 patients and ventilator-associated pneumonia: One year of experience

Background

Mechanical ventilators are essential biomedical devices for the respiratory support of patients with SARS-CoV-2 infection. These devices can be transmitters of bacterial pathogens. Therefore, it is necessary to implement effective disinfection procedures. The aim of this work was to show the impact of the modification of a cleaning and disinfection method of mechanical ventilators of patients with SARS-CoV-2 and ventilator-associated pneumonia.

Methods

A total of 338 mechanical ventilators of patients infected with SARS-CoV-2 and ESKAPE bacteria were divided in two groups. Group A and B were subjected to cleaning and disinfection with superoxidation solution-Cl/enzymatic detergent and isopropyl alcohol, respectively. Both groups were cultured for the detection of ESKAPE bacteria. The isolates were subjected to tests for identification, resistance, adherence, and genomic typing.

Results

Contamination rates of 21.6% (n = 36) were identified in group A. The inspiratory limb was the circuit involved in most cases of postdisinfection contamination. Acinetobacter baumanni, Pseudomonas aeruginosa, and multi-resistant Klebsiella pneumoniae were the pathogens involved in the contamination cases. The pathogens were highly adherent and in the case of A. baumanni, clonal dispersion was detected in 14 ventilators. Disinfection with enzymatic detergents allows a 100% reduction in contamination rates.

Conclusions

The implementation of cleaning and disinfection with enzymatic detergents/isopropyl alcohol of mechanical ventilators of patients with SARS-CoV-2 and ESKAPE bacteria had a positive impact on postdisinfection microbial contamination rates.

Low-cost, rapidly deployable emergency mechanical ventilators during the COVID-19 pandemic in a developing country: Comparing development feasibility between bag-valve and positive airway pressure designs

The COVID-19 pandemic disrupted the world by interrupting most supply chains, including that of the medical supply industry. The threat imposed by export restriction measures and the limitation in the availability of mechanical ventilators posed a higher risk for smaller, developing countries, used to importing most of their technologies. To actively respond to the possible device shortage, the initiative "Ventilators for Panama" was established and was able to develop two different, non-competing, open-source hardware mechanical ventilator models for emergency use in case of shortages: one based on a bag-valve design and another based on positive airway pressure. The aim of this article is to compare both devices in terms of feasibility and functionality. Results from the functional testing show that both devices perform within specification, as the error percentage is lower than 5% for the desired pressure values and a standard deviation of less than 0.5 for all cases.Clinical Relevance- This study shows the feasibility of quickly deploying two different mechanical ventilator designs for emergency use and their effectiveness.

Open access spreadsheet application for learning spontaneous breathing mechanics and mechanical ventilation

Mechanical ventilation, either invasive or noninvasive, is crucial to treat patients with acute or chronic respiratory failure in intensive care units and hospital wards. Optimal gas exchange is not easy to achieve in patients with respiratory failure since a considerable number of variables and mechanisms involving several organs and systems play a substantial role. Moreover, an added difficulty when managing invasive mechanical ventilation is that improvement of gas exchange must be achieved by minimising the risk of ventilator-induced lung injury. Hence, optimal application of mechanical ventilation requires fine tuning of the ventilator settings, tailoring them to each patient's needs. This process cannot be carried out by trial and error but based on a solid knowledge of the concepts and physical laws governing respiratory mechanics. Accordingly, it is important that medical students achieve a good background understanding of respiratory mechanics in undergraduate courses of physiology, and that this training is refreshed later when the student is introduced to mechanical ventilation learning and further when starting clinical training in this therapy [1].

Description and presentation of an open access spreadsheet application for learning spontaneous breathing mechanics and mechanical ventilationhttps://bit.ly/2TyXo1C

The clinical course of Duchenne muscular dystrophy in the corticosteroid treatment era: a systematic literature review

Background

Duchenne muscular dystrophy (DMD) is a severe rare progressive inherited neuromuscular disorder, leading to loss of ambulation (LOA) and premature mortality. The standard of care for patients with DMD has been treatment with corticosteroids for the past decade; however a synthesis of contemporary data describing the clinical course of DMD is lacking. The objective was to summarize age at key clinical milestones (loss of ambulation, scoliosis, ventilation, cardiomyopathy, and mortality) in the corticosteroid-treatment-era.

Methods

A systematic review was conducted using MEDLINE and EMBASE. The percentage experiencing key clinical milestones, and the mean or median age at those milestones, was synthesized from studies from North American populations, published between 2007 and 2018.

Results

From 5637 abstracts, 29 studies were included. Estimates of the percentage experiencing key clinical milestones, and age at those milestones, showed heterogeneity. Up to 30% of patients lost ambulation by age 10 years, and up to 90% by 15 years of age. The mean age at scoliosis onset was approximately 14 years. Ventilatory support began from 15 to 18 years, and up to half of patients required ventilation by 20 years of age. Registry-based estimates suggest that 70% had evidence of cardiomyopathy by 15 years and almost all by 20 years of age. Finally, mortality rates up to 16% by age 20 years were reported; among those surviving to adulthood mortality was up to 60% by age 30 years.

Conclusions

Contemporary natural history studies from North America report that LOA on average occurs in the early teens, need for ventilation and cardiomyopathy in the late teens, and death in the third or fourth decade of life. Variability in rates may be due to differences in study design, treatment with corticosteroids or other disease-modifying agents, variations in clinical practices, and dystrophin mutations. Despite challenges in synthesizing estimates, these findings help characterize disease progression among contemporary North American DMD patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13023-021-01862-w.

Accuracy of the dynamic signal analysis approach in respiratory mechanics during noninvasive pressure support ventilation: a bench study

OBJECTIVE

To evaluate the accuracy of respiratory mechanics using dynamic signal analysis during noninvasive pressure support ventilation (PSV).

METHODS

A Respironics V60 ventilator was connected to an active lung simulator to model normal, restrictive, obstructive, and mixed obstructive and restrictive profiles. The PSV was adjusted to maintain tidal volumes (V_T) that achieved 5.0, 7.0, and 10.0 mL/kg body weight, and the positive end-expiration pressure (PEEP) was set to 5 cmH₂O. Ventilator performance was evaluated by measuring the flow, airway pressure, and volume. The system compliance (C_rs) and airway resistance (inspiratory and expiratory resistance, R_insp and R_exp, respectively) were calculated.

RESULTS

Under active breathing conditions, the C_rs was overestimated in the normal and restrictive models, and it decreased with an increasing pressure support (PS) level. The R_insp calculated error was approximately 10% at 10.0 mL/kg of V_T, and similar results were obtained for the calculated R_exp at 7.0 mL/kg of V_T.

CONCLUSION

Using dynamic signal analysis, appropriate tidal volume was beneficial for R_rs, especially for estimating R_exp during assisted ventilation. The C_rs measurement was also relatively accurate in obstructive conditions.

Patient–Ventilator Interaction Testing Using the Electromechanical Lung Simulator xPULM™ during V/A-C and PSV Ventilation Mode

During mechanical ventilation, a disparity between flow, pressure and volume demands of the patient and the assistance delivered by the mechanical ventilator often occurs. This paper introduces an alternative approach of simulating and evaluating patient–ventilator interactions with high fidelity using the electromechanical lung simulator xPULM™. The xPULM™ approximates respiratory activities of a patient during alternating phases of spontaneous breathing and apnea intervals while connected to a mechanical ventilator. Focusing on different triggering events, volume assist-control (V/A-C) and pressure support ventilation (PSV) modes were chosen to test patient–ventilator interactions. In V/A-C mode, a double-triggering was detected every third breathing cycle, leading to an asynchrony index of 16.67%, which is classified as severe. This asynchrony causes a significant increase of peak inspiratory pressure (7.96 ± 6.38 vs. 11.09 ± 0.49 cmH2O, p < 0.01)) and peak expiratory flow (−25.57 ± 8.93 vs. 32.90 ± 0.54 L/min, p < 0.01) when compared to synchronous phases of the breathing simulation. Additionally, events of premature cycling were observed during PSV mode. In this mode, the peak delivered volume during simulated spontaneous breathing phases increased significantly (917.09 ± 45.74 vs. 468.40 ± 31.79 mL, p < 0.01) compared to apnea phases. Various dynamic clinical situations can be approximated using this approach and thereby could help to identify undesired patient–ventilation interactions in the future. Rapidly manufactured ventilator systems could also be tested using this approach.

Automated AMBU Ventilator With Negative Pressure Headbox and Transporting Capsule for COVID-19 Patient Transfer

Purpose: It is now clear that the COVID-19 viruses can be transferred via airborne transmission. The objective of this study was to attempt the design and fabrication of an AMBU ventilator with a negative pressure headbox linked to a negative pressure transporting capsule, which could provide a low-cost construction, flexible usage unit, and also airborne prevention that could be manufactured without a high level of technology. Method: The machine consists of an automated AMBU bag ventilator, a negative pressure headbox, and a transporting capsule. The function and working duration of each component were tested. Results: The two main settings of the ventilator include an active mode that can be set at the time range of 0 s-9 h 59 min 59 s and a resting mode, which could work continuously for 24 h. The blower motor and battery system, which were used to power the ventilator, create negative air pressure within the headbox, and the transporting capsule, could run for at least 2 h without being recharged. The transporting capsule was able to create an air change rate of 21.76 ACH with-10 Pa internal pressure. Conclusion: This automated AMBU ventilator allowed flow rate, rhythm, and volume of oxygen to be set. The hazardous expired air was treated by a HEPA filter. The patient's transporting capsule is of a compact size and incorporates the air treatment systems. Further development of this machine should focus on how to link seamlessly with imaging technology, to verify standardization, to test using human subjects, and then to be the commercialized.

Synchronized Inflations Generate Greater Gravity-Dependent Lung Ventilation in Neonates

OBJECTIVE

To describe the regional distribution patterns of tidal ventilation within the lung during mechanical ventilation that is synchronous or asynchronous with an infant's own breathing effort.

STUDY DESIGN

Intubated infants receiving synchronized mechanical ventilation at The Royal Children's Hospital neonatal intensive care unit were studied. During four 10-minute periods of routine care, regional distribution of tidal volume (V_T; electrical impedance tomography), delivered pressure, and airway flow (Florian Respiratory Monitor) were measured for every inflation. Post hoc, each inflation was then classified as synchronous or asynchronous from video data of the ventilator screen, and the distribution of absolute V_T and delivered ventilation characteristics determined.

RESULTS

In total, 2749 inflations (2462 synchronous) were analyzed in 19 infants; mean (SD) age 28 (30) days, gestational age 35 (5) weeks. Synchronous inflations were associated with a shorter respiratory cycle (P = .004) and more homogenous V_T (center of ventilation) along the right (0%) to left (100%) lung plane; 45.3 (8.6)% vs 48.8 (9.4)% (uniform ventilation 46%). The gravity-dependent center of ventilation was a mean (95% CI) 2.1 (-0.5, 4.6)% toward the dependent lung during synchronous inflations. Tidal ventilation relative to anatomical lung size was more homogenous during synchronized inflations in the dependent lung.

CONCLUSIONS

Synchronous mechanical ventilator lung inflations generate more gravity-dependent lung ventilation and more uniform right-to-left ventilation than asynchronous inflations.

Improving nurses' knowledge of managing endotracheal tube cuff pressure in intensive care units: A quasi-experimental study

BACKGROUND

Previous studies conducted on nurses' knowledge regarding endotracheal tube cuff pressure revealed that there were differences in intensive care nurses' knowledge, leading to varying practices.

AIM

This study aimed to evaluate how an educational intervention based on the existing evidence-based guidelines, using both passive and active implementation strategies, could improve the knowledge of nurses regarding managing endotracheal tube cuff pressures in Malawian intensive care units.

SETTING

Six functional ICUs (four public and two private) in Malawi.

METHODS

The study followed a quasi-experimental, pre- and post-test design using an educational intervention. Intensive care nurses of six functional intensive care units in Malawi were randomly assigned to two intervention groups. Both groups received a half-day educational session, a printed version of the evidence-based guidelines, a printed and laminated summary of the guidelines and a related algorithm. Additionally, Intervention 2 group received four monitoring visits. Pre- and post-test questionnaires were conducted between February and August 2016. Descriptive and inferential data analyses (a chi-square test and t-test) were utilised.

RESULTS

An improvement in knowledge was observed on the nursing care practices for the management of endotracheal tube cuff pressure for both groups following the educational intervention, although only the results comparing Intervention 2 group participants indicate that the level of knowledge was significant (t[df = 48] = 2.08, p = 0.043, d = 0.59).

CONCLUSION

Implementation of a formal training and mentorship programme for Malawian intensive care nurses would be of great benefit to enhance the knowledge and skills managing endotracheal tube cuff pressure. Follow-up studies would also assist in understanding how guidelines could be implemented most effectively to achieve better knowledge outcomes.

AI in the Intensive Care Unit: Up-to-Date Review

AI is the latest technologic trend that likely will have a huge impact in medicine. AI's potential lies in its ability to process large volumes of data and perform complex pattern analyses. The ICU is an area of medicine that is particularly conducive to AI applications. Much AI ICU research currently is focused on improving high volumes of data on high-risk patients and making clinical workflow more efficient. Emerging topics of AI medicine in the ICU include AI sensors, sepsis prediction, AI in the NICU or SICU, and the legal role of AI in medicine. This review will cover the current applications of AI medicine in the ICU, potential pitfalls, and other AI medicine-related topics relevant for the ICU.

Fully automated postoperative ventilation in cardiac surgery patients: a randomised clinical trial

BACKGROUND

Ensuring that lung-protective ventilation is achieved at scale is challenging in perioperative practice. Fully automated ventilation may be more effective in delivering lung-protective ventilation. Here, we compared automated lung-protective ventilation with conventional ventilation after elective cardiac surgery in haemodynamically stable patients.

METHODS

In this single-centre investigator-led study, patients were randomly assigned at the end of cardiac surgery to receive either automated (adaptive support ventilation) or conventional ventilation. The primary endpoint was the proportion of postoperative ventilation time characterised by exposure to predefined optimal, acceptable, and critical (injurious) ventilatory parameters in the first three postoperative hours. Secondary outcomes included severe hypoxaemia (Spo₂ <85%) and resumption of spontaneous breathing. Data are presented as mean (95% confidence intervals [CIs]).

RESULTS

We randomised 220 patients (30.4% females; age: 62-76 yr). Subjects randomised to automated ventilation (n=109) spent a 29.7% (95% CI: 22.1-37.4) higher mean proportion of postoperative ventilation time receiving optimal postoperative ventilation after surgery (P<0.001) compared with subjects receiving conventional postoperative ventilation (n=111). Automated ventilation also reduced the proportion of postoperative ventilation time that subjects were exposed to injurious ventilatory settings by 2.5% (95% CI: 1-4; P=0.003). Severe hypoxaemia was less likely in subjects randomised to automated ventilation (risk ratio: 0.26 [0.22-0.31]; P<0.01). Subjects resumed spontaneous breathing more rapidly when randomised to automated ventilation (hazard ratio: 1.38 [1.05-1.83]; P=0.03).

CONCLUSIONS

Fully automated ventilation in haemodynamically stable patients after cardiac surgery optimised lung-protective ventilation during postoperative ventilation, with fewer episodes of severe hypoxaemia and an accelerated resumption of spontaneous breathing.

CLINICAL TRIAL REGISTRATION

NCT03180203.

SVASTA, PRANA and VaU: Three Novel Ventilators from Space Community

This paper describes the design and development of three low-cost ventilators which can be mass produced to meet a surge in demand for such equipment. Each of these ventilators is having unique features while meeting standard functional specifications of mechanical ventilators. The first design works on compressed air source as control gas and does not require electrical power for its operation. Parameters like tidal volume, breathing rate etc. can be set mechanically in this ventilator. Second one is an automated Ambu bag based system, which has digital controller providing closed-loop control of critical ventilator parameters and a very unique geared actuation system that ensure long cyclic life to Ambu bag and fine control of parameters. The third design is an air blower based pneumatic circuit ventilator which is a state of the art ICU ventilator. Mathematical modeling of the systems is carried out to design the mechanical/electrical control elements and to simulate the performance of the system. Prototypes of ventilators were developed, testing and simulation runs were carried out and critical parameters were measured ensuring satisfactory performance of the system.

MADVent: A low-cost ventilator for patients with COVID-19

The COVID‐19 pandemic has produced critical shortages of ventilators worldwide. There is an unmet need for rapidly deployable, emergency‐use ventilators with sufficient functionality to manage COVID‐19 patients with severe acute respiratory distress syndrome. Here, we show the development and validation of a simple, portable and low‐cost ventilator that may be rapidly manufactured with minimal susceptibility to supply chain disruptions. This single‐mode continuous, mandatory, closed‐loop, pressure‐controlled, time‐terminated emergency ventilator offers robust safety and functionality absent in existing solutions to the ventilator shortage. Validated using certified test lungs over a wide range of compliances, pressures, volumes and resistances to meet U.S. Food and Drug Administration standards of safety and efficacy, an Emergency Use Authorization is in review for this system. This emergency ventilator could eliminate controversial ventilator rationing or splitting to serve multiple patients. All design and validation information is provided to facilitate ventilator production even in resource‐limited settings.

A Low-Cost Breath Analyzer Module in Domiciliary Non-Invasive Mechanical Ventilation for Remote COPD Patient Monitoring

Smart Breath Analyzers were developed as sensing terminals of a telemedicine architecture devoted to remote monitoring of patients suffering from Chronic Obstructive Pulmonary Disease (COPD) and home-assisted by non-invasive mechanical ventilation via respiratory face mask. The devices based on different sensors (CO₂/O₂ and Volatile Organic Compounds (VOCs), relative humidity and temperature (R.H. & T) sensors) monitor the breath air exhaled into the expiratory line of the bi-tube patient breathing circuit during a noninvasive ventilo-therapy session; the sensor raw signals are transmitted pseudonymized to National Health Service units by TCP/IP communication through a cloud remote platform. The work is a proof-of-concept of a sensors-based IoT system with the perspective to check continuously the effectiveness of therapy and/or any state of exacerbation of the disease requiring healthcare. Lab tests in controlled experimental conditions by a gas-mixing bench towards CO₂/O₂ concentrations and exhaled breath collected in a sampling bag were carried out to test the realized prototypes. The Smart Breath Analyzers were also tested in real conditions both on a healthy volunteer subject and a COPD suffering patient.

Cosmetic Ventilators (Co-V) for COVID-19

The COVID-19 pandemic has infiltrated all over our lives in every aspect and led to complete lockdown in almost every country and affected millions of people. It has overwhelmed the healthcare systems even of the most developed nations and this could be our future as well if situation is not controlled. We might fall short of ICU beds, ventilators, and trained manpower. Having understood that, many companies or even individuals have started to produce new and innovative kind of ventilators which prima facie are not at par with the standard ICU ventilators. Such ventilators, if approved for use in COVID-19 acute respiratory distress syndrome (ARDS), may not be of much use and rather cause harm. This commentary shall deal with the basics of COVID-19 ARDS, basics of an ICU ventilator, innovative low-cost ventilators, and the stark differences between the two and why their use may not be appropriate in the condition of our concern.

Application of Artificial Intelligence in the Health Care Safety Context: Opportunities and Challenges

There is a growing awareness that artificial intelligence (AI) has been used in the analysis of complicated and big data to provide outputs without human input in various health care contexts, such as bioinformatics, genomics, and image analysis. Although this technology can provide opportunities in diagnosis and treatment processes, there still may be challenges and pitfalls related to various safety concerns. To shed light on such opportunities and challenges, this article reviews AI in health care along with its implication for safety. To provide safer technology through AI, this study shows that safe design, safety reserves, safe fail, and procedural safeguards are key strategies, whereas cost, risk, and uncertainty should be identified for all potential technical systems. It is also suggested that clear guidance and protocols should be identified and shared with all stakeholders to develop and adopt safer AI applications in the health care context.

Invasive mechanical ventilation in the emergency department

Emergency department (ED) lenght of stay of the patients requiring admission to the intensive care units has increased gradually in recent years. Mechanical ventilation is an integral part of critical care and mechanically ventilated patients have to be managed and monitored by emergency physicians for longer than expected in EDs. This early period of care has significant impact on the outcomes of these patients. Therefore, emergency physicians should have comprehensive knowledge of mechanical ventilation. This review will summarize the current literature of the basic concepts, appropriate clinical applications, monitoring parameters, components and mechanisms of mechanical ventilation in the ED.

Nonlinear Flow Sensor Calibration with an Accurate Syringe

Flow sensors are required for monitoring patients on mechanical ventilation and in respiratory research. Proper calibration is important for ensuring accuracy and can be done with a precision syringe. This procedure, however, becomes complex for nonlinear flow sensors, which are commonly used. The objective of the present work was to develop an algorithm to allow the calibration of nonlinear flow sensors using an accurate syringe. We first noticed that a power law equation could properly fit the pressure-flow relationship of nonlinear flow sensors. We then developed a software code to estimate the parameters for this equation using a 3 L syringe (calibration syringe). Finally, we tested the performance of a calibrated flow sensor using a different 3 L syringe (testing syringe) and a commercially available spirometer. After calibration, the sensor had a bias ranging from −1.7% to 3.0% and precision from 0.012 L to 0.039 L for volumes measured with the 3 L testing syringe. Calibrated sensor performance was at least as good as the commercial sensor. This calibration procedure can be done at the bedside for both clinical and research purposes, therefore improving the accuracy of nonlinear flow sensors.