Summer 2024 Adult Acute Care Bulletin

Notes from the Chair

Elisabeth Caldwell, MBA-HC, RRT

I am thrilled and honored to introduce myself as your new Adult Acute Care Section chair for the AARC. My passion is advancing the field of respiratory therapy, and I am committed to driving positive change. I am excited to collaborate with fellow professionals in our shared mission to enhance patient care and elevate the standards of our profession.

I am happy to present the Adult Acute Section Bulletin topics for the Spring of 2024. Our first article, which addresses artificial intelligence (AI) in health care, considers the transformative impact of AI on respiratory therapy. As technology continues to evolve, AI presents unprecedented opportunities to optimize patient care, streamline processes, and enhance diagnostic and treatment capabilities. The exploration of this subject aims to provide insights into how respiratory therapists can harness the power of AI to improve clinical outcomes and overall health care efficiency.

The following article discusses how inspiratory and expiratory hold maneuvers serve as vital tools in the management of mechanically ventilated patients, offering crucial insights into patient-ventilator interaction and respiratory system health. By providing valuable measurements, these maneuvers empower clinicians to make informed decisions, enhancing the potential for positive patient outcomes.

I am eager to embark on my journey with you as the section chair, and I look forward to fostering collaboration, knowledge-sharing, and innovation within the Adult Acute Care Section of the AARC. Together, we can shape the future of respiratory therapy and continue to provide exceptional care to those who rely on our expertise.

Artificial Intelligence and Machine Learning in Respiratory Care: A Revolutionary Transformation

Brian Parsch, MS, RRT, RRT-NPS, CPFT, St. Philip’s College, San Antonio, TX

Thanks to the combination of artificial intelligence (AI) and machine learning (ML), new technologies are offering the opportunity for inventive solutions to the difficult problem of respiratory care, particularly for patients who are in critical condition. This influence encompasses a wide variety of applications and problems.1   

Algorithms powered by artificial intelligence, intelligent data analysis methods, and intelligent equipment all have the potential to revolutionize patient care, improve diagnosis, and enhance medical preparation on a global scale. In this evaluation, a quick look is taken at the various challenges that respiratory care faces in countries that are not yet developed, as well as the possibility for change via AI during times of humanitarian crisis.  

Novel options needed  

The fact that cardiovascular and pulmonary diseases are responsible for the majority of fatalities and illnesses around the world2 brings to light the necessity of developing novel therapeutic options. The already significant stress that is placed on health care systems and the difficulties that are associated with accessing therapeutic treatment have both been significantly exacerbated as a result of the COVID-19 pandemic. As Rajaraman points out, this has also brought to light the likelihood that AI will bring about a massive transformation in the health care industry.2
In addressing cardiopulmonary disorders like tuberculosis, heart disease, lung cancer, and COVID-19, prioritization is key. However, resource scarcity and limited information make the identification and management of these issues challenging. Early detection and accurate diagnosis are vital for reducing mortality rates. Artificial intelligence and machine learning offer innovative alternatives to traditional radiographic imaging techniques, such as CT scans and chest X-rays, enabling faster assessments in interpreting data and mitigating human error.2 Despite the limitations of conventional imaging, integrating AI and machine learning into cancer screening and diagnosis holds significant promise for improving patient care.

The Special Issue “Artificial Intelligence in Image-Based Screening, Diagnostics, and Clinical Care of Cardiopulmonary Diseases” presents research studies and literature reviews on AI/ML applications in cardiopulmonary disease screening, diagnosis, and clinical management.2 The papers are expected to significantly impact artificial intelligence, particularly in health care, and highlight challenges faced by less developed countries.  

Smart gadgets and more 

The authors of another paper suggest AI-powered smart gadgets could improve oxygen therapy in developing countries, with a focus on the environment, health care, education, and economic growth, emphasizing the necessity of developing infrastructure and fostering fair economic expansion and eradicating disparities.3 It is this input that emphasizes the significance of big data and machine learning in the health care setting, marking its efficacy in addressing health-related concerns. 

4 centers on developing an algorithm to accurately detect patient-ventilator asynchronies (PVAs), which many respiratory therapists and health care providers face daily. These unique endeavors offer an achievable remedy to a substantial issue in the field.
AI can significantly aid decision-making in health care by consistently measuring respiratory resistance and compliance as well.4 For instance, a real-time machine learning system developed in 2022 accurately calculates respiratory parameters by evaluating airway pressure and velocity, showcasing AI’s superiority in optimizing breath delivery.4  

Moreover, AI holds promise in improving oxygen therapy, particularly in underdeveloped nations facing oxygen insufficiency.4 Screening, diagnosing, and treating cardiopulmonary diseases like tuberculosis, cardiovascular disease, pulmonary malignancy, and COVID-19 can be challenging in resource-limited settings.5 Early recognition, accurate diagnosis, and proper classification of these diseases are crucial for reducing mortality rates. 

While AI offers a novel approach for image analysis, traditional radiographic imaging techniques like CT scans, echo ultrasonography, and chest X-rays continue to be essential for cancer screening and diagnosis.6 AI enables rapid evaluations and reduces human performance variability by replacing peer review.2  

Expediting care 

In conclusion, it is critical to prioritize the evaluation of cardiopulmonary disorders including COVID-19, lung cancer, TB, and heart disease. Nevertheless, the process of identifying and addressing these problems can be difficult due to scarce resources and inadequate information.6 Early detection, precise diagnosis, and proper classification of cardiopulmonary diseases are crucial in reducing mortality rates.  

Artificial intelligence and machine learning are innovative methods that have the potential to interpret traditional radiographic imaging modalities such as CT scans, echo ultrasounds, and chest X-rays correctly and accurately. This approach enables expedited assessments and reduces the impact of human performance inconsistencies by substituting expert evaluation. Although conventional radiographic imaging has limitations, the incorporation of AI and machine learning in cancer screening and diagnosis has the potential to greatly enhance patient care. 

References 

1. Lauer D. You cannot have AI ethics without ethics. AI and Ethics 2020;1(1):21-25.  
2. Rajaraman S, Antani S. Editorial on special issue “Artificial Intelligence in Image-Based Screening, Diagnostics, and Clinical Care of Cardiopulmonary Diseases.” Diagnostics 2022;12(11):2615. 
3. Mannuru NR, Shahriar S, Teel ZA, Wang T, Lund BD, Tijani S, Pohboon CO, Agbaji D, Alhassan J, Galley J, Kousari R, Ogbadu-Oladapo L, Saurav SK, Srivastava A, Tummuru SP, Uppala S, Vaidya P. Artificial intelligence in developing countries: The impact of generative artificial intelligence (AI) technologies for development. Information Development 2023. 
4. Filho LACB. Artificial intelligence: what should an intensivist have in mind in the beginning of the new era? Anaesthesia, Pain & Intensive Care 2021;25(1):8-12.  
5. Khemasuwan D, Sorensen JS, Colt HG. Artificial intelligence in pulmonary medicine: Computer vision, predictive model and COVID-19. Eur Respir Rev 2020;29(157):200181.  
6. Choudhury S, Chohan A, Dadhwal R, Vakil AP, Franco R, Taweesedt PT. Applications of artificial intelligence in common pulmonary diseases. Artificial Intelligence in Medical Imaging 2022;3(1):1-7.  
7. Top Shelf Tools: Inspiratory and Expiratory Hold Maneuvers

Caleb Adams, BSRT, RRT, RRT-ACCS, Respiratory Care Manager, Charleston Area Medical Center-General Hospital, Charleston, WV  

Understanding the interaction between the patient and the ventilator is one of the more challenging responsibilities for benevolent respiratory therapists. And for those who seek to do good, developing such proficiency is inherently necessary to achieve actual beneficence.   

Positioned prominently on the tool belts of these effective bedside clinicians must be two essential tools, inspiratory and expiratory hold maneuvers. When partnered with the knowledge and understanding necessary to take the information gathered through these maneuvers from measurement to meaningful application, the respiratory therapist fulfills their unique, value-added role within the patient-care team and directly improves the likelihood of positive outcomes for the patients they care for.1  

Inspiratory hold maneuvers  

An inspiratory hold maneuver produces a period at end-inspiration with cessation of gas flow. During this maneuver, the inspiratory and expiratory valves are closed, preventing flow from entering or exiting the system. Under these conditions, pressure equilibrium is reached throughout the entire system, from the ventilator to the alveoli, after a short pause. In turn, the pressure exerted on the alveoli at the end of inspiration can be measured by the ventilator. This metric is significant because pressure measurements during periods of inspiration that include gas flow do not distinguish between the effects of alveolar compliance and airway resistance on the breath.2-4 

Even in pressure control ventilation, the inspiratory time may be insufficient to achieve complete application of the set inspiratory pressure level throughout the entire system. This means, for both volume control and pressure control ventilation, the cause of peak inspiratory pressure changes (volume control ventilation) and tidal volume changes (pressure control ventilation) cannot be automatically assumed as either alveolar compliance or airway resistance without a distinguishing maneuver performed — namely, the inspiratory hold maneuver.5,6  

Additionally, important metrics for lung protective ventilation, such as the change in pressure in the alveoli during the inspiratory phase, PDRIVE, can only be derived once the maneuver is performed and measurement obtained. For instance, if patients with PDRIVE >15 have a statistically higher incidence of negative outcomes7, then PDRIVE must be considered in lung protective strategies. However, for PDRIVE to be utilized in lung protective strategies, the inspiratory hold maneuver must be performed to obtain PPLAT and then calculate PDRIVE. This sequence emphasizes the importance of the maneuver for routine assessment and ventilation strategy determinations. 

Expiratory hold maneuvers 

Expiratory hold maneuvers produce a period at end-expiration with cessation of gas flow. For patients who are passively breathing, this allows pressure equilibrium to be reached and alveolar pressure at end exhalation to be measured.  

This measurement is significant because the set baseline pressure, PEEPE, is not always reached on exhalation. This issue occurs when insufficient exhalation time causes unintentionally increased end-expiratory lung volume and incidentally increases the actual baseline pressure in the lungs, PEEPTOT. The problem is most likely in patients with increased airway resistance but may also occur in patients with high respiratory rates. The PEEPTOT measurement is important because it allows for accurate identification of baseline pressure at which inspiration begins to be known and correct calculations for derived measurements to be derived, such as PDRIVE.2,3 

Valuable tools  

Inspiratory and expiratory hold maneuvers are fundamentally valuable tools to use in the care of mechanically ventilated patients. These maneuvers produce valuable information on patient-ventilator interaction, contributing unique insight into the health of the patient’s respiratory system, and offer discernment as to which part of the system is affected, if any. The measurements gathered from these maneuvers add to the overall patient picture and allow the bedside clinician to more confidently and accurately act in the patient’s best interest to improve the likelihood of favorable patient outcomes. 

References  

1. Chatburn RL, Ford RM, Kauffman GW. Determining the value-efficiency of respiratory care. Respir Care 2021;66(12):1892. 
2. Hess DR. Respiratory mechanics in mechanically ventilated patients. Respir Care 2014;59(11):1773. 
3. Lotti GA, Braschi A. Measurements of respiratory mechanics during mechanical ventilation. Hamilton Medical Scientific Library, Rhäzüns, Switzerland; 1999. 
4. Chatburn RL. The complexities of mechanical ventilation: Toppling the tower of Babel. Respir Care 2023;68(6):796. 
5. Ashworth L, Norisue Y, Koster M, Anderson J, Takada J, Ebisu H. Clinical management of pressure control ventilation: An algorithmic method of patient ventilatory management to address “forgotten but important variables.” J Crit Care 2018;43:169-182. 
6. Mireles-Cabodevila E, Siuba MT, Chatburn RL. A taxonomy for patient-ventilator interactions and a method to read ventilator waveforms. Respir Care 2022;67(1):129. 
7. Amato MBP, Meade MO, Slutsky AS, Brochard L, Costa ELV, Schoenfeld DA, et al. Driving pressure and survival in the acute respiratory distress syndrome. N Engl J Med 2015;372(8):747-755. 

Section discussion list: Go to the Adult Acute Care Section on AARConnect to network with your fellow section members. 

Next Bulletin: Please email Karsten J. Roberts if you would like to contribute an article to the next Bulletin.