Anthony Rice ’27
Millions of patients suffer from post-surgical complications each year. If deaths occurring within
30 days of surgical procedures were accounted for by standard mortality statistics, they would
rank as the third leading cause of death worldwide (Glasbey et al., 2024). A marked portion of
these deaths are linked to opioid-induced respiratory depression (OIRD) (Lee et al., 2015).
Opioid drugs are commonly used in general anesthesia to control the body’s stress to surgical
pain and stress. However, they can inhibit the brain’s signal to breathe by binding mu-opioid
receptors in the brainstem’s respiratory center, ultimately causing reductions in the rate and
depth of breathing that could result in fatal respiratory failure (Ramirez et al., 2021).
The 2020 PRODIGY study, a large prospective observational trial of over 1,300 hospitalized
patients receiving opioid treatment across 16 sites in the U.S., Europe, and Asia, used
continuous respiratory monitoring, rather than standard intermittent checks after surgery
(Khanna et. al 2020). Close to half of these patients experienced one or more respiratory
depression episodes. The study also identified sleep related breathing disorders as major
independent risk factors for OIRD (Slowik et al., 2025). These included obstructive sleep apnea
(OSA), in which the airway repeatedly collapses during sleep and pauses breathing (Slowik et
al., 2025).
The findings of the PRODIGY study highlight a particularly concerning public health issue:
post-surgical respiratory complications contribute to higher rates of preventable morbidity,
mortality, and healthcare costs (Fernandez-Bustamante et al., 2017; Jungquist et al. 2018). If
nearly half of patients receiving opioids in the hospital experience dangerous respiratory
depression episodes, how can we better protect these vulnerable patients, both inside the
hospital and when they are discharged? This question guided my summer research in the
Artificial Pancreas Center at Thomas Jefferson University. There, I worked under the guidance
of Dr. Jeffrey Joseph, anesthesiologist and co-founder of RTM Vital Signs, a biotechnology
company that focused on developing wireless wearable devices to continuously monitor vital
signs in real time, detecting patterns of clinical decompensation early, before they lead to severe
disability or death (RTM Vital Signs, n.d.; Sundrani et al., 2023). My specific focus was on the
company’s RTMsense tracheal sound monitor, its latest innovation designed to identify
hypoventilation from obstructive sleep apnea and opioid use before it becomes life-threatening
(RTM Vital Signs, n.d.).
When I first joined the lab, I realized that I needed a deep understanding of the scientific
concepts underlying our work in order to contribute meaningfully. I immersed myself in the
foundational literature my PI provided on obstructive sleep apnea (OSA), opioid-induced
respiratory depression (OIRD), and tidal volume variability. Once understanding the lab’s
methodology and clinical context, I expanded my literature review to cutting-edge research in
these areas. This process was valuable as it allowed me to develop a shared language with the
team, transitioning from a learner to an active contributor. I was able to critically evaluate
experimental designs and use specialized terms to discuss the physiological mechanisms that
the RTM Respiratory Monitoring System aims to detect.
Once I acquired my foundational knowledge from the literature, I began to move into the more
practical and hands-on aspects of our project. For the lab’s NIH-funded study, we were required
to demonstrate that the acoustic sensor could accurately measure tidal volume, the amount of
air moving in or out of the lungs with each respiratory cycle, within a defined margin compared
to a “predicate,” an existing FDA-approved respiratory monitoring device (National Institutes of
Health, n.d.; Reid et al., 2023). Throughout many rounds of data collection, I became familiar
with the RTM sensor’s graphical user interface, learned how to properly affix the device to study
volunteers, and operate the system alongside the predicate Hamilton ventilator, including
calibration and securely fitted CPAP masks to each participant (Pinto et al., 2025). In addition, I
was trained to operate the Exspiron electrical impedance respiratory plethysmograph, another
predicate device that measured changes in the electrical resistance of the chest to calculate
volume changes and validate our device’s respiratory monitoring performance (Gatti et al.,
2024). A critical part of my responsibilities were to securely transfer the measured
breath-by-breath data to the company’s biomedical engineering team for signal analysis.
During a particular data collection session, one side of the acoustic sensor’s chestpiece
unexpectedly malfunctioned. Despite this major setback, we pushed forward with our
measurements. When I reviewed the data’s .WAV file, we were all pleasantly surprised when we
discovered that this “broken” sensor produced a signal-to-noise ratio nearly triple that of its
normal operation. This experience taught me the iterative nature of research: in order to make
progress, you often have to repeat your experiments, gradually refining design and functionality
through trial and error. It also taught me the importance of keeping an open mind, and
cultivating a growth mindset rather than a fixed one. Had we cut our data collection short
because of the malfunction, we would have missed out on a great opportunity to improve.
Moments like these were what made my research both unpredictable and deeply rewarding;
they helped me develop as a problem-solver throughout the summer.
Although my role was just one piece of a larger project, I experienced how research can make
impacts far beyond academia. The RTM Respiratory Monitoring System addresses two very
pressing public health challenges: potentially fatal post-surgical complications and the threat of
opioid overdose (Volkow & Blanco, 2021). Wireless wearable continuous vital sign monitors like
the one I worked on represent a major step forward in improving the standard of care (Leenen
et al., 2020). They empower clinicians to detect early signs of worsening function, intervening
before they become fatal and saving the lives of the most vulnerable.
For others interested in similar research, I would advise them to first invest the time in becoming
deeply familiar with your lab’s project and its topic. For me, this meant critically engaging with a
broad array of literature and asking questions about it during lab meetings. Having this broader
context of your research gives a greater level of purpose to each experiment; it transforms
routine tasks, and even failures, into learning opportunities that allow you to contribute to your
team in more meaningful ways.
In addition, I’ve learned that success in research relies on more than just technical knowledge.
You must also develop skills in effective communication and collaboration with individuals with a
variety of backgrounds. Finally, I would encourage students interested in research to find a
project that has a direct impact on people’s lives, even if it feels outside of your comfort zone at
first. I believe that projects like these are the most meaningful and give you the greatest
opportunity to learn new concepts and skills that will make you a valuable member of your
community.
Anthony Rice is an editor at The Princeton Medical Review. He can be reached at ar5395@princeton.edu
References
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Gatti, S., Rezoagli, E., Madotto, F., Foti, G., & Bellani, G. (2024). A non-invasive continuous and real-time volumetric monitoring in spontaneous breathing subjects based on bioimpedance-ExSpiron®Xi: a validation study in healthy volunteers. Journal of clinical monitoring and computing, 38(2), 539–551. https://doi.org/10.1007/s10877-023-01107-0
Glasbey, J., George, C., & Martin, J. (2024). Why do people die after surgery? A call for research action: post-operative mortality. Impact Surgery, 1(3), 90–92. https://doi.org/10.62463/surgery.66
Jungquist, C. R., Card, E., Charchaflieh, J., Gali, B., & Yilmaz, M. (2018). Preventing opioid-induced respiratory depression in the hospitalized patient with obstructive sleep apnea. Journal of Perianesthesia Nursing, 33(5), 601–607. https://doi.org/10.1016/j.jopan.2016.09.013
Khanna, A. K., Bergese, S. D., Jungquist, C. R., Morimatsu, H., Uezono, S., Lee, S., Ti, L. K., Urman, R. D., McIntyre, R., Tornero, C., Dahan, A., Saager, L., Weingarten, T. N., Wittmann, M., Auckley, D., Brazzi, L., Le Guen, M., Soto, R., Schramm, F., … PRODIGY Group Collaborators. (2020). Prediction of opioid-induced respiratory depression on inpatient wards using continuous capnography and oximetry: An international prospective, observational trial. Anesthesia & Analgesia, 131(4), 1012–1024. https://doi.org/10.1213/ANE.0000000000004788
Lee, L. A., Caplan, R. A., Stephens, L. S., Posner, K. L., Terman, G. W., Voepel-Lewis, T., & Domino, K. B. (2015). Postoperative opioid-induced respiratory depression: A closed claims analysis. Anesthesiology, 122(3), 659–665. https://doi.org/10.1097/ALN.0000000000000564
Leenen, J. P. L., Leerentveld, C., van Dijk, J. D., van Westreenen, H. L., Schoonhoven, L., & Patijn, G. A. (2020). Current Evidence for Continuous Vital Signs Monitoring by Wearable Wireless Devices in Hospitalized Adults: Systematic Review. Journal of medical Internet research, 22(6), e18636. https://doi.org/10.2196/18636
National Institutes of Health. (n.d.). Project details: 11146916. NIH RePORTER. Retrieved September 5, 2025, from https://reporter.nih.gov/search/f4XhO_EEUkSiDebr6xAD-A/project-details/11146916
Pinto, V. L. (2025, July 7). Continuous positive airway pressure. StatPearls [Internet]. https://www.ncbi.nlm.nih.gov/books/NBK482178/
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Sundrani, S., Chen, J., Jin, B. T., Abad, Z. S. H., Rajpurkar, P., & Kim, D. (2023). Predicting patient decompensation from continuous physiologic monitoring in the emergency department. NPJ digital medicine, 6(1), 60. https://doi.org/10.1038/s41746-023-00803-0
Volkow, N. D., & Blanco, C. (2021). The changing opioid crisis: development, challenges and opportunities. Molecular psychiatry, 26(1), 218–233. https://doi.org/10.1038/s41380-020-0661-4
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