By Diane Ladd, DNP, FNP-BC (Director, Clinical Affairs, Respiratory Motion Inc.)
The Centers for Medicare & Medicaid Services recently issued a guidance warning about the dangers of opioid-induced respiratory depression (“OIRD”) and required the following actions be taken:
Timely assessment and appropriate monitoring is essential in all hospital settings in which opioids are administered, to permit intervention to counteract respiratory depression should it occur.
The goal for the development of rapid response teams has been to identify the earliest time when a patient’s physiologic state is deteriorating, which would allow for timely interventions. The representation below shows the response of different physiologic parameters over time and the first indication of deteriorating respiratory status is minute ventilation (MV or Ve). Minute ventilation is the amount of air that goes in and out of the lungs in one minute and is the fundamental unit of breathing.
Chris Voscopoulos, M.D. (Duke University) and colleagues conducted a study using non-invasive respiratory volume monitoring to look at identifying patients at risk for post-operative, opioid induced respiratory depression. This study tested the ability of a risk-prediction model that would allow for identification of at-risk patients.
I was fortunate to be able to talk to Dr. Voscopoulos about the significance of this study.
Q: What is non-invasive respiratory volume monitoring, or as you say, RVM, and what does it measure?
A: RVM measures minute ventilation, tidal volume and respiratory rate in real time using an electrode padset similar to EKG electrodes to measure the amount of air in the lungs that goes in and out of your lungs in real time. Specifically, minute ventilation (or MV) is just respiratory rate (the number of breaths in a minute) multiplied by the tidal volume (the size of each breath). The RVM captures these metrics with high fidelity. Traditionally, accurate measurements of respiratory volumes were obtainable only for intubated patients. However, respiratory volume monitoring is equally, if not more, valuable in the care of non-intubated patients.
Q: Why is it important to measure ventilation if the patient isn’t on the ventilator anymore?
A: When someone is on the ventilator, we both control and monitor respiratory volumes. Until now, once we took out the breathing tube, we not only lost our ability to control respiration, but at the same time we also lost the capability to monitor respiration. If we give patients opioids when they are on the ventilator as part of their anesthesia, it doesn’t matter if they have respiratory depression, because we are breathing for them. Off the ventilator, we use opioids to control pain and respiratory depression can be a real problem, because we can’t quantify and often can’t even detect early signs of respiratory compromise. With the advent of the RVM, real-time respiratory monitoring is now available in this much larger patient population. Basically it is useful for assessing any patient not on the ventilator. Our ability to now measure respiratory status at the same level of reliability as in the intubated patient provides a window into clinical intervention at earlier stages. Because this technology has wide applicability, it has the potential to have a significant influence on total patient outcomes.
Q: What would be the benefits of predicting which post-surgical patients might be at risk for opioid-induced respiratory depression (OIRD)?
A: Since we can now assess a patient after surgery to determine if that patient is at-risk for OIRD. I see two major benefits. First, we can individualize care by identifying patients who can be made safer by receiving lower doses of opioids or a modified pain management regimen and/or by being monitored more closely in the PACU and also after discharge to the general hospital floor. Second, we can now detect early signs of respiratory compromise well before full-blown respiratory failure develops. Early identification and rapid, targeted intervention could prevent adverse events, improve patient safety and minimize the need for more costly interventions.
Q: Have previous efforts been successful at addressing the safety risks of OIRD?
A: Unfortunately, neither the use of patient-controlled analgesia nor more vigilant bedside monitoring has eliminated OIRD. Thousands of patients still die every year. Existing technologies, such as pulse oximetry, which measures oxygenation, and capnography, which measures end-tidal carbon dioxide, and respiratory rate monitors have been shown to be unreliable predictors of respiratory compromise. Measuring oxygen saturation can only provide a lagging indicator of respiratory status and only decreases after respiratory decompensation has begun, especially if the patient is receiving supplemental oxygen, a standard of post-operative care. Capnography (the measurement of end-tidal CO2), is also a poor predictor for a variety of reasons. In stable intubated patients, capnography is a useful tool, but in non-intubated patients, capnography may not be accurate because not all the exhaled air is captured by the sensor and there are errors due to changes in oxygen flow, potential mouth versus nose breathing, and maintenance of proper sensor positioning. Existing respiratory rate measurements have some built in data collection issues and studies have shown that by measuring rate alone we can miss respiratory depression episodes of low MV over 70% of the time. Our own studies demonstrate that non-invasive RVM adequately quantifies minute ventilation and shows respiratory patterns to identify and track the effects of opioids in non-intubated post-operative patients.
Q: That’s interesting. You would think that given the advances in medical technology, current monitoring should be able to provide more accurate information on respiratory status. Why have previous methods and technologies or known risk factors, such as OSA, obstructive sleep apnea, not been able to predict whether a patient might suffer from respiratory depression after opioids?
A: Well, our data has shown that pre-operative risk factors don’t always correlate well with the risk of OIRD. In fact, surprisingly we found that OSA is a poor predictor of OIRD, with a sensitivity below 10%. Other measurement techniques have not provided information that could be used to stratify patients. Other monitoring, such as pulse oximetry or end-tidal CO2, are not direct indicators of respiratory status and have ongoing issues with accuracy. Using the newly developed RVM we can, for the first time, actually have a direct measure of respiratory status. We can see the baseline status of the patient, respiratory trends and the impact of opioids on ventilation. To better understand the effects of opioids on a respiratory status for a given individual, our study categorized patients as “At-Risk” and “Not-At-Risk, based on their minute ventilation (MV) before initial opioid administration in the post-anesthesia care unit. Patients having a MV below 80% of their expected MV were considered “At-Risk”. Patients having a MV above 80% of their expected MV were considered “Not-At-Risk”.
Q: What happened to the patients who were given opioids when they were “At-Risk”?
A: In one of our first studies of 50 patients receiving opioids after surgery, 18 of the 50 were considered “At-Risk” and 13 of these 18 “At-Risk” patients had their MV drop into the “Un-Safe” range (MV less than 40% of their expected MV) after their first opioid dose. Only 1 of the 32 patients who were considered “Not-at-Risk” developed an ”Un-Safe” MV. This classification protocol had a success rate (sensitivity) of 93%, which is really quite good as is its correct rejection rate (specificity) of 86% and a negative predictive value of 97%. This kind of classification based on the post-operative respiratory status of the patient performed at the point-of-care can be a powerful tool. Ongoing RVM measurements can help in understanding the baseline of the patient after surgery and provides the ability to monitor the effect of opioids in real time after dosing
Q: That is really interesting data, but it is only on 50 patients, do you have additional data to support it.
Here are examples of two patients that demonstrate these points. Patient A was classified as “Not-At-Risk”, with a MV above 80% expected before opioid dosing and had no significant respiratory depression following several doses. On the other hand, Patient B started with a MV well under 80% of expected and developed dangerously low minute ventilation after opioid.
In these cases, the patients were only being observed and not treated on the basis of the RVM data. Both patients received a standard opioid dose when they pushed the button on their Patient Controlled Analgesia (PCA) pumps. Patient A was “Not-At-Risk”, never became “Un-Safe” and the opioid dosing on his PCA pump seems appropriate. Alternatively, Patient B started in the “At-Risk” category. The idea here is that if Patient B had received a lower dose of opioid in his PCA pump, he might not have dropped his MV into the “Un-Safe” range. Creating low dose opioid protocols for patients considered “At-Risk” for developing low minute ventilation with standard opioid dosing can have an important effect on improving patient safety.
Q: Based on this research, would you recommend the use of the device and this “80/40” opioid risk-prediction protocol?
A: Yes. I would recommend utilizing this “80/40” protocol. When patients are “At-Risk” with a MV less than 80% of their expected MV, it makes sense for the physician to individualize a patient’s pain management regimen with a lower dose opioid strategy and/or by using other drugs like non-steroidal anti-inflammatories or intra-venous Tylenol. It also helps the physician determine which patients would be best served by additional monitoring or respiratory interventions such as CPAP or BiPAP.
Q: Overall what do you think the impact of this device will have on patient care?”
A: The bottom line is that the previously unavailable information provided by the RVM at the point-of-care can help physicians and nurses communicate and make decisions based on real-time quantitative data instead of relying on preoperative risk assessment and subjective observations. I see this as improving both patient safety and patient satisfaction. Patients can receive the “right dose” of opioids to keep them both safe and comfortable.
By providing an accurate assessment of respiratory risk, the RVM can also help with timing of PACU discharge and the appropriate selection of patients to be transitioned to higher acuity settings or monitoring environments versus the general hospital floor. This has the potential to positively impact PACU through-put and decrease the substantive costs associated with prolonged PACU stays. It’s a win, win, win, for patients, caregivers and hospital systems.
 Pesaro C. Opioid-induced sedation and respiratory depression: evidence based monitoring guidelines. J Perianesth Nurs. 2012;27:208Y211. Willens JS, Junquist CR, Cohen A, Polomano R. ASPM survey-nurses’ practice patterns related to monitoring and preventing respiratory depression. Pain Manag Nurs. 2013;14:60Y65.
 Monitoring Minute Ventilation versus Respiratory Rate to Measure the Adequacy of Ventilation in Patients Undergoing Upper Endoscopic Procedures, Monitoring Minute Ventilation versus Respiratory Rate to Measure the Adequacy of Ventilation in Patients Undergoing Upper Endoscopic Procedures Katherine Holley, DO, et. al., poster presentation, IARS 2014
 Objective Post-Operative Ventilatory Assessment Algorithms in Obese Patients for PACU Monitoring, Roman Schumann , MD, et. al., Tufts Medical Center, Tufts University School of Medicine, Boston, MA poster presentation
The Use of a Non-Invasive Respiratory Volume Monitor to Measure the Adequacy of Ventilation in Patients under Conscious Sedation for Routine Endoscopic Procedures, Katherine Holley, DO, University of Vermont College of Medicine, Burlington, VT, IARS poster presentation.
 Objective Post-Operative Ventilatory Assessment Algorithms in Obese Patients for PACU Monitoring, Roman Schumann , MD, et. al., Tufts Medical Center, Tufts University School of Medicine, Boston, MA, IARS poster presentation