Great strides have been made to provide effective, affordable, patient-centered healthcare. But there are still patient issues that demand attention. One is respiratory compromise.
That’s why we sponsored the PRediction of Opioid‐induced respiratory Depression In patients monitored by capnoGraphY (PRODIGY) study. In the study, we examined the clinical benefits of pulse oximetry and capnography for patients receiving opioids on the medical-surgical floor. The purpose is to be able to intervene before respiratory compromise occurs.
In this blog post, we’ll define respiratory compromise, tell you more about the PRODIGY study, and highlight how to leverage the results of the study to reduce the risk of respiratory compromise.
What is respiratory compromise?
Respiratory compromise is a state in which there’s a high likelihood of respiratory function decompensation into respiratory insufficiency, failure, and death.1 In fact, respiratory compromise increases patient mortality by 30 percent.2
This medical scenario is common. In fact, respiratory failure is the leading cause of rescue calls,3 ICU admissions4, and code blues.5 It’s also costly to the healthcare system. An additional $18,208 is spent for every patient with hospital-contracted respiratory compromise.6
How does PRODIGY help identify high-risk patients?
Respiratory compromise can occur in patients who are prescribed opioids for pain management — referred to as opioid-induced respiratory depression (OIRD). Study results showed that prolonged periods of OIRD are very common in patients on the medical-surgical floor. OIRD occurred in 41 percent of all patients.7
Related: Find out more about postoperative opioid-induced respiratory depression. Read the closed claims analysis.
Ashish Khanna, MD, FCCP, FCCM, an associate professor of anesthesiology and associate chief of research at Wake Forest University School of Medicine in Winston-Salem, North Carolina was lead investigator on the PRODIGY study.
In an interview about the study, Dr. Khanna explains that when patients are on the medical-surgical floor, some signs of respiratory compromise go unrecognized. The study indicated clinicians are missing large chunks of time where hypoxemia, hyperventilation, and even hypotension occur in patients on the medical-surgical floor. And these events may translate into true clinical events that evolve into respiratory compromise.8
Another contributing factor to respiratory compromise is the use of opioids in postoperative care. There is an increasing focus on balancing the competing priorities of providing adequate postoperative pain control while avoiding the side effects opioids may trigger. Particularly in patients suffering from obstructive sleep apnea.9
A closed claim analysis by the American Society of Anesthesiologists revealed that 88 percent of respiratory depression events happened within 24 hours of a surgical procedure.10 Though patient etiologies and clinical care factors may both contribute to respiratory compromise, it’s important to consider continues capnography and pulse oximetry monitoring to help clinicians mitigate and prevent respiratory compromise.
How to reduce the risk of respiratory compromise
Detection and speedy intervention are key in reducing incidents of opioid-induced respiratory depression. The PRODIGY study offers insight into the benefits of continuous capnography and pulse oximetry monitoring as a method to reduce respiratory compromise occurrences in at risk patients. The study incorporated a risk assessment tool to identify patients who should be continuously monitored while on the medical-surgical floor.
In addition to patients’ age and gender, the scoring criteria includes ratings for whether the patient is opioid naïve, has a known sleep disordered breathing condition, and/or has diagnosed chronic heart failure. The risk assessment scoring tool, can help clinicians determine if the patient has low, moderate, or high risk of experiencing a respiratory depression episode.7
The assessment tool may give healthcare providers earlier insight into signs that a patient may be decompensating.
References , 2, 43-45.http://dx.doi.org/10.4236/ojem.2014.23007.
1. Morris TA, Gay PC, MacIntyre NR, et al. Respiratory compromise as a new paradigm for the care of vulnerable hospitalized patients. RespirCare 2017;62(4):497–512.
2. PhuaJ, BadiaJR, Adhikari NKJ, et al. Has mortality from acute respiratory distress syndrome decreased over time? A systematic review. Am J Respir Crit Care Med. 2009;179(3):220–227.
3. Chelluri, L. (2014) Preventable In-Hospital Cardiac Arrests―Are We Monitoring the Wrong Organ? Open Journal of Emergency Medicine
4. Critical Care Statistics. Society for Critical Care Medicine — The Intensive Care Professionals. http://www.sccm.org/Communications/Pages/CriticalCareStats.aspx.
5. Schein RM, HazdayN, Pena M, Ruben BH, Sprung CL. Clinical Antecedents to In-hospital Cardiopulmonary Arrest. Chest (1990) 98;6,1388–1392.
6. Kelley SD, Agarwal S, Parikh N, Erslon M, Morris P. Respiratory insufficiency, arrest, and failure among medical patients on the general care floor (Abstract 764). CritCare Med. 2012 Vol. 40, No. 12 (Suppl.).
7. Khanna AK, Bergese S, Jungquist C, Morimatsu H, Uezono S et al. Prediction of Opioid-Induced Respiratory Depression on Inpatient Wards Using Continuous Capnography and Oximetry: Depression on Inpatient Wards Using Continuous Capnography and Oximetry: An International Prospective, Observational Trial. U.S. National Library of Medicine. Clinical trials website. https://clinicaltrials.gov/ct2/show/NCT02811302
8. SCCM POD-379 Opioid-Induced Respiratory Depression Risk Prediction Tool. Society of Critical Care Medicine. https://www.sccm.org/Communications/iCritical-Care/All-Audio-iCritical-Care/SCCM-Pod-379-Opioid-Induced-Respiratory-Depression
9. Weingarten TN, Herasevich V, McGlinch MC. Predictors of delayed postoperative respiratory depression assessed from Naloxone administration. Anesth Analg. 2015;121(2):422–429.
10. Lee LA, Caplan RA, Stephens LS, et al. Postoperative Opioid-induced Respiratory Depression: A Closed Claims Analysis. Anesthesiology. 2015;122(3):659–665.
, 2, 43-45.http://dx.doi.org/10.4236/ojem.2014.23007.
Trial. Pending publication.
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