Law, Lawrence Siu‐Chun

BACKGROUND: Opioid-induced respiratory depression (OIRD) is common on the medical and surgical wards and is associated with increased morbidity and health care costs. While previous studies have investigated risk factors for OIRD, the role of race remains unclear. We aim to investigate the association between race and OIRD occurrence on the medical/surgical ward. METHODS: This is a post hoc analysis of the PRediction of Opioid-induced respiratory Depression In patients monitored by capnoGraphY (PRODIGY) trial; a prospective multinational observational blinded study of 1335 general ward patients who received parenteral opioids and underwent blinded capnography and oximetry monitoring to identify OIRD episodes. For this study, demographic and perioperative data, including race and comorbidities, were analyzed and assessed for potential associations with OIRD. Univariable χ 2 and Mann-Whitney U tests were used. Stepwise selection of all baseline and demographic characteristics was used in the multivariable logistic regression analysis. RESULTS: A total of 1253 patients had sufficient racial data (317 Asian, 158 Black, 736 White, and 42 other races) for inclusion. The incidence of OIRD was 60% in Asians (N = 190/317), 25% in Blacks (N = 40/158), 43% in Whites (N = 316/736), and 45% (N = 19/42) in other races. Baseline characteristics varied significantly: Asians were older, more opioid naïve, and had higher opioid requirements, while Blacks had higher incidences of heart failure, obesity, and smoking. Stepwise multivariable logistic regression revealed that Asians had increased risk of OIRD compared to Blacks (odds ratio [OR], 2.49; 95% confidence interval [CI], 1.54–4.04; P = .0002) and Whites (OR, 1.38; 95% CI, 1.01–1.87; P = .0432). Whites had a higher risk of OIRD compared to Blacks (OR, 1.81; 95% CI, 1.18–2.78; P = .0067). The model’s area under the curve was 0.760 (95% CI, 0.733–0.787), with a Hosmer-Lemeshow goodness-of-fit test P value of .23. CONCLUSIONS: This post hoc analysis of PRODIGY found a novel association between Asian race and increased OIRD incidence. Further study is required to elucidate its underlying mechanisms and develop targeted care pathways to reduce OIRD in susceptible populations.

BACKGROUND: Opioid-related adverse events are a serious problem in hospitalized patients. Little is known about patients who are likely to experience opioid-induced respiratory depression events on the general care floor and may benefit from improved monitoring and early intervention. The trial objective was to derive and validate a risk prediction tool for respiratory depression in patients receiving opioids, as detected by continuous pulse oximetry and capnography monitoring. METHODS: PRediction of Opioid-induced respiratory Depression In patients monitored by capnoGraphY (PRODIGY) was a prospective, observational trial of blinded continuous capnography and oximetry conducted at 16 sites in the United States, Europe, and Asia. Vital signs were intermittently monitored per standard of care. A total of 1335 patients receiving parenteral opioids and continuously monitored on the general care floor were included in the analysis. A respiratory depression episode was defined as respiratory rate ≤5 breaths/min (bpm), oxygen saturation ≤85%, or end-tidal carbon dioxide ≤15 or ≥60 mm Hg for ≥3 minutes; apnea episode lasting >30 seconds; or any respiratory opioid-related adverse event. A risk prediction tool was derived using a multivariable logistic regression model of 46 a priori defined risk factors with stepwise selection and was internally validated by bootstrapping. RESULTS: One or more respiratory depression episodes were detected in 614 (46%) of 1335 general care floor patients (43% male; mean age, 58 ± 14 years) continuously monitored for a median of 24 hours (interquartile range [IQR], 17–26). A multivariable respiratory depression prediction model with area under the curve of 0.740 was developed using 5 independent variables: age ≥60 (in decades), sex, opioid naivety, sleep disorders, and chronic heart failure. The PRODIGY risk prediction tool showed significant separation between patients with and without respiratory depression ( P < .001) and an odds ratio of 6.07 (95% confidence interval [CI], 4.44–8.30; P < .001) between the high- and low-risk groups. Compared to patients without respiratory depression episodes, mean hospital length of stay was 3 days longer in patients with ≥1 respiratory depression episode (10.5 ± 10.8 vs 7.7 ± 7.8 days; P < .0001) identified using continuous oximetry and capnography monitoring. CONCLUSIONS: A PRODIGY risk prediction model, derived from continuous oximetry and capnography, accurately predicts respiratory depression episodes in patients receiving opioids on the general care floor. Implementation of the PRODIGY score to determine the need for continuous monitoring may be a first step to reduce the incidence and consequences of respiratory compromise in patients receiving opioids on the general care floor.