Bergese, Sergio D.

BACKGROUND: The frequency and temporal distribution of postoperative respiratory depression (RD) events are not completely understood. This study determined the temporal distribution and frequency of RD episodes in postsurgical patients continuously monitored by bedside capnography and pulse oximetry. METHODS: This was a post hoc study of a subset of postsurgical patients enrolled in The PRediction of Opioid-induced respiratory Depression In patients monitored by capnoGraphY (PRODIGY) trial from 2 sites in the United States. These patients had undergone continuous bedside monitoring on general care wards. These data were adjudicated for potential RD episodes. The number of RD episodes per patient and the time of each RD episode were determined. The first RD episode experienced by a patient was classified as an “initial” episode, and the initial and all subsequent RD episodes experienced by a patient were classified as “all” episodes. A PRODIGY risk score was calculated. RESULTS: Data analyzed from 250 patients contained 2539 RD episodes in 155 (62.0%, 95% confidence interval, 55.7-68.0) patients with median 2 [0–8], range of 0–545 RD episodes per patient, with a PRODIGY risk score distribution of 100 (40.0%) low, 79 (31.6%) intermediate, 70 (28.0%) high (missing data from 1 patient). Median time to the initial RD episode was 8.8 [5.1–18.0] hours postoperatively. There was a peak occurrence of initial RD events between 14:00 and 20:00 on the day of surgery, and these were associated with a large number of subsequent events in the same timeframe. The peak time of all RD episodes occurred from 02:00 to 06:00. Patients with high PRODIGY risk scores had higher incidence and greater number of RD episodes per patient ( P < .001, overall comparisons between groups for both incidence [χ 2 ] and number of episodes [Kruskal-Wallis test]). CONCLUSIONS: Continuous monitoring of surgical patients demonstrates that RD episodes are common, and risk increases with higher PRODIGY scores. In this patient cohort, the rate of initial RD episodes peaked in the afternoon to early evening, while peak rate of all RD episodes occurred in early morning. Further, among patients with RD episodes, the number of episodes increased with higher PRODIGY scores.

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.