Uezono, Shoichi

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.

SummaryThis article reviews potential pediatric applications of 3 new technologies. (1) Pulse oximetry‐based hemoglobin determination: Hemoglobin determination using spectrophotometric methods recently has been introduced in adults with varied success. This non‐invasive and continuous technology may avoid venipuncture and unnecessary transfusion in children undergoing surgery with major blood loss, premature infants undergoing unexpected and complicated emergency surgery, and children with chronic illness. (2) Continuous cardiac output monitoring: In adults, advanced hemodynamic monitoring such as continuous cardiac output monitoring has been associated with better surgical outcomes. Although it remains unknown whether similar results are applicable to children, current technology enables the monitoring of cardiac output non‐invasively and continuously in pediatric patients. It may be important to integrate the data about cardiac output with other information to facilitate therapeutic interventions. (3) Anesthesia information management systems: Although perioperative electronic anesthesia information management systems are gaining popularity in operating rooms, their potential functions may not be fully appreciated. With advances in information technology, anesthesia information management systems may facilitate bedside clinical decisions, administrative needs, and research in the perioperative setting.