Overdyk, Frank J.

BACKGROUND: Sleep disorders affect up to 25% of the general population and are associated with increased risk of adverse perioperative events. The key sleep medicine topics that are most important for the practice of anesthesiology have not been well-defined. The objective of this study was to determine the high-priority sleep medicine topics that should be included in the education of anesthesia residents based on the insight of experts in the fields of anesthesia and sleep medicine. METHODS: We conducted a prospective cross-sectional survey of experts in the fields of sleep medicine and anesthesia based on the Delphi technique to establish consensus on the sleep medicine topics that should be incorporated into anesthesia residency curricula. Consensus for inclusion of a topic was defined as >80% of all experts selecting “agree” or “strongly agree” on a 5-point Likert scale. Responses to the survey questions were analyzed with descriptive statistical methods and presented as percentages or weighted mean values with standard deviations (SD) for Likert scale data. RESULTS: The topics that were found to have 100% agreement among experts were the influence of opioids and anesthetics on control of breathing and upper airway obstruction; potential interactions of wake-promoting/hypnotic medications with anesthetic agents; effects of sleep and anesthesia on upper airway patency; and anesthetic management of sleep apnea. Less than 80% agreement was found for topics on the anesthetic implications of other sleep disorders and future pathways in sleep medicine and anesthesia. CONCLUSIONS: We identify key topics of sleep medicine that can be included in the future design of anesthesia residency training curricula.

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: Obstructive sleep apnea (OSA) patients are at increased risk for pulmonary and cardiovascular complications; perioperative mortality risk is unclear. This report analyzes cases submitted to the OSA Death and Near Miss Registry, focusing on factors associated with poor outcomes after an OSA-related event. We hypothesized that more severe outcomes would be associated with OSA severity, less intense monitoring, and higher cumulative opioid doses. METHODS: Inclusion criteria were age ≥18 years, OSA diagnosed or suspected, event related to OSA, and event occurrence 1992 or later and <30 days postoperatively. Factors associated with death or brain damage versus other critical events were analyzed by tests of association and odds ratios (OR; 95% confidence intervals [CIs]). RESULTS: Sixty-six cases met inclusion criteria with known OSA diagnosed in 55 (83%). Patients were middle aged (mean = 53, standard deviation [SD] = 15 years), American Society of Anesthesiologists (ASA) III (59%, n = 38), and obese (mean body mass index [BMI] = 38, SD = 9 kg/m 2 ); most had inpatient (80%, n = 51) and elective (90%, n = 56) procedures with general anesthesia (88%, n = 58). Most events occurred on the ward (56%, n = 37), and 14 (21%) occurred at home. Most events (76%, n = 50) occurred within 24 hours of anesthesia end. Ninety-seven percent (n = 64) received opioids within the 24 hours before the event, and two-thirds (41 of 62) also received sedatives. Positive airway pressure devices and/or supplemental oxygen were in use at the time of critical events in 7.5% and 52% of cases, respectively. Sixty-five percent (n = 43) of patients died or had brain damage; 35% (n = 23) experienced other critical events. Continuous central respiratory monitoring was in use for 3 of 43 (7%) of cases where death or brain damage resulted. Death or brain damage was (1) less common when the event was witnessed than unwitnessed (OR = 0.036; 95% CI, 0.007–0.181; P < .001); (2) less common with supplemental oxygen in place (OR = 0.227; 95% CI, 0.070–0.740; P = .011); (3) less common with respiratory monitoring versus no monitoring (OR = 0.109; 95% CI, 0.031–0.384; P < .001); and (4) more common in patients who received both opioids and sedatives than opioids alone (OR = 4.133; 95% CI, 1.348–12.672; P = .011). No evidence for an association was observed between outcomes and OSA severity or cumulative opioid dose. CONCLUSIONS: Death and brain damage were more likely to occur with unwitnessed events, no supplemental oxygen, lack of respiratory monitoring, and coadministration of opioids and sedatives. It is important that efforts be directed at providing more effective monitoring for OSA patients following surgery, and clinicians consider the potentially dangerous effects of opioids and sedatives—especially when combined—when managing OSA patients postoperatively.

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.