Predicting opioid-induced oversedation in hospitalised patients: a multicentre observational study

Abstract

ObjectivesOpioid-induced respiratory depression (OIRD) and oversedation are rare but potentially devastating adverse events in hospitalised patients. We investigated which features predict an individual patient’s risk of OIRD or oversedation; and developed a risk stratification tool that can be used to aid point-of-care clinical decision-making.DesignRetrospective observational study.SettingTwelve acute care hospitals in a large not-for-profit integrated delivery system.ParticipantsAll inpatients ≥18 years admitted between 1 July 2016 and 30 June 2018 who received an opioid during their stay (163 190 unique hospitalisations).Main outcome measuresThe primary outcome was occurrence of sedation or respiratory depression severe enough that emergent reversal with naloxone was required, as determined from medical record review; if naloxone reversal was unsuccessful or if there was no evidence of hypoxic encephalopathy or death due to oversedation, it was not considered an oversedation event.ResultsAge, sex, body mass index, chronic obstructive pulmonary disease, concurrent sedating medication, renal insufficiency, liver insufficiency, opioid naïvety, sleep apnoea and surgery were significantly associated with risk of oversedation. The strongest predictor was concurrent administration of another sedating medication (adjusted HR, 95% CI=3.88, 2.48 to 6.06); the most common such medications were benzodiazepines (29%), antidepressants (22%) and gamma-aminobutyric acid analogue (14.7%). The c-statistic for the final model was 0.755. The 24-point Oversedation Risk Criteria (ORC) score developed from the model stratifies patients as high (>20%, ≥21 points), moderate (11%–20%, 10–20 points) and low risk (≤10%, <10 points).ConclusionsThe ORC risk score identifies patients at high risk for OIRD or oversedation from routinely collected data, enabling targeted monitoring for early detection and intervention. It can also be applied to preventive strategies—for example, clinical decision support offered when concurrent prescriptions for opioids and other sedating medications are entered that shows how the chosen combination impacts the patient’s risk.

Developing a risk stratification tool for predicting opioid-related respiratory depression after non-cardiac surgery: a retrospective study

“…Another difference between the present results and prior work relates to the impact of age, with the current study indicating higher respiratory depression risk in younger individuals but some other studies showing increased risk in older individuals. 3 7 15 While reasons for these differences cannot be conclusively determined, the fact that the current predictive findings were replicated in a separate validation sample lend them credence. Finally, our finding that history of drug abuse predicted risk for a serious opioid-related adverse drug event requiring naloxone administration is similar to results of a recent large-scale retrospective study.…”

“… 6 Several existing studies have also reported that female sex predicts respiratory depression as in the current work. 3 5 6 15 In contrast, three studies, including the only available prospective study, suggested that men were at elevated risk of respiratory depression. Differences regarding sex effects on respiratory depression between some prior studies and the current work may be due in part to the specific outcome measures targeted, which included respiratory depression indexed by oximetry and capnography 7 and opioid adverse events more broadly defined, 16 rather than severe respiratory depression requiring naloxone as in the current work.…”

“…Based on these findings, the authors developed a weighted oversedation risk criteria (ORC) scoring system (range 0–24) which could be used to stratify patients as high, moderate and low risk of requiring naloxone administration. 3 In the original derivation sample, this ORC scoring system showed good predictive value (c-index=0.755). However, neither the predictive model nor the ORC scoring system were validated in a separate sample, so it is unknown whether predictive accuracy would be similar in a new sample.…”

“…Available retrospective observational studies which have aimed to predict opioid-induced respiratory depression or oversedation requiring naloxone have several limitations. 3 4 A 2-year study investigating oversedation following opioid analgesic administration identified 53 events among patients above 18 years of age. 4 Being opioid naive prior to opioid administration was the only predictor of oversedation identified, although the small sample had little statistical power for testing predictors.…”

“…A larger (n=163 191) retrospective study encompassing 12 acute care hospitals tested predictors of opioid-related respiratory depression as indexed by naloxone administration. 3 In a multivariable model, occurrence of significant respiratory depression was predicted by older age; female sex; low or high body mass index; undergoing surgery; pre-existing opioid use; and presence of chronic obstructive pulmonary disease, hepatic or renal insufficiency, or sleep apnoea. In addition, the strongest predictor of naloxone administration was concurrent administration of sedating medication (most commonly, benzodiazepines).…”