Jeannine M Brant1, Lee Stringer2, Lisa R Jurkovich3, Nicholas C Coombs4, Elizabeth J Mullette4, Christy Buffington5, Sherry Herbert6, David Karera7. 1. Center for Clinical Translational Research, Billings Clinic, Billings, MT jbrant@billingsclinic.org. 2. Stringer Healthcare Consultants, Fort Lauderdale, FL. 3. Quality Resources, Billings Clinic, Billings, MT. 4. Center for Clinical Translational Research, Billings Clinic, Billings, MT. 5. Surgery Center, Billings Clinic, Billings, MT. 6. Billings Clinic, Billings, MT. 7. Department of Anesthesia, New York Medical College, Valhalla, NY.
Abstract
PURPOSE: Results of a study to determine demographic and clinical characteristics predictive of oversedation and potential opioid-induced respiratory depression (OIRD) in hospitalized patients are reported. METHODS: In a retrospective case-controlled study, an incident reporting database was searched to identify cases of in-hospital oversedation; to form the control group, patients who did not experience an oversedation event while hospitalized were sampled in reverse chronological order until the desired total sample size (n = 225) was obtained. An allocation ratio of 2:1 was specified to adjust for case variability. Binary logistic regression was employed to identify factors predictive of oversedation. RESULTS: Female sex (odds ratio [OR], 2.41; 95% confidence interval [CI], 1.05-5.50), comorbid renal disease (OR, 4.22; 95% CI, 1.66-10.70), untreated sleep apnea (OR, 32.32; 95% CI, 2.72-384.72), receipt of long-acting oxycodone (OR, 4.76; 95% CI, 1.70-13.33), and as-needed use of hydromorphone (OR, 2.73; 95% CI, 1.19-6.27) were significant predictors of oversedation; as-needed analgesia administered by the oral route (OR, 0.16; 95% CI, 0.07-0.36) or i.v. route (OR, 0.33; 95% CI, 0.14-0.80) had a significant protective effect. The final prediction model explained 47.8% of variance in oversedation risk and was found to have strong discriminatory performance. CONCLUSION: The identified risk factors for oversedation and potential OIRD in hospitalized patients can form the basis of quality-improvement initiatives to prevent oversedation through improved prescribing and patient monitoring.
PURPOSE: Results of a study to determine demographic and clinical characteristics predictive of oversedation and potential opioid-induced respiratory depression (OIRD) in hospitalized patients are reported. METHODS: In a retrospective case-controlled study, an incident reporting database was searched to identify cases of in-hospital oversedation; to form the control group, patients who did not experience an oversedation event while hospitalized were sampled in reverse chronological order until the desired total sample size (n = 225) was obtained. An allocation ratio of 2:1 was specified to adjust for case variability. Binary logistic regression was employed to identify factors predictive of oversedation. RESULTS: Female sex (odds ratio [OR], 2.41; 95% confidence interval [CI], 1.05-5.50), comorbid renal disease (OR, 4.22; 95% CI, 1.66-10.70), untreated sleep apnea (OR, 32.32; 95% CI, 2.72-384.72), receipt of long-acting oxycodone (OR, 4.76; 95% CI, 1.70-13.33), and as-needed use of hydromorphone (OR, 2.73; 95% CI, 1.19-6.27) were significant predictors of oversedation; as-needed analgesia administered by the oral route (OR, 0.16; 95% CI, 0.07-0.36) or i.v. route (OR, 0.33; 95% CI, 0.14-0.80) had a significant protective effect. The final prediction model explained 47.8% of variance in oversedation risk and was found to have strong discriminatory performance. CONCLUSION: The identified risk factors for oversedation and potential OIRD in hospitalized patients can form the basis of quality-improvement initiatives to prevent oversedation through improved prescribing and patient monitoring.
Authors: John Garrett; Anneliese Vanston; Gerald Ogola; Briget da Graca; Cindy Cassity; Maria A Kouznetsova; Lauren R Hall; Taoran Qiu Journal: BMJ Open Date: 2021-11-24 Impact factor: 2.692
Authors: Sounak Roy; Stephen Bruehl; Xiaoke Feng; Matthew S Shotwell; Thomas Van De Ven; Andrew D Shaw; Miklos D Kertai Journal: BMJ Open Date: 2022-09-05 Impact factor: 3.006