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State regulations have decreased prescribed opioids with more than 25% of patients abstaining from opioids. Despite this, 2 distinct populations of patients exist who consume "high" or "low" amounts of opioids. The aim of this study was to identify factors associated with postoperative opioid use after common surgical procedures and develop an opioid risk score.Patients undergoing 35 surgical procedures from 7 surgical specialties were identified at a 620-bed tertiary care academic center and surveyed 1 week after discharge regarding opioid use and adequacy of analgesia. Electronic medical record data were used to characterize postdischarge opioids, complications, demographics, medical history, and social factors. High opioid use was defined as75th percentile morphine milligram equivalents for each procedure. An opioid risk score was calculated from factors associated with opioid use identified by backward multivariate logistic regression analysis.A total of 1,185 patients were enrolled between September 2017 and February 2019. Bivariate analyses revealed patient factors associated with opioid use including earlier substance use (p0.001), depression (p = 0.003), anxiety (p0.001), asthma (p = 0.006), obesity (p = 0.03), migraine (p = 0.004), opioid use in the 7 days before surgery (p0.001), and 31 Clinical Classifications Software Refined classifications (p0.05). Significant multivariates included: insurance (p = 0.005), employment status (p = 0.005), earlier opioid use (odds ratio [OR] 2.38 [95% CI 1.21 to 4.68], p = 0.01), coronary artery disease (OR 0.38 [95% CI 0.16 to 0.86], p = 0.02), acute pulmonary embolism (OR 9.81 [95% CI 3.01 to 32.04], p0.001), benign breast conditions (OR 3.42 [95% CI 1.76 to 6.64], p0.001), opioid-related disorders (OR 6.67 [95% CI 1.87 to 23.75], p = 0.003), mental and substance use disorders (OR 3.80 [95% CI 1.47 to 9.83], p = 0.006), headache (OR 1.82 [95% CI 1.24 to 2.67], p = 0.002), and previous cesarean section (OR 5.10 [95% CI 1.33 to 19.56], p = 0.02). An opioid risk score base was developed with an area under the curve of 0.696 for the prediction of high opioid use.Preoperative patient characteristics associated with high opioid use postoperatively were identified and an opioid risk score was derived. Identification of patients with a higher need for opioids presents an opportunity for improved preoperative interventions, the use of nonopioid analgesic therapies, and alternative therapies.

Background Unplanned ICU admissions (up-ICUad) are associated with poor outcomes. It is difficult to identify who is at risk for up-ICUad in trauma patients. This study aimed to identify injury patterns and comorbidities associated with up-ICUad and develop a predictive tool for who is at risk. Methods A retrospective study compared trauma patients admitted to the floor who experienced an up-ICUad to similar patients without an up-ICUad. Univariate analysis and multivariate logistic regression identified independent risk factors associated with up-ICUad. Based on those factors, a Risk Score (RS) was created and compared between the two groups. Results 2.15% of the 7206 patients experienced an up-ICUad. The up-ICUad group was older, experienced longer length of stay, and had higher mortality. Age, congestive heart failure, COPD, peptic ulcer disease, mild liver disease, CKD, and significant injuries to the thorax, spine, and lower extremities were independently associated with up-ICUad. A RS equation was created and was used for each patient. Conclusions Trauma patients are at increased risk for up-ICUad based on specific factors. These factors can be used to calculate a RS to determine who is at greatest risk for an up-ICUad which may be helpful for preventing up-ICUad.