[논문]Predictors of chronic prescription opioid use after orthopedic surgery: derivation of a clinical prediction rule.

Rhon, Daniel I; Snodgrass, Suzanne J; Cleland, Joshua A; Sissel, Charles D; Cook, Chad E

doi:10.1186/s13741-018-0105-8

Predictors of chronic prescription opioid use after orthopedic surgery: derivation of a clinical prediction rule. 원문보기

Perioperative medicine, v.7 no.1, 2018년, pp.25 -

Rhon, Daniel I (Center for the Intrepid, Brooke Army Medical Center, 3551 Roger Brooke Drive, JBSA Fort Sam, Houston, TX 78234 USA) , Snodgrass, Suzanne J (School of Health Sciences, Faculty of Health and Medicine, The University of Newcastle, University Drive, Callaghan, NSW Australia) , Cleland, Joshua A (Department of Physical Therapy, Franklin Pierce University, Manchester, NH USA) , Sissel, Charles D (Program Analysis and Evaluation Division, US Army Medical Command, Joint Base San Antonio - Fort Sam Houston, San Antonio, TX 78234 USA) , Cook, Chad E (Division of Physical Therapy, Department of Orthopedics, Duke University, Duke MSK, Duke Clinical Research Institute, Durham, NC USA)

Abstract ▼ AI-Helper

BackgroundPrescription opioid use at high doses or over extended periods of time is associated with adverse outcomes, including dependency and abuse. The aim of this study was to identify mediating variables that predict chronic opioid use, defined as three or more prescriptions after orthopedic surgery.MethodsIndividuals were ages between 18 and 50 years and undergoing arthroscopic hip surgery between 2004 and 2013. Two categories of chronic opioid use were calculated based on individuals (1) having three or more unique opioid prescriptions within 2 years and (2) still receiving opioid prescriptions > 1 year after surgery. Univariate elationships were identified for each predictor variable, then significant variables (P > 0.15) were entered into a multivariate logistic regression model to identify the most parsimonious group of predictor variables for each chronic opioid use classification. Likelihood ratios were derived from the most robust groups of variables.ResultsThere were 1642 participants (mean age 32.5 years, SD 8.2, 54.1% male). Nine predictor variables met the criteria after bivariate analysis for potential inclusion in each multivariate model. Eight variables: socioeconomic status (from enlisted rank family), prior use of opioid medication, prior use of non-opioid pain medication, high health-seeking behavior before surgery, a preoperative diagnosis of insomnia, mental health disorder, or substance abuse were all predictive of chronic opioid use in the final model (seven variables for three or more opioid prescriptions; four variables for opioid use still at 1 year; all< 0.05). Post-test probability of having three or more opioid prescriptions was 93.7% if five of seven variables were present, and the probability of still using opioids after 1 year was 69.6% if three of four variables were present.ConclusionA combination of variables significantly predicted chronic opioid use in this cohort. Most of these variables were mediators, indicating that modifying them may be feasible, and the potential focus of interventions to decrease the risk of chronic opioid use, or at minimum better inform opioid prescribing decisions. This clinical prediction rule needs further validation.

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Predictors of chronic prescription opioid use after orthopedic surgery: derivation of a clinical prediction rule. 원문보기

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