Predicting poor postoperative pain control after elective spine surgery

dc.contributor.advisorRiva-Cambrin, Jay
dc.contributor.advisorCasha, Steven
dc.contributor.authorYang, Min-Han Michael
dc.contributor.committeememberSajobi, Tolulope
dc.contributor.committeememberJetté, Nathalie
dc.description.abstractBackground: Inadequate postoperative pain control after spine surgery is common and can lead to patient dissatisfaction and poor outcomes. Predictors for poorly controlled pain after spine surgery are unknown and preoperative prognostic tools are not available to aid in the identification of high-risk patients to help facilitate the development of personalized treatments. In this thesis, we performed (1) a systematic review on the predictors associated with poor pain control in surgical patients; (2) performed a retrospective cohort study evaluating predictors of poor postoperative pain control following spine surgery; and (3) developed and validated a clinical prediction score to identify patients at high-risk for developing poor pain control. Methods: (1) A random-effects model was used to meta-analyze the predictors for poor pain control after surgery in the systematic review. (2) Adults from the Canadian Spine Outcomes and Research Network registry who underwent elective cervical or thoracolumbar surgery were included. Preoperative predictors for poor pain control (mean numeric rating scale for pain>4 at rest during the first 24 hours after surgery) were identified using a multivariable logistic regression model. (3) The prediction score was developed and internally validated using a 70:30 split-sample method. Results: (1) Thirty-three studies representing 53,362 patients were included in the systematic review. Nine significant predictors for poor postoperative pain control were identified across surgical disciplines. (2) The retrospective cohort study included 1,300 patients, of which 56.7% had poor pain control after surgery. The multivariable model identified that younger age, female sex, preoperative daily opioid use, higher preoperative neck/back pain, higher depression scores on patient health questionnaire-9, ≥3 motion segment surgery, and fusion surgery were associated with poor pain control. (3) Patients identified as low-, high-, and extreme-risk by the score had 32.0%, 63.0%, and 85.0% probability of developing poor pain control, respectively. Conclusion: Seven significant predictors for poorly controlled pain after spine surgery were identified and incorporated into a prediction score. The score can discriminate patients at higher risk for, and accurately predict the probability of, developing poor pain control after surgery.en_US
dc.identifier.citationYang, M. H. M. (2019). Predicting poor postoperative pain control after elective spine surgery (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from
dc.publisher.facultyCumming School of Medicineen_US
dc.publisher.institutionUniversity of Calgaryen
dc.rightsUniversity of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.en_US
dc.subjectspine surgeryen_US
dc.subjectpostoperative painen_US
dc.subjectprediction modelen_US
dc.subjectpain measurementen_US
dc.subject.classificationMedicine and Surgeryen_US
dc.titlePredicting poor postoperative pain control after elective spine surgeryen_US
dc.typemaster thesisen_US – Community Health Sciencesen_US of Calgaryen_US of Science (MSc)en_US
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