Predicting poor postoperative pain control after elective spine surgery
Date
2019-06-26
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Abstract
Background: 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.
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Keywords
spine surgery, postoperative pain, prediction model, surgery, pain measurement
Citation
Yang, M. H. M. (2019). Predicting poor postoperative pain control after elective spine surgery (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca.