A score based on seven variables can accurately predict the probability of poorly controlled pain after elective spine surgery, according to a study published in the Journal of Neurosurgery: Spine. Researchers conducted a retrospective study in adults undergoing elective cervical or thoracolumbar spine surgery. A prediction model was developed based on 25 candidate variables. The model was transformed into an eight-tier risk based score, which was simplified into a three tier Calgary Postoperative Pain After Spine Surgery (CAPPS) score. In the first 24 hours after surgery, 57% of 1,300 spine surgery patients experienced poorly controlled pain. The prediction model incorporated seven significant variables: younger age, female sex, preoperative daily use of opioid medication, higher preoperative neck or back pain intensity, higher Patient Health Questionnaire-9 depression score, surgery involving ≥3 motion segments, and fusion surgery. The model had good discrimination (C-statistic, 0.74) and calibration (Hosmer- Lemeshow goodness-of-fit) for predicting outcome. The probability of experiencing poorly controlled pain was 32%, 63%, and 85%, respectively, in low-, high-, and extreme-risk groups stratified using the CAPPS score; these results were mirrored by observed incidence rates of 37%, 62%, and 81%, respectively, in the validation cohort. “This score can be used to facilitate preoperative patient education and the development of personalized clinical care pathways to improve postoperative acute pain outcomes,” the authors write.
