Prediction model based on seven variables, including younger age, preoperative daily opioid use
TUESDAY, Sept. 15, 2020 (HealthDay News) — A score based on seven variables can accurately predict the probability of poorly controlled pain after elective spine surgery, according to a study published online Sept. 15 in the Journal of Neurosurgery: Spine.
Michael M.H. Yang, M.D., from the University of Calgary in Alberta, Canada, and colleagues 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.
The researchers found that in the first 24 hours after surgery, 57 percent 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 percent, 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 percent, 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.
Two authors disclosed financial ties to the medical device industry.
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