Development and validation of a clinical prediction score for poor postoperative pain control following elective spine surgery

Abstract

OBJECTIVEThirty percent to sixty-four percent of patients experience poorly controlled pain following spine surgery, leading to patient dissatisfaction and poor outcomes. Identification of at-risk patients before surgery could facilitate patient education and personalized clinical care pathways to improve postoperative pain management. Accordingly, the aim of this study was to develop and internally validate a prediction score for poorly controlled postoperative pain in patients undergoing elective spine surgery.METHODSA retrospective cohort study was performed in adult patients (≥ 18 years old) consecutively enrolled in the Canadian Spine Outcomes and Research Network registry. All patients underwent elective cervical or thoracolumbar spine surgery and were admitted to the hospital. Poorly controlled postoperative pain was defined as a mean numeric rating scale score for pain at rest of > 4 during the first 24 hours after surgery. Univariable analysis followed by multivariable logistic regression on 25 candidate variables, selected through a systematic review and expert consensus, was used to develop a prediction model using a random 70% sample of the data. The model was transformed into an eight-tier risk-based score that was further simplified into the three-tier Calgary Postoperative Pain After Spine Surgery (CAPPS) score to maximize clinical utility. The CAPPS score was validated using the remaining 30% of the data.RESULTSOverall, 57% of 1300 spine surgery patients experienced poorly controlled pain during the first 24 hours after surgery. Seven significant variables associated with poor pain control were incorporated into a prediction model: 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. Notably, minimally invasive surgery, body mass index, and revision surgery were not associated with poorly controlled pain. The model was discriminative (C-statistic 0.74, 95% CI 0.71–0.77) and calibrated (Hosmer-Lemeshow goodness-of-fit, p = 0.99) at predicting the outcome. Low-, high-, and extreme-risk groups stratified using the CAPPS score had 32%, 63%, and 85% predicted probability of experiencing poorly controlled pain, respectively, which was mirrored closely by the observed incidence of 37%, 62%, and 81% in the validation cohort.CONCLUSIONSInadequate pain control is common after spine surgery. The internally validated CAPPS score based on 7 easily acquired variables accurately predicted the probability of experiencing poorly controlled pain after spine surgery.

Editorial. Postoperative pain control after spinal surgery: an opportunity

“…1 In the current issue of the Journal of Neurosurgery: Spine, Yang et al use data from the Canadian Spine Outcomes and Research Network (CSORN) to develop a predictive model for identifying patients who had a high or extremely high risk of having inadequate pain control after spinal surgery. 2 In their study, 57% of patients experienced inadequate pain control in the first 24 hours after surgery.…”

Prediction tools for postoperative pain

“… 5 Poor pain control may lead to increased postoperative opioid utilization, development of persistent surgical pain, and extended hospital stays. 2 , 4 In the cross-sectional study by Schnabel et al, 3 the authors used the PAIN-OUT registry containing 50,005 patients to elucidate 8 significant risk factors for severe acute postoperative pain (the numeric rating scale for pain ≥7) on postoperative day 1. Using a split-sample study design, they found patients with ≥3 risk factors were more likely to have severe postoperative pain, to spend more time in severe pain (>20%), and wished to have received more pain interventions.…”

“…Including these risk factors (eg, number of spinal levels operated and fusion procedures in spine surgery) may improve a prediction rule's predictive performance. 4 In some cases, these risk factors are modifiable as surgeons have the ability to choose which surgical procedure to offer. A shared-decision approach may help educate patients about the pros and cons of various surgical options while taking into account their impact on postoperative pain.…”

Response to Yang and Riva-Cambrin

“…Most scores derived earlier are hampered by aspects such as the small number of patients assessed, 1 mix of preoperative and postoperative variables to calculate the risk 1 making it impossible to assess the risk already before surgery, limiting the risk assessment to one specific surgical procedure alone, 4 , 5 , 12 or developing the score in one country (or even one hospital) alone. 1 , 3 – 5 , 12 We tried to overcome all of these limitations with—of course—accepting some others. Thus, we do not believe that our risk score is the final answer in the development of a model for the prediction of patients with poor postoperative pain outcome, but it is an important step on that way.…”

“…This is a slightly different approach to that performed by Yang et al for one surgical procedure. 12 Yes, we appreciate that as a neurosurgeon, it is important to use such a surgical-specific score for a shared-decision approach related to the surgical treatment. By contrast (or maybe better complementary to this), we would like to use it for a shared-decision approach related to the perioperative pain management modifiable by anesthetists.…”