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

Presented at the 2020 AANS/CNS Joint Section on Disorders of the Spine and Peripheral Nerves

Michael M. H. Yang, Jay Riva-Cambrin, Jonathan Cunningham, Nathalie Jetté, Tolulope T. Sajobi, Alex Soroceanu, Peter Lewkonia, W. Bradley Jacobs, and Steven Casha


Thirty 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.


A 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.


Overall, 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.


Inadequate 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.

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Daniel Yavin, Judy Luu, Matthew T. James, Derek J. Roberts, Garnette R. Sutherland, Nathalie Jette, and Samuel Wiebe


Because clinical examination and imaging may be unreliable indicators of intracranial hypertension, intraocular pressure (IOP) measurement has been proposed as a noninvasive method of diagnosis. The authors conducted a systematic review and meta-analysis to determine the correlation between IOP and intracranial pressure (ICP) and the diagnostic accuracy of IOP measurement for detection of intracranial hypertension.


The authors searched bibliographic databases (Ovid MEDLINE, Ovid EMBASE, and the Cochrane Central Register of Controlled Trials) from 1950 to March 2013, references of included studies, and conference abstracts for studies comparing IOP and invasive ICP measurement. Two independent reviewers screened abstracts, reviewed full-text articles, and extracted data. Correlation coefficients, sensitivity, specificity, and positive and negative likelihood ratios were calculated using DerSimonian and Laird methods and bivariate random effects models. The I2 statistic was used as a measure of heterogeneity.


Among 355 identified citations, 12 studies that enrolled 546 patients were included in the meta-analysis. The pooled correlation coefficient between IOP and ICP was 0.44 (95% CI 0.26–0.63, I2 = 97.7%, p < 0.001). The summary sensitivity and specificity for IOP for diagnosing intracranial hypertension were 81% (95% CI 26%–98%, I2 = 95.2%, p < 0.01) and 95% (95% CI 43%–100%, I2 = 97.7%, p < 0.01), respectively. The summary positive and negative likelihood ratios were 14.8 (95% CI 0.5–417.7) and 0.2 (95% CI 0.02–1.7), respectively. When ICP and IOP measurements were taken within 1 hour of another, correlation between the measures improved.


Although a modest aggregate correlation was found between IOP and ICP, the pooled diagnostic accuracy suggests that IOP measurement may be of clinical utility in the detection of intracranial hypertension. Given the significant heterogeneity between included studies, further investigation is required prior to the adoption of IOP in the evaluation of intracranial hypertension into routine practice.