Predictive value of self-reported patient information for the identification of lumbar spinal stenosis

Abstract

Background. To our knowledge, no objective criterion has been identified for the diagnosis of lumbar spinal stenosis (LSS) and no study has evaluated the predictive value of self-reported patient information for the identification of LSS. Objective. To develop and validate a prediction rule for the identification of LSS based on self-reported patient information alone. Methods. Prospective derivation study using a coefficient-based multivariable logistic regression scoring method with internal validation with primary care clinics and orthopaedic departments of medical centres, as well as university and other hospitals. Participants were consecutive patients with primary symptoms of pain or numbness in the lower extremities. Physician-diagnosed LSS was the main outcome measure. Results. Of 468 patients included in the analysis, 47.3% were diagnosed with LSS and divided into derivation and validation sets. The following items were retained at the conclusion of the derivation process: age (<60, 60-70 and >70), duration of symptoms over 6 months, symptom improvement when bending forward, symptom improvement when bending backward, symptom exacerbation while standing up, intermittent claudication and urinary incontinence. To derive a risk score for each patient, integer-based scores were assigned and summed. In the validation data sets, prevalence of LSS in patients from the first to fourth risk score quartile were 13.3%, 47.6%, 55.2% and 65.5%, respectively. Further, the likelihood ratio in the low-risk category was 0.154. Conclusions. We developed a prediction rule for the identification of LSS based on self-reported patient information alone. Further, the likelihood ratio in the low-risk category was sufficiently low. This rule may be used for screening of LSS. © The Author 2008. Published by Oxford University Press. All rights reserved.