PREOPERATIVE PAIN DRAWINGS AS PREDICTORS OF SUCCESS OF INTRADISCAL ELECTROTHERMAL THERAPY IN THE TREATMENT OF CHRONIC DISCOGENIC LOW BACK PAIN

Abstract

Introduction: Abnormal pain drawings have been shown in some studies to correlate well with psychological characteristics predicting poor outcome in spinal procedures. Our study evaluated whether pain drawings are a useful predictive tool for outcome following Intradiscal Electrothermal Therapy (IDET).

Method: 56 Patients underwent IDET for chronic discogenic lumbar pain as demonstrated by MRI and provocative discography. They were assessed pre and post operatively. Preoperatively patients were assessed by means of a questionnaire. Pain was measured using a visual analogue scale (VAS), a pain drawing was completed and demographic details and employment status were recorded. Post IDET patients were followed up by means of a postal questionnaire. The same details were recorded, in addition to which patients completed a Short Form 36 UK Version 1 and a subjective outcome assessment.

Pain drawings were classified as organic or non-organic according to the principle described by Mann et al.

Results: 46 (80.7%) patients were successfully followed up. Mean age was 41.2 years (Range 16–76), 27 were female and 19 male. 73.9% of pain drawings were classified as organic and 26.1% as non-organic. The pain diagram was a good predictive tool for outcome following IDET. Patients with “organic” pain drawings showed an improvement in mean pain VAS (Pre-6.7, Post 5.9), high patient satisfaction (Better 67.6%, Same 11.8%, Worse 20.6%), and higher physical component scores of the SF36 (Physical 64.1, Physical Role 45.6, Pain 54.0) compared to the “non-organic” group who demonstrated a deterioration in mean pain VAS (Pre-6.5, Post 8.2), low patient satisfaction (Better 8.3%, Same 58.3%, Worse 33.3%), and lower physical component scores of the SF36 (Physical 38.3, Physical Role 20.8, Pain 26.5).

Conclusion: We believe that our study demonstrates that a pre procedure pain diagram can be reliably used as a tool to predict outcome following IDET.