• Nagy Mekhail, Diana S Mehanny, Sherif Armanyous, Shrif Costandi, Youssef Saweris, Gerges Azer, and Robert Bolash.
• Evidence-Based Pain Management Research, Cleveland Clinic Foundation, Cleveland, Ohio, USA mekhain@ccf.org.
• Reg Anesth Pain Med. 2020 Jan 12.

AbstractContemporary nonmalignant pain treatment algorithms commence with conservative non-invasive strategies, later progressing from minimally invasive interventions to invasive techniques or implantable devices. The most commonly used implantable devices are spinal cord stimulation (SCS) systems or targeted drug delivery (TDD) devices. Historically, SCS had been considered in advance of TDD, positioning TDD behind SCS failures. Following Institutional Review Board approval, data were extracted from electronic medical records of patients who underwent SCS trial in the Department of Pain Management at Cleveland Clinic from 1994 to 2013. The sample size was analyzed in two cohorts: those who succeeded with SCS and those who failed SCS and consequently proceeded to TDD. Univariate and multivariate analyses were performed and a predictive formula for successful outcomes was created. 945 patients were included in the cohort of which 119 (12.6%) subjects achieved adequate pain relief with TDD after failure of SCS. Gender, age, depression and primary pain diagnosis were significantly different in this subgroup. Males were 52% less likely to experience pain relief with SCS. The odds of SCS success decreased as age increased by 6% per year. Patients with comorbid depression, interestingly, were 63% more likely to succeed with SCS. A logistic model was created to predict SCS success which was used to create a predictive formula. Older male patients diagnosed with spine-related pain were more likely to benefit from TDD than SCS. This observation potentially identifies a subgroup in whom consideration for TDD in advance of SCS failure could prove more efficient and cost effective. These retrospective findings warrant prospective comparative studies to validate this derived predictive formula.© American Society of Regional Anesthesia & Pain Medicine 2020. No commercial re-use. See rights and permissions. Published by BMJ.

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