• Richard B North, David D Brigham, Alexander Khalessi, Sherri-Kae Calkins, Steven Piantadosi, David S Campbell, Michael John Daly, P Bobby Dey, Giancarlo Barolat, and Rod Taylor.
• Departments of Neurosurgery, Anesthesiology and Critical Care Medicine, Johns Hopkins University, Baltimore, Maryland; Stimsoft, Inc., Columbia, Maryland; The Center for Pain Management, LLC, Baltimore, Maryland; Department of Neurosurgery, Thomas Jefferson University, Philadelphia, Pennsylvania; Department of Biostatistics, Johns Hopkins University, Baltimore, Maryland; Department of Public Health & Epidemiology, University of Birmingham, United Kingdom.
• Neuromodulation. 2004 Jan 1;7(1):13-25.

AbstractInternally powered, implanted pulse generators (IPGs) have been an important advance in spinal cord stimulation for the management of pain, but they require surgical replacement, with attendant cost and risk, when the implanted battery is depleted. Battery life is determined by the programmed settings of the implant, but until now the technical means to optimize settings for maximal battery life, delaying surgical replacement as long as possible, Materials and Methods.  We have developed a patient-interactive, computerized programmer for use with IPGs. It has been designed for easy operation and comprehensive data management, which have not been features of the standard programmers available until now. It automatically and rapidly presents to the patient a sequence of settings (contact combinations and pulse parameters) specified by the practitioner. Test results are analyzed and sorted to determine the optimal settings by multiple criteria, including battery life. In the present study we used new, improved algorithms to estimate battery life.  We have compared the computerized, patient-interactive system with standard practitioner-operated, manual programming methods in a randomized, controlled trial in 44 patients at two study centers.  In 95% of patients (41/43), the computerized, patient-interactive system identified new settings with improved estimated battery life (and corresponding anticipated cost savings) which had not been recognized as such using manual methods. The estimated battery life for the setting chosen by each patient using manual methods averaged 25.4 ± 49.5 (mean ± standard deviation) months; the longest battery life identified by computerized methods averaged 55.0 ± 71.7, a 2.2-fold or 29.6 month improvement. Seventy-two percent of patients (31/43) achieved better battery life at settings with technical results (visual analog scale rating of overlap or coverage of pain by stimulation paresthesias) equal or superior to those achieved by manual methods. The overall improvement over the setting chosen by manual methods was 1.41-fold or 10.5 months; averaged by patient, the improvement was 1.63-fold. Estimated cost savings averaged just over one-third. As reported previously, the new system also yields significantly (p < 0.0001) better technical results than traditional, manual methods in achieving coverage of pain by stimulation paresthesias; the very best technical results were achieved at some expense in estimated battery life (assuming the same frequency of use). We conclude that significant potential savings in longevity of the implanted battery are possible in the majority of patients with implanted spinal cord stimulators, but have not been realized until now for lack of appropriate methods. Computerized, patient-interactive programming addresses this problem and allows optimization of estimated battery life along with other treatment goals. Long-term clinical followup will be required to establish the full magnitude of the resulting savings.

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