Dorsal Root Ganglion (DRG) Stimulation in the Treatment of Phantom Limb Pain (PLP).

OBJECTIVES: Phantom limb pain (PLP) is a neuropathic condition in which pain is perceived as arising from an amputated limb. PLP is distinct from, although associated with, pain in the residual limb and nonpainful phantom sensations of the missing limb. Its treatment is extremely challenging; pharmaceutical options, while commonly employed, may be insufficient or intolerable. Neuromodulatory interventions such as spinal cord stimulation have generated mixed results and may be limited by poor somatotopic specificity. It was theorized that dorsal root ganglion (DRG) neuromodulation may be more effective. MATERIALS AND METHODS: Patients trialed a DRG neurostimulation system for their PLP and were subsequently implanted if results were positive. Retrospective chart review was completed, including pain ratings on a 100-mm visual analogue scale (VAS) and patient-reported outcomes. RESULTS: Across eight patients, the average baseline pain rating was 85.5 mm. At follow-up (mean of 14.4 months), pain was rated at 43.5 mm. Subjective ratings of quality of life and functional capacity improved. Some patients reduced or eliminated pain medications. Patients reported precise concordance of the paresthesia with painful regions, including in their phantom limbs; in one case, stimulation eliminated PLP as well as nonpainful phantom sensations. Three patients experienced a diminution of pain relief, despite good initial outcomes. CONCLUSIONS: DRG neuromodulation may be an effective tool in treating this pain etiology. Clinical outcomes in this report support recent converging evidence suggesting that the DRG may be the site of PLP generation and/or maintenance. Further research is warranted to elucidate mechanisms and optimal treatment pathways.

Reconciling fault-tolerant distributed algorithms and real-time computing.

We present generic transformations, which allow to translate classic fault-tolerant distributed algorithms and their correctness proofs into a real-time distributed computing model (and vice versa). Owing to the non-zero-time, non-preemptible state transitions employed in our real-time model, scheduling and queuing effects (which are inherently abstracted away in classic zero step-time models, sometimes leading to overly optimistic time complexity results) can be accurately modeled. Our results thus make fault-tolerant distributed algorithms amenable to a sound real-time analysis, without sacrificing the wealth of algorithms and correctness proofs established in classic distributed computing research. By means of an example, we demonstrate that real-time algorithms generated by transforming classic algorithms can be competitive even w.r.t. optimal real-time algorithms, despite their comparatively simple real-time analysis.