Phantom motor execution facilitated by machine learning and augmented reality as treatment for phantom limb pain: a single group, clinical trial in patients with chronic intractable phantom limb pain. Issue 10062 (10th December 2016)

• Record Type: Journal Article
• Authors: Ortiz-Catalan, Max; Guðmundsdóttir, Rannveig A; Kristoffersen, Morten B; Zepeda-Echavarria, Alejandra; Caine-Winterberger, Kerstin; Kulbacka-Ortiz, Katarzyna; Widehammar, Cathrine; Eriksson, Karin; Stockselius, Anita; Ragnö, Christina; Pihlar, Zdenka; Burger, Helena; Hermansson, Liselotte
• Is Part Of: Lancet. Volume 388:Issue 10062(2016)
• Page Start: 2885
• Page End: 2894
• Publication Date: 2016-12-10
• Subjects: Medicine -- Periodicals; Medicine -- Periodicals; Medicine; Medicine; Electronic journals; Periodicals; 610.5
• DOI: 10.1016/S0140-6736(16)31598-7
• Languages: English
• ISSNs: 0140-6736

Abstract

Summary: Background: Phantom limb pain is a debilitating condition for which no effective treatment has been found. We hypothesised that re-engagement of central and peripheral circuitry involved in motor execution could reduce phantom limb pain via competitive plasticity and reversal of cortical reorganisation. Methods: Patients with upper limb amputation and known chronic intractable phantom limb pain were recruited at three clinics in Sweden and one in Slovenia. Patients received 12 sessions of phantom motor execution using machine learning, augmented and virtual reality, and serious gaming. Changes in intensity, frequency, duration, quality, and intrusion of phantom limb pain were assessed by the use of the numeric rating scale, the pain rating index, the weighted pain distribution scale, and a study-specific frequency scale before each session and at follow-up interviews 1, 3, and 6 months after the last session. Changes in medication and prostheses were also monitored. Results are reported using descriptive statistics and analysed by non-parametric tests. The trial is registered atClinicalTrials.gov, numberNCT02281539 . Findings: Between Sept 15, 2014, and April 10, 2015, 14 patients with intractable chronic phantom limb pain, for whom conventional treatments failed, were enrolled. After 12 sessions, patients showed statistically and clinically significant improvements in all metrics of phantom limb pain. Phantom limb pain decreased from pre-treatment to the last treatment session by 47% (SD 39; absolute mean change 1·0 [0·8]; p=0·001) for weighted pain distribution, 32% (38; absolute mean change 1·6 [1·8]; p=0·007) for the numeric rating scale, and 51% (33; absolute mean change 9·6 [8·1]; p=0·0001) for the pain rating index. The numeric rating scale score for intrusion of phantom limb pain in activities of daily living and sleep was reduced by 43% (SD 37; absolute mean change 2·4 [2·3]; p=0·004) and 61% (39; absolute mean change 2·3 [1·8]; p=0·001), respectively. Two of four patients who were on medication reduced their intake by 81% (absolute reduction 1300 mg, gabapentin) and 33% (absolute reduction 75 mg, pregabalin). Improvements remained 6 months after the last treatment. Interpretation: Our findings suggest potential value in motor execution of the phantom limb as a treatment for phantom limb pain. Promotion of phantom motor execution aided by machine learning, augmented and virtual reality, and gaming is a non-invasive, non-pharmacological, and engaging treatment with no identified side-effects at present. Funding: Promobilia Foundation, VINNOVA, Jimmy Dahlstens Fond, PicoSolve, and Innovationskontor Väst.