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Multivariate resting-state functional connectivity predicts responses to real and sham acupuncture treatment in chronic low back pain.

Published on Jan 1, 2019in NeuroImage: Clinical3.943
· DOI :10.1016/j.nicl.2019.101885
Yiheng Tu7
Estimated H-index: 7
(Harvard University),
Ana Ortiz3
Estimated H-index: 3
(Harvard University)
+ 13 AuthorsJian Kong45
Estimated H-index: 45
(Harvard University)
Abstract
Abstract Despite the high prevalence and socioeconomic impact of chronic low back pain (cLBP), treatments for cLBP are often unsatisfactory, and effectiveness varies widely across patients. Recent neuroimaging studies have demonstrated abnormal resting-state functional connectivity (rsFC) of the default mode, salience, central executive, and sensorimotor networks in chronic pain patients, but their role as predictors of treatment responsiveness has not yet been explored. In this study, we used machine learning approaches to test if pre-treatment rsFC can predict responses to both real and sham acupuncture treatments in cLBP patients. Fifty cLBP patients participated in 4 weeks of either real (N = 24, age = 39.0 ± 12.6, 16 females) or sham acupuncture (N = 26, age = 40.0 ± 13.7, 15 females) treatment in a single-blinded trial, and a resting-state fMRI scan prior to treatment was used in data analysis. Both real and sham acupuncture can produce significant pain reduction, with those receiving real treatment experiencing greater pain relief than those receiving sham treatment. We found that pre-treatment rsFC could predict symptom changes with up to 34% and 29% variances for real and sham treatment, respectively, and the rsFC characteristics that were significantly predictive for real and sham treatment differed. These results suggest a potential way to predict treatment responses and may facilitate the development of treatment plans that optimize time, cost, and available resources.
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#1Binlong Zhang (Harvard University)H-Index: 2
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#1Jin Cao (Beijing University of Chinese Medicine)H-Index: 2
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#1Yiheng Tu (Harvard University)H-Index: 7
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Abstract In recent years, the brain mechanism research speeds up for the effect of acupuncture intervention on chronic pain. Currently, in the relevant articles, the brain mechanism research in chronic pain focuses on muscular and skeletal system diseases, in which, the rigorous controlled designs has been adopted in the most of researches and the effect verification has been predominated as the research objective. The corresponding results indicate that the brain mechanism of acupuncture effect...
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#1Yiheng TuH-Index: 7
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Objective To identify and validate an fMRI-based neural marker for migraine without aura (MwoA) and to examine its association with treatment response. Methods We conducted cross-sectional studies with resting-state fMRI data from 230 participants and machine learning analyses. In studies 1 through 3, we identified, cross-validated, independently validated, and cross-sectionally validated an fMRI-based neural marker for MwoA. In study 4, we assessed the relationship between the neural marker and...
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Chronic back pain (CBP) is a leading cause of disability and results in considerable socio-economic burdens worldwide. Although CBP patients are commonly diagnosed and treated with a focus on the ‘end organ dysfunction’ (i.e., peripheral nerve injuries or diseases), the evaluation of CBP remains flawed and problematic with great challenges. Given that the peripheral nerve injuries or diseases are insufficient to define the etiology of CBP in some cases, the evaluation of alterations in the centr...
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