Pedunculopontine Nucleus Deep Brain Stimulation Improves Gait Disorder in Parkinson’s Disease: A Systematic Review and Meta-analysis
Deep brain stimulation (DBS) of the pedunculopontine nucleus (PPN) has been proposed as a treatment strategy for gait disorder in patients with Parkinson’s disease (PD). We thus performed a systematic review and meta-analysis of randomized and nonrandomized controlled trials to assess the effect of this treatment on gait disorder in patients with PD. We systematically searched PubMed, Cochrane, Web of Knowledge, Wan Fang and WIP for randomized and nonrandomized controlled trials (published before July 29, 2014; no language restrictions) comparing PPN–DBS with other treatments. We assessed pooled data using a random effects model and a fixed effects model. Of 130 identified studies, 14 were eligible and were included in our analysis (N = 82 participants). Compared to those presurgery, the Unified Parkinson Disease Rating Scale (UPDRS) 27–30 scores for patients were lowered by PPN–DBS [3.94 (95% confidence interval, CI = 1.23 to 6.65)]. The UPDRS 13 and 14 scores did not improve with levodopa treatment [0.43 (− 0.35 to 1.20); 0.35 (− 0.50 to 1.19)], whereas the UPDRS 27–30 scores could be improved by the therapy [1.42 (95% CI 0.34 to 2.51)]. The Gait and Falls Questionnaire and UPDRS 13 and 14 scores showed significant improvements after PPN–DBS under the medication-off (MED-OFF) status [15.44 (95% CI = 8.44 to 22.45); 1.57 (95% CI = 0.84 to 2.30); 1.34 (95% CI = 0.84 to 1.84)]. PPN–DBS is a potential therapeutic target that could improve gait and fall disorders in patients with PD. Our findings will help improve the clinical application of DBS in PD patients with gait disorder.
KeywordsPedunculopontine nucleus Deep brain stimulation Parkinson’s disease Systematic review Meta-analysis
We thank all the researchers who participated in this study.
LF, WD and LC searched the scientific literature, collect the data and drafted the manuscript. CH, CL, YQ, CG3 and CG1 helped to collect the data and performed statistical analyses. CG1 contributed to conception, design, data interpretation, manuscript revision. All authors read and approved the manuscript.
This work is supported by grants from the Fujian Provincial Science and Technology Guiding Project (Nos. 2017Y0041, 2018Y0033), Joint Funds for the Innovation of Science and Technology, Fujian Province (No. 2017Y9010) and the National Key Research and Development Program of China (No. 2017YFC1310200).
Compliance with Ethical Standards
Conflicts of interest
The authors declare no conflicts of interests regarding the publication of this paper.
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