NeuralCipher Research overview
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Parkinson's disease (PD), the second most common progressive neurodegenerative disease, is characterized by various clinical symptoms and reduced quality of life. The standard dopaminergic therapy for PD has limitations such as drug wear-off, drug-related side effects, and drug-resistant PD symptoms. Traditional oriental medicine, which is a personalized approach based on pattern identification (PI), has been reported to relieve symptoms, halt disease progression, and improve the quality of life in patients with PD. This comprehensive systematic review will be conducted to gather clinical studies related to complementary traditional herbal therapies based on PI for idiopathic PD and assess its effectiveness. Clinical studies, including randomized controlled trials in English, Korean, and Chinese databases related to the efficacy of herbal medicine based on PI for PD will be searched in computer retrieval. In addition, the subdivided PI for each clinical manifestation of PD will be investigated. Two researchers will independently screen and select studies, extract data, and assess bias risk. The risk of bias will be evaluated using the Cochrane risk-of-bias assessment tool. After screening the studies, a meta-analysis will be performed. The primary outcome will be the unified Parkinson's disease rating scale to measure clinical symptom reduction. Secondary outcomes will consist of other validated scales to evaluate the improvement of PD, including improvement of clinical symptoms and quality of life. The quality of evidence will be evaluated through the Grading of Recommendations, Assessment, Development, and Evaluation pro. Complementary traditional medicine is a personalized medicine that classifies individual states based on PI. We expect that the results of this review will provide evidence for the efficacy of traditional herbal medicine based on PI for the treatment of PD. This protocol has been registered in the International Platform of Registered Systematic Review and Meta-Analysis Protocols (INPLASY) 2021 (registration number INPLASY2021100020).
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