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A systematic review of intervention studies examining nutritional and herbal therapies for mild cognitive impairment and dementia using neuroimaging methods: Study characteristics and intervention efficacy

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posted on 2024-07-10, 01:14 authored by Genevieve Z. Steiner, Danielle C. Mathersul, Freya MacMillan, David Camfield, Nerida L. Klupp, Sai W. Seto, Yong Huang, Mark I. Hohenberg, Dennis H. Chang
Neuroimaging facilitates the assessment of complementary medicines (CMs) by providing a noninvasive insight into their mechanisms of action in the human brain. This is important for identifying the potential treatment options for target disease cohorts with complex pathophysiologies. The aim of this systematic review was to evaluate study characteristics, intervention efficacy, and the structural and functional neuroimaging methods used in research assessing nutritional and herbal medicines for mild cognitive impairment (MCI) and dementia. Six databases were searched for articles reporting on CMs, dementia, and neuroimaging methods. Data were extracted from 21/2,742 eligible full text articles and risk of bias was assessed. Nine studies examined people with Alzheimer's disease, 7 MCI, 4 vascular dementia, and 1 all-cause dementia. Ten studies tested herbal medicines, 8 vitamins and supplements, and 3 nootropics. Ten studies used electroencephalography (EEG), 5 structural magnetic resonance imaging (MRI), 2 functional MRI (fMRI), 3 cerebral blood flow (CBF), 1 single photon emission tomography (SPECT), and 1 positron emission tomography (PET). Four studies had a low risk of bias, with the majority consistently demonstrating inadequate reporting on randomisation, allocation concealment, blinding, and power calculations. A narrative synthesis approach was assumed due to heterogeneity in study methods, interventions, target cohorts, and quality. Eleven key recommendations are suggested to advance future work in this area.

Funding

VEGETATION BIOPHYSICAL PARAMETER SUITE FROM MISR FOR ECOLOGICAL APPLICATIONS THE MISR LAI/FPAR ALGORITHM PERFORMS AN ACCURATE SEPARATION OF THE BACKGROUND REFLECTANCE FROM CANOPY-SURFACE SYSTEM AND ESTIMATES A SET OF SOME BASIC CANOPY PARAMETERS THAT HAVE

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ISSN

1741-4288

Journal title

Evidence-based Complementary and Alternative Medicine

Volume

2017

Article number

article no. 6083629

Publisher

Hindawi Publishing Corporation

Copyright statement

Copyright © 2017 Genevieve Z. Steiner et al. This is an open access article distributed under the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/).

Language

eng

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