Efficacy and neural mechanism of acupuncture treatment in older adults with subjective cognitive decline: study protocol for a randomised controlled clinical trial

Chao-Qun Yan, Ping Zhou, Xu Wang, Jian Feng Tu, Shang-Qing Hu, Jian-Wei Huo, Zhong-Yan Wang, Guang-Xia Shi, Ya-Nan Zhang, Jun-Qiu Li, Jun Wang, Cun-Zhi Liu, Chao-Qun Yan, Ping Zhou, Xu Wang, Jian Feng Tu, Shang-Qing Hu, Jian-Wei Huo, Zhong-Yan Wang, Guang-Xia Shi, Ya-Nan Zhang, Jun-Qiu Li, Jun Wang, Cun-Zhi Liu

Abstract

Introduction: Subjective cognitive decline (SCD) refers to individuals' perceived decline in memory and/or other cognitive abilities relative to their previous level of performance, while objective neuropsychological deficits are not observed. SCD may represent a preclinical phase of Alzheimer's disease. At this very early stage of decline, intervention could slow the rate of incipient decline to prolong and preserve cognitive and functional abilities. However, there is no effective treatment recommended for individuals with SCD. Acupuncture, as a non-pharmacological intervention, has been widely employed for patients with cognitive disorders.

Methods and analysis: The proposed study is a randomised, assessor-blinded and placebo-controlled study that investigates the efficacy and mechanism of acupuncture in SCD. Sixty patients with SCD will be randomly allocated either into an acupuncture group or a sham acupuncture group. They will receive 24 sessions of real acupuncture treatment or identical treatment sessions using a placebo needle. Global cognitive changes based on a multidomain neuropsychological test battery will be evaluated to detect the clinical efficacy of acupuncture treatment at baseline and end of treatment. MRI scans will be used to explore acupuncture-related neuroplasticity changes. Correlation analyses will be performed to investigate the relationships between the changes in brain function and symptom improvement.

Ethics and dissemination: The trial was approved by the research ethics committee. The results of the study will be published in a peer-reviewed academic journal and will also be disseminated electronically through conference presentations.

Trial registration number: NCT03444896.

Keywords: Acupuncture; Clinical trial; Dementia; Magnetic Resonance Imaging; Sham acupuncture; Subjective cognitive decline.

Conflict of interest statement

Competing interests: None declared.

© Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

Figures

Figure 1
Figure 1
Flow chart.
Figure 2
Figure 2
Location of acupoints or sham acupoints in the trial. BL15, Xinshu; BL45, Yixi; DU16, Fengfu; DU20, Baihui; DU24, Shengting; GB20, Fengchi; HT5, Tongli; KI6, Zhaohai; PC6, Neiguan; RN6, Qihai; RN12, Zhongwan; RN17, Danzhong; SA, sham acupoint; SP10, Xuehai; ST36, Zusanli.
Figure 3
Figure 3
MRI experimental paradigm and an illustrative diagram of the memory task. ASL, arterial spin labelling; DTI, diffusion tensor imaging.
Figure 4
Figure 4
Standard Protocol Items: Recommendations for Interventional Trials (SPIRIT) and the schedule of the trial. AFT, Animal Fluency Test; AVLT, Auditory Verbal Learning Test; DSST, Digit Symbol Substitution Test; SBSDS,Santa Barbara Sense of Direction Scale; HAMD, Hamilton Rating Scale forDepression; HAMA, Hamilton Rating Scale for Anxiety; PSQI, Pittsburgh Sleep Quality Index; SCDQ, Subjective Cognitive Decline Questionnaire; SCWT, Stroop Color and Word Test; TMT, Trail Making Test.

References

    1. Livingston G, Sommerlad A, Orgeta V, et al. . Dementia prevention, intervention, and care. The Lancet 2017;390:2673–734. 10.1016/S0140-6736(17)31363-6
    1. Delbeuck X, Van der Linden M, Collette F. Alzheimer's disease as a disconnection syndrome? Neuropsychol Rev 2003;13:79–92. 10.1023/A:1023832305702
    1. Ong SS, Doraiswamy PM, Lad EM. Controversies and future directions of ocular biomarkers in Alzheimer disease. JAMA Neurol 2018;75:650 10.1001/jamaneurol.2018.0602
    1. WHO Dementia: a public health priority. Geneva: World Health Organization—Alzheimer’s Disease International hwwimhpdrea.
    1. G8 dementia Summit Declaration. Available:
    1. Sperling RA, Aisen PS, Beckett LA, et al. . Toward defining the preclinical stages of Alzheimer’s disease: Recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease. Alzheimer's & Dementia 2011;7:280–92. 10.1016/j.jalz.2011.03.003
    1. Jack CR, Knopman DS, Jagust WJ, et al. . Tracking pathophysiological processes in Alzheimer's disease: an updated hypothetical model of dynamic biomarkers. The Lancet Neurology 2013;12:207–16. 10.1016/S1474-4422(12)70291-0
    1. Villemagne VL, Burnham S, Bourgeat P, et al. . Amyloid β deposition, neurodegeneration, and cognitive decline in sporadic Alzheimer's disease: a prospective cohort study. The Lancet Neurology 2013;12:357–67. 10.1016/S1474-4422(13)70044-9
    1. Jessen F, Amariglio RE, van Boxtel M, et al. . A conceptual framework for research on subjective cognitive decline in preclinical Alzheimer's disease. Alzheimer's & Dementia 2014;10:844–52. 10.1016/j.jalz.2014.01.001
    1. Jonker C, Geerlings MI, Schmand B. Are memory complaints predictive for dementia? A review of clinical and population-based studies. Int J Geriatr Psychiatry 2000;15:983–91. 10.1002/1099-1166(200011)15:11<983::AID-GPS238>;2-5
    1. Reisberg B, Gauthier S. Current evidence for subjective cognitive impairment (SCI) as the pre-mild cognitive impairment (MCI) stage of subsequently manifest Alzheimer's disease. Int. Psychogeriatr. 2008;20:1–16. 10.1017/S1041610207006412
    1. Stewart R. Subjective cognitive impairment. Curr Opin Psychiatry 2012;25:445–50. 10.1097/YCO.0b013e3283586fd8
    1. Scheef L, Spottke A, Daerr M, et al. . Glucose metabolism, gray matter structure, and memory decline in subjective memory impairment. Neurology 2012;79:1332–9. 10.1212/WNL.0b013e31826c1a8d
    1. van Harten AC, Visser PJ, Pijnenburg YAL, et al. . Cerebrospinal fluid Aβ42 is the best predictor of clinical progression in patients with subjective complaints. Alzheimer's & Dementia 2013;9:481–7. 10.1016/j.jalz.2012.08.004
    1. Molinuevo JL, Rabin LA, Amariglio R, et al. . Implementation of subjective cognitive decline criteria in research studies. Alzheimers Dement 2017;13:296–311. 10.1016/j.jalz.2016.09.012
    1. Rabin LA, Smart CM, Amariglio RE. Subjective cognitive decline in preclinical Alzheimer's disease. Annu Rev Clin Psychol 2017;13:369–96. 10.1146/annurev-clinpsy-032816-045136
    1. Smart CM, Karr JE, Areshenkoff CN, et al. . Non-Pharmacologic interventions for older adults with subjective cognitive decline: systematic review, meta-analysis, and preliminary recommendations. Neuropsychol Rev 2017;27:245–57. 10.1007/s11065-017-9342-8
    1. Wang S, Yang H, Zhang J, et al. . Efficacy and safety assessment of acupuncture and nimodipine to treat mild cognitive impairment after cerebral infarction: a randomized controlled trial. BMC Complement Altern Med 2016;16:361 10.1186/s12906-016-1337-0
    1. Deng M, Wang X-F. Acupuncture for amnestic mild cognitive impairment: a meta-analysis of randomised controlled trials. Acupuncture in Medicine 2016;34:342–8. 10.1136/acupmed-2015-010989
    1. Jiang DY, HW L. Effect of electroacupuncture on the cognitive function and plasma antibodies against beta-amyloid protein in aged rats with ketamine anesthesia]. Zhongguo Zhong Xi Yi Jie He Za Zhi 2011;31:1502–5.
    1. Campanella S. Why it is time to develop the use of cognitive event-related potentials in the treatment of psychiatric diseases. Neuropsychiatr Dis Treat 2013;9:1835–45. 10.2147/NDT.S53687
    1. de Waal H, Stam CJ, Lansbergen MM, et al. . The Effect of Souvenaid on Functional Brain Network Organisation in Patients with Mild Alzheimer’s Disease: A Randomised Controlled Study. PLoS One 2014;9:e86558 10.1371/journal.pone.0086558
    1. Smart CM, Segalowitz SJ, Mulligan BP, et al. . Mindfulness training for older adults with subjective cognitive decline: results from a pilot randomized controlled trial. JAD 2016;52:757–74. 10.3233/JAD-150992
    1. Mathotaarachchi S, Pascoal TA, Shin M, et al. . Identifying incipient dementia individuals using machine learning and amyloid imaging. Neurobiol Aging 2017;59:80–90. 10.1016/j.neurobiolaging.2017.06.027
    1. Boutron I, Moher D, Altman DG, et al. . Extending the CONSORT statement to randomized trials of nonpharmacologic treatment: explanation and elaboration. Ann Intern Med 2008;148:295–309. 10.7326/0003-4819-148-4-200802190-00008
    1. Schulz KF, Altman DG, Moher D, et al. . Consort 2010 statement: updated guidelines for reporting parallel group randomised trials. International Journal of Surgery 2011;9:672–7. 10.1016/j.ijsu.2011.09.004
    1. Jia JN ZJ, Xu J, Wei W, et al. . The recommendation of diagnosis and treatment of cognitive impairment in Chinese elderly. Chin J Geriatr 2014;33:817–25.
    1. Zhao Q, Lv Y, Zhou Y, et al. . Short-Term delayed recall of auditory verbal learning test is equivalent to long-term delayed recall for identifying amnestic mild cognitive impairment. PLoS One 2012;7:e51157 10.1371/journal.pone.0051157
    1. Zhao Q, Guo Q, Li F, et al. . The shape TRAIL test: application of a new variant of the TRAIL making test. PLoS One 2013;8:e57333 10.1371/journal.pone.0057333
    1. Yang L, Koyanagi A, Smith L, et al. . Hand grip strength and cognitive function among elderly cancer survivors. PLoS One 2018;13:e0197909 10.1371/journal.pone.0197909
    1. Cui Z, Zhong S, Xu P, et al. . Panda: a pipeline toolbox for analyzing brain diffusion images. Front Hum Neurosci 2013;7:42 10.3389/fnhum.2013.00042
    1. Bowie CR, Harvey PD. Administration and interpretation of the TRAIL making test. Nat Protoc 2006;1:2277–81. 10.1038/nprot.2006.390
    1. Chen SP, Bhattacharya J, Pershing S. Association of vision loss with cognition in older adults. JAMA Ophthalmol 2017;135:963–70. 10.1001/jamaophthalmol.2017.2838
    1. Terwindt PW, Hubers AAM, Giltay EJ, et al. . Screening for cognitive dysfunction in Huntington's disease with the clock drawing test. Int J Geriatr Psychiatry 2016;31:1013–20. 10.1002/gps.4412
    1. Rivera D, Perrin PB, Stevens LF, et al. . Stroop Color-Word interference test: normative data for the Latin American Spanish speaking adult population. NeuroRehabilitation 2015;37:591–624. 10.3233/NRE-151281
    1. Moradi E, Hallikainen I, Hänninen T, et al. . Rey's auditory verbal learning test scores can be predicted from whole brain MRI in Alzheimer's disease. Neuroimage 2017;13:415–27. 10.1016/j.nicl.2016.12.011
    1. Thomas ML, Green MF, Hellemann G, et al. . Modeling deficits from early auditory information processing to psychosocial functioning in schizophrenia. JAMA Psychiatry 2017;74:37–46. 10.1001/jamapsychiatry.2016.2980
    1. Rami L, Mollica MA, García-Sanchez C, et al. . The subjective cognitive decline questionnaire (SCD-Q): a validation study. JAD 2014;41:453–66. 10.3233/JAD-132027
    1. Boccia M, Vecchione F, Piccardi L, et al. . Effect of cognitive style on learning and retrieval of navigational environments. Front Pharmacol 2017;8:496 10.3389/fphar.2017.00496
    1. Buysse DJ, Germain A, Moul DE, et al. . Efficacy of brief behavioral treatment for chronic insomnia in older adults. Arch Intern Med 2011;171:887–95. 10.1001/archinternmed.2010.535
    1. Lombardo MV, Auyeung B, Holt RJ, et al. . Improving effect size estimation and statistical power with multi-echo fMRI and its impact on understanding the neural systems supporting mentalizing. Neuroimage 2016;142:55–66. 10.1016/j.neuroimage.2016.07.022
    1. Button KS, Ioannidis JPA, Mokrysz C, et al. . Power failure: why small sample size undermines the reliability of neuroscience. Nat Rev Neurosci 2013;14:365–76. 10.1038/nrn3475
    1. Guo Q, Thabane L, Hall G, et al. . A systematic review of the reporting of sample size calculations and corresponding data components in observational functional magnetic resonance imaging studies. Neuroimage 2014;86:172–81. 10.1016/j.neuroimage.2013.08.012
    1. Hayasaka S, Peiffer AM, Hugenschmidt CE, et al. . Power and sample size calculation for neuroimaging studies by non-central random field theory. Neuroimage 2007;37:721–30. 10.1016/j.neuroimage.2007.06.009
    1. Desmond JE, Glover GH. Estimating sample size in functional MRI (fMRI) neuroimaging studies: statistical power analyses. J Neurosci Methods 2002;118:115–28. 10.1016/S0165-0270(02)00121-8
    1. Mumford JA, Nichols TE. Power calculation for group fMRI studies accounting for arbitrary design and temporal autocorrelation. Neuroimage 2008;39:261–8. 10.1016/j.neuroimage.2007.07.061
    1. Barnes DE, Santos-Modesitt W, Poelke G, et al. . The mental activity and eXercise (max) trial: a randomized controlled trial to enhance cognitive function in older adults. JAMA Intern Med 2013;173:797–804. 10.1001/jamainternmed.2013.189
    1. Mormino EC, Betensky RA, Hedden T, et al. . Amyloid and APOE ε4 interact to influence short-term decline in preclinical Alzheimer disease. Neurology 2014;82:1760–7. 10.1212/WNL.0000000000000431
    1. Doraiswamy PM, Sperling RA, Johnson K, et al. . Florbetapir F 18 amyloid PET and 36-month cognitive decline:a prospective multicenter study. Mol Psychiatry 2014;19:1044–51. 10.1038/mp.2014.9
    1. Rabin LA, Smart CM, Crane PK, et al. . Subjective cognitive decline in older adults: an overview of self-report measures used across 19 international research studies. JAD 2015;48:S63–S86. 10.3233/JAD-150154
    1. Scheltens NME, Galindo-Garre F, Pijnenburg YAL, et al. . The identification of cognitive subtypes in Alzheimer's disease dementia using latent class analysis. J Neurol Neurosurg Psychiatry 2016;87:235–43. 10.1136/jnnp-2014-309582
    1. Simon SS, Yokomizo JE, Bottino CMC. Cognitive intervention in amnestic mild cognitive impairment: a systematic review. Neuroscience & Biobehavioral Reviews 2012;36:1163–78. 10.1016/j.neubiorev.2012.01.007
    1. Tang Y, Zhu Z, Liu Q, et al. . The efficacy of cognitive training in patients with vascular cognitive impairment, no dEmentia (the Cog-VACCINE study): study protocol for a randomized controlled trial. Trials 2016;17:392 10.1186/s13063-016-1523-x
    1. Reisberg B, Prichep L, Mosconi L, et al. . The pre–mild cognitive impairment, subjective cognitive impairment stage of Alzheimer’s disease. Alzheimer's & Dementia 2008;4:S98–S108. 10.1016/j.jalz.2007.11.017

Source: PubMed

3
Suscribir