This article combines researches and experiments of mild cognitive impairment (MCI) from 2005 to 2018. It makes a conclusion among psychological evaluation, imaging studies, nerve electrophysiology, neural circuit and mental models, and concludes the changes of patients with MCI, which helps to make a definite diagnosis of MCI in clinical practice. Due to the research above we can find the suitable way to improve the sensitivity and specificity of discovery of MCI, improve the predictive power of its development, and intervene potential Alzheimer’s disease effectively.
With the wide application of deep learning technology in disease diagnosis, especially the outstanding performance of convolutional neural network (CNN) in computer vision and image processing, more and more studies have proposed to use this algorithm to achieve the classification of Alzheimer’s disease (AD), mild cognitive impairment (MCI) and normal cognition (CN). This article systematically reviews the application progress of several classic convolutional neural network models in brain image analysis and diagnosis at different stages of Alzheimer’s disease, and discusses the existing problems and gives the possible development directions in order to provide some references.
Objective To evaluate the risk factors for cognitive impairment and their interactions in acute ischemic stroke (IS) patients. Methods IS patients admitted to the Department of Neurology, the People’s Hospital of Mianyang between January 2019 and January 2022 were selected. Patients were divided into a cognitive impairment group and a cognitive normal group. The demographic characteristics and clinical data of the subjects were collected, and the traditional risk factors for cognitive impairment were determined by univariate and multivariate logistic regression analysis. The multifactor dimensionality reduction test was used to detect the possible interactions between risk factors. Results A total of 255 patients were included. Among them, 88 cases (34.5%) in the cognitive impairment group and 167 cases (65.5%) in the cognitive normal group. The results of factor logistic regression analysis showed that after adjusting for covariates, big and medium infarction volume, severe IS, moderate to severe carotid artery stenosis as well as high hypersensitive C-reactive protein (hs-CRP) were associated with post-IS cognitive impairment (P<0.05). The cognitive impairment increased by 22.632 times [odds ratio=22.632, 95% confidence interval (5.980, 85.652), P<0.001] in patients with big and medium infarction volume, severe IS and high hs-CRP. Conclusions The cognitive impairment is common in acute IS. Patients with big and medium infarction volume, non-mild stroke, carotid artery stenosis, high hs-CRP, and non-right sided infarction are prone to cognitive impairment, and there are complex interactions among these risk factors.
ObjectivesTo systematically review the epidemiological characteristics of mild cognitive impairment (MCI) in Chinese elderly population.MethodsPubMed, EMbase, The Cochrane Library, CNKI, VIP, WanFang Data and CBM databases were electronically searched to collect studies on the epidemiological characteristics of mild cognitive impairment in the elderly in China from inception to May 2019. Two reviewers independently screened literature, extracted data and assessed risk of bias of included studies. Then, meta-analysis was performed by using Stata 12.0 software.ResultsA total of 25 studies involving 56 720 patients were included. The results of meta-analysis showed that the prevalence of MCI in Chinese elderly population was 14% (95%CI 12% to 17%), in which 12.1% (95%CI 9.7% to 14.5%) was male and 14.8% (95%CI 12.5% to 17.2%) was female. The prevalence of MCI was 8% (95%CI 6.0% to 10.1%) in the elderly aged 60 to 69, 13.1% (95%CI 10.6% to 15.6%) in the elderly aged 70 to 79 and 23.4% (95%CI 18.3% to 28.6%) in the elderly aged above 80. The prevalence of MCI was 23% (95%CI 18.3% to 27.6%) in the elderly who were illiterate, 15.2% (95%CI 11.2% to 19.2%) among the elderly with a primary education and 9.8% (95%CI 7.1% to 12.6%) among the elderly with an education above junior high school. The prevalence of MCI was 9.9% (95%CI 5.5% to 14.2%) in urban areas, and 16.7% (95%CI 11.2% to 22.2%) in rural areas. The prevalence of MCI was 12.1% (95%CI 7.7% to 16.5%) in married individuals and 17.1% (95%CI 13.9% to 20.2%) in single individuals. The prevalence of MCI was 15.4% (95%CI 11.4% to 19.4%) in northern China, 14.1% (95%CI 11.1% to 17.2%) in eastern China, 5.4% (95%CI 3.9% to 6.9%) in northeast China, 13% (95%CI 6.2% to 19.8%) in Central-south China, 11.7% (95%CI 10.2% to 13.2%) in the southwest China and 17.4% (95%CI 2.5% to 32.3%) in northwest China. By using the diagnostic criteria proposed by Petersen, the prevalence of MCI was 15.2% (95%CI 11.8% to 18.7%), and was 12.4% (95%CI 9.4% to 15.4%) using the criteria of the DSM-Ⅳ.ConclusionsThe prevalence of MCI is high in China, and varies with gender, age, education, location, marital status, region and diagnostic criteria.
Objective To evaluate diagnostic accuracy of several relevant cut-off points of Montreal cognitive assessment (MoCA) for mild cognitive impairment (MCI) in Chinese middle-aged adults. Methods Databases including PubMed, EMbase, Web of Science, The Cochrane Library (Issue 5, 2016), OVID, CBM, CNKI, VIP, WanFang Data were searched for diagnostic tests about MoCA for MCI from April 9th 2005 to December 31st 2015. Two reviewers independently screened literatures according to the inclusion and exclusion criteria, extracted data and assessed the methodological quality by QUADAS-2 tool. Then, meta-analysis was performed by Stata 14.0 software. Results A total of 27 studies involving 5 755 participants were included with mean ages from 60 to 80 years old. Among them, 1 997 were diagnosed as MCI patients by Petersen criteria. Based on maximal area under the ROC curve as well as optimal pooled sensitivity and specificity, the optimal cutoff value of MoCA was 25/26, the pooled sensitivity was 0.96 with 95%CI 0.93 to 0.97, specificity was 0.83 with 95%CI 0.75 to 0.89, and DOR was 107 with 95%CI 61 to 188. The subgroup analysis with different research designs, different sources of study participants and different MoCA versions all indicated 25/26 as an optimal cut-off value. Conclusion The optimal cutoff value of MoCA in Chinese middle-aged adults for screening MCI by Petersen criteria was 25/26.
Cerebral small vessel disease refers to a series of clinical, imaging, and pathological syndromes caused by various factors affecting small blood vessels in the brain. Cognitive impairment is one of the most common complications of cerebral small vessel disease. Current researches have found that cognitive impairment is related to various factors such as hypoxia. Hyperbaric oxygen therapy can achieve certain therapeutic effects by improving hypoxia. This article reviews the pathogenesis of cerebral small vessel disease, biomarkers of cerebral small vessel disease, research progress on hyperbaric oxygen therapy for cognitive impairment, and focuses on the research progress of hyperbaric oxygen therapy for mild cognitive impairment and dementia, providing more references for clinical treatment.
ObjectiveTo systematically review the efficacy of repetitive transcranial magnetic stimulation (rTMS) on patients with mild cognitive impairment (MCI). MethodsWe searched databases including PubMed, The Cochrane Library (Issue 10, 2015), EMbase, PsycINF, EBSCO, CBM, CNKI, WanFang Data and VIP from inception to October 2015 to collect randomized controlled trials (RCTs) about rTMS for patients with MCI. Two reviewers independently screened literature, extracted data and assessed the risk of bias of included studies. Then, meta-analysis was performed by using RevMan 5.3 software. ResultsA total of 5 RCTs involving 180 MCI patients were included. The results of meta-analysis showed that, compared with the control group, rTMS treatment could significantly improve the overall cognitive abilities of MCI patients (SMD=2.53, 95% CI 0.91 to 4.16, P=0.002), as well as the single-domain cognitive performances, including tests for episodic memory (MD=0.98, 95% CI 0.24 to 1.72, P=0.01) and verbal fluency (MD=2.08, 95% CI 0.46 to 3.69, P=0.01). rTMS was a well-tolerated therapy, with slightly more adverse events observed than the control group (RD=0.09, 95% CI 0.00 to 0.18, P=0.04), but cases were mainly transient headache, dizziness and scalp pain. ConclusionrTMS may benefit the cognitive abilities of MCI patients. Nevertheless, due to the limited quantity and quality of included studies, large-scale, multicenter, and high quality RCTs are required to verify the conclusion.
Normal brain aging and a serious of neurodegenerative diseases may lead to decline in memory, attention and executive ability and poorer quality of life. The mechanism of the decline is not clear now and is still a hot issue in the fields of neuroscience and medicine. A large number of researches showed that resting state functional brain networks based functional magnetic resonance imaging (fMRI) are sensitive and susceptive to the change of cognitive function. In this paper, the researches of brain functional connectivity based on resting fMRI in recent years were compared, and the results of subjects with different levels of cognitive decline including normal brain aging, mild cognitive impairment (MCI) and Alzheimer’s disease (AD) were reviewed. And the changes of brain functional networks under three different levels of cognitive decline are introduced in this paper, which will provide the basis for the detection of normal brain aging and clinical diseases.
Alzheimer’s disease (AD) is a common and serious form of elderly dementia, but early detection and treatment of mild cognitive impairment can help slow down the progression of dementia. Recent studies have shown that there is a relationship between overall cognitive function and motor function and gait abnormalities. We recruited 302 cases from the Rehabilitation Hospital Affiliated to National Rehabilitation Aids Research Center and included 193 of them according to the screening criteria, including 137 patients with MCI and 56 healthy controls (HC). The gait parameters of the participants were collected during performing single-task (free walking) and dual-task (counting backwards from 100) using a wearable device. By taking gait parameters such as gait cycle, kinematics parameters, time-space parameters as the focus of the study, using recursive feature elimination (RFE) to select important features, and taking the subject’s MoCA score as the response variable, a machine learning model based on quantitative evaluation of cognitive level of gait features was established. The results showed that temporal and spatial parameters of toe-off and heel strike had important clinical significance as markers to evaluate cognitive level, indicating important clinical application value in preventing or delaying the occurrence of AD in the future.
ObjectiveTo evaluate the efficacy of different non-pharmacological interventions on cognitive function in elderly patients with mild cognitive impairment by the network meta-analysis. MethodsThe PubMed, Embase, Cochrane Library, CINAHL, CNKI, WanFang Data, VIP and CBM databases were electronically searched to collect randomized controlled trials (RCTs) related to the objectives from inception to November 2022. Two reviewers independently screened literature, extracted data and assessed the risk of bias of the included studies. The network meta-analysis was then performed by using Stata 16.0 and Open BUGS 3.2.3 software. ResultsA total of 43 RCTs involving 2 986 patients were included, which involved 8 non-drug intervention methods. The best probability ranking results of the network meta-analysis showed that on the simple mental state scale (MMSE) scores: rTMS > acupressure > acupuncture therapy > exercise therapy > cognitive training > multicomponent intervention > VR > conventional care > health education, and on the Montreal cognitive assessment scale (MoCA) scores: VR > exercise therapy > rTMS > acupuncture therapy > acupressure > cognitive training > health education > conventional care. Conclusion?Current evidence shows that rTMS, acupressure, VR, exercise therapy and acupuncture may be effective interventions to improve cognitive function in elderly patients with mild cognitive impairment. Due to the limited quality and quantity of the included studies, more high quality studies are needed to verify the above conclusion.