目的 全面了解空巢老人认知功能障碍危险因素。 方法 检索Ovid Medline、Ovid Embase、Cochrane 图书馆及中国生物医学文献数据库（光盘版）等数据库，检索时间为各数据库建库至2011年12月31日。文献纳入标准：年龄≥60岁或作者指明以老人为研究对象；居住状态包括老人无子女或未与子女同住。两位研究者独立地对符合纳入标准的试验进行质量评价和资料提取。 结果 4篇文献（共1 485例）分析了养老机构老人认知障碍的影响因素，合并分析显示年龄[WMD=2.10岁，95%CI（1.28，2.92）岁，P＜0.000 01]、女性[OR=3.61，95%CI（1.63，8.01），P=0.002]、失能[SMD=0.78，95%CI （0.36，1.20），P=0.000 2]、躯体健康[SMD=0.06，95%CI （0.01，0.11），P=0.02]、未婚/寡居[OR=3.16，95%CI（1.43，6.96），P＜0.000 01]、文盲[OR=2.94，95%CI（1.06，8.14），P=0.04]、社会支持差[OR=7.29，95%CI（2.27，23.39），P=0.000 8]、朋友关系差[OR=2.14，95%CI（1.35，3.39），P=0.001]、参加活动少[OR=2.11，95%CI（1.36，3.29），P=0.000 9]及远离子女[OR=5.73，95%CI（3.33，9.87），P＜0.05]是其危险因素。 结论 养老机构老人认知功能障碍的危险因素包括老年、女性、文盲、未婚/寡居、社交差、与子女距离远、躯体健康水平差及抑郁等。结果仅来源于较少的研究和数量较小的对象，且均为横断面研究，需谨慎看待上述结论。
【摘要】 目的 通过比较遗忘型轻度认知障碍（amnestic mild cognitive impairment，aMCI）和血管性认知障碍非痴呆型（vascular cognitive impairment-no dementia，VCI-ND）患者及正常老年人群在简易智能精神状态检查量表（mini mental state examination，MMSE）、听觉词语学习测验（auditory verbal learning test，AVLT）、画钟试验（clock drawing test，CDT）及临床痴呆评定量表（clinical dementia rating scales，CDR）中的表现，进一步分析aMCI和VCI-ND在认知损害方面的不同特点。 方法 选取首都医科大学宣武医院神经内科门诊收治aMCI患者23例及VCI-ND患者27例（CDR＝0.5分），同时选取40名正常老年人（CDR=0分）作为对照组。每位受试者均进行MMSE、AVLT、CDT及CDR等神经心理学量表测查，分析以上3组被试各项神经心理学测查得分之间的差异。 结果 各组受试者的年龄、性别及受教育程度差异无统计学意义（Pgt;0.05），具有可比性。aMCI和VCI-ND组在MMSE、CDT、即刻记忆、延迟记忆及延迟再认检测中的平均值均低于对照组，且差异均具有统计学意义（Plt;0.05）。aMCI和VCI-ND两组除延迟再认检测外，其余各项测查的平均分均无统计学意义（Pgt;0.05）。在延迟再认检测中，aMCI组（6.65±4.00）较VCI-ND组（8.67±2.76）再认词语数量少，两组延迟再认的得分均低于对照组（12.83±1.77），差异有统计学意义（Plt;0.05）。 结论 aMCI和VCI-ND在记忆力、执行能力和信息处理能力方面较正常老年人均有所损害。由于aMCI和VCI-ND不同的病理改变，导致患者存在不同类型的记忆储存和提取机制。【Abstract】 Objective To investigate the different patterns of cognitive impairment in patients with amnestic mild cognitive impairment (amci), vascular cognitive impairment-no dementia (VCI-ND) and normal elder people. Methods A total of 23 patients with aMCI and 27 patients with VCI-ND (CDR＝0.5) and another 40 healthy elder people (CDR=0) were selected. Each individual underwent the neuropsychological tests, including mini mental state examination (MMSE), auditory verbal learning test (AVLT), clock drawing test (CDT), clinical dementia rating scales (CDR) and hamilton rating scale for depression (HAMD). The differences between the three groups were analyzed. Results The differences in age, sexes, and the education background among the three groups were not significant (Pgt;0.05) which meant comparability. The mean scores of MMSE, CDT, instant memory and delayed awareness in aMCI and VIC-ND group were much lower than that in the control group (Plt;0.05). The differences in all the test items except for delayed awareness between aMCI group and VCI-ND groups were not significant (Pgt;0.05). However, in the recall recognition test, these three groups had significant differences: the score in patients with aMCI (6.65±4.00) was much lower than that in patients with VCI-ND (8.67±2.76; Plt;0.05), and the scores of the two groups were both lower than that in the normal aging group (12.83±1.77; Plt;0.05). Conclusion Compared with normal elder people, the cognition of aMCI and VCI-ND patients is impaired severely. The memory tests suggeste that compared with aMCI patients, VCI-ND patients may have different neuropathological changes leading to different mechanism of memory encoding and retrieval.
ObjectiveTo observe the effect of rosiglitazone on cognitive function, serum high sensitive C reactive protein (hs-CRP) and expression of nuclear factor-κB (NF-κB), interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α) in hippocampal tissues of senile diabetic rats. MethodsThirty aged Wistar rats (20-22 months) were randomly divided into normal control group (n=6), diabetic model group (n=12), and rosiglitazone treatment group (n=12). Streptozotocin-induced diabetic rat model was established. In the rosiglitazone treatment group, the rats were treated with rosiglitazone 4mg/kg/d for 8 weeks. The cognitive function of rats was evaluated with the Morris water maze test. Serum hs-CRP was detected by ELISA. The expression of NF-κB in hippocampal tissues was detected by western blot and IL-6 and TNF-α by Real-time PCR. ResultsThe Morris water maze test showed that escape latency was longer in the rosiglitazone treatment group and the diabetic model group than that in the control group (P<0. 05). Compared with the diabetic model group, the rosiglitazone treatment group showed a significant decrease in the average time of escape latencies (P<0.05), and an increased percentage of time spent in the central area and the more times navigating the original platform position (P<0.05). Serum hs-CRP and the expression of NF-κB, IL-6 and TNF-α in the rosiglitazone treatment group and the diabetic model group was significantly higher than those in the control group (P<0.01). Compared with the diabetic model group, serum hs-CRP and the expression of NF-κB, IL-6 and TNF-α in the rosiglitazone treatment group was decreased (P<0.05). ConclusionCognitive impairment in senile diabetic rats is associated with serum hs-CRP. The cognitive function can be improved with rosiglitazone treatment. The protective mechanisms may be related to the decrease of serum hs-CRP, inhibition of NF-κB signal and down-regulation of the expression of IL-6 and TNF-α in hippocampal tissues.
To observe the effects of ultrasound-guided stellate ganglion block (SGB) on cerebral oxygen metabolism and postoperative cognitive dysfunction (POCD) of elderly patients, we collected 80 elderly patients undergoing selective coronary artery bypass graft under cardiopulmonary bypass. The Mini Mental State Examination (MMSE) was applied to test the cognitive function. The SjvO2, Da-jvO2 and CEO2 were used for the analysis of the cerebral oxygen metabolism. We found that POCD was related to disequilibrium of cerebral oxygen metabolism. Ultrasound-guided SGB before surgery reduced the incidence of POCD because of the improvement of cerebral oxygen metabolism.
We in the present research proposed a classification method that applied infomax independent component analysis (ICA) to respectively extract single modality features of structural magnetic resonance imaging (sMRI) and positron emission tomography (PET). And then we combined these two features by using a method of weight combination. We found that the present method was able to improve the accurate diagnosis of Alzheimer's disease (AD) and mild cognitive impairment (MCI). Compared AD to healthy controls (HC): the study achieved a classification accuracy of 93.75%, with a sensitivity of 100% and a specificity of 87.64%. Compared MCI to HC: classification accuracy was 89.35%, with a sensitivity of 81.85% and a specificity of 99.36%. The experimental results showed that the bi-modality method performed better than the individual modality in comparison to classification accuracy.
The cognitive impairment of type 2 diabetes patients caused by long-term metabolic disorders has been the current focus of attention. In order to find the related electroencephalogram (EEG) characteristics to the mild cognitive impairment (MCI) of diabetes patients, this study analyses the EEG synchronization with the method of multi-channel synchronization analysis--S estimator based on phase synchronization. The results showed that the S estimator values in each frequency band of diabetes patients with MCI were almost lower than that of control group. Especially, the S estimator values decreased significantly in the delta and alpha band, which indicated the EEG synchronization decrease. The MoCA scores and S value had a significant positive correlation in alpha band.
Mild cognitive impairment (MCI) is a clinical transition state between age-related cognitive decline and dementia. Researchers can use neuroimaging and neurophysiological techniques to obtain structural and functional information about the human brain. Using this information researchers can construct the brain network based on complex network theory. The literature on graph theory shows that the large-scale brain network of MCI patient exhibits small-world property, which ranges intermediately between Alzheimer's disease and that in the normal control group. But brain connectivity of MCI patients presents topologically structural disorder. The disorder is significantly correlated to the cognitive functions. This article reviews the recent findings on brain connectivity of MCI patients from the perspective of multimodal data. Specifically, the article focuses on the graph theory evidences of the whole brain structural and functional and the joint covariance network disorders. At last, the article shows the limitations and future research directions in this field.
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.
Objective To observe the relationship of serum levels of homocysteine (HCY) and chemokine C-C motifligand 2 (CCL2) with cognitive impairment in COPD patients with different degrees of emphysema. Methods Sixty-twoCOPD patients identified according to emphysema phenotype classification and admitted from January 2016 to March 2017 were recruited in the study. There were 37 cases in emphysema 1-2 grade and 25 cases in emphysema 3-4 grade. Simultaneous 30 healthy subjects undergoing physical examination were recruited as control. Montreal cognitive assessment (MoCA) scale investigation and serum HCY and CCL2 test were completed. Relationship analysis was conducted on serum HCY, CCL2 levels with cognitive impairment in the COPD patients with different degrees of emphysema. Results Compared with the 1-2 grade subgroup, the PaO2 was lower, PaCO2 was higher, the plasma HCY and CCL2 levels increased in the 3-4 grade subgroup with significant differences (all P<0.05). MoCA total score and subscores were relatively low in the COPD group with emphysema than the control group (except visuospatial ability scores in the 1-2 grade subgroup). MoCA scores were statistically lower in the 3-4 grade subgroup than those in the 1-2 grade subgroup (allP<0.05). Correlation analysis showed that HCY and CLL2 levels were negatively correlated with MoCA scores and subscores (P<0.01), and HCY and CLL2 were positively correlated (bothP<0.01). The area under the receiver operating characteristic curve of HCY and CLL2 for evaluating cognitive impairment was 0.79 and 0.97, respectively. Conclusion In patients with different degrees of emphysema phenotype, serum HCY and CCL2 levels are increased in different degree, and the degree of emphysema is closely related with cognitive dysfunction.
In order to solve the problem of early classification of Alzheimer’s disease (AD), the conventional linear feature extraction algorithm is difficult to extract the most discriminative information from the high-dimensional features to effectively classify unlabeled samples. Therefore, in order to reduce the redundant features and improve the recognition accuracy, this paper used the supervised locally linear embedding (SLLE) algorithm to transform multivariate data of regional brain volume and cortical thickness to a locally linear space with fewer dimensions. The 412 individuals were collected from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) including stable mild cognitive impairment (sMCI, n = 93), amnestic mild cognitive impairment (aMCI, n = 96), AD (n = 86) and cognitive normal controls (CN, n = 137). The SLLE algorithm used in this paper is to calculate the nearest neighbors of each sample point by adding the distance correction term, and the locally linear reconstruction weight matrix was obtained from its nearest neighbors, then the low dimensional mapping of the high dimensional data can be calculated. In order to verify the validity of SLLE in the task of classification, the feature extraction algorithms such as principal component analysis (PCA), Neighborhood MinMax Projection (NMMP), locally linear mapping (LLE) and SLLE were respectively combined with support vector machines (SVM) classifier to obtain the accuracy of classification of CN and sMCI, CN and aMCI, CN and AD, sMCI and aMCI, sMCI and AD, and aMCI and AD, respectively. Experimental results showed that our method had improvements (accuracy/sensitivity/specificity: 65.16%/63.33%/67.62%) on the classification of sMCI and aMCI by comparing with the combination algorithm of LLE and SVM (accuracy/sensitivity/specificity: 64.08%/66.14%/62.77%) and SVM (accuracy/sensitivity/specificity: 57.25%/56.28%/58.08%). In detail the accuracy of the combination algorithm of SLLE and SVM is 1.08% higher than the combination algorithm of LLE and SVM, and 7.91% higher than SVM. Thus, the combination of SLLE and SVM is more effective in the early diagnosis of Alzheimer’s disease.