Objective To systematically review the efficacy of six cognitive interventions on cognitive function of patients with mild cognitive impairment after stroke. Methods The PubMed, EMbase, Cochrane Library, SinoMed, WanFang Data and CNKI databases were electronically searched to collect randomized controlled trials on the effects of non-drug interventions on the cognitive function of patients with mild cognitive impairment after stroke from inception to March 2023. Two reviewers independently screened the literature, extracted data, and assessed the risk of bias of the included studies. Network meta-analysis was then performed using Openbugs 3.2.3 and Stata 16.0 software. Results A total of 72 studies involving 4 962 patients were included. The results of network meta-analysis showed that the following five cognitive interventions improved the cognitive function of stroke patients with mild cognitive impairment: cognitive control intervention (SMD=−1.28, 95%CI −1.686 to −0.90, P<0.05) had the most significant effect on the improvement of cognitive function, followed by computer cognitive training (SMD=−1.02, 95%CI −1.51 to −0.53, P<0.05), virtual reality cognitive training (SMD=−1.20, 95%CI −1.78 to −0.62, P<0.05), non-invasive neural regulation (SMD=−1.09, 95%CI −1.58 to −0.60, P<0.05), and cognitive stimulation (SMD=−0.94, 95%CI −1.82 to −0.07, P<0.05). Conclusion Five cognitive interventions are effective in improving cognitive function for stroke patients with mild cognitive impairment, among which cognitive control intervention is the most effective. Due to the limited quantity and quality of the included studies, more high-quality studies are needed to verify the above conclusion.
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.
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 systematically review the detection rate of cognitive impairment in Chinese patients with type 2 diabetes mellitus (T2DM).MethodsPubMed, EMbase, The Cochrane Library, CBM, CNKI, WanFang Data and VIP databases were searched to collect studies on the detection rate of cognitive impairment in Chinese patients with T2DM from inception to January 20th, 2021. Two reviewers independently screened literature, extracted data and evaluated the risk of bias of included studies. Meta-analysis was then performed using Stata 12.0 software.ResultsA total of 27 studies involving 7 920 cases were included. Meta-analysis results showed that the total detection rate of cognitive impairment in Chinese patients with T2DM was 43.2% (95%CI 36.9% to 49.6%). The results of subgroup analysis showed that in T2DM patients, the detection rate of cognitive impairment in males was 42.4% (95%CI 34.4% to 50.4%), and that in females was 48.2% (95%CI 40.9% to 55.6%). The detection rate of cognitive impairment was 25.4% (95%CI 14.7% to 36.0%) in patients under the age of 60 years, and 47.0% (95%CI 30.0% to 64.0%) in patients aged 60 years or above. The detection rate of cognitive impairment among those with primary school education level or below was 67.1% (95%CI 48.9% to 85.3%). The detection rate of cognitive impairment was 37.1% (95%CI 27.3% to 46.8%) among those with education level of junior high school or above. The detection rate of cognitive impairment in patients with disease duration less than 10 years was 28.4% (95%CI 16.0% to 40.9%) and that in patients with disease duration more than 10 years was 50.6% (95%CI 33.2% to 68.0%). The detection rate of cognitive impairment in married individuals was 45.6% (95%CI 35.8% to 55.4%) and that in singles was 68.1% (95%CI 57.5% to 78.7%). The detection rate of cognitive impairment in smokers was 38.9% (95%CI 30.7% to 47.2%) and in non-smokers was 40.9% (95%CI 32.1% to 49.6%). The detection rate of cognitive impairment in drinkers was 35.6% (95%CI 27.3% to 44.0%) and that in non-drinkers was 41.8% (95%CI 32.2% to 51.4%).ConclusionsThe detection rate of cognitive impairment in Chinese patients with T2DM is high. Due to the quantity and quality of included studies, more high-quality studies are needed to verify the above conclusions.
ObjectiveTo systematically review the accuracy of the mini-mental state examination scale (MMSE) in the screening of poststroke cognitive impairment (PSCI), and the diagnostic value of different cut-off values of the scale, so as to provide references for the selection of the threshold of the MMSE scale. MethodsDatabases including PubMed, EMbase, Cochrane Library, Web of Science, CINAHL, CBM, VIP, CNKI, and WanFang data were searched for diagnostic tests about MMSE for PSCI from inception to November 2022. Two researchers independently screened the literatures, extracted data and assessed the risk of bias of the included studies. Then, meta-analysis was performed by Stata 16.0 software. ResultsA total of 23 studies involving 1 525 patients were included. The results of meta-analysis showed that after the analysis of bivariate mixed effect model, the optimal cutoff value of MMSE scale was 23/24 (the pooled sensitivity=0.75, 95%CI 0.52 to 0.89; the pooled Specificity=0.90, 95%CI 0.81 to 0.95; DOR=28, 95%CI 12 to 65; AUC=0.92, 95%CI 0.89 to 0.94). The results of hierarchical summary receiver-operating characteristic (HSROC) curve model showed that the pooled sensitivity=0.77, 95%CI 0.70 to 0.83; the pooled specificity=0.76, 95%CI 0.69 to 0.83, Beta=0.1, 95%CI −0.13 to 0.33, Z=0.82, P=0.41, Lambda=2.38, 95%CI 2.12 to 2.64, and the area under the SROC curve was 0.84. Fagan pre-test probability was 38%, positive likelihood ratio was 3.3, positive post-test probability was 67%, negative likelihood ratio was 0.3,negative post-test probability was 16%. ConclusionThe current evidence shows that MMSE has a certain diagnostic value as a screening tool for PSCI, the overall diagnostic efficacy is moderate, and the diagnostic value is highest when the cut-off value is 23/24. Due to the limited quality and quantity of the included studies, more high quality studies are required to verify the above conclusion.
ObjectiveTo analyze the related factors of cognitive impairment in patients with post-traumatic epilepsy. MethodsFrom January 2016 to January 2019, 45 patients with post-traumatic epilepsy (epilepsy group) and 48 patients with physical examination (control group) at the Department of Neurosurgery, the 904th Hospital of PLA were analyzed retrospectively. Cognitive assessment were evaluated by the following scales: Montreal cognitive assessment (MoCA), Mini-mental state examination (MMSE), Audio verbal memory test (AVMT), Rey-osterrieth complex figure test (CFT) and Trail making test (TMT). Then we analyzed the influences of gender, age, course of disease, cause, type, degree and location of injury, seizure frequency and Anti-seizure medications (ASMs) on cognitive impairment. ResultsThe results showed that there were significant differences between the epilepsy group and the control group in all scales (P<0.01). Analysis of influencing factors in epilepsy group showed: MoCA and MMSE scores: there were statistical significance in the comparison of seizure frequency and injury degree (P<0.05); AVMT, CFT and TMT scores: there were statistical significance in the comparison of seizure frequency, injury degree and location, ASMs within the group (P<0.05). ConclusionPost-traumatic epilepsy can cause cognitive impairment. The more frequent epileptic seizures and the more severe the degree of trauma, the more serious the cognitive impairment. Different injury sites affect the scope of cognitive impairment, temporal lobe injury is easy to cause memory function decline, frontal lobe injury is easy to cause spatial structure and executive ability decline, at the same time, the combined use of ASMs has an impact on cognitive function.
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.
Objective To analyze the efficacy of music therapy on the rehabilitation of post-stroke cognitive impairment (PSCI) and to provide a reference for rehabilitation intervention methods for PSCI. Methods Patients hospitalized in Beijing Bo’Ai Hospital, China Rehabilitation Research Center and diagnosed with PSCI between December 2020 and July 2022 were prospectively selected. According to the random number table method, patients were divided into a music therapy group and a control group. Both groups were given conventional neurology medication, nursing care, and conventional rehabilitation. The music therapy group received additional music therapy training, and both groups received treatment for one month. The Montreal Cognitive Assessment (MoCA), National Institute of Health Stroke Scale (NIHSS), Fugl-Meyer Assessment Scale (FMA), and modified Barthel Index (MBI) were used before and after treatment to assess patients’ cognitive function, degree of neurological deficits, motor function and activities of daily live. Results A total of 48 patients were included, with 24 patients in both groups. There was no statistically significant difference in gender, age, education level, stroke type, lesion location, comorbidities, history of myocardial infarction or peripheral vascular disease, and smoking status between the two groups of patients (P>0.05). Before and after treatment, most patients in the two groups did not score in terms of language and delayed recall scores, and the difference were not statistically significant (P>0.05). There was no statistically significant difference in MoCA scores, visual space and executive function, naming, attention, calculation, abstract thinking, and orientation scores between the two groups of patients before treatment (P>0.05). After treatment, the MoCA score, visual space and executive function, naming, attention, calculation, abstract thinking, and orientation scores of the music therapy group improved compared to before treatment (P<0.05), while the MoCA score, visual space and executive function, naming, attention, and orientation scores of the control group improved compared to before treatment (P<0.05). After treatment, the improvement in MoCA scores [5.0 (3.0, 6.0) vs. 2.5 (1.0, 4.0)], attention [1.0 (0.0, 1.0) vs. 0.0 (0.0, 1.0)], and abstract thinking scores [0.0 (0.0, 1.0) vs. 0.0 (0.0, 0.0)] in the music therapy group were better than that in the control group (P<0.05). There was no statistically significant difference in NIHSS, FMA, and MBI scores between the two groups of patients before treatment (P>0.05), and both groups improved after treatment compared to before treatment (P<0.05). After treatment, there was no statistically significant difference in the improvement of NIHSS, FMA, and MBI scores between the two groups of patients (P>0.05). Conclusions Compared with conventional rehabilitation therapy, training combined with music therapy is more beneficial for improving cognitive function in PSCI patients, especially in the cognitive domains of attention and abstract thinking. However, significant advantages have not been found in improving the degree of neurological impairment, limb motor function, and daily living activities.