ObjectiveTo explore the association between prediabetes and early vascular cognitive impairment (VCI) in patients with acute cerebral infarction. MethodsNon-diabetes mellitus patients with first-ever acute cerebral infarction hospitalized in the Department of Neurology, the First Affiliated Hospital of Henan University of Science and Technology between January and April 2019 were retrospectively enrolled. The enrolled patients were divided into prediabetes group and normal blood glucose group according to the level of glycosylated hemoglobin, and the patients were divided into normal cognitive function group and cognitive impairment group according to the Montreal Cognitive Assessment score. The general information and clinical related data of the included patients were compared. Results A total of 129 patients were enrolled. Among them, 46 cases were in the prediabetes group and 83 cases were in the normal blood glucose group. There were 82 cases in the normal cognitive function group and 47 cases in the cognitive impairment group. Multivariate logistic regression analysis showed that compared with the normal blood glucose group, the prediabetes group was associated with early VCI in patients with acute cerebral infarction [odds ratio (OR)=4.172, 95% confidence interval (CI) (1.786, 9.754), P=0.001]; the higher the NationalInstitutes of Health Stroke Scale score at the first admission was, the higher the risk of early VCI was [OR=1.379, 95%CI (1.183, 1.650), P<0.001]. Conclusion In patients with first-ever acute cerebral infarction, prediabetes is associated with early VCI.
Objective To systematically review the influencing factors of mild cognitive impairment in type 2 diabetic patients. MethodsPubMed, Web of Science, EMbase, The Cochrane Library, CNKI, WanFang Data, VIP, and CBM databases were electronically searched to collect studies on the influencing factors of mild cognitive impairment in patients with type 2 diabetes from inception to December 31, 2021. Two reviewers independently screened the literature, extracted data, and assessed the risk of bias of included studies; then, meta-analysis was performed by using RevMan 5.4 software and Stata 12.0 software. ResultsA total of 32 studies involving 7 519 subjects were included. The results of the meta-analysis showed that the main influencing factors of mild cognitive impairment in type 2 diabetic patients were age, duration of type 2 diabetes, educational level, cerebral infarction, hypertension, smoking, insulin resistance index, glycosylated hemoglobin, and homocysteine. ConclusionCurrent evidence shows that some factors such as age, duration, and educational level are the main influencing factors of mild cognitive impairment in type 2 diabetic patients. Due to the limited quality and quantity of the included studies, more high quality studies are needed to verify the above conclusions.
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.
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.
Due to the aging population intensifies, the number of people suffering from mild cognitive impairment (MCI) or dementia is expected to increase, which may lead to a series of public health and social health problems. In the absence of drugs to prevent the transformation of MCI into dementia, it is urgent to find effective non-pharmacological therapies to delay the progress of cognitive impairment. This article will review the diagnosis of MCI and the research progress of non-pharmacological therapies, focusing on the non-pharmacological therapies related to MCI in recent years, including exercise intervention, cognitive intervention, physical and mental exercise, dietary intervention, electroacupuncture, repeated transcranial magnetic stimulation, and multi-component intervention, in order to provide an effective treatment for preventing or delaying the progression of MCI to dementia.
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.
Objective To investigate the prevalence of cognitive impairment and identify its influencing factors among lung cancer patients undergoing chemotherapy, providing a scientific basis for targeted interventions. Methods A convenience sample of lung cancer patients receiving chemotherapy at West China Hospital, Sichuan University between April and October 2024 was enrolled. Data were collected using a general information questionnaire, the Mini-Mental State Examination, Nutritional Risk Screening 2002, Hospital Anxiety and Depression Scale, Barthel index, and FRAIL scale. Univariate analyses and multivariate logistic regression were performed to determine factors associated with cognitive impairment. Results A total of 380 patients undergoing chemotherapy for lung cancer were enrolled, and 205 (53.9%) of them had cognitive impairment. Univariate analyses revealed that there were statistically significant differences between the cognitively normal group and the cognitive impairment group in age, educational level, work status, nutritional status, Barthel index, and FRAIL scale score (P<0.05). Multivariate logistic regression showed that advanced age [odds ratio (OR)=1.045, 95% confidence interval (CI) (1.015, 1.075), P=0.002] and FRAIL scale score [OR=1.369, 95%CI (1.165, 1.609), P<0.001] were identified as independent risk factors for cognitive impairment, whereas higher educational attainment served as a protective factor, compared with patients with primary school education or below, patients with junior high school, high school/secondary vocational school, college, or undergraduate education and above had a lower risk of cognitive impairment [OR=0.437, 0.258, 0.243, 0.120, P<0.05]. Conclusions Cognitive impairment is highly prevalent among lung cancer patients undergoing chemotherapy and is significantly influenced by age, educational level, and frailty. Healthcare providers should develop targeted interventions based on these factors to reduce the prevalence of cognitive impairment.
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 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.
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.
