Background: Mild cognitive impairment (MCI) is an important stage between the normal cognitive decline of aging and dementia. The aim of this study was to compare and harmonize the recommendations for the diagnosis and treatment of MCI based on current clinical practice guidelines.Methods: We searched the PubMed, EMBASE, China National Knowledge Infrastructure, Wanfang Database, Chinese Science and Technology Periodical Database, and Chinese Biological Medicine Database from their inception date to April 24, 2021 to identify all published guidelines on MCI. The qualities of the eligible guidelines were appraised by two reviewers using the Appraisal of Guidelines for Research and Evaluation II instrument.Results: Thirteen guidance documents (four guidelines and nine consensus statements) with specific recommendations were included. Nine guidelines and consensus statements covered the screening and diagnosis of MCI. The evaluation of the documents showed that neuropsychological testing and biomarker assessments were the most common recommendations for the diagnosis of MCI. Nine of the 13 guidance documents covered the treatment and management of MCI. The recommendations for the treatment and management were classified into four categories, namely: intervention for risk reduction, pharmacologic interventions, non-pharmacologic interventions, and counseling. Regarding pharmacological interventions, three guidelines recommend no pharmacologic intervention. The use of cholinesterase inhibitors for MCI is contraindicated in three guidance documents, whereas one proposes that cholinesterase inhibitors and memantine should be deprescribed. EHb761®, Chinese herbal decoctions, and Chinese traditional patent medicine are recommended in two documents. A total of seven guidance documents recommend non-pharmacological interventions, including physical activity interventions, cognitive interventions, dietary and nutritional interventions, and acupuncture.Conclusion: An updated search for possible evidence on the diagnosis and treatment of MCI is needed. Potentially effective diagnoses and treatments, either conventional or complementary, and alternative therapies should be highly valued and addressed in correlation with the supporting evidence.
ObjectivesThis study aims to explore the benefits and harms of Chinese Herbal Medicine (CHM) for mild cognitive impairment (MCI).MethodsElectronic searching was conducted in two English and four Chinese databases till 2021 December. Randomized clinical trials on CHM compared to no intervention, placebo or other therapies for MCI were included.ResultsForty-nine RCTs (48 finished trials and 1 protocol) were identified. The overall methodological quality of included trials was relatively low. This review found that compared to no intervention or placebo, CHM can significantly decrease the number of patients who progressed to dementia (RR 0.36, 95% CI 0.22–0.58) and increase the cognitive function assessed by MMSE (MD 1.96, 95% CI 1.41–2.50) and MoCA (MD 2.44, 95% CI 1.57–3.31). The subgroup analysis of different CHM showed that Ginko leaf tablets can significantly improve the cognitive function compared to no intervention or placebo when assessed by MMSE (MD 2.03, 95% CI 1.18–2.88) and MoCA (MD 3.11, 95% CI 1.90–4.33). Compared to western medicine, CHM can significantly increase the score of MMSE (MD 0.88 95% CI 0.46–1.30) and MoCA (MD 0.87, 95% CI 0.33–1.41), but there was no significant difference on the score of ADL (SMD −0.61, 95% CI −1.49 to 0.27). None of the RCTs reported on the quality of life. Of 22 RCTs that reported adverse events, there was no statistical difference between the CHM and the control group.ConclusionsCHM, Ginko leaf extracts in particular, could help to prevent progression into dementia and to improve cognitive function and ability of daily living activities. More qualified RCTs were needed to confirm the conclusion due to the low quality of current trials.Systematic Review RegistrationUnique Identifier: CRD42020157148.
ObjectivesTo assess the beneficial and harmful effects of adding ivabradine to usual care in participants with heart failure.DesignA systematic review with meta-analysis and trial sequential analysis.Eligibility criteriaRandomised clinical trials comparing ivabradine and usual care with usual care (with or without) placebo in participants with heart failure.Information sourcesMedline, Embase, CENTRAL, LILACS, CNKI, VIP and other databases and trial registries up until 31 May 2021.Data extractionPrimary outcomes were all-cause mortality, serious adverse events and quality of life. Secondary outcomes were cardiovascular mortality, myocardial infarction and non-serious adverse events. We performed meta-analysis of all outcomes. We used trial sequential analysis to control risks of random errors, the Cochrane risk of bias tool to assess the risks of systematic errors and the Grading of Recommendations Assessment, Development and Evaluation (GRADE) to assess the certainty of the evidence.ResultsWe included 109 randomised clinical trials with 26 567 participants. Two trials were at low risk of bias, although both trials were sponsored by the company that developed ivabradine. All other trials were at high risk of bias. Meta-analyses and trial sequential analyses showed that we could reject that ivabradine versus control reduced all-cause mortality (risk ratio (RR)=0.94; 95% CI 0.88 to 1.01; p=0.09; high certainty of evidence). Meta-analysis and trial sequential analysis showed that ivabradine seemed to reduce the risk of serious adverse events (RR=0.90; 95% CI 0.87 to 0.94; p<0.00001; number needed to treat (NNT)=26.2; low certainty of evidence). This was primarily due to a decrease in the risk of ‘cardiac failure’ (RR=0.83; 95% CI 0.71 to 0.97; p=0.02; NNT=43.9), ‘hospitalisations’ (RR=0.89; 95% CI 0.85 to 0.94; p<0.0001; NNT=36.4) and ‘ventricular tachycardia’ (RR=0.59; 95% CI 0.43 to 0.82; p=0.001; NNT=212.8). However, the trials did not describe how these outcomes were defined and assessed during follow-up. Meta-analyses showed that ivabradine increased the risk of atrial fibrillation (RR=1.19; 95% CI 1.04 to 1.35; p=0.008; number needed to harm (NNH)=116.3) and bradycardia (RR=3.95; 95% CI 1.88 to 8.29; p=0.0003; NNH=303). Ivabradine seemed to increase quality of life on the Kansas City Cardiomyopathy Questionnaire (KCCQ) (mean difference (MD)=2.92; 95% CI 1.34 to 4.50; p=0.0003; low certainty of evidence), but the effect size was small and possibly without relevance to patients, and on the Minnesota Living With Heart Failure Questionnaire (MLWHFQ) (MD=−5.28; 95% CI −6.60 to −3.96; p<0.00001; very low certainty of evidence), but the effects were uncertain. Meta-analysis showed no evidence of a difference between ivabradine and control when assessing cardiovascular mortality and myocardial infarction. Ivabradine seemed to increase the risk of non-serious adverse events.Conclusion and relevanceHigh certainty evidence shows that ivabradine does not seem to affect the risks of all-cause mortality and cardiovascular mortality. The effects on quality of life were small and possibly without relevance to patients on the KCCQ and were very uncertain for the MLWHFQ. The effects on serious adverse events, myocardial infarction and hospitalisation are uncertain. Ivabradine seems to increase the risk of atrial fibrillation, bradycardia and non-serious adverse events.PROSPERO registration number: CRD42018112082.
ObjectiveTo determine the impact of ivabradine on outcomes important to patients with angina pectoris caused by coronary artery disease.MethodsWe conducted a systematic review. We included randomised clinical trials comparing ivabradine versus placebo or no intervention for patients with angina pectoris due to coronary artery disease published prior to June 2020. We used Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, Cochrane methodology, Trial Sequential Analysis, Grading of Recommendations Assessment, Development, and Evaluation, and our eight-step procedure. Primary outcomes were all-cause mortality, serious adverse events and quality of life.ResultsWe included 47 randomised clinical trials enrolling 35 797 participants. All trials and outcomes were at high risk of bias. Ivabradine compared with control did not have effects when assessing all-cause mortality (risk ratio [RR] 1.04; 95% CI 0.96 to 1.13), quality of life (standardised mean differences −0.05; 95% CI −0.11 to 0.01), cardiovascular mortality (RR 1.07; 95% CI 0.97 to 1.18) and myocardial infarction (RR 1.03; 95% CI 0.91 to 1.16). Ivabradine seemed to increase the risk of serious adverse events after removal of outliers (RR 1.07; 95% CI 1.03 to 1.11) as well as the following adverse events classified as serious: bradycardia, prolonged QT interval, photopsia, atrial fibrillation and hypertension. Ivabradine also increased the risk of non-serious adverse events (RR 1.13; 95% CI 1.11 to 1.16). Ivabradine might have a statistically significant effect when assessing angina frequency (mean difference (MD) 2.06; 95% CI 0.82 to 3.30) and stability (MD 1.48; 95% CI 0.07 to 2.89), but the effect sizes seemed minimal and possibly without any relevance to patients, and we identified several methodological limitations, questioning the validity of these results.ConclusionOur findings do not support that ivabradine offers significant benefits on patient important outcomes, but rather seems to increase the risk of serious adverse events such as atrial fibrillation and non-serious adverse events. Based on current evidence, guidelines need reassessment and the use of ivabradine for angina pectoris should be reconsidered.PROSPERO registration numberCRD42018112082.
Accumulated studies have determined the changes in functional connectivity in autism spectrum disorder (ASD) and spurred the application of machine learning for classifying ASD. Graph Neural Network provides a new method for network analysis in brain disorders to identify the underlying network features associated with functional deficits. Here, we proposed an improved model of Graph Isomorphism Network (GIN) that implements the Weisfeiler-Lehman (WL) graph isomorphism test to learn the graph features while taking into account the importance of each node in the classification to improve the interpretability of the algorithm. We applied the proposed method on multisite datasets of resting-state functional connectome from Autism Brain Imaging Data Exchange (ABIDE) after stringent quality control. The proposed method outperformed other commonly used classification methods on five different evaluation metrics. We also identified salient ROIs in visual and frontoparietal control networks, which could provide potential neuroimaging biomarkers for ASD identification.
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