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Lithium therapy's potential to lower dementia risk and the prevalence of Alzheimer's disease: a meta-analysis. 锂疗法降低痴呆症风险和阿尔茨海默病发病率的潜力：一项荟萃分析。

European Neurology Pub Date : 2024-04-24 DOI: 10.1159/000538846

Qiuying Lu, Huijing Lv, Xiaotong Liu, Lili Zang, Yue Zhang, Qinghui Meng

{"title":"Lithium therapy's potential to lower dementia risk and the prevalence of Alzheimer's disease: a meta-analysis.","authors":"Qiuying Lu, Huijing Lv, Xiaotong Liu, Lili Zang, Yue Zhang, Qinghui Meng","doi":"10.1159/000538846","DOIUrl":"https://doi.org/10.1159/000538846","url":null,"abstract":"INTRODUCTION\u0000Dementia is a neurodegenerative disease with insidious onset and progressive progression, of which the most common type is Alzheimer's disease (AD). Lithium, a trace element in the body, has neuroprotective properties. However, whether lithium can treat dementia or AD remains a highly controversial topic. Therefore we conducted a meta-analysis.\u0000\u0000\u0000METHODS\u0000A systematic literature review was conducted in PubMed, Embase, and Web of Science. Comparison of the effects of lithium on Alzheimer's disease or dementia in terms of use, duration, and dosage, and meta-analysis to test whether lithium therapy is beneficial in ameliorating the onset of dementia or Alzheimer's disease. Sensitivity analyses were performed using a stepwise exclusion method. The Newcastle-Ottawa Scale (NOS) was used to assess the quality of included studies. We determined the relative risk (RR) between patient groups using a random effects model.\u0000\u0000\u0000RESULTS\u0000A total of seven studies were included. The forest plot results showed that taking lithium therapy reduced the risk of Alzheimer's disease (RR 0.59, 95% CI: 0.44-0.78), and is also protective in reducing the risk of dementia (RR 0.66, 95% CI: 0.56-0.77). The duration of lithium therapy was able to affect the dementia incidence (RR 0.70, 95% CI: 0.55-0.88); however, it is unclear how this effect might manifest in AD. It's also uncertain how many prescriptions for lithium treatment lower the chance of dementia development.\u0000\u0000\u0000CONCLUSION\u0000The duration of treatment and the usage of lithium therapy seem to lower the risk of AD and postpone the onset of dementia.","PeriodicalId":505778,"journal":{"name":"European Neurology","volume":"37 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140663200","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Longitudinal feasibility of the Montreal Cognitive Assessment (MoCA) in non-demented ALS patients. 蒙特利尔认知评估 (MoCA) 在非痴呆 ALS 患者中的纵向可行性。

European Neurology Pub Date : 2024-04-20 DOI: 10.1159/000538828

E. Aiello, F. Solca, Silvia Torre, Eleonora Colombo, Alessio Maranzano, Alberto De Lorenzo, Valerio Patisso, Mauro Treddenti, Beatrice Curti, C. Morelli, A. Doretti, F. Verde, R. Ferrucci, Sergio Barbieri, F. Ruggiero, Alberto Priori, V. Silani, N. Ticozzi, B. Poletti

{"title":"Longitudinal feasibility of the Montreal Cognitive Assessment (MoCA) in non-demented ALS patients.","authors":"E. Aiello, F. Solca, Silvia Torre, Eleonora Colombo, Alessio Maranzano, Alberto De Lorenzo, Valerio Patisso, Mauro Treddenti, Beatrice Curti, C. Morelli, A. Doretti, F. Verde, R. Ferrucci, Sergio Barbieri, F. Ruggiero, Alberto Priori, V. Silani, N. Ticozzi, B. Poletti","doi":"10.1159/000538828","DOIUrl":"https://doi.org/10.1159/000538828","url":null,"abstract":"INTRODUCTION\u0000The present study aimed at testing the longitudinal feasibility of the Montreal Cognitive Assessment (MoCA) in an Italian cohort of non-demented amyotrophic lateral sclerosis (ALS) patients.\u0000\u0000\u0000METHODS\u0000N=39 non-demented ALS patients were followed-up at a 5-to-10-month interval (M=6.8; SD=1.4) with the MoCA and the Edinburgh Cognitive and Behavioral ALS Screen (ECAS). Practice effects, test-retest reliability and predictive validity (against follow-up ECAS scores) were assessed. Reliable change indices (RCIs) were derived via a regression-based approach by accounting for retest interval and baseline confounders (i.e., demographics, disease duration and severity and progression rate).\u0000\u0000\u0000RESULTS\u0000At retest, 100% and 69.2% of patients completed the ECAS and the MoCA, respectively. Patients who could not complete the MoCA showed a slightly more severe and fast-progressing disease. The MoCA was not subject to practice effects (t(32)=-.80; p=.429) and was reliable at retest (ICC=.82). Moreover, baseline MoCA scores predicted the ECAS at retest. RCIs were successfully derived - with baseline MoCA scores being the only significant predictor of retest performances (ps<.001).\u0000\u0000\u0000CONCLUSIONS\u0000As long as motor disabilities do not undermine its applicability, the MoCA appears to be longitudinally feasible at a 5-to-10-month interval in non-demented ALS patients. However, ALS-specific screeners - such as the ECAS - should be preferred whenever possible.","PeriodicalId":505778,"journal":{"name":"European Neurology","volume":"102 13","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140680010","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An Explainable Artificial Intelligence Model to Predict Malignant Cerebral Edema after Acute Anterior Circulating Large Hemisphere Infarction. 预测急性前循环大脑梗塞后恶性脑水肿的可解释人工智能模型

European Neurology Pub Date : 2024-04-02 DOI: 10.1159/000538424

Liping Cao, Xiaoming Ma, Wendie Huang, Geman Xu, Yumei Wang, Meng Liu, Shiying Sheng, Keshi Mao

{"title":"An Explainable Artificial Intelligence Model to Predict Malignant Cerebral Edema after Acute Anterior Circulating Large Hemisphere Infarction.","authors":"Liping Cao, Xiaoming Ma, Wendie Huang, Geman Xu, Yumei Wang, Meng Liu, Shiying Sheng, Keshi Mao","doi":"10.1159/000538424","DOIUrl":"https://doi.org/10.1159/000538424","url":null,"abstract":"INTRODUCTION\u0000Malignant cerebral edema (MCE) is a serious complication and the main cause of poor prognosis in patients with large-hemisphere infarction (LHI). Therefore, the rapid and accurate identification of potential patients with MCE is essential for timely therapy. This study utilized an artificial intelligence-based machine learning approach to establish an interpretable model for predicting MCE in patients with LHI.\u0000\u0000\u0000METHODS\u0000This study included 314 patients with LHI not undergoing recanalization therapy. The patients were divided into MCE and non-MCE groups, the extreme Gradient boosting (XGBoost) model was developed. A confusion matrix was used to measure the prediction performance of the XGBoost model. We also utilized the SHapley Additive extension (SHAP) method to explain the XGBoost model. Decision curve analysis and receiver operating characteristic (ROC) curve were performed to evaluate the net benefits of the model.\u0000\u0000\u0000RESULTS\u0000MCE was observed in 121(38.5%) of the 314 patients with LHI. The model showed excellent predictive performance, with an area under the curve of 0.916. The SHAP method revealed the top 10 predictive variables of the MCE such as ASPECTS score, NIHSS score, CS score, APACHE II score, HbA1c, AF, NLR, PLT, GCS and Age based on their importance ranking.\u0000\u0000\u0000CONCLUSION\u0000An interpretable predictive model can increase transparency and help doctors accurately predict the occurrence of MCE in LHI patients, not undergoing recanalization therapy within 48h from onset, providing patients with better treatment strategies and enabling optimal resource allocation.","PeriodicalId":505778,"journal":{"name":"European Neurology","volume":"101 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140754269","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0