INTRODUCTION Dementia 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. METHODS A 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. RESULTS A 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. CONCLUSION The duration of treatment and the usage of lithium therapy seem to lower the risk of AD and postpone the onset of dementia.
简介：痴呆症是一种起病隐匿、进展缓慢的神经退行性疾病，其中最常见的类型是阿尔茨海默病（AD）。锂是人体内的一种微量元素，具有保护神经的作用。然而，锂是否能治疗痴呆症或阿尔茨海默病仍是一个极具争议的话题。因此，我们进行了一项荟萃分析。方法我们在 PubMed、Embase 和 Web of Science 上进行了系统的文献综述。比较了锂在使用、持续时间和剂量方面对阿尔茨海默病或痴呆症的影响，并进行了荟萃分析，以检验锂疗法是否有利于改善痴呆症或阿尔茨海默病的发病。采用逐步排除法进行了敏感性分析。采用纽卡斯尔-渥太华量表（NOS）评估纳入研究的质量。我们使用随机效应模型确定了患者组间的相对风险 (RR)。森林图结果显示，锂疗法可降低阿尔茨海默病的发病风险（RR 0.59，95% CI：0.44-0.78），同时对降低痴呆症的发病风险具有保护作用（RR 0.66，95% CI：0.56-0.77）。锂治疗的持续时间能够影响痴呆症的发病率（RR 0.70，95% CI：0.55-0.88）；但是，目前还不清楚这种影响在AD中会如何体现。结论 锂治疗的持续时间和使用情况似乎能降低 AD 的风险并推迟痴呆症的发生。
{"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}
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
INTRODUCTION The 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. METHODS N=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). RESULTS At 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). CONCLUSIONS As 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.
本研究旨在测试蒙特利尔认知评估（MoCA）在意大利非痴呆性肌萎缩性脊髓侧索硬化症（ALS）患者队列中的纵向可行性。方法对 39 名非痴呆性 ALS 患者（中=6.8；标度=1.4）进行了为期 5-10 个月的 MoCA 和爱丁堡认知与行为 ALS 筛选（ECAS）随访。对实践效果、重复测试可靠性和预测有效性（针对随访的 ECAS 分数）进行了评估。通过考虑重测间隔和基线混杂因素（即人口统计学、病程、严重程度和进展率），采用基于回归的方法得出可靠的变化指数（RCIs）。无法完成MoCA的患者病情稍重，进展较快。MoCA不受练习效应的影响（t(32)=-.80; p=.429），并且在重测时是可靠的（ICC=.82）。此外，基线 MoCA 分数还能预测重测时的 ECAS 分数。结论只要运动障碍不影响其适用性，MoCA 在非痴呆 ALS 患者中间隔 5 到 10 个月进行纵向测试似乎是可行的。不过，在可能的情况下，应首选 ALS 专用筛查工具（如 ECAS）。
{"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}
INTRODUCTION Malignant 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. METHODS This 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. RESULTS MCE 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. CONCLUSION An 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.
{"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}
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