Markers for the Risk of Progression from Mild Cognitive Impairment to Alzheimer's Disease
Markers for the Risk of Progression from Mild Cognitive Impairment to Alzheimer's Disease
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DOI：
10.3233/jad-143135
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发表时间：
2015-01-01
影响因子：
4
通讯作者：
Silvestrini, Mauro
中科院分区：
文献类型：
--
作者：
Buratti, Laura;Balestrini, Simona;Silvestrini, Mauro
背景资料：定义可靠的标志物转换为痴呆可能是第一步，以确定适当的治疗策略为轻度认知功能障碍（MCI）patients.Objective：开发一种工具，能够预测从MCI进展到阿尔茨海默病（AD）的风险。方法：对406例MCI患者进行为期一年的随访。人口统计学特征，血管危险因素，脑血管病变的程度，颈动脉粥样硬化的标志物与超声评估（斑块指数和内膜中层厚度）和脑血管反应性呼吸暂停（屏气指数）被认为是潜在的预测因素的conversion.Results：106（26%）MCI患者显示转换为AD。斑块指数、内膜中层厚度和屏气指数是转换的相关预测因素（p = 0.042; p = 0.003; p < 0.001，多变量logistic回归分析）。根据估计的多项逻辑回归β系数结果的大小设计了一个简化的评分系统。总分计算为每个预测因素的总和，范围为0-5。最佳截止评分为≥ 3（敏感性，23.6%，95% CI 15.9%-32.8%;特异性，97.7%，95% CI 95.3%-99.1%;阳性似然比，10.1，95% CI 4.5%-22.7%;阴性似然比，0.78，95% CI 0.70%-0.87%）。AUC为0.71（95%CI，0.65-0.77）。结论：我们的研究结果表明，通过考虑颈动脉区动脉粥样硬化变化和脑血流动力学受损的存在，可以获得从MCI转换为痴呆的风险的预测指标。这种方法可以使我们制定一个正确的预后在70%以上的健忘性MCI患者。
Background: Defining reliable markers of conversion to dementia could be the first step in order to identify appropriate treatment strategies for mild cognitive impairment (MCI) patients.Objective: To develop a tool able to predict the risk of progression from MCI to Alzheimer's disease (AD). Methods: 406 MCI patients were included and followed for a one-year period. Demographic characteristics, vascular risk factors, extent of cerebrovascular lesions, markers of carotid atherosclerosis investigated with an ultrasonographic assessment (plaque index and intima-media thickness) and cerebrovascular reactivity to apnea (breath-holding index) were considered as potential predictors of conversion.Results: 106 (26%) MCI patients showed a conversion to AD. Plaque index, intima-media thickness, and breath-holding index were relevant predictors of conversion (p = 0.042; p = 0.003; p < 0.001, multivariate logistic regression analysis). A simplified scoring system was devised based on the magnitude of the estimated multinomial logistic regression beta coefficient results. A total score was calculated as the sum of each predictive factor which resulted in a 0-5 range. The optimal cut-off score was >= 3 (sensitivity, 23.6%, 95% CI 15.9%-32.8%; specificity, 97.7%, 95% CI 95.3%-99.1%; positive likelihood ratio, 10.1, 95% CI 4.5%-22.7%; negative likelihood ratio, 0.78, 95% CI 0.70%-0.87%). The AUC was 0.71 (95% CI, 0.65-0.77).Conclusions: Our findings show the possibility to obtain a predictive indicator of the risk of conversion from MCI to dementia by considering the presence of both atherosclerotic changes in the carotid district and impairment of cerebral hemodynamics. Such an approach may allow us to formulate a correct prognosis in more than 70% of patients with amnesic MCI.