轻度认知功能障碍患者预后情况的评估预测模型

李佳承; 黄嘉诚; 周澜; 罗万春

doi:10.16016/j.1000-5404.201609173

您当前的位置：

首页 >

文章列表页 >

轻度认知功能障碍患者预后情况的评估预测模型

临床医学 | 更新时间：2026-01-09

- 轻度认知功能障碍患者预后情况的评估预测模型
- Predictive modeling for prognosis in mild cognitive impairment
- 第三军医大学学报 2017年39卷第3期页码：281-285
- 作者机构：
- 作者简介：
- 基金信息：
  
  重庆市自然科学基金(CSTC2013jcyjA10041)
- DOI：10.16016/j.1000-5404.201609173
  中图分类号：
- 收稿：2016-09-27，
  
  纸质出版：2017-01-15
- 稿件说明：
移动端阅览
李佳承, 黄嘉诚, 周澜, 等. 轻度认知功能障碍患者预后情况的评估预测模型[J]. 第三军医大学学报, 2017,39(3):281-285.

Jiacheng Li, Jiacheng Huang, Lan Zhou, et al. Predictive modeling for prognosis in mild cognitive impairment[J]. Journal of Third Military Medical University, 2017, 39(3): 281-285.
李佳承, 黄嘉诚, 周澜, 等. 轻度认知功能障碍患者预后情况的评估预测模型[J]. 第三军医大学学报, 2017,39(3):281-285. DOI： 10.16016/j.1000-5404.201609173.

Jiacheng Li, Jiacheng Huang, Lan Zhou, et al. Predictive modeling for prognosis in mild cognitive impairment[J]. Journal of Third Military Medical University, 2017, 39(3): 281-285. DOI： 10.16016/j.1000-5404.201609173.

摘要

Abstract

Objective

To establish a predictive model for estimating 24-month prognosis in the patients of mild cognitive impairment based on mathematics.

Methods

Twenty-seven clinical indicators of 152 cases patients with confirmed mild cognitive impairment from the Alzheimer's Disease Neuroimaging Initiative (ADNI

<a href="https://ida.loni.ucla.edu/login.jsp">https://ida.loni.ucla.edu/login.jsp</a>) were collected and analyzed. Bayes discriminant analysis

Decision tree

BP neural network

fuzzy C-means clustering and K-means clustering were used to evaluate the prediction

and the model with higher accuracy was selected.

Results

According to

0.01

6 indicators were selected to establish a diagnostic model by significance test. There were 5 predictive models of estimation established. After 100 times of random sampling for diagnosis simulation in the patients

Bayes discriminant analysis indicated that the average diagnosis accuracy was 74.86%

and the highest accuracy was 84.21%.

Conclusion

Our established model is of high predictive accuracy for 24-month prognosis in mild cognitive impairment.

关键词

Keywords

references

Petersen R C Smith G E Waring S C Mild cognitive impairment: clinical characterization and outcome Arch Neurol 1999 56 3 303 308 10.1001/archneur.56.3.303 Petersen R C, Smith G E, Waring S C, et al. Mild cognitive impairment: clinical characterization and outcome[J]. Arch Neurol, 1999, 56(3): 303-308. DOI:10.1001/archneur.56.3.303

Panza F Capurso C D'Introno A Mild cognitive impairment: risk of Alzheimer disease and rate of cognitive decline Neurology 2007 68 12 964 965 10.1212/01.wnl.0000259691.26674.d3 Panza F, Capurso C, D'Introno A, et al. Mild cognitive impairment: risk of Alzheimer disease and rate of cognitive decline[J]. Neurology, 2007, 68(12): 964-965.DOI: 10.1212/01.wnl.0000259691.26674.d3

Cheng G Huang C Deng H Diabetes as a risk factor for dementia and mild cognitive impairment: a meta-analysis of longitudinal studies Intern Med J 2012 42 5 484 491 10.1111/j.1445-5994.2012.02758.x Cheng G, Huang C, Deng H, et al. Diabetes as a risk factor for dementia and mild cognitive impairment: a meta-analysis of longitudinal studies[J]. Intern Med J, 2012, 42(5): 484-491. DOI:10.1111/j.1445-5994.2012.02758.x

Grundman M Petersen R C Ferris S H Mild cognitive impairment can be distinguished from Alzheimer disease and normal aging for clinical trials Arch Neurol 2004 61 1 59 66 10.1001/archneur.61.1.59 Grundman M, Petersen R C, Ferris S H, et al. Mild cognitive impairment can be distinguished from Alzheimer disease and normal aging for clinical trials[J]. Arch Neurol, 2004, 61(1): 59-66. DOI:10.1001/archneur.61.1.59

Ward A Tardiff S Dye C Rate of Conversion from Prodromal Alzheimer's Disease to Alzheimer's Dementia: A Systematic Review of the Literature Dement Geriatr Cogn Dis Extra 2013 3 1 320 332 10.1159/000354370 Ward A, Tardiff S, Dye C, et al. Rate of Conversion from Prodromal Alzheimer's Disease to Alzheimer's Dementia: A Systematic Review of the Literature[J]. Dement Geriatr Cogn Dis Extra, 2013, 3(1): 320-332. DOI:10.1159/000354370

Busse A Hensel A Gühne U Mild cognitive impairment: long-term course of four clinical subtypes Neurology 2006 67 12 2176 2185 10.1212/01.wnl.0000249117.23318.e1 Busse A, Hensel A, Gühne U, et al. Mild cognitive impairment: long-term course of four clinical subtypes[J]. Neurology, 2006, 67(12): 2176-2185. DOI:10.1212/01.wnl.0000249117.23318.e1

Manly J J Tang M X Schupf N Frequency and course of mild cognitive impairment in a multiethnic community Ann Neurol 2008 63 4 494 506 10.1002/ana.21326 Manly J J, Tang M X, Schupf N, et al. Frequency and course of mild cognitive impairment in a multiethnic community[J]. Ann Neurol, 2008, 63(4): 494-506. DOI:10.1002/ana.21326

Ganguli M Snitz B E Saxton J A Outcomes of mild cognitive impairment by definition: a population study Arch Neurol 2011 68 6 761 767 10.1001/archneurol.2011.101 Ganguli M, Snitz B E, Saxton J A, et al. Outcomes of mild cognitive impairment by definition: a population study[J]. Arch Neurol, 2011, 68(6): 761-767. DOI:10.1001/archneurol.2011.101

Graña M Termenon M Savio A Computer aided diagnosis system for Alzheimer disease using brain diffusion tensor imaging features selected by Pearson's correlation Neurosci Lett 2011 502 3 225 229 10.1016/j.neulet.2011.07.049 Graña M, Termenon M, Savio A, et al. Computer aided diagnosis system for Alzheimer disease using brain diffusion tensor imaging features selected by Pearson's correlation[J]. Neurosci Lett, 2011, 502(3): 225-229. DOI:10.1016/j.neulet.2011.07.049

McEvoy L K Holland D Hagler D J Jr Mild cognitive impairment: baseline and longitudinal structural MR imaging measures improve predictive prognosis Radiology 2011 259 3 834 843 10.1148/radiol.11101975 McEvoy L K, Holland D, Hagler D J Jr, et al. Mild cognitive impairment: baseline and longitudinal structural MR imaging measures improve predictive prognosis[J]. Radiology, 2011, 259(3): 834-843. DOI:10.1148/radiol.11101975

罗万春阿尔茨海默病和轻度认知损伤诊断的建模分析第三军医大学学报 2013 35 15 1613 1615 http://aammt.tmmu.edu.cn/oa/DArticle.aspx?type=view&id=201304134 罗万春.阿尔茨海默病和轻度认知损伤诊断的建模分析[J].第三军医大学学报, 2013, 35(15): 1613-1615.DOI:10.16016/j.1000-5404.2013.15.027

马翠周先东罗万春阿尔茨海默病和轻度认知损伤诊断的逐步Fisher判别模型第三军医大学学报 2016 38 13 1501 1505 10.16016/j.1000-5404.201509138 马翠, 周先东, 罗万春.阿尔茨海默病和轻度认知损伤诊断的逐步Fisher判别模型[J].第三军医大学学报, 2016, 38(13): 1501-1505. DOI:10.16016/j.1000-5404.201509138

浏览量

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

住院高血压患者伴发轻度认知功能障碍的风险预测模型构建