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阿尔茨海默病亚型的证据及其对病因学的意义。

Evidence of subtypes of Alzheimer's disease and implications for etiology.

作者信息

Bondareff W, Mountjoy C Q, Wischik C M, Hauser D L, LaBree L D, Roth M

机构信息

Department of Psychiatry and Behavioral Sciences, University of Southern California School of Medicine, Los Angeles.

出版信息

Arch Gen Psychiatry. 1993 May;50(5):350-6. doi: 10.1001/archpsyc.1993.01820170028004.

Abstract

OBJECTIVE

Because age of onset does not reliably define two subtypes of Alzheimer's disease, classification based on the severity of neuronal degeneration was tested.

DESIGN

Numbers of extracellular tangles and pyramidal neurons in the hippocampus were used to group patients.

PATIENTS

The study population consisted of 46 elderly patients satisfying DSM-III criteria for dementia and NINCDS-ADRDA criteria for definite Alzheimer's disease after death.

RESULTS

Univariate logistic regression analysis showed the numbers of neurofibrillary tangles and pyramidal neurons and the duration of dementia were significantly associated with grouping based on the presence of abundant extracellular tangles. Ninety-one percent of patients were correctly classified as compared with 85% correctly classified by age of onset data. Odds ratios showed that increasing numbers of neurofibrillary tangles predicted greater severity of neuronal loss.

CONCLUSION

The results of the study indicate the importance of neurofibrillary degeneration, not the deposition of amyloid, in the pathogenesis of Alzheimer's disease. They support a classification of Alzheimer's disease related more closely to the severity of neurofibrillary degeneration than to age at onset.

摘要

目的

由于发病年龄不能可靠地界定阿尔茨海默病的两种亚型,因此对基于神经元变性严重程度的分类方法进行了测试。

设计

利用海马体中细胞外缠结和锥体神经元的数量对患者进行分组。

患者

研究群体由46名老年患者组成,这些患者生前符合痴呆症的DSM-III标准以及死后确诊阿尔茨海默病的NINCDS-ADRDA标准。

结果

单因素逻辑回归分析显示,神经原纤维缠结和锥体神经元的数量以及痴呆持续时间与基于大量细胞外缠结的分组显著相关。91%的患者被正确分类,相比之下,根据发病年龄数据进行分类的正确率为85%。优势比表明,神经原纤维缠结数量的增加预示着神经元损失的严重程度更高。

结论

研究结果表明,在阿尔茨海默病的发病机制中,神经原纤维变性而非淀粉样蛋白沉积具有重要意义。这些结果支持一种与神经原纤维变性严重程度而非发病年龄更紧密相关的阿尔茨海默病分类方法。

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