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阿尔茨海默病进展的预测因素:对3553例患者进行211个月随访的综合回顾性分析

Predictive factors for Alzheimer's disease progression: a comprehensive retrospective analysis of 3,553 cases with 211 months follow-up.

作者信息

Özge Aynur, Ghouri Reza, Öksüz Nevra, Taşdelen Bahar

机构信息

Department of Neurology, School of Medicine, Mersin University, Mersin, Türkiye.

Department of Biostatistics, School of Medicine, Mersin University, Mersin, Türkiye.

出版信息

Front Neurol. 2023 Aug 24;14:1239995. doi: 10.3389/fneur.2023.1239995. eCollection 2023.

Abstract

BACKGROUND

There is conflicting data regarding the predictors of Alzheimer's Disease (AD), the most common form of dementia. The main objective of the study is to evaluate potential predictors of AD progression using a comprehensive follow-up dataset that includes functional/cognitive assessments, clinical and neuropsychiatric evaluations, and neuroimaging biomarkers such as hippocampal atrophy or white matter intensities (WMIs).

METHOD

A total of 161 AD cases were recruited from a dementia database consisting of individuals who consulted the Dementia Outpatient Clinic of the Neurology Department at Mersin University Medical Faculty between 2000 and 2022, under the supervision of the same senior author have at least 3 full evaluation follow-up visit including functional, clinical, biochemical, neuropsychological, and radiological screening. Data were exported and analyzed by experts accordingly.

RESULTS

Mean follow-up duration of study sample was 71.66 ± 41.98, min 15 to max 211 months. The results showed a fast and slow progressive subgroup of our AD cases with a high sensitivity (Entropy = 0.836), with a close relationship with several cofactors and the level of disability upon admittance. Hippocampal atrophy and WMIs grading via Fazekas were found to be underestimated predictors of AD progression, and functional capacity upon admittance was also among the main stakeholders.

CONCLUSION

The study highlights the importance of evaluating multiple potential predictors for AD progression, including functional capacity upon admittance, hippocampal atrophy, and WMIs grading via Fazekas. Our findings provide insight into the complexity of AD progression and may contribute to the development of effective strategies for managing and treating AD.

摘要

背景

关于阿尔茨海默病(AD)这一最常见的痴呆形式的预测因素,存在相互矛盾的数据。本研究的主要目的是使用一个全面的随访数据集来评估AD进展的潜在预测因素,该数据集包括功能/认知评估、临床和神经精神评估,以及海马萎缩或白质强度(WMI)等神经影像学生物标志物。

方法

从一个痴呆数据库中招募了总共161例AD病例,该数据库由2000年至2022年间在梅尔辛大学医学院神经科痴呆门诊就诊的个体组成,在同一位资深作者的监督下,这些个体至少进行了3次全面评估随访,包括功能、临床、生化、神经心理和放射学筛查。数据由专家导出并相应分析。

结果

研究样本的平均随访时长为71.66±41.98个月,最短15个月,最长211个月。结果显示,我们的AD病例存在快速进展和缓慢进展亚组,敏感性较高(熵=0.836),与几个辅助因素以及入院时的残疾程度密切相关。发现海马萎缩和通过法泽卡斯分级的WMI是AD进展的被低估的预测因素,入院时的功能能力也是主要相关因素之一。

结论

该研究强调了评估AD进展的多个潜在预测因素的重要性,包括入院时的功能能力、海马萎缩和通过法泽卡斯分级的WMI。我们的研究结果深入了解了AD进展的复杂性,并可能有助于制定管理和治疗AD的有效策略。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c04b/10484751/c140cf2cec1d/fneur-14-1239995-g001.jpg

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