Mayo Normative Studies: Amyloid and Neurodegeneration Negative Normative Data for the Auditory Verbal Learning Test and Sex-Specific Sensitivity to Mild Cognitive Impairment/Dementia.

Journal of Alzheimer's disease : JAD(2024)

引用 0|浏览0
暂无评分
摘要
Background:Conventional normative samples include individuals with undetected Alzheimer's disease neuropathology, lowering test sensitivity for cognitive impairment. Objective:We developed Mayo Normative Studies (MNS) norms limited to individuals without elevated amyloid or neurodegeneration (A-N-) for Rey's Auditory Verbal Learning Test (AVLT). We compared these MNS A-N- norms in female, male, and total samples to conventional MNS norms with varying levels of demographic adjustments. Methods:The A-N- sample included 1,059 Mayo Clinic Study of Aging cognitively unimpaired (CU) participants living in Olmsted County, MN, who are predominantly non-Hispanic White. Using a regression-based approach correcting for age, sex, and education, we derived fully-adjusted T-score formulas for AVLT variables. We validated these A-N- norms in two independent samples of CU (n = 261) and mild cognitive impairment (MCI)/dementia participants (n = 392) > 55 years of age. Results:Variability associated with age decreased by almost half in the A-N- norm sample relative to the conventional norm sample. Fully-adjusted MNS A-N- norms showed approximately 7- 9% higher sensitivity to MCI/dementia compared to fully-adjusted MNS conventional norms for trials 1- 5 total and sum of trials. Among women, sensitivity to MCI/dementia increased with each normative data refinement. In contrast, age-adjusted conventional MNS norms showed greatest sensitivity to MCI/dementia in men. Conclusions:A-N- norms show some benefits over conventional normative approaches to MCI/dementia sensitivity, especially for women. We recommend using these MNS A-N- norms alongside MNS conventional norms. Future work is needed to determine if normative samples that are not well characterized clinically show greater benefit from biomarker-refined approaches.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要