排程困擾？一種用於輕度認知障礙與輕度阿茲海默症微妙認知衰退的可靠檢測工具

// Lost in Scheduling? A Reliable Tool for Detecting Subtle Cognitive Decline in Mild Cognitive Impairment and Mild Alzheimer's Disease

本研究評估「日常數學生態評估量表（EABN）」在輕度認知障礙（MCI）及輕度阿茲海默症（AD）中偵測細微認知退化的效能｜共66名參與者，EABN 整體準確率高（AUC=0.83），其中「預約子測驗」辨識力最佳｜數學認知能力早期受損且無明顯主訴，異常EABN分數能預測70% MCI患者病程惡化｜結果支持EABN用於早期診斷及介入，助於維持患者自主功能。

// This study evaluates the Ecological Assessment Battery for Numbers (EABN) to detect subtle cognitive decline in mild cognitive impairment (MCI) and mild Alzheimer's disease (AD) through everyday math tasks. Using a cross-sectional design with 66 participants, EABN showed strong accuracy (AUC=0.83) in distinguishing patients from controls, with the Appointment subtest being most discriminative. Mathematical cognition impairments appear early, even without patient complaints, and pathological EABN scores predicted progression in 70% of MCI cases. The findings support using EABN for early diagnosis and intervention in neurodegenerative diseases to help preserve patient autonomy.

Published 2026年7月14日