Clinical Manifestations.

Area of Science:

• Neurology
• Gerontology
• Cognitive Science

Background:

• Mild cognitive impairment (MCI) is an early indicator of Alzheimer's Disease (AD), impacting memory and cognition.
• Timely MCI detection is vital for the efficacy of newly approved disease-modifying treatments.
• Current screening tools like MoCA and MMSE are time-consuming, and their individual item accuracy for MCI detection is not well-established.

Purpose of the Study:

• To conduct an item-level analysis of the MoCA and MMSE to determine their accuracy in detecting MCI.
• To identify the specific test components that contribute most significantly to MCI detection.
• To explore opportunities for optimizing MCI screening tests for improved efficiency and effectiveness.

Main Methods:

• Utilized the National Alzheimer's Coordinating Center (NACC) data repository for analysis.
• Performed item-level analysis on MoCA and MMSE data from MCI and cognitively normal participants.
• Employed Area Under the Receiver Operating Characteristic Curves (AUC-ROC) to assess test and item accuracy.

Main Results:

• Overall MoCA AUC-ROC was 0.81 and MMSE AUC-ROC was 0.76, indicating moderate accuracy for both tests.
• Item-level analysis revealed that only a subset of test components are effective in MCI detection.
• A six-item combination focusing on memory recall and orientation accounted for over 98% of the full tests' accuracy.

Conclusions:

• The MoCA and MMSE demonstrate moderate efficacy in MCI detection, with specific items being the primary drivers of accuracy.
• Significant reduction in the number of test items is feasible without compromising MCI detection effectiveness, leading to reduced administration time.
• Further research is warranted to identify optimal item combinations for maximizing MCI detection accuracy and minimizing testing duration.