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The MCI Screen's high accuracy is achieved by applying sophisticated mathematical scoring methods to the well-validated protocols of the CERAD 10-word recall test and the ADAS-Cog 10-word recall test.

The traditional scoring for the CERAD and ADAS-Cog 10-word recall tests uses a cut-off score based on the number of words recalled during the delayed recall task. However, considering the 1 trillion (240) patterns of recalling 10 words across four trials (3 immediate recall trials and 1 free delayed recall trial), the use of only the delayed recall total score ignores almost all of the available information.

To improve on the traditional approach, the MCI Screen draws upon the subject's complete recall pattern across all four recall trials, and uses computerized analysis to optimize the scoring method. It then compares the optimized score to the normal range for the patient's demographic peer group. In this way, physicians can identify those patients with "below-normal" cognitive function and can consider further clinical evaluation.

View a summary of peer-reviewed publications on the accuracy of the MCI Screen.