Background: Reaction time is affected under different neurological conditions but has not been much investigated considering all types of mild cognitive impairment (MCI). Objective: This study investigated the diagnostic accuracy of CompCog, a computerized cognitive screening battery focusing on reaction time measurements. Methods: A sample of 52 older adults underwent neuropsychological assessments, including CompCog, and medical appointments, to be classified as a control group or be diagnosed with MCI. The accuracy of CompCog for distinguishing between the two groups was calculated. Results: The results from diagnostic accuracy analyses showed that the AUCs of ROC curves were as high as 0.915 (CI 0.837-0.993). The subtest with the highest sensitivity and specificity (choice reaction time subtest) had 91.7% sensitivity and 89.3% specificity. The logistic regression final model correctly classified 92.3% of individuals, with 92.9% specificity and 91.7% sensitivity, and included only four variables from different subtests. Conclusions: In summary, the study showed that reaction time assessed through CompCog is a good screening measure to differentiate between normal aging and MCI. Reaction time measurements in milliseconds were more accurate than correct answers. This test can form part of routine clinical tests to achieve the objectives of screening for MCI, indicating further procedures for investigation and diagnosis and planning interventions.

Diagnostic accuracy of CompCog: reaction time as a screening measure for mild cognitive impairment

Balboni, Giulia;
2022

Abstract

Background: Reaction time is affected under different neurological conditions but has not been much investigated considering all types of mild cognitive impairment (MCI). Objective: This study investigated the diagnostic accuracy of CompCog, a computerized cognitive screening battery focusing on reaction time measurements. Methods: A sample of 52 older adults underwent neuropsychological assessments, including CompCog, and medical appointments, to be classified as a control group or be diagnosed with MCI. The accuracy of CompCog for distinguishing between the two groups was calculated. Results: The results from diagnostic accuracy analyses showed that the AUCs of ROC curves were as high as 0.915 (CI 0.837-0.993). The subtest with the highest sensitivity and specificity (choice reaction time subtest) had 91.7% sensitivity and 89.3% specificity. The logistic regression final model correctly classified 92.3% of individuals, with 92.9% specificity and 91.7% sensitivity, and included only four variables from different subtests. Conclusions: In summary, the study showed that reaction time assessed through CompCog is a good screening measure to differentiate between normal aging and MCI. Reaction time measurements in milliseconds were more accurate than correct answers. This test can form part of routine clinical tests to achieve the objectives of screening for MCI, indicating further procedures for investigation and diagnosis and planning interventions.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11391/1531253
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