Validation of the Montreal Cognitive Assessment in Patients With Mild and Major Neurocognitive Disorder

Due to the demographical development, age-related diseases will drastically increase over the next decades. To face this healthcare challenge, early and accurate identification of cognitive impairment is crucial. The early detection of cognitive decline requires a tool that is short, easy to administer and interpret, and has high diagnostic accuracy. Currently, a widely used instrument is the Mini-Mental State Examination (MMSE). However, the MMSE sensitivity is poor when identifying individuals with MCI, and it lacks meaningful assessment of executive functions. The Montreal Cognitive Assessment (MoCA) has been developed to address these weaknesses. It has demonstrated better diagnostic accuracy in patients with MCI, has less ceiling effect, and a higher test-retest-reliability. In addition, the MoCA better captures the cognitive domains proposed in the Diagnostic and Statistical Manual of Mental Disorders (DSM-5).

In 2018, the investigators generated demographically adjusted normative values for the German version of the MoCA in cognitively healthy individuals. However, these normative data alone are not suitable to determine the exact diagnostic accuracy. Therefore, the investigators aim to analyze data from patients with cognitive disorders to validate the German version of the MoCA.

Validation studies for the MoCA have been performed in various languages and different etiologies, mainly in patients with MCI and AD. However, when applying the MoCA in a clinical routine setting, the patient population is more heterogeneous and different etiologies may lead to deficits in characteristic cognitive domains. Therefore, patients with diseases other than AD may perform differently on items of the MoCA. This might translate into differences regarding the optimal cut-off score to detect possible cognitive impairment. Thus, when solely relying on a cut-off score that has been validated in a population of AD patients, patients with other diseases leading to cognitive impairment may be missed.

The investigators therefore aim to establish the diagnostic accuracy of the MoCA when applied in a clinically diverse patient sample, namely, a sample that is seen in a typical Memory Clinic. In a first step, the diagnostic properties of the MoCA will be investigated by differentiating between healthy controls and all patients with mild and major neurocognitive disorders (NCD). In a second step, healthy controls will be compared separately to patients with mild NCD and to patients with major NCD. The investigators further aim to investigate the aptness of the MoCA for differential diagnostic. The MoCA performance of different diagnostic patient groups will be compared. Investigating the presence or absence of deficits per subitem in each patient group may reveal if different etiologies lead to characteristic MoCA profiles.