Validating the MoCA for screening 3 75 For theoriginal suggestedcut-offscoreof 26 todiscriminateMCI fromHC thesensitivityand specificity are 94% and 73%, respectively (in the original article 90% and 87%)(Nasreddine et al., 2005). Using the same cut-off score in a realistic setting (i.e. discriminating against referred NoCI) leads to a drop in specificity to 37%. The clinical situation of detecting CI (MD+MCI) below this cut-off had a sensitivity of 95%. Table 2: The effect of using HC instead of NoCI as comparisons on Area Under the Curve between variations of groups and their sensitivity and specificity at cut-off scores 26 and 21, often used in literature. groups AUC SE CutOff <26 CutOff <21 Sens Spec Sens Spec Dem vs NoDem .865 .018 .975 .737 .901 .740 Dem vs HC .983 .007 .975 .726 .901 .988 Dem vs MCI .810 .029 .975 .065 .901 .627 CI vs NoCI .765 .018 .949 .368 .556 .778 CI vs HC .925 .016 .949 .726 .556 .988 MCI vs NoCI .702 .022 .935 .368 .373 .778 MCI vs HC .894 .022 .935 .726 .373 .988 Dem: Dementia (n=81); NoDem: No Dementia (MCI + NoCI; n=612); MCI: Mild Cognitive impairment (n=153); NoCI: Referred patients no Cognitive Impairment (n=459); HC: Healthy Controls (n=84); CI; Cognitive Impairment (Dem + MCI; n=234). AUC: Area Under the Curve. SE: standard error. Sens: sensitivity. Spec: specificity. A cut-off score for diagnosing dementia is still under debate, but is often set around 21 (Thissen et al., 2010; Waldron-Perrine and Axelrod, 2012; Davis et al., 2015), which in our study results in a sensitivity of 90%. The specificity dropped from 99% using Dementia vs HC, to 74% in a clinical setting (Dementia vs MCI+NoCI), and 63% for Dementia vs MCI. To find the “best” cut-off score for our population, the specificity and sensitivity were calculated for different scores of the MoCA (table 3).
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