AUTHOR=Gomes-Osman Joyce , Borson Soo , Toro-Serey Claudio , Banks Russell , Ciesla Marissa , Jannati Ali , Morrow W. Isaiah , Swenson Rod , Libon David , Bates David , Showalter John , Tobyne Sean , Pascual-Leone Alvaro 

TITLE=Digital Clock and Recall: a digital, process-driven evolution of the Mini-Cog

JOURNAL=Frontiers in Human Neuroscience

VOLUME=18

YEAR=2024

URL=https://www.frontiersin.org/journals/human-neuroscience/articles/10.3389/fnhum.2024.1337851

DOI=10.3389/fnhum.2024.1337851

ISSN=1662-5161

ABSTRACT=<sec id="sec1"><title>Introduction</title><p>Alzheimer’s disease and related dementias (ADRD) represent a substantial global public health challenge with multifaceted impacts on individuals, families, and healthcare systems. Brief cognitive screening tools such as the Mini-Cog© can help improve recognition of ADRD in clinical practice, but widespread adoption continues to lag. We compared the Digital Clock and Recall (DCR), a next-generation process-driven adaptation of the Mini-Cog, with the original paper-and-pencil version in a well-characterized clinical trial sample.</p></sec><sec id="sec2"><title>Methods</title><p>DCR was administered to 828 participants in the Bio-Hermes-001 clinical trial (age median ± SD = 72 ± 6.7, IQR = 11; 58% female) independently classified as cognitively unimpaired (<italic>n</italic> = 364) or as having mild cognitive impairment (MCI, <italic>n</italic> = 274) or dementia likely due to AD (DLAD, <italic>n</italic> = 190). MCI and DLAD cohorts were combined into a single impaired group for analysis. Two experienced neuropsychologists rated verbal recall accuracy and digitally drawn clocks using the original Mini-Cog scoring rules. Inter-rater reliability of Mini-Cog scores was computed for a subset of the data (<italic>n</italic> = 508) and concordance between Mini-Cog rule-based and DCR scoring was calculated.</p></sec><sec id="sec3"><title>Results</title><p>Inter-rater reliability of Mini-Cog scoring was good to excellent, but Rater 2’s scores were significantly higher than Rater 1’s due to variation in clock scores (<italic>p</italic> &lt; 0.0001). Mini-Cog and DCR scores were significantly correlated (<italic>τ</italic><sub>B</sub> = 0.71, <italic>p</italic> &lt; 0.0001). However, using a Mini-Cog cut score of 4, the DCR identified more cases of cognitive impairment (<italic>n</italic> = 47; <italic>χ</italic><sup>2</sup> = 13.26, <italic>p</italic> &lt; 0.0005) and Mini-Cog missed significantly more cases of cognitive impairment (<italic>n</italic> = 87). In addition, the DCR correctly classified significantly more cognitively impaired cases missed by the Mini-Cog (<italic>n</italic> = 44) than vice versa (<italic>n</italic> = 4; <italic>χ</italic><sup>2</sup> = 21.69, <italic>p</italic> &lt; 0.0001).</p></sec><sec id="sec4"><title>Discussion</title><p>Our findings demonstrate higher sensitivity of the DCR, an automated, process-driven, and process-based digital adaptation of the Mini-Cog. Digital metrics capture clock drawing dynamics and increase detection of diagnosed cognitive impairment in a clinical trial cohort of older individuals.</p></sec>