Digital Clock and Recall: a digital, process-driven evolution of the Mini-Cog
Joyce Gomes-Osman, Soo Borson, Claudio Toro-Serey, Russell Banks, Marissa Ciesla, Ali Jannati, W. Isaiah Morrow, Rod Swenson, David Libon, David Bates, John Showalter, Sean Tobyne, Alvaro Pascual-Leone
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{"title":"Digital Clock and Recall: a digital, process-driven evolution of the Mini-Cog","authors":"Joyce Gomes-Osman, Soo Borson, Claudio Toro-Serey, Russell Banks, Marissa Ciesla, Ali Jannati, W. Isaiah Morrow, Rod Swenson, David Libon, David Bates, John Showalter, Sean Tobyne, Alvaro Pascual-Leone","doi":"10.3389/fnhum.2024.1337851","DOIUrl":null,"url":null,"abstract":"IntroductionAlzheimer’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.MethodsDCR 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 (<jats:italic>n</jats:italic> = 364) or as having mild cognitive impairment (MCI, <jats:italic>n</jats:italic> = 274) or dementia likely due to AD (DLAD, <jats:italic>n</jats: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 (<jats:italic>n</jats:italic> = 508) and concordance between Mini-Cog rule-based and DCR scoring was calculated.ResultsInter-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 (<jats:italic>p</jats:italic> &lt; 0.0001). Mini-Cog and DCR scores were significantly correlated (<jats:italic>τ</jats:italic><jats:sub>B</jats:sub> = 0.71, <jats:italic>p</jats:italic> &lt; 0.0001). However, using a Mini-Cog cut score of 4, the DCR identified more cases of cognitive impairment (<jats:italic>n</jats:italic> = 47; <jats:italic>χ</jats:italic><jats:sup>2</jats:sup> = 13.26, <jats:italic>p</jats:italic> &lt; 0.0005) and Mini-Cog missed significantly more cases of cognitive impairment (<jats:italic>n</jats:italic> = 87). In addition, the DCR correctly classified significantly more cognitively impaired cases missed by the Mini-Cog (<jats:italic>n</jats:italic> = 44) than vice versa (<jats:italic>n</jats:italic> = 4; <jats:italic>χ</jats:italic><jats:sup>2</jats:sup> = 21.69, <jats:italic>p</jats:italic> &lt; 0.0001).DiscussionOur 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.","PeriodicalId":2,"journal":{"name":"ACS Applied Bio Materials","volume":null,"pages":null},"PeriodicalIF":4.6000,"publicationDate":"2024-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Bio Materials","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.3389/fnhum.2024.1337851","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATERIALS SCIENCE, BIOMATERIALS","Score":null,"Total":0}
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