Frontiers in Human Neuroscience (Aug 2024)

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

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

DOI
https://doi.org/10.3389/fnhum.2024.1337851
Journal volume & issue
Vol. 18

Abstract

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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 (n = 364) or as having mild cognitive impairment (MCI, n = 274) or dementia likely due to AD (DLAD, n = 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 (n = 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 (p < 0.0001). Mini-Cog and DCR scores were significantly correlated (τB = 0.71, p < 0.0001). However, using a Mini-Cog cut score of 4, the DCR identified more cases of cognitive impairment (n = 47; χ2 = 13.26, p < 0.0005) and Mini-Cog missed significantly more cases of cognitive impairment (n = 87). In addition, the DCR correctly classified significantly more cognitively impaired cases missed by the Mini-Cog (n = 44) than vice versa (n = 4; χ2 = 21.69, p < 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.

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