■阿尔茨海默病和相关痴呆(ADRD)是一个巨大的全球公共卫生挑战,对个人产生多方面的影响。家庭,和医疗保健系统。简短的认知筛查工具,如Mini-Cog©可以帮助提高临床实践中对ADRD的认识。但是广泛的采用仍然滞后。我们比较了数字时钟和召回(DCR),Mini-Cog的下一代过程驱动自适应,在一个特征明确的临床试验样本中使用原始的纸笔版本。
■对Bio-Hermes-001临床试验中的828名参与者(年龄中位数±SD=72±6.7,IQR=11;58%女性)进行了DCR独立分类,分为认知未受损(n=364)或轻度认知障碍(MCI,n=274)或可能由AD引起的痴呆(DLAD,n=190)。将MCI和DLAD队列合并为单个受损组进行分析。两位经验丰富的神经心理学家使用原始的Mini-Cog评分规则对口头回忆的准确性和数字绘制的时钟进行了评分。对数据子集(n=508)计算Mini-Cog评分的评分者间可靠性,并计算基于Mini-Cog规则和DCR评分之间的一致性。
■Mini-Cog评分的评分者间可靠性良好至优异,但由于时钟评分的变化,评分者2的评分明显高于评分者1的评分(p<0.0001)。Mini-Cog和DCR得分显著相关(τB=0.71,p<0.0001)。然而,使用Mini-Cog评分为4分,DCR识别出更多的认知障碍病例(n=47;χ2=13.26,p<0.0005),Mini-Cog错过了更多的认知障碍病例(n=87)。此外,DCR正确分类的Mini-Cog遗漏的认知障碍病例(n=44)明显多于前者(n=4;χ2=21.69,p<0.0001)。
■我们的研究结果表明DCR的灵敏度更高,一个自动化的,过程驱动,和Mini-Cog的基于过程的数字自适应。数字指标可捕获时钟绘制动态,并增加对老年人临床试验队列中诊断出的认知障碍的检测。
UNASSIGNED: 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.
UNASSIGNED: 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 (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.
UNASSIGNED: 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 (p < 0.0001). Mini-Cog and DCR scores were significantly correlated (τ B = 0.71, p < 0.0001). However, using a Mini-Cog cut score of 4, the DCR identified more cases of cognitive impairment (n = 47; χ 2 = 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; χ 2 = 21.69, p < 0.0001).
UNASSIGNED: 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.