Kang Jae Myeong, Manjavong Manchumad, Jin Chengshi, Diaz Adam, Ashford Miriam T, Eichenbaum Joseph, Thorp Emily, Wragg Elizabeth, Zavitz Kenton H, Cormack Francesca, Aaronson Anna, Mackin R Scott, Tank Rachana, Landavazo Bernard, Cavallone Erika, Truran Diana, Farias Sarah Tomaszewski, Weiner Michael W, Nosheny Rachel L
Department of Psychiatry and Behavioral Sciences, University of California San Francisco, San Francisco, CA, USA.
VA Advanced Imaging Research Center, San Francisco Veteran's Administration Medical Center, San Francisco, CA, USA.
Alzheimers Res Ther. 2025 Jan 7;17(1):10. doi: 10.1186/s13195-024-01641-2.
Digital, online assessments are efficient means to detect early cognitive decline, but few studies have investigated the relationship between remotely collected subjective cognitive change and cognitive decline. We hypothesized that the Everyday Cognition Scale (ECog), a subjective change measure, predicts longitudinal change in cognition in the Brain Health Registry (BHR), an online registry for neuroscience research.
This study included BHR participants aged 55 + who completed both the baseline ECog and repeated administrations of the CANTAB Paired Associates Learning (PAL) visual learning and memory test. Both self-reported ECog (Self-ECog) and study partner-reported ECog (SP-ECog), and two PAL scores (first attempt memory score [FAMS] and total errors adjusted [TEA]) were assessed. We estimated associations between multiple ECog scoring outputs (ECog positive [same or above cut-off score], ECog consistent [report of consistent decline in any item], and total score) and longitudinal change in PAL. Additionally we assessed the ability of ECog to identify 'decliners', who exhibited the worst PAL progression slopes corresponding to the fifth percentile and below.
Participants (n = 16,683) had an average age of 69.07 ± 7.34, 72.04% were female, and had an average of 16.66 ± 2.26 years of education. They were followed for an average of 2.52 ± 1.63 visits over a period of 11.49 ± 11.53 months. Both Self-ECog positive (estimate = -0.01, p < 0.001, R²m = 0.56) and Self-ECog consistent (estimate=-0.01, p = 0.002, R²m = 0.56) were associated with longitudinal change in PAL FAMS after adjusting demographics and clinical confounders. Those who were Self-ECog total (Odds ratio [95% confidence interval] = 1.390 [1.121-1.708]) and SP-ECog consistent (2.417 [1.591-3.655]) had higher probability of being decliners based on PAL FAMS.
In the BHR's unsupervised online setting, baseline subjective change was feasible in predicting longitudinal decline in neuropsychological tests. Online, self-administered measures of subjective cognitive change might have a potential to predict objective subjective change and identify individuals with cognitive impairments.
数字化的在线评估是检测早期认知衰退的有效手段，但很少有研究调查远程收集的主观认知变化与认知衰退之间的关系。我们假设日常认知量表（ECog），一种主观变化测量方法，能够预测大脑健康登记处（BHR）中认知的纵向变化，BHR是一个用于神经科学研究的在线登记处。
本研究纳入了年龄在55岁及以上的BHR参与者，他们完成了基线ECog以及重复进行的剑桥神经心理测试自动化成套系统（CANTAB）配对联想学习（PAL）视觉学习和记忆测试。评估了自我报告的ECog（Self-ECog）和研究伙伴报告的ECog（SP-ECog），以及两个PAL分数（首次尝试记忆分数 [FAMS] 和调整后的总错误数 [TEA]）。我们估计了多个ECog评分输出（ECog阳性 [等于或高于临界分数]、ECog一致 [任何项目中持续下降的报告] 和总分）与PAL纵向变化之间的关联。此外，我们评估了ECog识别“衰退者”的能力，这些“衰退者”表现出对应于第五百分位数及以下的最差PAL进展斜率。
参与者（n = 16683）的平均年龄为69.07 ± 7.34岁，72.04% 为女性，平均受教育年限为16.66 ± 2.26年。在11.49 ± 11.53个月的时间里，他们平均接受了2.52 ± 1.63次随访。在调整人口统计学和临床混杂因素后，Self-ECog阳性（估计值 = -0.01，p < 0.001，R²m = 0.56）和Self-ECog一致（估计值 = -0.01，p = 0.002，R²m = 0.56）均与PAL FAMS的纵向变化相关。根据PAL FAMS，Self-ECog总分者（优势比 [95% 置信区间] = 1.390 [1.121 - 1.708]）和SP-ECog一致者（2.417 [1.591 - 3.655]）成为“衰退者”的可能性更高。
在BHR的无监督在线环境中，基线主观变化对于预测神经心理测试中的纵向衰退是可行的。在线的、自我管理的主观认知变化测量方法可能有潜力预测客观认知变化并识别认知受损个体。
