Montefiore Einstein Robust Geriatric Normative Project (MERGER-NP): standardized regression-based formulas and multivariate base rates for evaluating cognitive change.

IF 2.1
Bryan M Freilich, Roee Holtzer
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Abstract

Objective: This study extends the Montefiore Einstein Robust Geriatric (MERGER) norms by developing and validating standardized regression-based (SRB) change formulas for a co-normed neuropsychological battery in a robust sample of older adults. We also examine their clinical utility for differentiating mild cognitive impairment (MCI) and dementia and provide multivariate base rates of decline.

Methods: Standardized regression-based equations were derived from a subsample of MERGER participants (n = 320) using backward regression to predict Time 2 scores from Time 1 performance and relevant demographic factors. Equations were validated in an independent subset (n = 100) and applied to 63 individuals with MCI and 32 with dementia who completed at least two study visits but were excluded from normative analyses. Clinical utility was examined by comparing predicted and observed performance across diagnostic groups. Categorical and multivariate base-rate analyses were used to establish clinically meaningful thresholds.

Results: Baseline performance was the strongest predictor of follow-up scores, with demographic factors adding measure-specific variance. SRB equations performed well in the validation sample. Exploratory clinical validation analyses indicated that decline was uncommon in cognitively unimpaired (CU) participants but more frequent in MCI and dementia, particularly on memory and executive tasks. Multivariate analyses showed that decline on ≥3 measures was rare in CU participants but observed in nearly half of participants with MCI and most individuals with dementia.

Conclusions: MERGER SRB change formulas offer a practical, individualized method for tracking cognitive change in older adults. Incorporating multivariate base rates of decline further improves differentiation between normal aging, MCI, and dementia, supporting more accurate longitudinal interpretation and clinical decision-making.

Montefiore Einstein稳健老年规范项目(merge - np):基于标准化回归的公式和评估认知变化的多变量基准率。
目的:本研究通过在老年人样本中开发和验证基于标准化回归(SRB)的共同规范神经心理电池变化公式,扩展了Montefiore Einstein稳健老年(merge)规范。我们还研究了它们在区分轻度认知障碍(MCI)和痴呆方面的临床应用,并提供了多元基本下降率。方法:从合并参与者的子样本(n = 320)中导出标准化回归方程,使用反向回归来预测时间1表现和相关人口因素的时间2得分。方程在一个独立的子集(n = 100)中得到验证,并应用于63名轻度认知障碍患者和32名痴呆症患者,他们至少完成了两次研究访问,但被排除在规范分析之外。通过比较诊断组的预测和观察表现来检查临床效用。分类和多变量基础率分析用于建立具有临床意义的阈值。结果:基线表现是随访评分的最强预测因子,人口统计学因素增加了测量特定方差。SRB方程在验证样本中表现良好。探索性临床验证分析表明,在认知未受损(CU)的参与者中,这种下降并不常见,但在轻度认知损伤和痴呆患者中更为常见,尤其是在记忆和执行任务方面。多变量分析显示,在CU参与者中,≥3项指标的下降是罕见的,但在近一半的MCI参与者和大多数痴呆患者中观察到。结论:合并SRB变化公式为跟踪老年人认知变化提供了一种实用的、个性化的方法。纳入多元基本下降率进一步提高了正常衰老、轻度认知障碍和痴呆之间的区分,支持更准确的纵向解释和临床决策。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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