Aggregate learning ratio from the Neuropsychological Assessment Battery distinguishes between amnestic and non-amnestic mild cognitive impairment in a real-world clinical sample

Mild cognitive impairment (MCI) is a heterogeneous syndrome with varying cognitive profiles and trajectories. Amnestic MCI (aMCI) is associated with memory deficits and increased risk of Alzheimer's disease, while non-amnestic MCI (naMCI) often involves executive dysfunction and may signal risk for other dementias. Encoding deficits, though more prominent in aMCI, are also observed in naMCI. This study examined the utility of the Neuropsychological Assessment Battery (NAB) learning ratio (LR) scores-specifically List LR, Story LR, and an Aggregate LR-to distinguish among cognitively normal individuals, aMCI, and naMCI in a real-world clinical sample (N = 121). The NAB Aggregate LR showed superior diagnostic discriminability, with significantly larger effect sizes and greater predictive value in differentiating aMCI from naMCI compared to individual LRs. Receiver operating characteristic (ROC) analysis confirmed strong classification accuracy (area under the curve [AUC] = .824). Findings suggest encoding performance, as captured by the Aggregate LR, reflects underlying differences in cognitive processing and neuroanatomical involvement across MCI subtypes. The Aggregate LR also demonstrated stronger associations with executive functioning in naMCI. These results highlight the NAB Aggregate LR as a clinically valuable tool for improving differential diagnosis in MCI, which may support earlier and more targeted interventions to improve patient outcomes. Notably, the Aggregate LR accounted for incremental variance in group classification beyond age, IQ, and individual LRs. Its sensitivity to both memory and executive dysfunction-especially in early-stage impairment-underscores its utility in clinical neuropsychological assessment. Earlier and more precise identification of MCI subtypes may enable more effective cognitive interventions and improve long-term care planning.