Background Early detection of Alzheimer's disease (AD) is critical for timely intervention. Subjective cognitive decline (SCD), defined as self-perceived cognitive worsening while objective performance on standardized tests remains normal, when accompanied by neurodegenerative changes on brain imaging (e.g., hippocampal atrophy), can be classified as SCD with neurodegeneration of AD form (SCD-NDAD). This phenotype may represent an early stage of AD. Objective Investigate the prevalence and clinical characteristics of SCD-NDAD in general population. Methods: This multicenter, community-based cross-sectional study was conducted from 2013 to 2019 across 31 communities in eight major cities of northern, eastern, southern, and western China. Community-dwelling adults aged 50 years and older were recruited through cluster sampling. Participants underwent standardized interviews, neuropsychological assessments, and magnetic resonance imaging, on the basis of which SCD-NDAD was identified. The prevalence of SCD-NDAD was estimated with age- and sex-standardized weights. Results Of 5054 participants (mean age 69.4 years, 60.6% women), 2886 completed MRI. In participants aged ≥50 years, the prevalence of SCD-NDAD was 4.9% (95% confidence interval: 4.1% to 5.8%). In participants aged 65 years and older, prevalence increased to 6.5% (95% confidence interval: 5.5% to 7.7%). While these individuals exhibited preserved cognitive function across all domains, they demonstrated significant hippocampal atrophy, a key marker of AD-related neurodegeneration. Conclusions SCD-NDAD is common among older adults in China, with an estimated prevalence affecting 12.4 million individuals aged ≥65 years. Identifying this cohort may offer a critical window for early intervention and holds significant implications for public health strategies aimed at dementia prevention.

Introduction Age, sex, race, and education are well-established determinants of cognitive performance in traditional testing, yet their impact on novel digital measures is less understood. Digital assessments offer scalable, precise evaluation of cognition and may reveal subtle demographic differences important for early risk detection. Leveraging three distinct cohorts from the Disparities and Equity in Childhood Cardiovascular Exposures and Alzheimer’s Dementia (DECADES) project, we examined demographic influences on two digital cognitive tools. Methods Participants included 236 community-dwelling adults (age 38-69 years; 79.5% female; 68.3% White) drawn from three midlife DECADES cohorts, each with distinct racial/ethnic and socioeconomic profiles. Demographic predictors of interest were age, sex, and race; obesity and hypertension were also considered, given their cognitive relevance. Cognitive performance was measured using two tablet-based instruments: (1) the Rowan Digital Cancellation Test (RDCT), which includes letter, symbol, and mixed conditions with outcomes of accuracy and processing speed, and (2) the Linus Digital Clock Drawing Task, which includes command and copy conditions with metrics of latency, stroke conformity, speed, and total completion time. Standardized protocols were used for administration across sites. One-way ANOVA models were used to test differences between demographic variables and digital outcomes. Significant differences were further examined with pairwise post hoc comparisons to delineate group differences. Results Older participants demonstrated slower processing across RDCT and clock tasks (letter speed F=36.5, p<0.001; mixed speed F=29.8, p<0.001). Women outperformed men on RDCT speed (letter F=22.9, p<0.001; symbol F=9.6, p=0.002) and on clock copy time (F=4.9, p=0.027). Black participants exhibited longer clock command latencies (F=22.7, p<0.001), more stroke errors (F=6.9, p<0.001), and slower cancellation performance (letter speed F=10.5, p=0.001). Obesity was associated with slower digital processing, as indicated by reduced performance on clock average speed (F = 4.83, p = 0.02) and cancellation average speed (F = 4.82, p = 0.029), whereas hypertension did not show a significant association. Conclusions Demographic factors—including age, sex, and race—exert a strong influence on digital cognitive performance in midlife, paralleling traditional neuropsychological test findings. RDCT and digital clock drawing are sensitive to sociodemographic differences, underscoring their potential as scalable tools to identify at-risk groups before clinical symptoms emerge.

Introduction: Cognitive decline is a growing public health concern as the prevalence of Alzheimer’s Disease and Related Dementias (ADRD) is expected to rise. Moreover, vascular health has been shown to be linked to the eventual emergence of ADRD. Carotid intima-media thickness (cIMT) is a noninvasive measure that could potentially reveal subclinical vascular disease that could identify individuals at risk of ADRD earlier in life. Hypothesis: Increased cIMT is independently associated with worse cognitive function in healthy adults in midlife. Methods: We analyzed 174 adults (mean age 54±8 years; 83% female; 61% Caucasian) from two International Childhood Cardiovascular Cohort (i3C) studies - National Growth and Health Study and Princeton Lipid Research Study. Anthropometrics and laboratory evaluation were performed. Participants underwent carotid ultrasound to measure cIMT (mean of internal, bulb, and common carotid segments measured bilaterally) and completed the three Rowan Digital Cancellation Tests (RDCT; Letter, Symbol, Mixed Letter/Symbol) to measure executive and graphomotor information processing speed. Cancelation performance was expressed using composite scores that combine accuracy and processing speed. Variables were log transformed if indicated. General linear models with backward selection were used to identify predictors of RDCT performance, with logcIMT, age, sex, race, BMI, blood pressure, LDL, TG:HDL ratio, and logCRP. Results: After backward selection, logcIMT and age remained significant predictors across all RDCT forms. Higher logcIMT was associated with worse cognitive function independently of age (Letter: β=-0.18, p<0.01; Symbol: β=-0.15, p=0.02; Mixed: β=-0.11, p=0.01). Age was also inversely associated with cognitive performance (Letter: β=-0.006, Symbol: β=-0.005, Mixed: β=-0.004; p<0.01 for all). Additional covariates retained in some models included race (Symbol: β=-0.04, p=0.0495), LDL (Symbol: β=0.0006, p=0.04), and logCRP (Mixed: β=-0.01, p=0.04). Model R 2 were 0.15 (Letter), 0.18 (Symbol), and 0.19 (Mixed). Conclusions: In healthy middle-aged adults, greater cIMT is associated with greater executive and graphomotor processing speed deficits, independent of age and select cardiovascular risk factors. These findings suggest that subclinical vascular disease may be associated with cognitive decline earlier in the life course. Future studies should examine whether interventions targeting vascular health can preserve cognition.

OBJECTIVES:Neuropsychological (NP) tests are multi-domain in execution. Reliance on a single score representing specific domains obscures the detection of subtle cognitive changes and increases risk of inaccurate assessment. Rooted in the Boston Process Approach (BPA), the Framingham Heart Study (FHS) captures multi-dimensional errors and process features within and across NP tests. We examined these BPA variables in community-dwelling older adults. METHODS:We analyzed data from 2363 dementia-free participants aged 60 and above. Exploratory and confirmatory factor analyses used Kemeny covariance structures. Measurement invariance was estimated across age, sex, and education groups. We assessed the impact of demographics on latent factors, and the ability of these factors to predict future conversion to all-cause dementia. We trained machine learning (ML) models to compare NP and BPA data. RESULTS:Participants were older adults (mean age 71.5 ± 8.7 years), primarily female (54.2%), and non-Hispanic White (96.5%). The bifactor model was the only model with adequate fit (CFI = 0.96, RMSEA = 0.03). General and specific factors captured ability for accurate and strategic responses, test-specific variance, and nuanced executive and semantic processes distributed across tests. Higher general ability and stronger verbatim story recall were associated with a reduced likelihood of developing all-cause dementia (general: OR = 0.15, 95% CI [0.12-0.86]; recall: OR = 0.24, 95% CI [0.23-0.90]) over a median of 5.2 years. With NP/BPA data, ML models identified >99% of 222 converters. CONCLUSIONS:This study highlights the strengths of NP/BPA data. Multidimensional cognitive features may enhance sensitivity to early changes predictive of incipient dementia.

Traditional neuropsychological assessments for cognitive decline are lengthy in-clinic evaluations by a specialist, with typical wait times of 6-8 months. This creates a substantial patient burden and prolonged diagnostic and treatment timelines. Digital cognitive assessments (DCA) offer a scalable solution to these challenges, but their validation is challenged by the scarcity of large, high-quality datasets with established ground truth. To develop a model to identify mild cognitive impairment (MCI) and probable dementia using metrics from the Digital Assessment of Cognition (DAC), a brief, remote-capable DCA. A secondary objective was to conduct a preliminary assessment of the model's validity. We applied a semi-supervised model-based clustering method to combine a large dataset (N=1189) of DAC assessments alone, with a smaller dataset pairing DAC assessments with ground-truth neuropsychological diagnoses (N=248). We examined the model's predictive validity by comparing its predictions with diagnoses on a held-out test set. We examined congruent validity by testing associations with traditional analog assessments and demographic variables. We identified a 6-cluster model with 3 MCI clusters and 2 probable dementia clusters. The model identified cognitively unimpaired, MCI, and dementia groups with high accuracy (78.7%) on the held-out test dataset, and showed excellent ability to identify cognitive impairment (AUROC=0.985) and dementia (AUROC=0.932). We identified strong associations with traditional analog assessments and demographic variables. An exploratory analysis showed evidence that clusters correspond to clinically meaningful subtypes of MCI. These results validate prior exploratory work and demonstrate the potential for more nuanced, holistic, and scalable cognitive assessments in non-specialist settings.

BackgroundProblems with visual attention can be an early indication for the emergence of dementia.ObjectiveThe current research assessed visual attention using three iPad administered, digital cancellation tests.MethodsLetter and Symbol Cancellation Tests asked participants to circle a specific letter or symbol. On the Mixed Cancellation Test, participants alternated circling a letter, then a symbol. Five outcome variables were tallied: correct hits; mean intra-response pause or "think" time; mean drawing or "ink" time to circle correct hits; mean distance or search between correct targets; and commission errors. All but commission errors were expressed in four cumulative time epochs; 0-30 s, 0-60 s, 0-90 s, and 0-120 s. Using a protocol of paper/ pencil neuropsychological tests, Jak, Bondi criteria were used to classify 145 memory clinic patients into groups suggesting normal cognitive abilities (CL; n = 45); subtle or mild cognitive impairment (MCI; n = 62); and mild dementia (DEM; n = 38).ResultsFor correct hits and mean pause/ "think" time, the three groups were dissociated from each other at 60, 90, and 120 s. For mean drawing/'ink' time far fewer between-group differences were found. There was no difference across the three tests for mean search. On the Symbol and Mixed Cancellation Tests, MCI and DEM patients produced more commission errors than CL participants.ConclusionsFaster pause or "think time", perhaps reflecting better disengagement from circling target items, may underlie better cancellation test performance. When brought to scale, The Rowan Cancellation Tests could be an effective means to screen for MCI and emergent dementia.

BackgroundDigital cognitive testing allows for assessment of more granular aspects of cognition that may enhance the ability to detect cognitive decline and Alzheimer's disease earlier.ObjectiveTo assess cognition using a smartphone-based Stroop Task in older adults.MethodsThe smartphone-based Stroop Task consisted of four subtests including two with minimal cognitive demand, i.e., color matching (subtest 1) and color-word matching (subtest 2), and two with greater cognitive demand i.e., inhibition (subtest 3); and inhibition/switching (subtest 4). Each subtest consisted of five trials. Repeated measures ANOVA were conducted to examine mean completion times within and between the four test conditions. Completion times were also compared to traditional neuropsychological tests.ResultsAmong 478 iPhone users, 429 (89.7%) used the app-based Stroop Test (mean age 73.5 years (6.4), 58% female, 87% non-Hispanic White, mean MMSE score 28.75 ± 1.4). Error-free performance occurred in 395 participants on subtest 1, 404 on subtest 2, 320 on subtest 3, and 183 on subtest 4. Mean completion times differed between the four subtests (all p < 0.0001) with faster subtest 2 completion (1.45 to 1.19 s across the five trials) and slower subtest 4 completion (2.95 to 2.75 s across the 5 trials) than the other subtests. Completion times were positively associated with paper/pencil measures of processing speed but negatively associated with measures of episodic and working memory and language.ConclusionsWe demonstrate the feasibility and construct validity of administering a fully self-administered smartphone-based Stroop cognitive test in older adults completed outside a clinical setting.

BackgroundIn prior research, the Digital Assessment of Cognition (DAC), a brief digitally administered neuropsychological protocol that assesses verbal episodic memory, verbal working memory, and language, has been used to classify a small sample of memory clinic patients (n = 77) into four meaningful clinical groups.ObjectiveThe current research sought to extend these findings with a considerably larger sample.MethodsThe DAC was administered to 179 ambulatory care/memory clinic patients (45.30% female; 91.10% Caucasian). A comprehensive analysis of DAC core outcome measures and behavior reflecting process/errors was undertaken. Traditional paper/pencil assessment was also obtained. Using Jak, Bondi criteria (2009), paper/pencil test results classified patients into five groups: cognitively unimpaired (CU; n = 74), subtle cognitive impairment (SCI; n = 21), amnestic mild cognitive impairment (aMCI; n = 21), combined dysexecutive/mixed MCI (dys/mxMCI; n = 22), and mild dementia (n = 41).ResultsThe aMCI group presented with many of the classic features consistent with amnesia, i.e., rapid forgetting, reduced free recall clustering, and profligate responding to recognition foils. Latency for correct recognition responding was slower for aMCI compared to the CU group and appears to be associated with a neurocognitive network measuring both memory and language-related operations. SCI and dys/mxMCI groups tended to produce more perseverations on working memory test trials; and produced lower scores on DAC executive outcome measures that assessed auditory span and semantic fluency.ConclusionsThese findings support the criterion and construct validity of the DAC. When brought to scale the DAC could be an effective tool to assess for emergent MCI and dementia syndromes.

Background The Digital Assessment of Cognition (DAC) is a brief, 7-minute iPad administered-scored neuropsychological protocol.Objective The current research sought to investigate relationships between DAC test results and family ratings for neurocognitive decline; instrumental activities of daily living (IADL) impairment; psychiatric symptoms, and physician-determined cardiovascular risks.Methods 179 memory clinic patients were assessed. Family members rated the severity of neurocognitive impairment, IADL decline, and psychiatric symptoms using the Everyday Cognition Scales (ECog); the Functional Assessment Questionnaire (FAQ); the Instrumental Activities of Daily Living-Compensation Scale (IADL-C); and the Neuropsychiatric Inventory (NPI), respectively. An index measuring cardiovascular risk was extracted from medical records.Results Partial correlations controlled for age, education, and sex found that greater functional disability and elevated cardiovascular risks were associated with lower DAC memory and executive index scores. Lower DAC memory scores were seen in relation to family ratings suggesting impaired Ecog Episodic Memory difficulty; relatively intact ECog Executive/Attention ability; and impaired IADL-C Memory/Self-Management difficulty. By contrast, lower DAC executive performance was seen in relation to family ratings suggesting impaired Ecog Executive/Planning difficulty and IADL-C Social Skills difficulty. Lower DAC-executive index scores were also associated with greater informant rated apathy.Conclusions The relations between DAC index scores and total informant FAQ and IADL-scores; Ecog and IADL-C subscales; and selected NPI-defined psychiatric problems suggest that the DAC is both sensitive to gross IADL decline, and specific to differing ECog and IADL-C and psychiatric problems. Combining digital assessment with family IADL ratings could help with clinical decision-making.

Context: Obesity is a driver of cardiometabolic (CM) disease and previous studies have suggested a relationship between obesity measures and structural brain health and cognition. However, most studies focused solely on BMI. Here we evaluate 2023 Lancet Commission obesity classifications, which include abnormal CM physiology, and MRI markers of brain integrity. Objective: To examine associations between obesity status across early-to-mid adulthood, using Lancet Commission obesity classifications, and midlife MRI markers of brain integrity in the Bogalusa Heart Study (BHS). Design, Setting, and Participants: The BHS is a longitudinal study which began in childhood and followed black and white boys and girls in Bogalusa, Louisiana, for >50 years into midlife. Participants underwent repeated CM phenotyping between 1985–2010. Six examinations during young adulthood to midlife had all information necessary for the analysis. Brain MRI was obtained on n=283 participants between 2016–2024 to quantify white matter hyperintensity (WMH) and gray to total matter volume (GMV/TV). Longitudinal analyses included 283 participants. Analyses on specific examinations included 144 to 212 participants. Main Outcomes and Measures: Participants were classified as Non-Obese, Preclinically Obese, or Clinically Obese at each examination, per LancetCommission obesity guidelines. WMH and GMV/TV were compared across groups. Using Kruskal–Wallis tests followed by Dunn’s post hoc comparisons (Bonferroni adjusted), Hodges–Lehmann estimators, RT-ANCOVA followed by Holms post hoc test (to adjust for covariates), Results: Mean (SD) age at initial young adult examinations was 23.3 (2.2) years and 42.7 (4.3) during the last exam prior to MRI . Mean (SD) age at MRI was 57.4 (4.6) yrs. Participants who were clinically obese (n=184) at any time in their young adult years had significantly higher WMH volume in midlife compared to participants who were non-obese (n = 92) during the entirety of that same period (Bonferroni adjusted p = 0.0022; HL difference = 0.076 mL, 95% CI: 0.027–0.14, Holmes p= 0.0415). Conclusions: Having clinical obesity, as defined by the 2023 Lancet Commission, at any point in in young adulthood was significantly associated with greater WMH burden in midlife compared with non-obese individuals. These findings suggest that excess adiposity when paired with abnormal CM physiology may have long-term consequences for brain health and cognition.

Although the relationships between birthweight, gestational age (GA), and cognitive function (CF) before midlife have been demonstrated, the relationships after midlife and potential racial disparities remain inconclusive. This study examined the association between birthweight, GA, and midlife CF stratified by race. 1,032 subjects from the Bogalusa Heart Study (67

OBJECTIVE:Understanding how well older individuals with suspected cognitive impairment are functioning within the real-world environment can have important implications for diagnosis and treatment. To evaluate whether an individual is experiencing functional limitations suggesting the presence of mild cognitive impairment (MCI) or dementia, we establish diagnostic cutoff scores for the informant version of the Instrumental Activities of Daily Living-Compensation (IADL-C) scale. METHOD:Informants of research (n = 488) and clinical (n = 119) samples of participants designated as healthy older controls, MCI, or dementia completed the IADL-C. Receiver operating characteristic curve analyses and diagnostic statistics were used to determine optimal cutoffs on the IADL-C for both the 27-item IADL-C and an 11-item short form created using item-level analysis. RESULTS:The optimal cutoff scores that maximized the Youden Index for the research sample long-form were 1.41 in distinguishing cognitively healthy versus MCI participants, and 3.60 in distinguishing dementia from MCI participants, favoring specificity for the clinical sample, the optimal cutoffs were 1.32 and 3.06, yielding higher sensitivity. CONCLUSIONS:These cutoff scores, when used as a screening measure or combined with other clinical and cognitive measures, may be useful for understanding whether an individual may be experiencing functional difficulties in everyday life consistent with a diagnosis of MCI or dementia.

Background: Area-level socioeconomic deprivation is linked to cognitive impairment in older adults, but its impact from middle age is unclear. Evidence on the early-life deprivation effect on midlife cognitive function (CF) is limited. Objective: To investigate the effect of early-life Area Deprivation Index (ADI), on CF in middle-aged adults Methods: We assessed the association between early-life ADI and midlife CF in 1,099 subjects from the Bogalusa Heart Study (58.0% Whites, 42.0% Blacks, mean age at ADI: 12.6±5.9, mean age at CF: 48.7±5.0). Census data for 17 block-group variables were collected, including education, poverty, income, employment, and housing. Home ownership was excluded due to a factor loading below 0.3, leaving 16 variables for ADI calculation through factor analysis. The ADI was divided into quintiles, with the 1st quintile as the least deprived and 5th as most. CF was assessed through tests measuring episodic memory, working memory, attention, graphomotor information processing speed (GIPS), and global CF. Associations between ADI and CF were evaluated using a generalized estimation equation, adjusting for age at first exam, sex, race, year, and education. Interaction terms of race and education with ADI quintiles were tested. Results: The independent t-test showed Blacks had a higher ADI than Whites, indicating greater deprivation (0.81±0.58 vs. –0.60±0.80, p <0.001). Global CF decreased in the 5th ADI quintile compared to the 1st (β=–0.002 standardized unit [SE: 0.001], p =0.001), with a downward trend across quintiles ( p =0.002). Episodic memory, working memory, attention, and GIPS also decreased as the quintile of ADI increased ( p <0.001). Interaction terms with education showed significant negative effect on CF among high school graduates (1 st vs. 4 th quintile: β=–0.004 [SE: 0.002]), and those with education beyond high school (1 st vs. 5 th quintile: β=–0.004 [SE: 0.002]), but not among less than high school (1 st vs. 5 th quintile: β=–0.003 [SE: 0.001]; p for interaction: 0.011). Interactions between ADI quintiles and race were not significant. Conclusion: Higher early-life ADI was associated with lower midlife CF, with a decline observed in CF in the most deprived quintile, although effect sizes were modest. The strongest negative impact was observed among those with high school education or higher. Keywords area deprivation index; cognition; middle-aged adults

Background: Plasma proteins associated with Alzheimer’s disease (AD) include β-amyloid-42 (Aβ 42 ), phosphorylated -tau at threonine-181 (p-tau 181 ), and neurofilament light chain (NfL). This study assessed the relationship between these biomarkers and digital neuropsychological test performance. Methods: Middle-aged participants in the DECADE study had blood drawn and completed the Rowan Digital Cancellation Test (RDCT) consisting of 64 targets embedded among foils. Within 90 seconds, participants circled as many targets as possible, alternating between letters and symbols. RDCT outcomes included correct targets; ‘think’ time between correct targets; ‘ink’ time to circle correct targets; total pen strokes; commission errors; and total pen stroke distance and were summarized using factor analysis. Their association with AD biomarkers was done using linear regression. Results: The first 77 participants (age=55.3±8.7; 81.6% female) were included, with serum Aβ 42 (mean±SD: 7.8 + 2.7 pg/ml), p-Tau 181 (17.2 + 11.1 pg/ml), and NfL (10.5 + 13.8 pg/ml) assessed. Factor analysis identified 2 factors (Table). Higher scores on Factor 1 (49.2% variance) correspond to fewer correct responses, more think time, commission errors, and pen strokes. Higher scores on Factor 2 (27.9% variance) correspond to more correct responses, fewer commission errors, ink time, and pen strokes. Adjusting for age, sex, education, and both RDCT factor scores, NfL was negatively associated with Factor 2 (R 2 = 0.176, β= -0.445[JW1] , SE=2.57; p< 0.01 ) suggesting worse RDCT test performance with increasing biomarker level. In contrast, Aβ42 was positively associated with Factor 1 (R 2 =0.268, β= 0.503, SE= p< 0.003. Analyses involving p-Tau 181 were not significant. Conclusion: In this community-dwelling, middle-aged sample, plasma levels of AD-related proteins are associated with digital measures of neurocognitive performance. Middle-age assessment of serum AD-related proteins and digital neuropsychological performance have the potential to help identify emergent neurodegenerative illness.

Mild cognitive impairment, a precursor to Alzheimer’s disease and related disorders (ADRD), is widely underdiagnosed. Routine screenings are key for identifying older adults with emerging neurodegenerative disease. As women have increased risk of ADRD and often use their gynecologist as their primary care physician, the annual well woman visit offers a critical opportunity to screen older women for ADRD. This study aimed to examine objective cognitive outcomes using a novel digital screening tool easily deployed in clinical settings. Women 50 and older were invited to participate in the current study at the time of their annual visit to the Columbia University Integrated Women’s Health Center. Participants completed a brief tablet-based cognitive screener, the Core Cognitive Evaluation (CCE), developed by Linus Health. The CCE includes an immediate and delayed three-word recall (3 points) and clock drawing (2 points) for a maximum of 5 points (Normal>3, Borderline 2-3, Impaired<2), based on both core and error/process variables. A continuous 100-point clock score is also produced with eight indices. Of 130 eligible participants, 71(55%) agreed to participate in the study (see Table 1 for demographics). Continuous clock scores ranged from 16 to 100 (Mean(SD) = 73.15(21.2)). As described in Table 2, 62% participants scored in the Normal range, 37% in the Borderline range and 1% in the Impaired range. After a delay, 76% of participants recalled all or more of the words initially recalled. Lower scores were observed in clock drawing than delayed word recall, with spatial reasoning being the lowest the clock index score on average. See Figure 1 for clock indices. The majority of women obtained Normal CCE scores while 38% performed in the Borderline or Impaired range. By capturing subtle information about the process used to complete cognitive tasks, tablet-based testing offers a sensitive means of detecting cognitive changes. Future work is needed to evaluate screener outcomes in relation to comprehensive neuropsychological testing and cognitive change over time. A limitation of this study is the sociodemographic homogeneity of the participants. Future work aims to expand into gynecology settings with more diverse patient populations.

With the advent of monoclonal antibody therapy to treat mild cognitive impairment and mild dementia due to Alzheimer’s disease (AD) there is a need to develop tests to screen for neurocognitive difficulty that are reliable and easily deployed. The Rowan Digital Cancellation Tests (RDCT) is comprised of three tests administered using an iPad Pro. Each test was preceded by a practice trial. During practice and test trials a buzzer sounded when commission errors were made. For each test, participants worked for 180 sec. Sixteen targets were located in each quadrant. Target items were embedded within a random array modeled after Weintraub (2000). The Digital Letter Cancellation Test asked participants to circle the letter “A”. The target for the Digital Symbol Cancellation was a geometric symbol. On the Digital Letter/Symbol Switching Cancellation test participants alternated first circling a specific letter, then a specific symbol. Five outcome variables were compiled including correct hits (range 0-64), distance per correct hit; mean non-motor/‘think’ time/hit; mean Apple pencil touch; and mean commission errors. A group of 21 community-dwelling participants were assessed (age = 51.9±7.2; education = 14.9±2.0; White = 66%, female = 91.5%). A graded pattern of performance was seen for most outcome variables (Table 1) such that more targets were identified for letter>symbol>letter/symbol (p< 0.003), and mean distance traveled per target was less for letter<letter/symbol and symbol< letter/symbol (p< 0.001). Non-motor/‘think’ time and mean Apple pencil touch increased contingent on task complexity letter<symbol<letter/symbol (p< 0.016, & p< 0.004, respectively). More commission errors emerged on the letter/symbol vs letter test condition (p< 0.002). Among this sample of community dwelling, generally healthy participants, the RDCT was well-tolerated. Preliminary data generally yielded graded pattern of performance based on test complexity. When brought to scale these tests could provide a reliable method to screen for neurocognitive decline among patients with neurodegenerative illness.

The Digital Assessment of Cognition (DAC) is a self-administered digital neuropsychological protocol requiring approximately 7 minutes to administer, either in-clinic or remotely. The DAC yields numerous metrics including episodic memory and working memory indices. The current research assessed relationships between the DAC and traditional paper/pencil neuropsychological tests. 171 memory clinic patients were assessed with the DAC. A k-mean cluster analysis classified patients presenting with dysexecutive MCI ( n  = 34); amnestic MCI ( n  = 20); mixed MCI ( n  = 43); dementia ( n  = 26,) and normal cognition (NC, n  = 48). A portion of these patients ( n  = 107) were assessed with a protocol of paper/pencil neuropsychological tests assessing five neurocognitive domains: attention (WAIS-IV Digits Forward, Trails A); working memory (WMS-IV Symbol Span, letter fluency), processing speed (Trails B, WAIS-III Digit Symbol), language (Boston Naming Test, WAIS-III Similarities), and episodic memory (CVLT-9 delayed free recall/recognition). Using normative values, tests were averaged to create five paper/pencil indices. The concordance between k-mean and paper/pencil classification was 89%. When a linear, stepwise regression analysis (DAC memory index = dependent variable; five paper/pencil indices = independent variables) was conducted, the paper/pencil episodic memory index entered first (beta=0.538, p  <0.001) followed by the paper/pencil language index (beta=0.302, p  <0.001). When a similar regression analysis for the DAC executive index was conducted, the paper/pencil working memory index entered first (beta=0.503, p  <0.001), followed by the paper/pencil attention index (beta=0.288, p  <0.001), followed by the paper/pencil memory index (beta=0.163, p  <0.017). A multinomial logistic regression analysis (NC = reference group) found that the paper/pencil attention (Wald=6.15, p  <0.013) and working memory indices (Wald=7.88, p  <0.005) classified patients into the dMCI group; only the paper/pencil episodic memory index (Wald=15.08, p  <0.001) classified patients into the aMCI group; both the paper/pencil working memory (Wald=11.02, p  <0.001) and episodic memory indices (Wald=5.43, p  <0.020) classified patients into the mixed MCI group; and the paper/pencil working memory (Wald=9.11, p  <0.001), language (Wald=3.72, p  <0.050) and episodic memory indices (Wald=9.49, p  <0.001) classified patients into the dementia group These data provide evidence for both the construct and criterion validity of the DAC. The parsimony and ease associated with DAC administration/scoring suggests that the DAC can be deployed as a frontline assessment to flag emergent cognitive impairment.

BackgroundNeuropsychological (NP) assessment is crucial for diagnosing prodromal and Alzheimer's disease and related dementia (ADRD) syndromes. Yet, traditional NP scores often overlook errors and the process by which summary scores are obtained; information that can provide deeper insights into cognitive impairments and clinical heterogeneity.ObjectiveTo classify community-dwelling adults into neurocognitive phenotypes, identify NP test errors and processes that differentiate between groups, and explore their association with brain imaging measures.MethodsFramingham Heart Study (FHS) data were analyzed, focusing on NP summary scores and errors derived from the Boston Process Approach. Latent class analysis identified distinct neurocognitive phenotypes. Regression analyses assessed the relationships with NP errors and brain MRI measures.ResultsA total of 1195 participants (mean age 69.6 and 56.3% women) were included. Cognitively normal (CN), moderate-mixed, and dysexecutive impairment groups were identified. The number of Trail Making Test - Part B (TMT-B) pen lifts and TMT-B examiner-corrected errors were associated with the dysexecutive phenotype and differentiated it from the CN group (OR = 1.39, 95% CI = 1.28-1.52, p < 0.001, AUC = 0.85 and OR = 3.40, 95% CI = 2.65-4.38, p < 0.001, AUC = 0.92; respectively). Similarly, Boston Naming Test (BNT) circumlocution errors were associated with the moderate-mixed phenotype and differentiated it from the CN group (OR = 1.87, 95% CI = 1.49-2.35, p < 0.001, AUC = 0.81). These scores were significantly associated with reduced hippocampal volumes.ConclusionsDetailed NP error and process analysis enhances traditional methods, offering a comprehensive approach to identifying and understanding cognitive impairments.

The Digital Cognitive Assessment (DAC) is a 7-minute, iPad administered/scored protocol that assesses verbal episodic memory, verbal working memory, and language-related skills. The current research examined relations between DAC-memory and executive indices and family ratings for neurocognitive decline, instrumental activities of daily living (IADL) impairment, and psychiatric symptoms. 179 memory clinic patients were assessed with the DAC. Spouses or knowledgeable family members rated the severity of neurocognitive impairment, IADL decline, and psychiatric symptoms using the Everyday Cognition Scales (Ecog); the Functional Assessment Questionnaire (FAQ) and the Instrumental Activities of Daily Living – Compensation Scale (IADL-C); and the Neuropsychiatric Inventory (NPI). Partial correlations controlled for age, education, and sex found that greater informant total Ecog, FAQ and IADL-C scores were associated with lower DAC Memory and Executive summary scores. Greater IADL-C Money/Self-Management difficulty was associated with a lower DAC Memory summary score; while greater IADL-C Social Skills difficulty was associated with a lower DAC Executive summary score. A lower DAC Executive summary score was associated with greater informant rated NPI-apathy. The Digital Assessment of Cognition is powerful tool to assess neurocognitive abilities. The relations between DAC summary scores, total informant FAQ and IADL- scores; and IADL-C subscales and selected NPI-defined psychiatric problems suggest that DAC assessment of memory and executive abilities are both sensitive to gross IADL decline, and specific to differing IADL-C difficulty and selected psychiatric problems. Combining the DAC with informant IADL ratings is an effective strategy to assess for emergent MCI and dementia syndromes.

The association between preoperative cognitive status and surgical outcomes is a critical yet scarcely explored area. We assessed how preoperative cognitive status, as measured by clock drawing tests, contributed to predicting length of hospital stay, charges, pain during follow-up, and 1-year mortality beyond intraoperative variables, demographics, physical status, and comorbidities. We expanded our analysis to 6 surgical groups where sufficient data was available. Clock drawings were represented by 10 constructional features discovered by a semi-supervised deep learning algorithm, validated to differentiate between dementia and non-dementia patients. Machine learning models were trained using 5-fold cross-validation to classify postoperative outcomes. Shapley Additive Explanations analysis was used to find the most predictive features. Our results showed that the perioperative cognitive dataset served as the best dataset for 12 of 18 possible surgery-outcome combinations. Interpretability analysis showed that surgery duration was the most significant predictor of adverse outcomes, followed by anesthetic concentration. Disruptions in baseline correlations between intraoperative variables revealed that low average blood pressure and high standard deviation of blood pressure predicted adverse outcomes. Among the clock features, clock size was the most significant predictor of adverse outcomes. Our findings have relevance for improving healthcare modeling and perioperative risk prediction.