Baseline Neuropsychological Testing Research Articles

A Serious Game-Derived Index for Detecting Children With Heterogeneous Developmental Disabilities: Randomized Controlled Trial.

BackgroundDevelopmental disabilities are a set of heterogeneous delays or difficulties in one or more areas of neuropsychological development. Considering that childhood is an essential stage of brain development and developmental delays lead to personal or social burdens, the early detection of childhood developmental disabilities is important. However, early screening for developmental disabilities has been a challenge because of the fear of positive results, expensive tests, differences in diagnosis depending on examiners’ abilities, and difficulty in diagnosis arising from the need for long-term follow-up observation.ObjectiveThis study aimed to assess the feasibility of using a serious game–derived index to identify heterogeneous developmental disabilities. This study also examines the correlation between the game-derived index and existing neuropsychological test results.MethodsThe randomized controlled trial involved 48 children with either normal development or developmental disabilities. In this clinical trial, we used 19 features (6 from the Korean-Wechsler Preschool and Primary Scale of Intelligence, 8 from the Psychoeducational Profile Revised, 2 from the Bruininks-Oseretsky Test of Motor Proficiency, Second Edition, and 3 from the Pediatric Evaluation of Disability Inventory) from neuropsychological tests and 9 (7 game scores, path accuracy, and completion rate) from the serious game, DoBrain. The following analysis was conducted based on participants’ baseline information and neuropsychological test and game-derived index data for one week: (1) we compared the baseline information between the normal development and developmental disabilities groups; (2) then we measured the correlation between the game-derived index and the neuropsychological test scores for each group; and (3) we built a classifier based on the game-derived index with a Gaussian process method and then compared the area under the curve (AUC) with a model based on neuropsychological test results.ResultsA total of 16 children (normal development=9; developmental disabilities=7) were analyzed after selection. Their developmental abilities were assessed before they started to play the serious games, and statistically significant differences were found in both groups. Specifically, the normal development group was more developed than the developmental disabilities group in terms of social function, gross motor function, full-scale IQ, and visual motor imitation, in that order. Similarly, the normal development group obtained a higher score on the game-derived index than the developmental disabilities group. In the correlation analysis between the game-derived index and the neuropsychological tests, the normal development group showed greater correlation with more variables than the developmental disabilities group. The game-derived index–based model had an AUC=0.9, a similar detection value as the neuropsychological test–based model’s AUC=0.86.ConclusionsA game-derived index based on serious games can detect children with heterogenous developmental disabilities. This suggests that serious games can be used as a potential screening tool for developmental disabilities.Trial RegistrationClinical Research Information Service KCT0003247; https://cris.nih.go.kr/cris/en/search/search_result_st01 .jsp?seq=12365

The Influence of Atypical Sleep Before Baseline Concussion Testing

Abstract Objective To examine the role of an atypical night of sleep prior to baseline neuropsychological testing on symptom reporting and cognitive functioning in student-athletes. Method 182 (M = 138, F = 44) athletes were assessed on neuropsychological battery at baseline. Athletes were categorized as sleeping a typical amount (within 1.5 hours, N = 128) or less (> 1.5 hours less, N = 54) the night prior to baseline. The Cognitive Health Questionnaire (CHQ) assessed typical levels of sleep and the Immediate Post-Concussion Assessment and Cognitive Testing (ImPACT) assessed hours of sleep the night before. Independent samples t-tests compared the two groups on the following outcome measures: affective, somatic, sleep, and cognitive post-concussion symptom scale (PCSS) clusters, headache, Beck-Depression Inventory-Fast Screen (BDI-FS), and composites of memory and attention/processing speed. Results Athletes getting less sleep than typical the night before a baseline assessment reported significantly more depression symptoms on the BDI-FS (p < .001) and significantly more symptoms on all PCSS symptoms scales: affective (p < .001), cognitive (p < .001), physical (p < .001), and sleep (p = .001). A trend in the same direction was present for headache (p = .06). The groups did not significantly differ on performance on either composite of cognitive functioning (p > .05). Conclusions Sleeping less than the typical amount the night before a baseline assessment results in self-reported higher levels of depression symptoms across all domains of the PCSS.

A comparison study assessing neuropsychological outcome of patients with post-operative pediatric cerebellar mutism syndrome and matched controls after proton radiation therapy.

Post-operative pediatric cerebellar mutism syndrome (CMS), characterized by mutism, ataxia/hypotonia, and emotional lability, can result in long-term deficits following resection of posterior fossa (PF) tumors. This longitudinal study compared neuropsychological outcomes of pediatric patients with post-operative CMS to a matched control patient group without CMS. Fifty-eight PF tumor patients received post-surgical proton radiation therapy (PRT) and testing at baseline and at ≥ 1-year post-PRT over a 10-year period. Of these, 18 (31%) had post-operative CMS with baseline and follow-up neuropsychological test data. Those participants were matched to 18 controls by tumor location, age, gender, and handedness; no significant group differences were found at baseline for clinical/demographic variables. Total mean age at baseline was 7.26years (SD = 4.42); mean follow-up interval was 3.26years (SD = 2.24). Areas assessed: overall intelligence, expressive and receptive vocabulary, visuomotor integration, fine motor speed, inhibition, emotional control, depression, and anxiety. Patients were 52% male; 86% medulloblastoma/14% ependymoma; 86% craniospinal irradiation/14% focal radiation; and 86% chemotherapy. No group differences were found between most mean baseline scores; expressive vocabulary and fine motor speed were significantly lower in the post-operative CMS group (p< 0.05). Mean change scores revealed no significant differences for the sample; scores were within the normal range except fine motor skills were impaired for both groups. Longitudinal neuropsychological outcomes for post-operative pediatric CMS patients did not differ significantly from matched controls without this condition. Patients were in the normal range in all areas except fine motor speed, which was impaired for both groups independent of CMS diagnosis.

Prediction of cognitive progression in Parkinson's disease using three cognitive screening measures

IntroductionCognitive impairment is a common complication of Parkinson's disease (PD) and identifying risk factors for progression to Parkinson's disease dementia (PDD) is important. However, little research has been done comparing the utility of commonly used cognitive screening tests in predicting cognitive progression in PD. MethodsWe retrospectively reviewed data from patients with PD enrolled in the Pacific Udall Center who had baseline and longitudinal neuropsychological and global cognitive screening tests. The diagnostic accuracies of 3 common screening tests were compared: Montreal Cognitive Assessment (MoCA), Mattis Dementia Rating Scale (DRS-2), and Mini Mental Status Examination (MMSE). Cognitive diagnoses of PD with mild cognitive impairment (PD-MCI) and PDD were based on full neuropsychological testing and established Movement Disorder Society criteria. Logistic regression and Cox proportional hazards regression models were used to examine predictors of cognitive decline. ResultsFour hundred seventy patients for whom scores on all 3 screening tests were available from the same assessment were included in a cross-sectional analysis. The MoCA demonstrated the best overall diagnostic accuracy for PD-MCI (AUC = 0.79, sensitivity = 76.4%) and for PDD (AUC = 0.89, sensitivity = 81.0%) compared to the DRS-2 and MMSE.A longitudinal analysis was performed on the subset of patients (316/470; 67.2%) who were nondemented at baseline and had undergone two or more assessments. After controlling for covariates, the MoCA was the only test associated with progression to PDD (OR = 1.27 95% CI 1.1–1.5, p = 0.001) and faster time to dementia (HR = 1.3, 95% CI 1.1–1.4, p < 0.0001). ConclusionsThis study provides additional support for the use of the MoCA as a primary screening tool for cognitive impairment in PD and is the first to show that the MoCA is a predictor of conversion to PDD.

B Sharp—The cognitive effects of a pilot community music program for people with dementia-related disorders

IntroductionDementia has been described as the greatest global challenge for healthcare in the 21st century. Pharmaceutical interventions have dominated dementia treatment despite limited efficacy. There is increasing interest in alternatives to delay the progression of cognitive decline, such as community-based programs, promoting social and stimulating experiences. This article discusses a pilot music-based community program (B Sharp) for persons with dementia-related disorders. MethodIn the pilot study, we assessed 23 persons with dementia-related disorders who, with their caregivers, attended the symphony season and accompanying social hours over a 10-month period. Participants completed a baseline and follow-up brief neuropsychological test to assess cognitive changes. ResultsSignificant improvements were observed between the pre– and post–B Sharp program assessments (P < .010). DiscussionResults support the feasibility of the B Sharp program as a community-based program to target cognitive decline. Additional research is needed to understand the mechanisms involved in the improvements observed in this program.

Half of purposeful sandbaggers undetected by ImPACT's embedded invalidity indicators

ObjectiveThe primary objective of this study is to determine the ability of embedded invalidity indicators (EIIs) within the Immediate Post-concussion Assessment and Cognitive Test (ImPACT) to accurately identify individuals purposefully underperforming (sandbagging) on the baseline assessment. The secondary objective is to determine if any of the 5 specific EIIs are more or less likely to identify purposeful sandbaggers.BackgroundSandbagging baseline neuropsychological tests is a growing problem with significant potential consequences including premature post-concussion clearance.Design/methodsVolunteers were recruited to complete a baseline ImPACT assessment. Participants were randomized to either a control group or a coached sandbagging group. Primary outcome measures were the number of participants identified as invalid via any EII, as well as mean raw composite scores and percentiles for each sub-section within the ImPACT assessment.ResultsSeventy-seven participants (37 control and 40 sandbaggers) completed the study. Only half (50%, n = 20) of the purposeful sandbaggers were identified via any EII. Appropriately, no participants in the control group were identified as invalid. The Working Memory EII correctly identified 40% of the purposeful sandbaggers, and the Three Letters EII identified 35% of purposeful sandbaggers. All other EIIs identified 15% of purposeful sandbaggers. Twenty-six purposeful sandbaggers achieved at least 1 composite sub-score, 1st percentile; 27% of those were not identified via any EII. One participant scored ≤ 1st percentile in every composite category and was not identified via any EII.ConclusionSandbagging baseline ImPACT assessments without detection likely occurs more often than previous literature suggests. Half of purposeful sandbaggers were not identified via current EIIs, and 3 of 5 EIIs identified 15% of purposeful sandbaggers. Re-evaluation or recalibration of ImPACT's current EIIs may be appropriate.Disclosures: Dr. Raab has nothing to disclose. Dr. Peak has nothing to disclose.

Neuropsychological predictors of conversion from mild cognitive impairment to Alzheimer\u2019s disease: a feature selection ensemble combining stability and predictability

BackgroundPredicting progression from Mild Cognitive Impairment (MCI) to Alzheimer’s Disease (AD) is an utmost open issue in AD-related research. Neuropsychological assessment has proven to be useful in identifying MCI patients who are likely to convert to dementia. However, the large battery of neuropsychological tests (NPTs) performed in clinical practice and the limited number of training examples are challenge to machine learning when learning prognostic models. In this context, it is paramount to pursue approaches that effectively seek for reduced sets of relevant features. Subsets of NPTs from which prognostic models can be learnt should not only be good predictors, but also stable, promoting generalizable and explainable models.MethodsWe propose a feature selection (FS) ensemble combining stability and predictability to choose the most relevant NPTs for prognostic prediction in AD. First, we combine the outcome of multiple (filter and embedded) FS methods. Then, we use a wrapper-based approach optimizing both stability and predictability to compute the number of selected features. We use two large prospective studies (ADNI and the Portuguese Cognitive Complaints Cohort, CCC) to evaluate the approach and assess the predictive value of a large number of NPTs.ResultsThe best subsets of features include approximately 30 and 20 (from the original 79 and 40) features, for ADNI and CCC data, respectively, yielding stability above 0.89 and 0.95, and AUC above 0.87 and 0.82. Most NPTs learnt using the proposed feature selection ensemble have been identified in the literature as strong predictors of conversion from MCI to AD.ConclusionsThe FS ensemble approach was able to 1) identify subsets of stable and relevant predictors from a consensus of multiple FS methods using baseline NPTs and 2) learn reliable prognostic models of conversion from MCI to AD using these subsets of features. The machine learning models learnt from these features outperformed the models trained without FS and achieved competitive results when compared to commonly used FS algorithms. Furthermore, the selected features are derived from a consensus of methods thus being more robust, while releasing users from choosing the most appropriate FS method to be used in their classification task.

Detecting Non-cognitive Features of Prodromal Neurodegenerative Diseases.

: Background: Prodromal Neurodegenerative Disease (ND) due to tauopathies such as Alzheimer’s Disease (AD) and Synucleinopathies (SN) such as Parkinson's Disease (PD) and Dementia with Lewy Bodies (DLB) present subtly. Although ND are considered cognitive disorders, in fact ND present with behavioral and even medical symptomatology years to decades prior to the onset of cognitive changes. Recognizing prodromal ND syndromes is a public health priority because ND is common, disabling and expensive. Diagnosing prodromal ND in real world clinical settings is challenging because ND of the same pathology can present with different symptoms in different people. Individual variability in nature and variability in nurture across the life course influence how ND pathology manifests clinically. The objective of this study was to describe how non-cognitive symptoms from behavioral, medical, neurological and psychiatric domains cluster in prodromal and early stages of ND.Methods: This was an observational study of patients receiving routine clinical care for memory disorders. All patients receiving a standardized evaluation including complete neurological history and examination and standardized brief neuropsychological testing. A Principal Component Analysis (PCA) considering emotion, motor, sensory and sleep factors was performed on the entire sample of patients in order to identify co-occurring symptom clusters. All patients received a consensus diagnosis adjudicated by at least two dementia experts. Patients were grouped into Cognitively Normal, Detectable Cognitive Impairment, and Mild Cognitive Impairment categories due to AD and/or PD/LBD or NOS pathology. Symptom cluster scores were compared between clinical diagnostic groups.Results: In this study 165 patients completed baseline neuropsychological testing and reported subjective measures of non-cognitive symptoms. Four syndrome specific symptom factors emerged and eight non-specific symptom factors. Symptoms of personality changes, paranoia, hallucinations, cravings, agitation, and changes in appetite grouped together into a cluster consistent with an “SN Non-motor Phenotype”. Appetite, walking, balance, hearing, increased falls, and dandruff grouped together into a cluster consistent with an “SN Motor Phenotype”. The Prodromal AD phenotype included symptoms of anxiety, irritability, apathy, sleep disturbance and social isolation. The fourth factor included symptoms of increased sweating, twitching, and tremor grouped into a cluster consistent with an Autonomic phenotype.Conclusions: Non-cognitive features can be reliably measured by self-report in busy clinical settings. Such measurement can be useful in distinguishing patients with different etiologies of ND. Better characterization of unique, prodromal, non-cognitive ND trajectories could improve public health efforts to modify the course of ND for all patients at risk.

Prediction Models of Cognitive Trajectories in Patients with Nonamnestic Mild Cognitive Impairment

To evaluate prediction models of cognitive trajectories in patients with nonamnestic mild cognitive impairment (naMCI) using group-based trajectory analysis, we evaluated 121 patients with naMCI who underwent at least their first three yearly assessments. Group-based trajectory models were used to classify cognitive trajectories based on Clinical Dementia Rating Sum of Boxes scores over four years in patients with naMCI. A total of 22 patients (18.2%) were classified into the “fast-decliners” group, while 99 patients (81.8%) were classified into the “slow-decliners” group. The mean age was higher in the fast-decliners than in the slow-decliners (p = 0.037). Compared to the slow-decliners, the fast-decliners were more frequently impaired in the domains of language (p = 0.038) and frontal/executive functions (p = 0.042), and had more frequent multiple-domain cognitive impairment (p = 0.006) on baseline neuropsychological tests. The rate of conversion to dementia was significantly higher in the fast-decliners than in the slow-decliners (86.4% vs. 10.1%, p < 0.001). Our findings showed that there are indeed distinct patterns of cognitive trajectories in patients with naMCI. Close observation of naMCI patients’ baseline demographic and clinical profiles in clinical settings may help identify individuals at greatest risk for dementia.

Neuropsychological Predictors of Long-Term (10 Years) Mild Cognitive Impairment Stability.

Although the diagnosis of mild cognitive impairment (MCI) corresponds to a condition likely to progress to dementia, essentially Alzheimer's disease, longitudinal studies have shown that some patients may not convert to dementia and maintain the diagnosis of MCI even after many years. To determine whether patients that maintain the diagnosis of MCI in the long term (10 years) are really stable or just declining slowly, and to identify clinical and neuropsychological characteristics associated with long-term stability. The Cognitive Complaints Cohort (CCC) was searched for MCI cases who maintained that diagnosis for at least 10 years. For each long-term-stable MCI patient, two MCI patients that converted to dementia during follow-up, matched for age and education, were selected from the same database. The baseline and last neuropsychological evaluations for long-term-stable MCI and converter MCI were compared. Baseline neuropsychological predictors of long-term stability were searched for. Long-term-stable MCI (n = 22) and converter MCI (n = 44) patients did not differ in terms of gender distribution, education, age at first assessment and time between symptom onset and first evaluation. Time of follow-up was on average 11 years for long-term-stable MCI and 3 years for converter MCI. The baseline and follow-up neuropsychological tests were not significantly different in long-term-stable MCI patients, whereas a general decline was observed in converter MCI patients. Higher scores on one memory test, the Word Delayed Total Recall, and on the non-verbal abstraction test, Raven's Progressive Matrices, at the baseline predicted long-term (10 years) clinical stability. Some patients with MCI remain clinically and neuropsychologically stable for a decade. Better performances at baseline in memory and non-verbal abstraction tests predict long-term stability.

Does a cognitive stress test predict progression from mild cognitive impairment to dementia equally well in clinical versus population-based settings?

Participants with MCI in the clinical (n = 184) and population-based (n = 435) samples were followed for up to four years. We employed receiver operating characteristic (ROC) methods to establish optimal thresholds for four different SIT indices. Threshold performance was compared in the two samples using logistic and Cox proportional hazard regression models. Within four years, 42 (22.8%) MCI individuals in the clinical sample and 45 (10.3%) individuals in the population-based sample progressed to dementia. Overall classification accuracy of SIT thresholds ranged from 61.4% to 84.8%. Different subtests of the SIT had slightly different performance characteristics in the two samples. However, regression models showed that thresholds established in the clinical sample performed similarly in the population sample before and after adjusting for demographics and other baseline neuropsychological test scores. Despite differences in demographic composition and progression rates, baseline SIT scores predicted progression from MCI to dementia similarly in both samples. Thresholds that best predicted progression were slightly below thresholds established for distinguishing between amnestic MCI and cognitively normal subjects in clinical practice. This confirms the utility of the SIT in both clinical and population-based samples and establishes thresholds most predictive of progression of individuals with MCI.

Unmasking the benefits of donepezil via psychometrically precise identification of mild cognitive impairment: A secondary analysis of the ADCS vitamin E and donepezil in MCI study

IntroductionCriteria for mild cognitive impairment (MCI) used in many clinical trials are susceptible to “false-positive (FP)” errors that can be avoided by an actuarial psychometric approach. MethodsCluster analysis was applied to baseline neuropsychological test data from 756 MCI participants in the Alzheimer's Disease Cooperative Study donepezil trial. Treatment groups were compared after FP MCI cases were removed. ResultsCluster analyses revealed three groups: “single-domain amnestic MCI” (31%), “multi-domain amnestic MCI” (39%), and “FP MCI” (30%). After removing FP MCI cases, the donepezil treatment group had a lower rate of progression to Alzheimer's disease and better performance on cognitive tests than the placebo/vitamin E group. DiscussionRemoval of FP MCI diagnoses unmasked beneficial effects of donepezil, despite a 30% reduction in sample size. MCI subject selection based on actuarial methods with comprehensive neuropsychological test data can result in more efficient clinical trials and improved ability to detect treatment effects.

Amyloid β Deposition and Suspected Non-Alzheimer Pathophysiology and Cognitive Decline Patterns for 12 Years in Oldest Old Participants Without Dementia

ImportanceThe prevalence of pathologic conditions of the brain associated with Alzheimer disease increases strongly with age. Little is known about the distribution and clinical significance of preclinical biomarker staging in the oldest old, when most individuals without dementia are likely to have positive biomarkers.ObjectiveTo compare the patterns of long-term cognitive decline in multiple domains by preclinical biomarker status in the oldest old without dementia.Design, Setting, and ParticipantsA longitudinal observational study with a mean (SD) of 12.2 (2.2) years (range 7.2-15.1 years) of follow-up was conducted in an academic medical center from August 24, 2000, to January 14, 2016, including and extending observations from the Ginkgo Evaluation of Memory study. A total of 197 adults who had completed the Ginkgo Evaluation of Memory study, were free of dementia, and were able to undergo magnetic resonance imaging were eligible for a neuroimaging study in 2009. Of these patients, 175 were included in the present analyses; 140 (80%) were cognitively normal and 35 (20%) had mild cognitive impairment.Main Outcomes and MeasuresBiomarker groups included amyloid β negative (Aβ−)/neurodegeneration negative (ND−), amyloid β positive (Aβ+)/ND−, Aβ−/neurodegeneration positive (ND+), and Aβ+/ND+ based on Pittsburgh Compound B retention and hippocampal volume in 2009. Participants completed baseline neuropsychological testing from 2000 to 2002 and annual testing from 2004 to 2016. Domains included memory, executive function, language, visual-spatial reasoning, and attention and psychomotor speed. Slopes of decline were evaluated with linear mixed models adjusted for age, sex, and years of education.ResultsOf the 175 participants (71 women and 104 men), at imaging, mean (SD) age was 86.0 (2.9) years (range, 82-95 years). A total of 42 participants (24.0%) were Aβ−/ND−, 32 (18.3%) were Aβ+/ND−, 35 (20.0%) were Aβ−/ND+, and 66 (37.7%) were Aβ+/ND+. On all cognitive measures, the Aβ+/ND+ group showed the steepest decline. Compared with the Aβ−/ND− group, the amyloid deposition alone (Aβ+/ND−) group showed faster decline on tests of verbal and visual memory (–0.3513; 95% CI, –0.5269 to –0.1756), executive function (0.0158; 95% CI, 0.0013-0.0303), and language (–0.1934; 95% CI, –0.3520 to –0.0348). The Aβ−/ND+ group showed faster visual memory decline than the Aβ−/ND− reference group (–0.3007; 95% CI, –0.4736 to –0.1279).Conclusions and RelevanceIn the oldest old without dementia, presence of either or both Aβ and hippocampal atrophy is typical (>75%). Isolated hippocampal volume atrophy is associated only with greater decline in memory. However, isolated Aβ is associated with decline in memory plus language and executive functions. These findings suggest different underlying pathophysiologic processes in the Aβ+/ND− and Aβ−/ND+ groups.

Cognition and the course of prodromal Parkinson's disease.

Prospective data on cognition in prodromal Parkinson's disease are limited. The objectives of this study were to assess in prodromal PD (1) if baseline cognition predicts conversion to clinical PD, (2) if baseline dopamine transporter binding predicts longitudinal changes in cognition, and (3) if impaired olfaction predicts future cognitive decline. Prodromal participants were 136 hyposmic individuals enrolled in the Parkinson Associated Risk Study. We examined baseline neuropsychological test performance in PD converters versus nonconverters and the association between baseline dopamine transporter binding and change in cognition. An additional 73 normosmic individuals were included in analyses of the relationship between hyposmia and cognitive decline. In prodromal participants, baseline cognitive scores did not significantly predict conversion, but converters performed numerically worse on 5 of the 6 cognitive domains assessed, with the greatest differences in executive function/working memory (0.68 standard deviation lower) and global cognition (0.64 standard deviation lower). Lower baseline dopamine transporter binding predicted greater future decline in processing speed/attention (P = 0.02). Hyposmia predicted greater future decline in language (P = 0.005) and memory (P = 0.01) abilities. Given hyposmia in the general population predicts cognitive decline, the role of cognition in predicting conversion in prodromal PD needs to be assessed in large cohorts followed long-term. The dopamine system may be associated with changes in processing speed/attention in individuals at risk for PD. © 2017 International Parkinson and Movement Disorder Society.

Dementia-Predicting Cognitive Risk Score and Its Correlation with Cortical Thickness in Parkinson Disease

Background: We developed a risk score system to predict risks of developing dementia in individual Parkinson disease (PD) patients using baseline neuropsychological tests. Methods: A total of 216 nondemented PD patients underwent a baseline neuropsychological evaluation and were followed up for a mean of 2.7 (±1.1) years. Univariate Cox regression models controlled for age, gender, and education selected neuropsychological tests individually predicting dementia risk. Then, a multivariate Cox regression model combined them into a cognitive risk score system. Cortical areas correlating with cognitive risk score were investigated using a separate MRI data set from 207 nondemented PD patients. Results: Fifty-two patients (23.9%) developed dementia. The univariate Cox regression analyses identified the confrontational naming and semantic fluency tests, frontal/executive function tests, immediate verbal memory test, and visuospatial function test as predicting dementia risk. The calculated cognitive risk score (range 53-188) predicted future dementia with moderate accuracy (integrated area under the curve = 0.79; 95% CI: 0.73-0.85). A higher cognitive risk score correlated with cortical thinning in the right anteromedial temporal cortex, bilateral posterior cingulate cortex, right anterior cingulate cortex, left parahippocampal gyrus, and right superior frontal cortex in a separate MRI data set. Conclusion: The cognitive risk score system is a useful approach to predict the dementia risk among PD patients.

COGNITIVE TRAJECTORIES IN PATIENTS WITH NON-AMNESTIC MILD COGNITIVE IMPAIRMENT: A LONGITUDINAL STUDY

There are few studies that evaluate the clinical outcomes of patients with non-amnestic mild cognitive impairment (naMCI). The purpose of this study was to evaluate the cognitive trajectories in patients with naMCI and compared the baseline neuroimaging and neuropsychological features between fast and slow decliners. We recruited 121 patients who had been diagnosed as naMCI and had at least three years follow up. Worsening on the Clinical Dementia Rating sum of boxes (CDR-SOB) was defined as an outcome of clinical progression. Finite mixture modeling was employed to examine the quitting trajectories by the SAS Proc Traj group-based modeling procedure. Cortical thickness was measured using a surface-based method. We compared baseline cortical thickness, neuropsychological tests, and other risk factors between fast and slow decliners. A total 22 patients with naMCI progressed clinically (fast decliners), and 99 patients remained stable over 3 years (slow decliners). Compared to slow decliners, fast decliners were older. Fast decliners had lower raw scores on memory tasks, language impairment, and frontal/executive dysfunction at baseline neuropsychological tests, and more converted to dementia compared to slow decliners. In addition, fast decliners showed cortical thinning in the left dorsolateral prefrontal cortex and bilateral medial temporal lobes, compared to slow decliners.

Neuropsychological Profiles Differentiate Alzheimer Disease from Subcortical Ischemic Vascular Dementia in an Autopsy-Defined Cohort

Background/Aims: The aim of this study was to assess the ability of neuropsychological tests to differentiate autopsy-defined Alzheimer disease (AD) from subcortical ischemic vascular dementia (SIVD). Methods: From a sample of 175 cases followed longitudinally that underwent autopsy, we selected 23 normal controls (NC), 20 SIVD, 69 AD, and 10 mixed cases of dementia. Baseline neuropsychological tests, including Memory Assessment Scale word list learning test, control oral word association test, and animal fluency, were compared between the three autopsy-defined groups. Results: The NC, SIVD, and AD groups did not differ by age or education. The SIVD and AD groups did not differ by the Global Clinical Dementia Rating Scale. Subjects with AD performed worse on delayed recall (p < 0.01). A receiver operating characteristics analysis comparing the SIVD and AD groups including age, education, difference between categorical (animals) versus phonemic fluency (letter F), and the first recall from the word learning test distinguished the two groups with a sensitivity of 85%, specificity of 67%, and positive likelihood ratio of 2.57 (AUC = 0.789, 95% CI 0.69-0.88, p < 0.0001). Conclusion: In neuropathologically defined subgroups, neuropsychological profiles have modest ability to distinguish patients with AD from those with SIVD.

An Examination of Adolescent Athletes and Non-athletes on Baseline Neuropsychological Test Scores

An estimated 15.3 million adolescent students are enrolled in high school. However, approximately 7.6 million participate in athletics. Research has examined different demographics in high school athletes, however athletic participation may play a larger role in test performance than previously thought. Currently, research involving concussion assessment utilizes non-injured athletes as controls, but due to the intense nature of athletics, this may not be appropriate. PURPOSE: Examine differences between athletes and non-athletes using a common computerized neuropsychological test. METHODS: 662 adolescent high school students (athletes (ATH): n = 383, non-athletes (NON): n = 279) were administered a computerized neuropsychological test battery (ImPACT ®) during baseline concussion assessment. Differences between groups were calculated using a one-way ANOVA. All statistical analyses were conducted using SPSS 23.0. Significance levels were set a priori at p ≤ .05. RESULTS: Statistically significant differences were found between ATH and NON in Composite Verbal Memory (F(1, 660) = 4.653, p = .031), Composite Reaction Time (F(1, 660) = 15.869, p ≤ .001), and Total Symptom Score (F(1, 660) = 38.996, p ≤ .001). Non-athletes performed better on verbal memory and reported more symptoms, while ATH had faster reaction times. No significant differences were found in composite visual memory, composite visual motor, and composite impulse control (p ≥ 0.05). CONCLUSION: Significant differences were found between ATH and NON for symptom reporting, verbal memory, and reaction time. Athletes may have additional training or motivational factors during testing which may affect participation or return to play decisions. Overall, these significant differences in baseline performance should be accounted for when making concussion diagnostic and management decisions. Future research should be conducted to examine the influence of athletic participation on the recovery process to see if non-athletes can be used as healthy controls. Supported by: The National Operating Committee on Standards for Athletic Equipment (NOCSAE).

Parahippocampal and Entorhinal Resection Extent Predicts Verbal Memory Decline in an Epilepsy Surgery Cohort.

The differential contribution of medial-temporal lobe regions to verbal declarative memory is debated within the neuroscience, neuropsychology, and cognitive psychology communities. We evaluate whether the extent of surgical resection within medial-temporal regions predicts longitudinal verbal learning and memory outcomes. This single-center retrospective observational study involved patients with refractory temporal lobe epilepsy undergoing unilateral anterior temporal lobe resection from 2007 to 2015. Thirty-two participants with Engel Class 1 and 2 outcomes were included (14 left, 18 right) and followed for a mean of 2.3 years after surgery (±1.5 years). Participants had baseline and postsurgical neuropsychological testing and high-resolution T1-weighted MRI scans. Postsurgical lesions were manually traced and coregistered to presurgical scans to precisely quantify resection extent of medial-temporal regions. Verbal learning and memory change scores were regressed on hippocampal, entorhinal, and parahippocampal resection volume after accounting for baseline performance. Overall, there were no significant differences in learning and memory change between patients who received left and right anterior temporal lobe resection. After controlling for baseline performance, the extent of left parahippocampal resection accounted for 27% (p = .021) of the variance in verbal short delay free recall. The extent of left entorhinal resection accounted for 37% (p = .004) of the variance in verbal short delay free recall. Our findings highlight the critical role that the left parahippocampal and entorhinal regions play in recall for verbal material.

A Delayed Recall Battery as a Sensitive Screening for Mild Cognitive Impairment: Follow-up Study of Memory Clinic Patients after 10 years

I examined the predictive value of the combination of three delayed recall tests to distinguish (1) those with probable Alzheimer's disease (AD) from those within normal range, and (2) those with Mild cognitive impairment (MCI) from those within normal range. The data from 90 visitors to a memory clinic in Tokyo was used. I first examined patients clinically, neuroradiologically, and excluded the mental and neurological illness. AD was diagnosed according to the NINCDS-ADRDA criteria, MCI according to the criteria of Petersen et al.. Normal must be free from any disease examined above. After the diagnosis, the baseline neuropsychological tests were performed for all participants; the Mini Mental State Examination, Raven's Colored Progressive Matrices, the Stroop Test, a 10-words list learning and recall test, a story recall test, and the Rey-Osterrieth Complex Figure Test. After 10 years, all patients were reassessed and diagnosed again. Of the MCI patients for follow-up (n=29), 19 were converted to AD, while 5 not. One died. 4 lost. All AD patients (n=30) remained as AD. The combination of 3 delayed recall battery provides clinically useful predictive values for both AD and MCI in a memory clinics and dementia research clinics.