Assessing the Utility of the Montreal Cognitive Assessment in Screening for Cognitive Impairment in Patients With Systemic Lupus Erythematosus.

OBJECTIVE: Screening for cognitive impairment (CI) in systemic lupus erythematosus (SLE) relies on the American College of Rheumatology (ACR) neuropsychological battery (NB). By studying the concurrent criterion validity, our goal was to assess the Montreal Cognitive Assessment (MoCA) as a screening tool for CI compared to the ACR-NB and to evaluate the added value of the MoCA to the Automated Neuropsychological Assessment Metrics (ANAM). METHODS: A total of 285 adult SLE patients were administered the ACR-NB, MoCA, and ANAM. For the ACR-NB, patients were classified as having CI if there was a Z score of ≤-1.5 in ≥2 domains. The area under the curve (AUC) and sensitivities/specificities were determined. A discriminant function analysis was applied to assess the ability of the MoCA to differentiate between CI, undetermined CI, and non-CI patients. RESULTS: CI was not accurately identified by the MoCA compared to the ACR-NB (AUC of 0.66). Sensitivity and specificity were poor at 50% and 69%, respectively, for the cutoff of 26, and 80% and 45%, respectively, for the cutoff of 28. The MoCA had a low ability to identify CI status. The addition of the MoCA to the ANAM led to improvement on the AUC by only 2.5%. CONCLUSION: The MoCA does not have adequate concurrent criterion validity to accurately identify CI in patients with SLE. The low specificity of the MoCA may lead to overdiagnosis and concern among patients. Adding the MoCA to the ANAM does not substantially improve the accuracy of the ANAM. These results do not support using the MoCA as a screening tool for CI in patients with SLE.

Common Data Elements to Facilitate Sharing and Re-use of Participant-Level Data: Assessment of Psychiatric Comorbidity Across Brain Disorders.

The Ontario Brain Institute's "Brain-CODE" is a large-scale informatics platform designed to support the collection, storage and integration of diverse types of data across several brain disorders as a means to understand underlying causes of brain dysfunction and developing novel approaches to treatment. By providing access to aggregated datasets on participants with and without different brain disorders, Brain-CODE will facilitate analyses both within and across diseases and cover multiple brain disorders and a wide array of data, including clinical, neuroimaging, and molecular. To help achieve these goals, consensus methodology was used to identify a set of core demographic and clinical variables that should be routinely collected across all participating programs. Establishment of Common Data Elements within Brain-CODE is critical to enable a high degree of consistency in data collection across studies and thus optimize the ability of investigators to analyze pooled participant-level data within and across brain disorders. Results are also presented using selected common data elements pooled across three studies to better understand psychiatric comorbidity in neurological disease (Alzheimer's disease/amnesic mild cognitive impairment, amyotrophic lateral sclerosis, cerebrovascular disease, frontotemporal dementia, and Parkinson's disease).

Validation of the automated neuropsychological assessment metrics for assessing cognitive impairment in systemic lupus erythematosus.

OBJECTIVE: We previously demonstrated the utility of the Automated Neuropsychological Assessment Metrics (ANAM) for screening cognitive impairment (CI) in patients with systemic lupus erythematosus (SLE) and developed composite indices for interpreting ANAM results. Our objectives here were to provide further support for the ANAM's concurrent criterion validity against the American College of Rheumatology neuropsychological battery (ACR-NB), identify the most discriminatory subtests and scores of the ANAM for predicting CI, and provide a new approach to interpret ANAM results using Classification and Regression Tree (CART) analysis. METHODS: 300 adult SLE patients completed an adapted ACR-NB and ANAM on the same day. As per objectives, six models were built using combinations of ANAM subtests and scores and submitted to CART analysis. Area under the curve (AUC) was calculated to evaluate the ANAM's criterion validity compared to the adapted ACR-NB; the most discriminatory ANAM subtests and scores in each model were selected, and performance of models with the highest AUCs were compared to our previous composite indices; decision trees were generated for models with the highest AUCs. RESULTS: Two models had excellent AUCs of 86 and 89%. Eight most discriminatory ANAM subtests and scores were identified. Both models demonstrated higher AUCs against our previous composite indices. An adapted decision tree was created to simplify the interpretation of ANAM results. CONCLUSION: We provide further validity evidence for the ANAM as a valid CI screening tool in SLE. The decision tree improves interpretation of ANAM results, enhancing clinical utility.

Metrics and definitions used in the assessment of cognitive impairment in systemic lupus erythematosus: A systematic review.

OBJECTIVE: To review: 1) degree of conformity to the American College of Rheumatology neuropsychological battery (ACR-NB) among studies that used a NB, 2) review definitions of cognitive impairment (CI) from studies that used a NB, and 3) characterize measurement tools used to assess CI in systemic lupus erythematosus (SLE). METHODS: The literature search was conducted in Ovid Medline, Embase, and PsycINFO for articles on CI in adult SLE patients. We reviewed studies that used a NB and compared their tests to the ACR-NB to assess the degree of conformity. Definitions of CI from studies that used a NB were reviewed when sufficient information was available. We reviewed and categorized CI measurement tools into four broad categories: NB, screening, incomplete/mixed batteries, and computerized batteries. RESULTS: Of 8727 references, 118 were selected for detailed review and 97 were included in the final analysis. Of 43 studies that used a NB, none of the studies used the ACR-NB exactly as published. Many studies supplemented with other tests. Overall, there was inconsistent use of ACR-NB tests. Definitions for CI varied, with cut-offs ranging from 1 to 3 standard deviations below normative values on domains/tests varying in type and number. The most frequently used measurement tool for assessing CI in SLE was a NB. Use of screening tests and computerized batteries have also increased over the last decade. CONCLUSION: The assessment and definition of CI in SLE remains heterogeneous. A consensus meeting to address existing inconsistencies should be considered to harmonize the field of CI in SLE.

Exploratory Assessment of K-means Clustering to Classify 18F-Flutemetamol Brain PET as Positive or Negative.

RATIONALE: We evaluated K-means clustering to classify amyloid brain PETs as positive or negative. PATIENTS AND METHODS: Sixty-six participants (31 men, 35 women; age range, 52-81 years) were recruited through a multicenter observational study: 19 cognitively normal, 25 mild cognitive impairment, and 22 dementia (11 Alzheimer disease, 3 subcortical vascular cognitive impairment, and 8 Parkinson-Lewy Body spectrum disorder). As part of the neurocognitive and imaging evaluation, each participant had an 18F-flutemetamol (Vizamyl, GE Healthcare) brain PET. All studies were processed using Cortex ID software (General Electric Company, Boston, MA) to calculate SUV ratios in 19 regions of interest and clinically interpreted by 2 dual-certified radiologists/nuclear medicine physicians, using MIM software (MIM Software Inc, Cleveland, OH), blinded to the quantitative analysis, with final interpretation based on consensus. K-means clustering was retrospectively used to classify the studies from the quantitative data. RESULTS: Based on clinical interpretation, 46 brain PETs were negative and 20 were positive for amyloid deposition. Of 19 cognitively normal participants, 1 (5%) had a positive 18F-flutemetamol brain PET. Of 25 participants with mild cognitive impairment, 9 (36%) had a positive 18F-flutemetamol brain PET. Of 22 participants with dementia, 10 (45%) had a positive 18F-flutemetamol brain PET; 7 of 11 participants with Alzheimer disease (64%), 1 of 3 participants with vascular cognitive impairment (33%), and 2 of 8 participants with Parkinson-Lewy Body spectrum disorder (25%) had a positive 18F-flutemetamol brain PET. Using clinical interpretation as the criterion standard, K-means clustering (K = 2) gave sensitivity of 95%, specificity of 98%, and accuracy of 97%. CONCLUSIONS: K-means clustering may be a powerful algorithm for classifying amyloid brain PET.

Structural Brain Magnetic Resonance Imaging to Rule Out Comorbid Pathology in the Assessment of Alzheimer's Disease Dementia: Findings from the Ontario Neurodegenerative Disease Research Initiative (ONDRI) Study and Clinical Trials Over the Past 10 Years.

BACKGROUND/OBJECTIVE: Structural brain magnetic resonance imaging (MRI) is not mandatory in Alzheimer's disease (AD) research or clinical guidelines. We aimed to explore the use of structural brain MRI in AD/mild cognitive impairment (MCI) trials over the past 10 years and determine the frequency with which inclusion of standardized structural MRI acquisitions detects comorbid vascular and non-vascular pathologies. METHODS: We systematically searched ClinicalTrials.gov for AD clinical trials to determine their neuroimaging criteria and then used data from an AD/MCI cohort who underwent standardized MRI protocols, to determine type and incidence of clinically relevant comorbid pathologies. RESULTS: Of 210 AD clinical trials, 105 (50%) included structural brain imaging in their eligibility criteria. Only 58 (27.6%) required MRI. 16,479 of 53,755 (30.7%) AD participants were in trials requiring MRI. In the observational AD/MCI cohort, 141 patients met clinical criteria; 22 (15.6%) had relevant MRI findings, of which 15 (10.6%) were exclusionary for the study. DISCUSSION: In AD clinical trials over the last 10 years, over two-thirds of participants could have been enrolled without brain MRI and half without even a brain CT. In a study sample, relevant comorbid pathology was found in 15% of participants, despite careful screening. Standardized structural MRI should be incorporated into NIA-AA diagnostic guidelines (when available) and research frameworks routinely to reduce diagnostic heterogeneity.

Validity Evidence for the Use of Automated Neuropsychologic Assessment Metrics As a Screening Tool for Cognitive Impairment in Systemic Lupus Erythematosus.

OBJECTIVE: Screening for cognitive impairment in systemic lupus erythematosus (SLE) conventionally relies on the American College of Rheumatology (ACR) neuropsychologic battery (NB), which is not universally available. To develop a more accessible screening approach, we assessed validity of the Automated Neuropsychological Assessment Metrics (ANAM). Using the ACR NB as the gold standard for cognitive impairment classification, the objectives were 1) to measure overall discriminative validity of the ANAM for cognitive impairment versus no cognitive impairment, 2) to identify ANAM subtests and scores that best differentiate patients with cognitive impairment from those with no cognitive impairment, and 3) to derive ANAM composite indices and cutoffs. METHODS: A total of 211 consecutive adult patients, female and male, with SLE were administered the ANAM and ACR NB. 1) For overall discriminative validity of the ANAM, we compared patients with cognitive impairment versus those with no cognitive impairment on 4 scores. 2) Six ANAM models using different scores were developed, and the most discriminatory subtests were selected using logistic regression analyses. The area under the receiver operating characteristic curve (AUC) was calculated to establish ANAM validity against the ACR NB. 3) ANAM composite indices and cutoffs were derived for the best models, and sensitivities and specificities were calculated. RESULTS: Patients with no cognitive impairment performed better on most ANAM subtests, supporting ANAM's discriminative validity. Cognitive impairment could be accurately identified by selected ANAM subtests with top models, demonstrating excellent AUCs of 81% and 84%. Derived composite indices and cutoffs demonstrated sensitivity of 78-80% and specificity of 70%. CONCLUSION: This study provides support for ANAM's discriminative validity for cognitive impairment and utility for cognitive screening in adult SLE. Derived composite indices and cutoffs enhance clinical applicability.

Key factors for the assessment of mobility in advanced dementia: A consensus approach.

INTRODUCTION: Loss of mobility is common in advanced dementia and has important negative consequences related to fall risk, loss of independence, and lack of participation in meaningful activities. The causes of decline are multifactorial, including disease-specific changes in motor function, behavior, and cognition. To optimize clinical management of mobility, there is a need to better characterize capacity for safe and independent mobility. This study aimed to identify key factors that impact on mobility in dementia. METHODS: Expert input was gathered using a modified Delphi consensus approach. The primary criterion for participation was specialist knowledge in mobility or dementia, either as a clinician or a researcher. Participants rated elements of mobility for importance and feasibility of assessment in advanced dementia and prioritized items for inclusion in a mobility staging tool. Descriptive statistics and qualitative content analysis were used to summarize responses. RESULTS: Thirty-six experts completed the first survey with an 80% retention rate over three rounds. One-third of 61 items reached consensus for being both important and feasible to assess, representing five categories of elements. Items reaching agreement for a staging tool included walking, parkinsonism, gait, impulsivity, fall history, agitation, transfers, and posture control. DISCUSSION: This study highlights the need for a multidimensional, dementia-specific approach to mobility assessment. Results have implications for development of assessment methods and management guidelines to support the clinical care of mobility impairment in people with dementia.

Assessment of Oculomotor Function in Patients With Postconcussion Syndrome: A Systematic Review.

BACKGROUND: Concussion and its associated sequel, postconcussion syndrome (PCS), have a debilitating impact on the lives of concussed patients. However, a diagnostic biomarker for this condition is lacking. Recently, there has been a surge of interest in using oculomotor function testing as an objective assessment of patients with PCS. OBJECTIVES: To systematically synthesize, appraise, and summarize all published empirical studies that have assessed alteration of oculomotor functions in patients with PCS. METHODS: Medline, Embase, PsychINFO, and CINAHL databases searched up to July 2016 for studies that used oculomotor function assessment in patients with postconcussion symptoms. RESULTS: The search identified 1637 citations, and finally 8 case-control studies were included. Of these, 5 studies used a similar task with a target moving in a circular trajectory. Three other studies measured conventional oculomotor tasks such as saccade, vergence, and smooth pursuit eye movements. CONCLUSIONS: Currently, there is limited support for the recommendation of oculomotor function assessments for diagnosis and identification of patients with PCS following head trauma. Therefore, more rigorous studies assessing oculomotor function changes in patients with PCS are warranted.