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Donders J, Maher T. Clinical Utility of the Neuropsychological Assessment Battery Judgment Subtest in the Evaluation of Older Adults. Arch Clin Neuropsychol 2024:acae035. [PMID: 38712367 DOI: 10.1093/arclin/acae035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2023] [Revised: 04/05/2024] [Accepted: 04/11/2024] [Indexed: 05/08/2024] Open
Abstract
OBJECTIVE The purpose of this retrospective archival study was to explore the clinical utility of the Judgment subtest of the Neuropsychological Assessment Battery (NAB) in older adults who were referred because of cognitive concerns. Specifically, we were interested in how NAB Judgment covaried with other measures of executive functioning. METHOD 226 adults, aged 61-89 years (48% dementia, 35% mild cognitive impairment, 18% cognitively intact) completed NAB Judgment. They also completed Trail Making Test (TMT) A and B. In addition, Behavior Rating Inventory of Executive Function (BRIEF-A) informant and self-reports were obtained to measure executive functioning in daily life. RESULTS Scores on NAB Judgment did not correlate significantly with BRIEF-A informant ratings. However, there was a statistically significant correlation between BRIEF-A informant ratings and TMT B. Better performance on TMT B was associated with fewer informant concerns. Furthermore, subgroups with versus without informant BRIEF-A Metacognition indices in the range of impairment demonstrated a statistically significant difference on TMT B but not on Judgment. CONCLUSIONS Executive functioning in older adults should not be assessed using NAB Judgment alone. Such an evaluation should be supplemented with other in-person tests as well as informant ratings of daily functioning.
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Affiliation(s)
- Jacobus Donders
- Department of Psychology, Mary Free Bed Rehabilitation Hospital, Grand Rapids, MI, USA
| | - Tracy Maher
- Department of Psychology, Mary Free Bed Rehabilitation Hospital, Grand Rapids, MI, USA
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Ashendorf L, Withrow S, Gavett BE. The Neuropsychological Assessment Battery Driving Scenes Test in a Dementia Clinic. Arch Clin Neuropsychol 2024:acae034. [PMID: 38704735 DOI: 10.1093/arclin/acae034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2023] [Revised: 03/06/2024] [Accepted: 04/11/2024] [Indexed: 05/07/2024] Open
Abstract
OBJECTIVE In dementia research, the Driving Scenes test from the Neuropsychological Assessment Battery has been shown to relate to memory, dementia diagnosis, and functional impairment. The aim of the current study was to examine Driving Scenes and its component scores, and their relationships with cognition and daily functioning, in a mixed dementia clinic sample. METHOD One hundred U.S. military veterans between the ages of 55 and 88 were administered a full neuropsychological protocol that included Driving Scenes. RESULTS The Driving Scenes score and its subscores were strongly related to memory skills, and there were additional subscore associations with language and visuospatial functions. Driving Scenes uniquely predicted reported bill payment difficulties and tendency to get lost while driving, which were not predicted by other performances across cognitive domains. CONCLUSION Driving Scenes is a clinically and functionally relevant measure of memory. Although the Driving Scenes total score remains useful in dementia evaluations, component scores and error scores contribute additional practical information.
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Affiliation(s)
- Lee Ashendorf
- Mental Health Service Line, VA Central Western Massachusetts Health Care System, Worcester, MA, USA
- Department of Psychiatry, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Susanne Withrow
- Behavioral Health Service Line, VA Pittsburgh Health Care System, Pittsburgh, PA, USA
| | - Brandon E Gavett
- Department of Neurology, UC Davis School of Medicine, Davis, CA, USA
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Ding H, Kim M, Searls E, Sunderaraman P, De Anda-Duran I, Low S, Popp Z, Hwang PH, Li Z, Goyal K, Hathaway L, Monteverde J, Rahman S, Igwe A, Kolachalama VB, Au R, Lin H. Digital neuropsychological measures by defense automated neurocognitive assessment: reference values and clinical correlates. Front Neurol 2024; 15:1340710. [PMID: 38426173 PMCID: PMC10902432 DOI: 10.3389/fneur.2024.1340710] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2023] [Accepted: 01/29/2024] [Indexed: 03/02/2024] Open
Abstract
Introduction Although the growth of digital tools for cognitive health assessment, there's a lack of known reference values and clinical implications for these digital methods. This study aims to establish reference values for digital neuropsychological measures obtained through the smartphone-based cognitive assessment application, Defense Automated Neurocognitive Assessment (DANA), and to identify clinical risk factors associated with these measures. Methods The sample included 932 cognitively intact participants from the Framingham Heart Study, who completed at least one DANA task. Participants were stratified into subgroups based on sex and three age groups. Reference values were established for digital cognitive assessments within each age group, divided by sex, at the 2.5th, 25th, 50th, 75th, and 97.5th percentile thresholds. To validate these values, 57 cognitively intact participants from Boston University Alzheimer's Disease Research Center were included. Associations between 19 clinical risk factors and these digital neuropsychological measures were examined by a backward elimination strategy. Results Age- and sex-specific reference values were generated for three DANA tasks. Participants below 60 had median response times for the Go-No-Go task of 796 ms (men) and 823 ms (women), with age-related increases in both sexes. Validation cohort results mostly aligned with these references. Different tasks showed unique clinical correlations. For instance, response time in the Code Substitution task correlated positively with total cholesterol and diabetes, but negatively with high-density lipoprotein and low-density lipoprotein cholesterol levels, and triglycerides. Discussion This study established and validated reference values for digital neuropsychological measures of DANA in cognitively intact white participants, potentially improving their use in future clinical studies and practice.
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Affiliation(s)
- Huitong Ding
- Department of Anatomy and Neurobiology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, United States
- The Framingham Heart Study, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, United States
| | - Minzae Kim
- Department of Anatomy and Neurobiology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, United States
| | - Edward Searls
- Department of Anatomy and Neurobiology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, United States
| | - Preeti Sunderaraman
- The Framingham Heart Study, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, United States
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, United States
| | - Ileana De Anda-Duran
- School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, United States
| | - Spencer Low
- Department of Anatomy and Neurobiology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, United States
| | - Zachary Popp
- Department of Anatomy and Neurobiology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, United States
| | - Phillip H. Hwang
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, United States
| | - Zexu Li
- Department of Anatomy and Neurobiology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, United States
| | - Kriti Goyal
- Department of Anatomy and Neurobiology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, United States
| | - Lindsay Hathaway
- Department of Anatomy and Neurobiology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, United States
| | - Jose Monteverde
- Department of Anatomy and Neurobiology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, United States
| | - Salman Rahman
- Department of Anatomy and Neurobiology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, United States
| | - Akwaugo Igwe
- Department of Anatomy and Neurobiology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, United States
| | - Vijaya B. Kolachalama
- Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, United States
- Department of Computer Science, Faculty of Computing & Data Sciences, Boston University, Boston, MA, United States
| | - Rhoda Au
- Department of Anatomy and Neurobiology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, United States
- The Framingham Heart Study, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, United States
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, United States
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, United States
- Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, United States
- Slone Epidemiology Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, United States
| | - Honghuang Lin
- Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, United States
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Popp Z, Low S, Igwe A, Rahman MS, Kim M, Khan R, Oh E, Kumar A, De Anda‐Duran I, Ding H, Hwang PH, Sunderaraman P, Shih LC, Lin H, Kolachalama VB, Au R. Shifting From Active to Passive Monitoring of Alzheimer Disease: The State of the Research. J Am Heart Assoc 2024; 13:e031247. [PMID: 38226518 PMCID: PMC10926806 DOI: 10.1161/jaha.123.031247] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/17/2024]
Abstract
Most research using digital technologies builds on existing methods for staff-administered evaluation, requiring a large investment of time, effort, and resources. Widespread use of personal mobile devices provides opportunities for continuous health monitoring without active participant engagement. Home-based sensors show promise in evaluating behavioral features in near real time. Digital technologies across these methodologies can detect precise measures of cognition, mood, sleep, gait, speech, motor activity, behavior patterns, and additional features relevant to health. As a neurodegenerative condition with insidious onset, Alzheimer disease and other dementias (AD/D) represent a key target for advances in monitoring disease symptoms. Studies to date evaluating the predictive power of digital measures use inconsistent approaches to characterize these measures. Comparison between different digital collection methods supports the use of passive collection methods in settings in which active participant engagement approaches are not feasible. Additional studies that analyze how digital measures across multiple data streams can together improve prediction of cognitive impairment and early-stage AD are needed. Given the long timeline of progression from normal to diagnosis, digital monitoring will more easily make extended longitudinal follow-up possible. Through the American Heart Association-funded Strategically Focused Research Network, the Boston University investigative team deployed a platform involving a wide range of technologies to address these gaps in research practice. Much more research is needed to thoroughly evaluate limitations of passive monitoring. Multidisciplinary collaborations are needed to establish legal and ethical frameworks for ensuring passive monitoring can be conducted at scale while protecting privacy and security, especially in vulnerable populations.
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Affiliation(s)
- Zachary Popp
- Department of Anatomy & NeurobiologyBoston University Chobanian & Avedisian School of MedicineBostonMAUSA
- Boston University Alzheimer’s Disease Research Center, Boston University Chobanian & Avedisian School of MedicineBostonMAUSA
| | - Spencer Low
- Department of Anatomy & NeurobiologyBoston University Chobanian & Avedisian School of MedicineBostonMAUSA
- Boston University Alzheimer’s Disease Research Center, Boston University Chobanian & Avedisian School of MedicineBostonMAUSA
- Department of EpidemiologyBoston University School of Public HealthBostonMAUSA
| | - Akwaugo Igwe
- Department of Anatomy & NeurobiologyBoston University Chobanian & Avedisian School of MedicineBostonMAUSA
- Boston University Alzheimer’s Disease Research Center, Boston University Chobanian & Avedisian School of MedicineBostonMAUSA
| | - Md Salman Rahman
- Department of Anatomy & NeurobiologyBoston University Chobanian & Avedisian School of MedicineBostonMAUSA
- Boston University Alzheimer’s Disease Research Center, Boston University Chobanian & Avedisian School of MedicineBostonMAUSA
| | - Minzae Kim
- Department of Anatomy & NeurobiologyBoston University Chobanian & Avedisian School of MedicineBostonMAUSA
- Boston UniversityBostonMAUSA
| | - Raiyan Khan
- Department of Anatomy & NeurobiologyBoston University Chobanian & Avedisian School of MedicineBostonMAUSA
- Boston UniversityBostonMAUSA
| | - Emily Oh
- Department of Anatomy & NeurobiologyBoston University Chobanian & Avedisian School of MedicineBostonMAUSA
- Boston UniversityBostonMAUSA
| | - Ankita Kumar
- Department of Anatomy & NeurobiologyBoston University Chobanian & Avedisian School of MedicineBostonMAUSA
- Boston UniversityBostonMAUSA
| | - Ileana De Anda‐Duran
- Department of EpidemiologyTulane University School of Public Health & Tropical MedicineNew OrleansLAUSA
| | - Huitong Ding
- Department of Anatomy & NeurobiologyBoston University Chobanian & Avedisian School of MedicineBostonMAUSA
- Framingham Heart StudyBoston University Chobanian & Avedisian School of Medicine School of MedicineBostonMAUSA
| | - Phillip H. Hwang
- Department of EpidemiologyBoston University School of Public HealthBostonMAUSA
| | - Preeti Sunderaraman
- Boston University Alzheimer’s Disease Research Center, Boston University Chobanian & Avedisian School of MedicineBostonMAUSA
- Framingham Heart StudyBoston University Chobanian & Avedisian School of Medicine School of MedicineBostonMAUSA
- Department of NeurologyBoston University Chobanian & Avedisian School of Medicine School of MedicineBostonMAUSA
| | - Ludy C. Shih
- Boston University Alzheimer’s Disease Research Center, Boston University Chobanian & Avedisian School of MedicineBostonMAUSA
- Framingham Heart StudyBoston University Chobanian & Avedisian School of Medicine School of MedicineBostonMAUSA
- Department of NeurologyBoston University Chobanian & Avedisian School of Medicine School of MedicineBostonMAUSA
| | - Honghuang Lin
- Department of MedicineUniversity of Massachusetts Chan Medical SchoolWorcesterMA
| | - Vijaya B. Kolachalama
- Boston University Alzheimer’s Disease Research Center, Boston University Chobanian & Avedisian School of MedicineBostonMAUSA
- Department of MedicineBoston University Chobanian & Avedisian School of Medicine School of MedicineBostonMAUSA
| | - Rhoda Au
- Department of Anatomy & NeurobiologyBoston University Chobanian & Avedisian School of MedicineBostonMAUSA
- Boston University Alzheimer’s Disease Research Center, Boston University Chobanian & Avedisian School of MedicineBostonMAUSA
- Department of EpidemiologyBoston University School of Public HealthBostonMAUSA
- Framingham Heart StudyBoston University Chobanian & Avedisian School of Medicine School of MedicineBostonMAUSA
- Department of NeurologyBoston University Chobanian & Avedisian School of Medicine School of MedicineBostonMAUSA
- Department of MedicineBoston University Chobanian & Avedisian School of Medicine School of MedicineBostonMAUSA
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5
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Ally M, Sugarman MA, Zetterberg H, Blennow K, Ashton NJ, Karikari TK, Aparicio HJ, Frank B, Tripodis Y, Martin B, Palmisano JN, Steinberg EG, Simkin I, Farrer LA, Jun GR, Turk KW, Budson AE, O'Connor MK, Au R, Goldstein LE, Kowall NW, Killiany R, Stern RA, Stein TD, McKee AC, Qiu WQ, Mez J, Alosco ML. Cross-sectional and longitudinal evaluation of plasma glial fibrillary acidic protein to detect and predict clinical syndromes of Alzheimer's disease. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2023; 15:e12492. [PMID: 37885919 PMCID: PMC10599277 DOI: 10.1002/dad2.12492] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Revised: 09/15/2023] [Accepted: 09/26/2023] [Indexed: 10/28/2023]
Abstract
Introduction This study examined plasma glial fibrillary acidic protein (GFAP) as a biomarker of cognitive impairment due to Alzheimer's disease (AD) with and against plasma neurofilament light chain (NfL), and phosphorylated tau (p-tau)181+231. Methods Plasma samples were analyzed using Simoa platform for 567 participants spanning the AD continuum. Cognitive diagnosis, neuropsychological testing, and dementia severity were examined for cross-sectional and longitudinal outcomes. Results Plasma GFAP discriminated AD dementia from normal cognition (adjusted mean difference = 0.90 standard deviation [SD]) and mild cognitive impairment (adjusted mean difference = 0.72 SD), and demonstrated superior discrimination compared to alternative plasma biomarkers. Higher GFAP was associated with worse dementia severity and worse performance on 11 of 12 neuropsychological tests. Longitudinally, GFAP predicted decline in memory, but did not predict conversion to mild cognitive impairment or dementia. Discussion Plasma GFAP was associated with clinical outcomes related to suspected AD and could be of assistance in a plasma biomarker panel to detect in vivo AD.
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Affiliation(s)
- Madeline Ally
- Boston University Alzheimer's Disease Research Center and CTE CenterBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- Department of PsychologyUniversity of ArizonaTucsonArizonaUSA
| | - Michael A. Sugarman
- Boston University Alzheimer's Disease Research Center and CTE CenterBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- Department of NeurologyMedical University of South CarolinaCharlestonSouth CarolinaUSA
| | - Henrik Zetterberg
- Department of Neurodegenerative DiseaseUCL Institute of NeurologyLondonUK
- UK Dementia Research Institute at UCL, UCL Institute of NeurologyUniversity College LondonLondonUK
- Clinical Neurochemistry LaboratorySahlgrenska University HospitalMölndalSweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and PhysiologyThe Sahlgrenska Academy at the University of GothenburgGothenburgSweden
| | - Kaj Blennow
- Clinical Neurochemistry LaboratorySahlgrenska University HospitalMölndalSweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and PhysiologyThe Sahlgrenska Academy at the University of GothenburgGothenburgSweden
| | - Nicholas J. Ashton
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and PhysiologyThe Sahlgrenska Academy at the University of GothenburgGothenburgSweden
- Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology, and NeuroscienceKing's College LondonLondonUK
- NIHR Biomedical Research Centre for Mental Health and Biomedical Research Unit for Dementia at South London and MaudsleyNHS FoundationLondonUK
- Centre for Age‐Related MedicineStavanger University HospitalStavangerNorway
| | - Thomas K. Karikari
- Clinical Neurochemistry LaboratorySahlgrenska University HospitalMölndalSweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and PhysiologyThe Sahlgrenska Academy at the University of GothenburgGothenburgSweden
- Department of PsychiatryUniversity of Pittsburgh School of MedicinePittsburghPennsylvaniaUSA
| | - Hugo J. Aparicio
- Boston University Alzheimer's Disease Research Center and CTE CenterBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- Department of NeurologyBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
| | - Brandon Frank
- Boston University Alzheimer's Disease Research Center and CTE CenterBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- US Department of Veterans AffairsVA Boston Healthcare SystemJamaica PlainMassachusettsUSA
| | - Yorghos Tripodis
- Boston University Alzheimer's Disease Research Center and CTE CenterBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- Department of BiostatisticsBoston University School of Public HealthBostonMassachusettsUSA
| | - Brett Martin
- Boston University Alzheimer's Disease Research Center and CTE CenterBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- Biostatistics and Epidemiology Data Analytics CenterBoston University School of Public HealthBostonMassachusettsUSA
| | - Joseph N. Palmisano
- Boston University Alzheimer's Disease Research Center and CTE CenterBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- Biostatistics and Epidemiology Data Analytics CenterBoston University School of Public HealthBostonMassachusettsUSA
| | - Eric G. Steinberg
- Boston University Alzheimer's Disease Research Center and CTE CenterBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
| | - Irene Simkin
- Department of MedicineBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
| | - Lindsay A. Farrer
- Boston University Alzheimer's Disease Research Center and CTE CenterBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- Department of NeurologyBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- Department of BiostatisticsBoston University School of Public HealthBostonMassachusettsUSA
- Department of MedicineBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- The Framingham Heart StudyFraminghamMassachusettsUSA
- Department of EpidemiologyBoston University School of Public HealthBostonMassachusettsUSA
- Department of OphthalmologyBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
| | - Gyungah R. Jun
- Department of MedicineBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
| | - Katherine W. Turk
- Boston University Alzheimer's Disease Research Center and CTE CenterBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- Department of NeurologyBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- US Department of Veterans AffairsVA Boston Healthcare SystemJamaica PlainMassachusettsUSA
| | - Andrew E. Budson
- Boston University Alzheimer's Disease Research Center and CTE CenterBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- Department of NeurologyBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- US Department of Veterans AffairsVA Boston Healthcare SystemJamaica PlainMassachusettsUSA
| | - Maureen K. O'Connor
- Boston University Alzheimer's Disease Research Center and CTE CenterBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- Department of NeuropsychologyEdith Nourse Rogers Memorial Veterans HospitalBedfordMassachusettsUSA
| | - Rhoda Au
- Boston University Alzheimer's Disease Research Center and CTE CenterBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- Department of NeurologyBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- The Framingham Heart StudyFraminghamMassachusettsUSA
- Department of EpidemiologyBoston University School of Public HealthBostonMassachusettsUSA
- Department of Anatomy and NeurobiologyBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
| | - Lee E. Goldstein
- Boston University Alzheimer's Disease Research Center and CTE CenterBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- Biostatistics and Epidemiology Data Analytics CenterBoston University School of Public HealthBostonMassachusettsUSA
- Department of OphthalmologyBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- Department of Biomedical, Electrical, and Computer EngineeringBoston University College of EngineeringBostonMassachusettsUSA
| | - Neil W. Kowall
- Boston University Alzheimer's Disease Research Center and CTE CenterBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- Department of NeurologyBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- US Department of Veterans AffairsVA Boston Healthcare SystemJamaica PlainMassachusettsUSA
- Department of Pathology and Laboratory MedicineBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
| | - Ronald Killiany
- Boston University Alzheimer's Disease Research Center and CTE CenterBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- Department of Anatomy and NeurobiologyBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- Center for Biomedical ImagingBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
| | - Robert A. Stern
- Boston University Alzheimer's Disease Research Center and CTE CenterBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- Department of NeurologyBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- Department of Anatomy and NeurobiologyBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- Department of NeurosurgeryBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
| | - Thor D. Stein
- Boston University Alzheimer's Disease Research Center and CTE CenterBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- US Department of Veterans AffairsVA Boston Healthcare SystemJamaica PlainMassachusettsUSA
- Department of Pathology and Laboratory MedicineBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- US Department of Veterans AffairsVA Bedford Healthcare SystemBedfordMassachusettsUSA
| | - Ann C. McKee
- Boston University Alzheimer's Disease Research Center and CTE CenterBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- Department of NeurologyBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- US Department of Veterans AffairsVA Boston Healthcare SystemJamaica PlainMassachusettsUSA
- Department of Pathology and Laboratory MedicineBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- US Department of Veterans AffairsVA Bedford Healthcare SystemBedfordMassachusettsUSA
| | - Wei Qiao Qiu
- Boston University Alzheimer's Disease Research Center and CTE CenterBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- Department of PsychiatryBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- Department of Pharmacology and Experimental TherapeuticsBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
| | - Jesse Mez
- Boston University Alzheimer's Disease Research Center and CTE CenterBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- Department of NeurologyBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
| | - Michael L. Alosco
- Boston University Alzheimer's Disease Research Center and CTE CenterBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- Department of NeurologyBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
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Anda-Duran ID, Hwang PH, Popp ZT, Low S, Ding H, Rahman S, Igwe A, Kolachalama VB, Lin H, Au R. Matching science to reality: how to deploy a participant-driven digital brain health platform. FRONTIERS IN DEMENTIA 2023; 2:1135451. [PMID: 38706716 PMCID: PMC11067045 DOI: 10.3389/frdem.2023.1135451] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 05/07/2024]
Abstract
Introduction Advances in digital technologies for health research enable opportunities for digital phenotyping of individuals in research and clinical settings. Beyond providing opportunities for advanced data analytics with data science and machine learning approaches, digital technologies offer solutions to several of the existing barriers in research practice that have resulted in biased samples. Methods A participant-driven, precision brain health monitoring digital platform has been introduced to two longitudinal cohort studies, the Boston University Alzheimer's Disease Research Center (BU ADRC) and the Bogalusa Heart Study (BHS). The platform was developed with prioritization of digital data in native format, multiple OS, validity of derived metrics, feasibility and usability. A platform including nine remote technologies and three staff-guided digital assessments has been introduced in the BU ADRC population, including a multimodal smartphone application also introduced to the BHS population. Participants select which technologies they would like to use and can manipulate their personal platform and schedule over time. Results Participants from the BU ADRC are using an average of 5.9 technologies to date, providing strong evidence for the usability of numerous digital technologies in older adult populations. Broad phenotyping of both cohorts is ongoing, with the collection of data spanning cognitive testing, sleep, physical activity, speech, motor activity, cardiovascular health, mood, gait, balance, and more. Several challenges in digital phenotyping implementation in the BU ADRC and the BHS have arisen, and the protocol has been revised and optimized to minimize participant burden while sustaining participant contact and support. Discussion The importance of digital data in its native format, near real-time data access, passive participant engagement, and availability of technologies across OS has been supported by the pattern of participant technology use and adherence across cohorts. The precision brain health monitoring platform will be iteratively adjusted and improved over time. The pragmatic study design enables multimodal digital phenotyping of distinct clinically characterized cohorts in both rural and urban U.S. settings.
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Affiliation(s)
- Ileana De Anda-Duran
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, United States
| | - Phillip H. Hwang
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, United States
| | - Zachary Thomas Popp
- Department of Anatomy and Neurobiology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, United States
| | - Spencer Low
- Department of Anatomy and Neurobiology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, United States
| | - Huitong Ding
- Department of Anatomy and Neurobiology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, United States
- Framingham Heart Study, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, United States
| | - Salman Rahman
- Department of Anatomy and Neurobiology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, United States
| | - Akwaugo Igwe
- Department of Anatomy and Neurobiology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, United States
| | - Vijaya B. Kolachalama
- Boston University Alzheimer’s Disease Research Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, United States
- Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, United States
- Department of Computer Science and Faculty of Computing & Data Sciences, Boston University, Boston, MA, United States
| | - Honghuang Lin
- Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, United States
| | - Rhoda Au
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, United States
- Department of Anatomy and Neurobiology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, United States
- Framingham Heart Study, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, United States
- Boston University Alzheimer’s Disease Research Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, United States
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, United States
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7
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Frank B, Ally M, Brekke B, Zetterberg H, Blennow K, Sugarman MA, Ashton NJ, Karikari TK, Tripodis Y, Martin B, Palmisano JN, Steinberg EG, Simkina I, Turk KW, Budson AE, O’Connor MK, Au R, Goldstein LE, Jun GR, Kowall NW, Stein TD, McKee AC, Killiany R, Qiu WQ, Stern RA, Mez J, Alosco ML. Plasma p-tau 181 shows stronger network association to Alzheimer's disease dementia than neurofilament light and total tau. Alzheimers Dement 2022; 18:1523-1536. [PMID: 34854549 PMCID: PMC9160800 DOI: 10.1002/alz.12508] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2021] [Revised: 07/07/2021] [Accepted: 09/22/2021] [Indexed: 01/29/2023]
Abstract
INTRODUCTION We examined the ability of plasma hyperphosphorylated tau (p-tau)181 to detect cognitive impairment due to Alzheimer's disease (AD) independently and in combination with plasma total tau (t-tau) and neurofilament light (NfL). METHODS Plasma samples were analyzed using the Simoa platform for 235 participants with normal cognition (NC), 181 with mild cognitive impairment due to AD (MCI), and 153 with AD dementia. Statistical approaches included multinomial regression and Gaussian graphical models (GGMs) to assess a network of plasma biomarkers, neuropsychological tests, and demographic variables. RESULTS Plasma p-tau181 discriminated AD dementia from NC, but not MCI, and correlated with dementia severity and worse neuropsychological test performance. Plasma NfL similarly discriminated diagnostic groups. Unlike plasma NfL or t-tau, p-tau181 had a direct association with cognitive diagnosis in a bootstrapped GGM. DISCUSSION These results support plasma p-tau181 for the detection of AD dementia and the use of blood-based biomarkers for optimal disease detection.
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Affiliation(s)
- Brandon Frank
- Boston University Alzheimer’s Disease Center and CTE
CenterBoston University School of Medicine, Boston, Massachusetts, USA
- U.S. Department of Veteran Affairs, VA Bedford Healthcare
System, Bedford, Massachusetts, USA
| | - Madeline Ally
- Boston University Alzheimer’s Disease Center and CTE
CenterBoston University School of Medicine, Boston, Massachusetts, USA
| | - Bailee Brekke
- Boston University Alzheimer’s Disease Center and CTE
CenterBoston University School of Medicine, Boston, Massachusetts, USA
| | - Henrik Zetterberg
- Department of Neurodegenerative Disease, UCL Institute of
Neurology, London, UK
- UK Dementia Research Institute at UCL, London, UK
- Clinical Neurochemistry Laboratory, Sahlgrenska University
Hospital, Mölndal, Sweden
- Department of Psychiatry and Neurochemistry, Institute of
Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg,
Gothenburg, Sweden
| | - Kaj Blennow
- Clinical Neurochemistry Laboratory, Sahlgrenska University
Hospital, Mölndal, Sweden
- Department of Psychiatry and Neurochemistry, Institute of
Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg,
Gothenburg, Sweden
| | - Michael A. Sugarman
- Boston University Alzheimer’s Disease Center and CTE
CenterBoston University School of Medicine, Boston, Massachusetts, USA
- U.S. Department of Veteran Affairs, VA Bedford Healthcare
System, Bedford, Massachusetts, USA
| | - Nicholas J. Ashton
- Clinical Neurochemistry Laboratory, Sahlgrenska University
Hospital, Mölndal, Sweden
- Department of Psychiatry and Neurochemistry, Institute of
Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg,
Gothenburg, Sweden
| | - Thomas K. Karikari
- Clinical Neurochemistry Laboratory, Sahlgrenska University
Hospital, Mölndal, Sweden
- Department of Psychiatry and Neurochemistry, Institute of
Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg,
Gothenburg, Sweden
| | - Yorghos Tripodis
- Boston University Alzheimer’s Disease Center and CTE
CenterBoston University School of Medicine, Boston, Massachusetts, USA
- Department of Biostatistics, Boston University School of
Public Health, Boston, Massachusetts, USA
| | - Brett Martin
- Boston University Alzheimer’s Disease Center and CTE
CenterBoston University School of Medicine, Boston, Massachusetts, USA
- Biostatistics and Epidemiology Data Analytics Center,
Boston University School of Public Health, Boston, Massachusetts, USA
| | - Joseph N. Palmisano
- Boston University Alzheimer’s Disease Center and CTE
CenterBoston University School of Medicine, Boston, Massachusetts, USA
- Biostatistics and Epidemiology Data Analytics Center,
Boston University School of Public Health, Boston, Massachusetts, USA
| | - Eric G. Steinberg
- Boston University Alzheimer’s Disease Center and CTE
CenterBoston University School of Medicine, Boston, Massachusetts, USA
| | - Irene Simkina
- Department of Medicine, Boston University School of
Medicine, Boston, Massachusetts, USA
| | - Katherine W. Turk
- Boston University Alzheimer’s Disease Center and CTE
CenterBoston University School of Medicine, Boston, Massachusetts, USA
- Department of Neurology, Boston University School of
Medicine, Boston, Massachusetts, USA
- U.S. Department of Veteran Affairs, VA Boston Healthcare
System, Jamaica Plain, Massachusetts, USA
| | - Andrew E. Budson
- Boston University Alzheimer’s Disease Center and CTE
CenterBoston University School of Medicine, Boston, Massachusetts, USA
- Department of Neurology, Boston University School of
Medicine, Boston, Massachusetts, USA
- U.S. Department of Veteran Affairs, VA Boston Healthcare
System, Jamaica Plain, Massachusetts, USA
| | - Maureen K. O’Connor
- Boston University Alzheimer’s Disease Center and CTE
CenterBoston University School of Medicine, Boston, Massachusetts, USA
- U.S. Department of Veteran Affairs, VA Bedford Healthcare
System, Bedford, Massachusetts, USA
| | - Rhoda Au
- Boston University Alzheimer’s Disease Center and CTE
CenterBoston University School of Medicine, Boston, Massachusetts, USA
- Department of Neurology, Boston University School of
Medicine, Boston, Massachusetts, USA
- Department of Anatomy & Neurobiology, Boston
University School of Medicine, Boston, Massachusetts, USA
- Framingham Heart Study, Boston University School of
Medicine, Boston, Massachusetts, USA
- Department of Epidemiology, Boston University School of
Public Health, Boston, Massachusetts, USA
| | - Lee E. Goldstein
- Boston University Alzheimer’s Disease Center and CTE
CenterBoston University School of Medicine, Boston, Massachusetts, USA
- Department of Pathology and Laboratory Medicine, Boston
University School of Medicine, Boston, Massachusetts, USA
- Departments of Psychiatry and Ophthalmology, Boston
University School of Medicine, Boston, Massachusetts, USA
- Departments of Biomedical, Electrical & Computer
Engineering, Boston University College of Engineering, Boston, Massachusetts,
USA
| | - Gyungah R. Jun
- Department of Medicine, Boston University School of
Medicine, Boston, Massachusetts, USA
| | - Neil W. Kowall
- Boston University Alzheimer’s Disease Center and CTE
CenterBoston University School of Medicine, Boston, Massachusetts, USA
- Department of Neurology, Boston University School of
Medicine, Boston, Massachusetts, USA
- Department of Pathology and Laboratory Medicine, Boston
University School of Medicine, Boston, Massachusetts, USA
- U.S. Department of Veteran Affairs, VA Boston Healthcare
System, Jamaica Plain, Massachusetts, USA
| | - Thor D. Stein
- Boston University Alzheimer’s Disease Center and CTE
CenterBoston University School of Medicine, Boston, Massachusetts, USA
- U.S. Department of Veteran Affairs, VA Bedford Healthcare
System, Bedford, Massachusetts, USA
- Department of Pathology and Laboratory Medicine, Boston
University School of Medicine, Boston, Massachusetts, USA
- U.S. Department of Veteran Affairs, VA Boston Healthcare
System, Jamaica Plain, Massachusetts, USA
| | - Ann C. McKee
- Boston University Alzheimer’s Disease Center and CTE
CenterBoston University School of Medicine, Boston, Massachusetts, USA
- U.S. Department of Veteran Affairs, VA Bedford Healthcare
System, Bedford, Massachusetts, USA
- Department of Neurology, Boston University School of
Medicine, Boston, Massachusetts, USA
- Department of Pathology and Laboratory Medicine, Boston
University School of Medicine, Boston, Massachusetts, USA
- U.S. Department of Veteran Affairs, VA Boston Healthcare
System, Jamaica Plain, Massachusetts, USA
| | - Ronald Killiany
- Boston University Alzheimer’s Disease Center and CTE
CenterBoston University School of Medicine, Boston, Massachusetts, USA
- Department of Neurology, Boston University School of
Medicine, Boston, Massachusetts, USA
- Department of Anatomy & Neurobiology, Boston
University School of Medicine, Boston, Massachusetts, USA
- Center for Biomedical Imaging, Boston University School
of Medicine, Boston, Massachusetts, USA
| | - Wei Qiao Qiu
- Boston University Alzheimer’s Disease Center and CTE
CenterBoston University School of Medicine, Boston, Massachusetts, USA
- Department of Psychiatry, Boston University School of
Medicine, Boston, Massachusetts, USA
- Department of Pharmacology & Experimental
Therapeutics, Boston University School of Medicine, Boston, Massachusetts, USA
| | - Robert A. Stern
- Boston University Alzheimer’s Disease Center and CTE
CenterBoston University School of Medicine, Boston, Massachusetts, USA
- Department of Neurology, Boston University School of
Medicine, Boston, Massachusetts, USA
- Department of Anatomy & Neurobiology, Boston
University School of Medicine, Boston, Massachusetts, USA
- Department of Neurosurgery, Boston University School of
Medicine, Boston, Massachusetts, USA
| | - Jesse Mez
- Boston University Alzheimer’s Disease Center and CTE
CenterBoston University School of Medicine, Boston, Massachusetts, USA
- Department of Neurology, Boston University School of
Medicine, Boston, Massachusetts, USA
- Framingham Heart Study, Boston University School of
Medicine, Boston, Massachusetts, USA
| | - Michael L. Alosco
- Boston University Alzheimer’s Disease Center and CTE
CenterBoston University School of Medicine, Boston, Massachusetts, USA
- Department of Neurology, Boston University School of
Medicine, Boston, Massachusetts, USA
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Development of a Web-Based Mini-Driving Scene Screening Test (MDSST) for Clinical Practice in Driving Rehabilitation. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph19063582. [PMID: 35329268 PMCID: PMC8954781 DOI: 10.3390/ijerph19063582] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Revised: 03/12/2022] [Accepted: 03/14/2022] [Indexed: 02/01/2023]
Abstract
(1) Background: For the elderly and disabled, self-driving is very important for social participation. An understanding of changing driving conditions is essential in order to drive safely. This study aimed to develop a web-based Korean Mini-Driving Scene Screening Test (MDSST) and to verify its reliability and validity for clinical application. (2) Methods: We developed a web-based MDSST, and its content validity was verified by an expert group. The tests were conducted with 102 elderly drivers to verify the internal consistency and reliability of items, and the validity of convergence with the existing Korean-Safe Driving Behavior Measure (K-SDBM) and the Korean-Adelaide Driving Self-Efficacy Scale (K-ADSES) driving tests was also verified. The test–retest reliability was verified using 54 individuals who participated in the initial test. (3) Results: The average content validity index of MDSST was 0.90, and the average internal consistency of all items was 0.822, indicating high content validity and internal consistency. The exploratory factor analysis for construct validity, the KOM value of the data, was 0.658, and Bartlett’s sphericity test also showed a strongly significant result. The four factors were road traffic and signal perception, situation understanding, risk factor recognition, and situation prediction. The explanatory power was reliable at 61.27%. For the convergence validation, MDSST and K-SDBM showed r = 0.435 and K-ADSES showed r = 0.346, showing a moderate correlation. In the evaluation–reevaluation reliability verification, the reliability increased to r = 0.952. (4) Conclusions: The web-based MDSST test developed in this study is a useful tool for detecting and understanding real-world driving situations faced by elderly drivers. It is hoped that the MDSST test can be applied more widely as a driving ability test that can be used in the clinical field of driving rehabilitation.
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9
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Alosco ML, Mian AZ, Buch K, Farris CW, Uretsky M, Tripodis Y, Baucom Z, Martin B, Palmisano J, Puzo C, Ang TFA, Joshi P, Goldstein LE, Au R, Katz DI, Dwyer B, Daneshvar DH, Nowinski C, Cantu RC, Kowall NW, Huber BR, Alvarez VE, Stern RA, Stein TD, Killiany RJ, McKee AC, Mez J. Structural MRI profiles and tau correlates of atrophy in autopsy-confirmed CTE. Alzheimers Res Ther 2021; 13:193. [PMID: 34876229 PMCID: PMC8653514 DOI: 10.1186/s13195-021-00928-y] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2021] [Accepted: 10/31/2021] [Indexed: 12/14/2022]
Abstract
BACKGROUND Chronic traumatic encephalopathy (CTE), a neurodegenerative tauopathy, cannot currently be diagnosed during life. Atrophy patterns on magnetic resonance imaging could be an effective in vivo biomarker of CTE, but have not been characterized. Mechanisms of neurodegeneration in CTE are unknown. Here, we characterized macrostructural magnetic resonance imaging features of brain donors with autopsy-confirmed CTE. The association between hyperphosphorylated tau (p-tau) and atrophy on magnetic resonance imaging was examined. METHODS Magnetic resonance imaging scans were obtained by medical record requests for 55 deceased symptomatic men with autopsy-confirmed CTE and 31 men (n = 11 deceased) with normal cognition at the time of the scan, all >60 years Three neuroradiologists visually rated regional atrophy and microvascular disease (0 [none]-4 [severe]), microbleeds, and cavum septum pellucidum presence. Neuropathologists rated tau severity and atrophy at autopsy using semi-quantitative scales. RESULTS Compared to unimpaired males, donors with CTE (45/55=stage III/IV) had greater atrophy of the orbital-frontal (mean diff.=1.29), dorsolateral frontal (mean diff.=1.31), superior frontal (mean diff.=1.05), anterior temporal (mean diff.=1.57), and medial temporal lobes (mean diff.=1.60), and larger lateral (mean diff.=1.72) and third (mean diff.=0.80) ventricles, controlling for age at scan (ps<0.05). There were no effects for posterior atrophy or microvascular disease. Donors with CTE had increased odds of a cavum septum pellucidum (OR = 6.7, p < 0.05). Among donors with CTE, greater tau severity across 14 regions corresponded to greater atrophy on magnetic resonance imaging (beta = 0.68, p < 0.01). CONCLUSIONS These findings support frontal-temporal atrophy as a magnetic resonance imaging finding of CTE and show p-tau accumulation is associated with atrophy in CTE.
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Affiliation(s)
- Michael L Alosco
- Boston University Alzheimer's Disease Research Center and CTE Center, Department of Neurology, Boston University School of Medicine, 72 E Concord Street, Suite B7800, Boston, MA, 02118, USA
| | - Asim Z Mian
- Department of Radiology, Boston University School of Medicine, Boston, USA
| | - Karen Buch
- Department of Radiology, Massachusetts General Hospital, Boston, USA
| | - Chad W Farris
- Department of Radiology, Boston University School of Medicine, Boston, USA
- Department of Radiology, Massachusetts General Hospital, Boston, USA
| | - Madeline Uretsky
- Boston University Alzheimer's Disease Research Center and CTE Center, Department of Neurology, Boston University School of Medicine, 72 E Concord Street, Suite B7800, Boston, MA, 02118, USA
| | - Yorghos Tripodis
- Department of Biostatistics, Boston University School of Public Health, Boston, USA
| | - Zachary Baucom
- Department of Biostatistics, Boston University School of Public Health, Boston, USA
| | - Brett Martin
- Biostatistics and Epidemiology Data Analytics Center, Boston University School of Public Health, Boston, USA
| | - Joseph Palmisano
- Biostatistics and Epidemiology Data Analytics Center, Boston University School of Public Health, Boston, USA
| | - Christian Puzo
- Boston University Alzheimer's Disease Research Center and CTE Center, Department of Neurology, Boston University School of Medicine, 72 E Concord Street, Suite B7800, Boston, MA, 02118, USA
| | - Ting Fang Alvin Ang
- Framingham Heart Study, Boston University School of Medicine, 72 E Concord Street, Suite B7800, Boston, MA, 02118, USA
| | - Prajakta Joshi
- Framingham Heart Study, Boston University School of Medicine, 72 E Concord Street, Suite B7800, Boston, MA, 02118, USA
| | - Lee E Goldstein
- Boston University Alzheimer's Disease Research Center and CTE Center, Department of Neurology, Boston University School of Medicine, 72 E Concord Street, Suite B7800, Boston, MA, 02118, USA
- Department of Radiology, Boston University School of Medicine, Boston, USA
- Department of Pathology and Laboratory Medicine, Boston University School of Medicine, Boston, USA
- Department of Psychiatry, Boston University School of Medicine, Boston, USA
- Departments of Biomedical, Electrical & Computer Engineering, Boston University College of Engineering, Boston, USA
| | - Rhoda Au
- Boston University Alzheimer's Disease Research Center and CTE Center, Department of Neurology, Boston University School of Medicine, 72 E Concord Street, Suite B7800, Boston, MA, 02118, USA
- Framingham Heart Study, Boston University School of Medicine, 72 E Concord Street, Suite B7800, Boston, MA, 02118, USA
- Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, USA
- Department of Epidemiology, Boston University School of Public Health, Boston, USA
| | - Douglas I Katz
- Boston University Alzheimer's Disease Research Center and CTE Center, Department of Neurology, Boston University School of Medicine, 72 E Concord Street, Suite B7800, Boston, MA, 02118, USA
- Braintree Rehabilitation Hospital, Braintree, MA, USA
| | - Brigid Dwyer
- Boston University Alzheimer's Disease Research Center and CTE Center, Department of Neurology, Boston University School of Medicine, 72 E Concord Street, Suite B7800, Boston, MA, 02118, USA
- Braintree Rehabilitation Hospital, Braintree, MA, USA
| | - Daniel H Daneshvar
- Boston University Alzheimer's Disease Research Center and CTE Center, Department of Neurology, Boston University School of Medicine, 72 E Concord Street, Suite B7800, Boston, MA, 02118, USA
| | | | - Robert C Cantu
- Boston University Alzheimer's Disease Research Center and CTE Center, Department of Neurology, Boston University School of Medicine, 72 E Concord Street, Suite B7800, Boston, MA, 02118, USA
- Concussion Legacy Foundation, Boston, MA, USA
- Department of Neurosurgery, Boston University School of Medicine, Boston, USA
- Department of Neurosurgery, Emerson Hospital, Concord, USA
| | - Neil W Kowall
- Boston University Alzheimer's Disease Research Center and CTE Center, Department of Neurology, Boston University School of Medicine, 72 E Concord Street, Suite B7800, Boston, MA, 02118, USA
- Department of Pathology and Laboratory Medicine, Boston University School of Medicine, Boston, USA
- US Department of Veteran Affairs, VA Boston Healthcare System, Boston, USA
| | - Bertrand Russell Huber
- Boston University Alzheimer's Disease Research Center and CTE Center, Department of Neurology, Boston University School of Medicine, 72 E Concord Street, Suite B7800, Boston, MA, 02118, USA
- US Department of Veteran Affairs, VA Boston Healthcare System, Boston, USA
- National Center for PTSD, VA Boston Healthcare, Boston, USA
| | - Victor E Alvarez
- Boston University Alzheimer's Disease Research Center and CTE Center, Department of Neurology, Boston University School of Medicine, 72 E Concord Street, Suite B7800, Boston, MA, 02118, USA
- US Department of Veteran Affairs, VA Boston Healthcare System, Boston, USA
- Department of Veterans Affairs Medical Center, Bedford, MA, USA
| | - Robert A Stern
- Boston University Alzheimer's Disease Research Center and CTE Center, Department of Neurology, Boston University School of Medicine, 72 E Concord Street, Suite B7800, Boston, MA, 02118, USA
- Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, USA
- Department of Neurosurgery, Boston University School of Medicine, Boston, USA
| | - Thor D Stein
- Boston University Alzheimer's Disease Research Center and CTE Center, Department of Neurology, Boston University School of Medicine, 72 E Concord Street, Suite B7800, Boston, MA, 02118, USA
- Framingham Heart Study, Boston University School of Medicine, 72 E Concord Street, Suite B7800, Boston, MA, 02118, USA
- Department of Pathology and Laboratory Medicine, Boston University School of Medicine, Boston, USA
- US Department of Veteran Affairs, VA Boston Healthcare System, Boston, USA
- Department of Veterans Affairs Medical Center, Bedford, MA, USA
| | - Ronald J Killiany
- Boston University Alzheimer's Disease Research Center and CTE Center, Department of Neurology, Boston University School of Medicine, 72 E Concord Street, Suite B7800, Boston, MA, 02118, USA
- Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, USA
- Center for Biomedical Imaging, Boston University School of Medicine, Boston, USA
| | - Ann C McKee
- Boston University Alzheimer's Disease Research Center and CTE Center, Department of Neurology, Boston University School of Medicine, 72 E Concord Street, Suite B7800, Boston, MA, 02118, USA
- Framingham Heart Study, Boston University School of Medicine, 72 E Concord Street, Suite B7800, Boston, MA, 02118, USA
- Department of Pathology and Laboratory Medicine, Boston University School of Medicine, Boston, USA
- US Department of Veteran Affairs, VA Boston Healthcare System, Boston, USA
- Department of Veterans Affairs Medical Center, Bedford, MA, USA
| | - Jesse Mez
- Boston University Alzheimer's Disease Research Center and CTE Center, Department of Neurology, Boston University School of Medicine, 72 E Concord Street, Suite B7800, Boston, MA, 02118, USA.
- Framingham Heart Study, Boston University School of Medicine, 72 E Concord Street, Suite B7800, Boston, MA, 02118, USA.
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do Vale-Britto PHF, Rabin L, Spindola L, Nitrini R, Brucki SMD. Assessment of judgment ability in a Brazilian sample of patients with mild cognitive impairment and dementia. Dement Neuropsychol 2021; 15:200-209. [PMID: 34345361 PMCID: PMC8283876 DOI: 10.1590/1980-57642021dn15-020007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2020] [Accepted: 12/29/2020] [Indexed: 12/03/2022] Open
Abstract
Judgment is the ability to make sound decisions after consideration of relevant information, possible solutions, likely outcomes, and contextual factors. Loss of judgment is common in patients with mild cognitive impairment (MCI) and dementia. The Test of Practical Judgment (TOP-J) evaluates practical judgment in adults and the elderly, with 15- and 9-item versions that require individuals to listen to scenarios about everyday problems and report their solutions.
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Affiliation(s)
- Patrícia Helena Figueirêdo do Vale-Britto
- Behavioral and Cognitive Neurology Unit, Department of Neurology, Cognitive Disorders Reference Center, Hospital das Clínicas, Universidade de São Paulo ‒ São Paulo, SP, Brazil
| | - Laura Rabin
- Department of Psychology, Brooklyn College and the Graduate Center of the City University of New York ‒ Brooklyn, New York, USA
| | - Livia Spindola
- Behavioral and Cognitive Neurology Unit, Department of Neurology, Cognitive Disorders Reference Center, Hospital das Clínicas, Universidade de São Paulo ‒ São Paulo, SP, Brazil
| | - Ricardo Nitrini
- Behavioral and Cognitive Neurology Unit, Department of Neurology, Cognitive Disorders Reference Center, Hospital das Clínicas, Universidade de São Paulo ‒ São Paulo, SP, Brazil
| | - Sonia Maria Dozzi Brucki
- Behavioral and Cognitive Neurology Unit, Department of Neurology, Cognitive Disorders Reference Center, Hospital das Clínicas, Universidade de São Paulo ‒ São Paulo, SP, Brazil
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11
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Margolis SA, Hallowell ES, Davis JD, Kenney LE, Tremont GN. The Clinical Utility and Ecological Validity of the Medication Management Ability Assessment in Older Adults with and without Dementia. Arch Clin Neuropsychol 2021; 36:37-50. [PMID: 32808040 DOI: 10.1093/arclin/acaa058] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/08/2020] [Indexed: 11/13/2022] Open
Abstract
OBJECTIVE Older adults are susceptible to medication nonadherence, which may signify functional decline. Thus, performance-based proxies of medication-taking behavior may help diagnose dementia. We assessed the Medication Management Ability Assessment's (MMAA) clinical utility and ecological validity. METHOD This was a retrospective chart review of 180 outpatients (age = 72 ± 8 years) who completed the MMAA during clinical evaluations. Forty-seven were cognitively normal (CN), 103 had mild cognitive impairment (MCI), and 30 had dementia. Most (136) were independent in medication management, whereas 28 were assisted and 16 were dependent. Kruskal-Wallis tests assessed whether MMAA scores differed by diagnosis and independence. Receiver operating characteristic (ROC) analyses identified diagnostic cut-offs. Classification accuracy estimates were derived. RESULTS MMAA performance differed across diagnosis as expected (p's < .001). Those who were independent in medication management outperformed assisted and dependent counterparts (p's < .001). Assisted and dependent cases were no different. At a cut-off = 23, the MMAA was good-to-strong in distinguishing dementia from CN cases (Sn = 0.96, Sp = 0.83), dementia from MCI (Sn = 0.70, Sp = 0.83), and dementia from functionally unimpaired cases (Sn = 0.78, Sp = 0.83). At a cut-off = 27, it had good sensitivity but weaker specificity when distinguishing both MCI and all cognitively impaired patients (MCI and dementia) from CN cases (Sn = 0.81, Sp = 0.66 and Sn = 0.81, Sp = 0.72, respectively). CONCLUSIONS The MMAA has ecological validity and clinical utility in identifying dementia. Its inclusion in neuropsychological practice may be especially useful when medication mismanagement is suspected.
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Affiliation(s)
- Seth A Margolis
- Department of Psychiatry, Rhode Island Hospital, Providence, RI, USA.,Department of Psychiatry & Human Behavior, Warren Alpert Medical School, Brown University, Providence, RI, USA
| | - Emily S Hallowell
- Department of Psychiatry & Human Behavior, Warren Alpert Medical School, Brown University, Providence, RI, USA
| | - Jennifer D Davis
- Department of Psychiatry, Rhode Island Hospital, Providence, RI, USA.,Department of Psychiatry & Human Behavior, Warren Alpert Medical School, Brown University, Providence, RI, USA
| | - Lauren E Kenney
- Department of Clinical and Health Psychology, University of Florida, Gainesville, FL, USA
| | - Geoffrey N Tremont
- Department of Psychiatry, Rhode Island Hospital, Providence, RI, USA.,Department of Psychiatry & Human Behavior, Warren Alpert Medical School, Brown University, Providence, RI, USA
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12
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Oey MJ, Brouwer VHEW, Buijs MJ, Wijnia JW, Postma A, Oudman E. Unraveling Apathy in Korsakoff Syndrome Patients Receiving Long-Term Care With and Without Cerebrovascular Comorbidity. Alcohol Clin Exp Res 2021; 45:131-139. [PMID: 33196105 PMCID: PMC7898846 DOI: 10.1111/acer.14513] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2020] [Accepted: 11/09/2020] [Indexed: 01/08/2023]
Abstract
BACKGROUND Korsakoff syndrome (KS) is a severe neuropsychiatric disorder caused by acute deficiency of vitamin B1 and concomitant alcoholism. Patients with KS are particularly vulnerable for cerebrovascular comorbidity. KS is characterized by cognitive and neuropsychiatric symptoms, one of which is apathy. Apathy is a pathological lack of goal-directed behaviors, goal-directed cognitions, and goal-directed emotions. Cerebrovascular accidents are known to carry a risk for developing apathy. Apathy has a dramatic effect on the autonomy and daily lives of patients suffering from this condition. METHODS We assessed general apathy and related subconstructs in fifteen patients with KS, fifteen patients with KS and cerebrovascular comorbidity who reside in a 24-hour care facility, and fifteen healthy controls. RESULTS Compared with healthy controls, both KS patient groups showed higher levels of apathy as rated by a close informant. We found no difference between both KS patient groups and the healthy control group on the self-report section of the Pleasant Activities List, suggesting that motivation is still intact in KS patients. It is important to note a discrepancy was found between self-reporting and proxy reporting on this list. KS patients with cerebrovascular comorbidity showed more severe emotional blunting compared to both KS patients without cerebrovascular comorbidity and healthy controls. The competency to consent was lower in patients compared with healthy controls, but no difference was found between KS patients with cerebrovascular comorbidity and those without. CONCLUSIONS Our results suggest that KS patients show increased levels of general apathy compared with healthy controls. Patients show a diminished competency to consent and increased emotional blunting, while motivation is not compromised. Cerebrovascular comorbidity in KS forms a high risk for emotional blunting. The results of this study suggest that apathy is a severe problem in KS. More attention in both the literature and clinical practice would benefit this complex patient population.
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Affiliation(s)
- Misha J. Oey
- From theExperimental Psychology(MJO, VHEWB, MJB, AP, EO)Helmholtz InstituteUtrecht UniversityUtrechtThe Netherlands
- Lelie Care Group(MJO, JWW, AP, EO)Slingedael Korsakoff CenterRotterdamThe Netherlands
| | - Veerle H. E. W. Brouwer
- From theExperimental Psychology(MJO, VHEWB, MJB, AP, EO)Helmholtz InstituteUtrecht UniversityUtrechtThe Netherlands
| | - Marie J. Buijs
- From theExperimental Psychology(MJO, VHEWB, MJB, AP, EO)Helmholtz InstituteUtrecht UniversityUtrechtThe Netherlands
| | - Jan Watze Wijnia
- Lelie Care Group(MJO, JWW, AP, EO)Slingedael Korsakoff CenterRotterdamThe Netherlands
| | - Albert Postma
- From theExperimental Psychology(MJO, VHEWB, MJB, AP, EO)Helmholtz InstituteUtrecht UniversityUtrechtThe Netherlands
- Lelie Care Group(MJO, JWW, AP, EO)Slingedael Korsakoff CenterRotterdamThe Netherlands
| | - Erik Oudman
- From theExperimental Psychology(MJO, VHEWB, MJB, AP, EO)Helmholtz InstituteUtrecht UniversityUtrechtThe Netherlands
- Lelie Care Group(MJO, JWW, AP, EO)Slingedael Korsakoff CenterRotterdamThe Netherlands
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Sugarman MA, Zetterberg H, Blennow K, Tripodis Y, McKee AC, Stein TD, Martin B, Palmisano JN, Steinberg EG, Simkin I, Budson AE, Killiany R, O'Connor MK, Au R, Qiu WWQ, Goldstein LE, Kowall NW, Mez J, Stern RA, Alosco ML. A longitudinal examination of plasma neurofilament light and total tau for the clinical detection and monitoring of Alzheimer's disease. Neurobiol Aging 2020; 94:60-70. [PMID: 32585491 DOI: 10.1016/j.neurobiolaging.2020.05.011] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2019] [Revised: 05/19/2020] [Accepted: 05/22/2020] [Indexed: 12/22/2022]
Abstract
We examined baseline and longitudinal associations between plasma neurofilament light (NfL) and total tau (t-tau), and the clinical presentation of Alzheimer's disease (AD). A total of 579 participants (238, normal cognition [NC]; 185, mild cognitive impairment [MCI]; 156, AD dementia) had baseline blood draws; 82% had follow-up evaluations. Plasma samples were analyzed for NfL and t-tau using Simoa technology. Baseline plasma NfL was higher in AD dementia than MCI (standardized mean difference = 0.55, 95% CI: 0.37-0.73) and NC (standardized mean difference = 0.68, 95% CI: 0.49-0.88), corresponded to Clinical Dementia Rating scores (OR = 1.94, 95% CI: 1.35-2.79]), and correlated with all neuropsychological tests (r's = 0.13-0.42). Longitudinally, NfL did not predict diagnostic conversion but predicted decline on 3/10 neuropsychological tests. Baseline plasma t-tau was higher in AD dementia than NC with a small effect (standardized mean difference = 0.33, 95% CI: 0.10-0.57) but not MCI. t-tau did not statistically significant predict any longitudinal outcomes. Plasma NfL may be useful for the detection of AD dementia and monitoring of disease progression. In contrast, there was minimal evidence in support of plasma t-tau.
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Affiliation(s)
- Michael A Sugarman
- Boston University Alzheimer's Disease Center and CTE Center, Boston University School of Medicine, Boston, MA, USA; Department of Neuropsychology, Edith Nourse Rogers Memorial Veterans Hospital, Bedford, MA, USA
| | - Henrik Zetterberg
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK; UK Dementia Research Institute at UCL, London, UK; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden; Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden
| | - Kaj Blennow
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden; Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden
| | - Yorghos Tripodis
- Boston University Alzheimer's Disease Center and CTE Center, Boston University School of Medicine, Boston, MA, USA; Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Ann C McKee
- Boston University Alzheimer's Disease Center and CTE Center, Boston University School of Medicine, Boston, MA, USA; Department of Neurology, Boston University School of Medicine, Boston, MA, USA; Department of Pathology and Laboratory Medicine, Boston University School of Medicine, Boston, MA, USA; U.S. Department of Veteran Affairs, VA Boston Healthcare System, Jamaica Plain, MA, USA; Department of Veterans Affairs Medical Center, Bedford, MA, USA
| | - Thor D Stein
- Boston University Alzheimer's Disease Center and CTE Center, Boston University School of Medicine, Boston, MA, USA; U.S. Department of Veteran Affairs, VA Boston Healthcare System, Jamaica Plain, MA, USA; Department of Veterans Affairs Medical Center, Bedford, MA, USA
| | - Brett Martin
- Boston University Alzheimer's Disease Center and CTE Center, Boston University School of Medicine, Boston, MA, USA; Biostatistics and Epidemiology Data Analytics Center, Boston University School of Public Health, Boston, MA, USA
| | - Joseph N Palmisano
- Boston University Alzheimer's Disease Center and CTE Center, Boston University School of Medicine, Boston, MA, USA; Biostatistics and Epidemiology Data Analytics Center, Boston University School of Public Health, Boston, MA, USA
| | - Eric G Steinberg
- Boston University Alzheimer's Disease Center and CTE Center, Boston University School of Medicine, Boston, MA, USA
| | - Irene Simkin
- Department of Medicine, Boston University School of Medicine, Boston, MA, USA
| | - Andrew E Budson
- Boston University Alzheimer's Disease Center and CTE Center, Boston University School of Medicine, Boston, MA, USA; Department of Neurology, Boston University School of Medicine, Boston, MA, USA; U.S. Department of Veteran Affairs, VA Boston Healthcare System, Jamaica Plain, MA, USA
| | - Ronald Killiany
- Boston University Alzheimer's Disease Center and CTE Center, Boston University School of Medicine, Boston, MA, USA; Department of Anatomy & Neurobiology, Boston University School of Medicine, Boston, MA, USA; Center for Biomedical Imaging, Boston University School of Medicine, Boston, MA, USA
| | - Maureen K O'Connor
- Boston University Alzheimer's Disease Center and CTE Center, Boston University School of Medicine, Boston, MA, USA; Department of Neuropsychology, Edith Nourse Rogers Memorial Veterans Hospital, Bedford, MA, USA
| | - Rhoda Au
- Boston University Alzheimer's Disease Center and CTE Center, Boston University School of Medicine, Boston, MA, USA; Department of Neurology, Boston University School of Medicine, Boston, MA, USA; Department of Anatomy & Neurobiology, Boston University School of Medicine, Boston, MA, USA; Framingham Heart Study, National Heart, Lung, and Blood Institute, Framingham, MA, USA; Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA
| | - Wendy Wei Qiao Qiu
- Boston University Alzheimer's Disease Center and CTE Center, Boston University School of Medicine, Boston, MA, USA; Department of Psychiatry, Boston University School of Medicine, Boston, MA, USA; Department of Pharmacology & Experimental Therapeutics, Boston University School of Medicine, Boston, MA, USA
| | - Lee E Goldstein
- Boston University Alzheimer's Disease Center and CTE Center, Boston University School of Medicine, Boston, MA, USA; Department of Pathology and Laboratory Medicine, Boston University School of Medicine, Boston, MA, USA; Departments of Psychiatry and Ophthalmology, Boston University School of Medicine, Boston, MA, USA; Departments of Biomedical, Electrical & Computer Engineering, Boston University College of Engineering, Boston, MA, USA
| | - Neil W Kowall
- Boston University Alzheimer's Disease Center and CTE Center, Boston University School of Medicine, Boston, MA, USA; Department of Neurology, Boston University School of Medicine, Boston, MA, USA; Department of Pathology and Laboratory Medicine, Boston University School of Medicine, Boston, MA, USA; U.S. Department of Veteran Affairs, VA Boston Healthcare System, Jamaica Plain, MA, USA
| | - Jesse Mez
- Boston University Alzheimer's Disease Center and CTE Center, Boston University School of Medicine, Boston, MA, USA; Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| | - Robert A Stern
- Boston University Alzheimer's Disease Center and CTE Center, Boston University School of Medicine, Boston, MA, USA; Department of Neurology, Boston University School of Medicine, Boston, MA, USA; Department of Anatomy & Neurobiology, Boston University School of Medicine, Boston, MA, USA; Department of Neurosurgery, Boston University School of Medicine, Boston, MA, USA
| | - Michael L Alosco
- Boston University Alzheimer's Disease Center and CTE Center, Boston University School of Medicine, Boston, MA, USA; Department of Neurology, Boston University School of Medicine, Boston, MA, USA.
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Kenney LE, Margolis SA, Davis JD, Tremont G. The Screening Utility and Ecological Validity of the Neuropsychological Assessment Battery Bill Payment Subtest in Older Adults with and without Dementia. Arch Clin Neuropsychol 2019; 34:1156-1164. [DOI: 10.1093/arclin/acz033] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2019] [Revised: 05/31/2019] [Indexed: 11/12/2022] Open
Abstract
Abstract
Objective
The Neuropsychological Assessment Battery Bill Payment subtest has shown strong diagnostic accuracy in dementia due to Alzheimer’s disease (AD) versus non-AD. Its relationship to mild cognitive impairment (MCI) or all-cause dementia has not been fully examined nor has its ecological validity as a proxy of financial independence.
Method
We describe 270 women (63%) and men (age = 72 ± 8.39) who completed Bill Payment during outpatient neuropsychological evaluation. Seventy-one were cognitively normal (CN), 160 had MCI, and 39 had Dementia. Two hundred fourteen were independent in money management, 31 were assisted (had oversight/some help), and 25 were dependent (relied on others). Receiver operating characteristic (ROC) curves tested Bill Payment’s utility as a dementia screen. Kruskal–Wallis tests examined whether Bill Payment differed by levels of financial independence.
Results
At a cutoff of 17, Bill Payment had strong sensitivity (0.87) and specificity (0.80) for dementia versus CN cases. A cutoff of 15 distinguished dementia from MCI (Sn = 0.64, Sp = 0.85), whereas a cutoff of 16 distinguished dementia from functionally unimpaired cases (MCI + CN) with greater sensitivity and similar specificity (Sn = 0.74, Sp = 0.81). Sensitivity attenuated in MCI versus CN cases (Sn = 0.46, Sp = 0.83). Those who were independent in money management had higher scores than assisted and dependent cases (p ≤ 0.046). Assisted and dependent cases were no different (p > 0.05).
Conclusions
Bill Payment is a valid screen of all-cause dementia. Lower Bill Payment scores may mark subtle functional decline beyond cognitive impairment alone. Specifically, results provide preliminary evidence of Bill Payment’s ecological validity as a measure related to financial independence. It may prove useful when impaired financial abilities are suspected but unreported.
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Affiliation(s)
- Lauren E Kenney
- Department of Psychiatry, Rhode Island Hospital, Providence, RI, USA
| | - Seth A Margolis
- Department of Psychiatry, Rhode Island Hospital, Providence, RI, USA
- Department of Psychiatry & Human Behavior, Warren Alpert Medical School, Brown University, Providence, RI, USA
| | - Jennifer D Davis
- Department of Psychiatry, Rhode Island Hospital, Providence, RI, USA
- Department of Psychiatry & Human Behavior, Warren Alpert Medical School, Brown University, Providence, RI, USA
| | - Geoffrey Tremont
- Department of Psychiatry, Rhode Island Hospital, Providence, RI, USA
- Department of Psychiatry & Human Behavior, Warren Alpert Medical School, Brown University, Providence, RI, USA
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Ashendorf L, Alosco ML, Bing-Canar H, Chapman KR, Martin B, Chaisson CE, Dixon D, Steinberg EG, Tripodis Y, Kowall NW, Stern RA. Clinical Utility of Select Neuropsychological Assessment Battery Tests in Predicting Functional Abilities in Dementia. Arch Clin Neuropsychol 2018; 33:530-540. [PMID: 29126099 PMCID: PMC6116785 DOI: 10.1093/arclin/acx100] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2016] [Revised: 08/21/2017] [Accepted: 10/02/2017] [Indexed: 11/13/2022] Open
Abstract
OBJECTIVE Neuropsychological test performance can provide insight into functional abilities in patients with dementia, particularly in the absence of an informant. The relationship between neuropsychological measures and instrumental activities of daily living (IADLs) is unclear due to hetereogeneity in cognitive domains assessed and neuropsychological tests administered. Practical and ecologically valid performance-based measures of IADLs are also limited. The Neuropsychological Assessment Battery (NAB) is uniquely positioned to provide a dual-purpose assessment of cognitive and IADL function, as it includes Daily Living tests that simulate real-world functional tasks. We examined the utility of select NAB tests in predicting informant-reported IADLs in mild cognitive impairment and dementia. METHODS The sample of 327 participants included 128 normal controls, 97 individuals with mild cognitive impairment, and 102 individuals with Alzheimer's disease dementia from the Boston University Alzheimer's Disease Center research registry. Informants completed the Lawton Brody Instrumental Activities of Daily Living Scale, and study participants were administered selected NAB tests that were complementary to the existing protocol. RESULTS ROC curves showed strongest prediction of IADL (AUC > 0.90) for memory measures (List Learning delayed recall and Daily Living Memory delayed recall) and Daily Living Driving Scenes. At a predetermined level of specificity (95%), List Learning delayed recall (71%) and Daily Living Memory delayed recall (88%) were the most sensitive. The Daily Living Memory and Driving Scenes tests strongly predicted IADL status, and the other Daily Living tests contributed unique variance. CONCLUSIONS NAB memory measures and Daily Living Tests may have clinical utility in detecting informant-rated functional impairment in dementia.
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Affiliation(s)
- Lee Ashendorf
- Department of Psychiatry, Boston University School of Medicine, Boston, Massachusetts, USA
- Edith Nourse Rogers Memorial Veterans Hospital, Bedford, Massachusetts, USA
| | - Michael L Alosco
- Boston University Alzheimer’s Disease and CTE Center, Boston University School of Medicine, Boston, Massachusetts, USA
- Department of Neurology, Boston University School of Medicine, Boston, Massachusetts, USA
| | - Hanaan Bing-Canar
- Boston University Alzheimer’s Disease and CTE Center, Boston University School of Medicine, Boston, Massachusetts, USA
| | - Kimberly R Chapman
- Boston University Alzheimer’s Disease and CTE Center, Boston University School of Medicine, Boston, Massachusetts, USA
| | - Brett Martin
- Boston University Alzheimer’s Disease and CTE Center, Boston University School of Medicine, Boston, Massachusetts, USA
- Data Coordinating Center, Boston University School of Public Health, Boston, Massachusetts, USA
| | - Christine E Chaisson
- Boston University Alzheimer’s Disease and CTE Center, Boston University School of Medicine, Boston, Massachusetts, USA
- Data Coordinating Center, Boston University School of Public Health, Boston, Massachusetts, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, USA
| | - Diane Dixon
- Boston University Alzheimer’s Disease and CTE Center, Boston University School of Medicine, Boston, Massachusetts, USA
- Data Coordinating Center, Boston University School of Public Health, Boston, Massachusetts, USA
| | - Eric G Steinberg
- Boston University Alzheimer’s Disease and CTE Center, Boston University School of Medicine, Boston, Massachusetts, USA
| | - Yorghos Tripodis
- Boston University Alzheimer’s Disease and CTE Center, Boston University School of Medicine, Boston, Massachusetts, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, USA
| | - Neil W Kowall
- Boston University Alzheimer’s Disease and CTE Center, Boston University School of Medicine, Boston, Massachusetts, USA
- Department of Neurology, Boston University School of Medicine, Boston, Massachusetts, USA
- Department of Pathology, Boston University School of Medicine, Boston, Massachusetts, USA
- Neurology Service, VA Boston Healthcare System, Boston, Massachusetts, USA
| | - Robert A Stern
- Boston University Alzheimer’s Disease and CTE Center, Boston University School of Medicine, Boston, Massachusetts, USA
- Department of Neurology, Boston University School of Medicine, Boston, Massachusetts, USA
- Departments of Neurosurgery, and Anatomy & Neurobiology, Boston University School of Medicine, Boston, Massachusetts, USA
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16
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Giannouli V, Stamovlasis D, Tsolaki M. Exploring the Role of Cognitive Factors in a New Instrument for Elders’ Financial Capacity Assessment. J Alzheimers Dis 2018; 62:1579-1594. [DOI: 10.3233/jad-170812] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Affiliation(s)
- Vaitsa Giannouli
- School of Medicine, Aristotle University of Thessaloniki, Greece
| | | | - Magda Tsolaki
- School of Medicine, Aristotle University of Thessaloniki, Greece
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17
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Screening Utility of the King-Devick Test in Mild Cognitive Impairment and Alzheimer Disease Dementia. Alzheimer Dis Assoc Disord 2017; 31:152-158. [PMID: 27299935 DOI: 10.1097/wad.0000000000000157] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
The King-Devick (K-D) test is a 1 to 2 minute, rapid number naming test, often used to assist with detection of concussion, but also has clinical utility in other neurological conditions (eg, Parkinson disease). The K-D involves saccadic eye and other eye movements, and abnormalities thereof may be an early indicator of Alzheimer disease (AD)-associated cognitive impairment. No study has tested the utility of the K-D in AD and we sought to do so. The sample included 206 [135 controls, 39 mild cognitive impairment (MCI), and 32 AD dementia] consecutive subjects from the Boston University Alzheimer's Disease Center registry undergoing their initial annual evaluation between March 2013 and July 2015. The K-D was administered during this period. Areas under the receiver operating characteristic curves generated from logistic regression models revealed the K-D test distinguished controls from subjects with cognitive impairment (MCI and AD dementia) [area under the curve (AUC)=0.72], MCI (AUC=0.71) and AD dementia (AUC=0.74). K-D time scores between 48 and 52 seconds were associated with high sensitivity (>90.0%) and negative predictive values (>85.0%) for each diagnostic group. The K-D correlated strongly with validated attention, processing speed, and visual scanning tests. The K-D test may be a rapid and simple effective screening tool to detect cognitive impairment associated with AD.
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18
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Weissberger GH, Strong JV, Stefanidis KB, Summers MJ, Bondi MW, Stricker NH. Diagnostic Accuracy of Memory Measures in Alzheimer's Dementia and Mild Cognitive Impairment: a Systematic Review and Meta-Analysis. Neuropsychol Rev 2017; 27:354-388. [PMID: 28940127 PMCID: PMC5886311 DOI: 10.1007/s11065-017-9360-6] [Citation(s) in RCA: 89] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2016] [Accepted: 08/16/2017] [Indexed: 11/26/2022]
Abstract
With an increasing focus on biomarkers in dementia research, illustrating the role of neuropsychological assessment in detecting mild cognitive impairment (MCI) and Alzheimer's dementia (AD) is important. This systematic review and meta-analysis, conducted in accordance with PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) standards, summarizes the sensitivity and specificity of memory measures in individuals with MCI and AD. Both meta-analytic and qualitative examination of AD versus healthy control (HC) studies (n = 47) revealed generally high sensitivity and specificity (≥ 80% for AD comparisons) for measures of immediate (sensitivity = 87%, specificity = 88%) and delayed memory (sensitivity = 89%, specificity = 89%), especially those involving word-list recall. Examination of MCI versus HC studies (n = 38) revealed generally lower diagnostic accuracy for both immediate (sensitivity = 72%, specificity = 81%) and delayed memory (sensitivity = 75%, specificity = 81%). Measures that differentiated AD from other conditions (n = 10 studies) yielded mixed results, with generally high sensitivity in the context of low or variable specificity. Results confirm that memory measures have high diagnostic accuracy for identification of AD, are promising but require further refinement for identification of MCI, and provide support for ongoing investigation of neuropsychological assessment as a cognitive biomarker of preclinical AD. Emphasizing diagnostic test accuracy statistics over null hypothesis testing in future studies will promote the ongoing use of neuropsychological tests as Alzheimer's disease research and clinical criteria increasingly rely upon cerebrospinal fluid (CSF) and neuroimaging biomarkers.
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Affiliation(s)
- Gali H Weissberger
- Brain, Behavior, and Aging Research Center, VA Greater Los Angeles Healthcare System, Los Angeles, CA, USA
- Psychology Service, VA Boston Healthcare System, Boston, MA, USA
| | - Jessica V Strong
- Psychology Service, VA Boston Healthcare System, Boston, MA, USA
- New England Geriatric Research, Education and Clinical Center (GRECC), Boston VA Healthcare System, Boston, MA, USA
| | - Kayla B Stefanidis
- Sunshine Coast Mind and Neuroscience - Thompson Institute, University of the Sunshine Coast, Sippy Downs, Queensland, Australia
| | - Mathew J Summers
- Sunshine Coast Mind and Neuroscience - Thompson Institute, University of the Sunshine Coast, Sippy Downs, Queensland, Australia
| | - Mark W Bondi
- VA San Diego Healthcare System, San Diego, CA, USA
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Nikki H Stricker
- Psychology Service, VA Boston Healthcare System, Boston, MA, USA.
- Department of Psychiatry and Psychology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.
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19
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Karzmark P, Deutsch GK. Accuracy statistics in predicting Independent Activities of Daily Living (IADL) capacity with comprehensive and brief neuropsychological test batteries. APPLIED NEUROPSYCHOLOGY. ADULT 2017. [PMID: 28631986 DOI: 10.1080/23279095.2017.1286347] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
This investigation was designed to determine the predictive accuracy of a comprehensive neuropsychological and brief neuropsychological test battery with regard to the capacity to perform instrumental activities of daily living (IADLs). Accuracy statistics that included measures of sensitivity, specificity, positive and negative predicted power and positive likelihood ratio were calculated for both types of batteries. The sample was drawn from a general neurological group of adults (n = 117) that included a number of older participants (age >55; n = 38). Standardized neuropsychological assessments were administered to all participants and were comprised of the Halstead Reitan Battery and portions of the Wechsler Adult Intelligence Scale-III. A comprehensive test battery yielded a moderate increase over base-rate in predictive accuracy that generalized to older individuals. There was only limited support for using a brief battery, for although sensitivity was high, specificity was low. We found that a comprehensive neuropsychological test battery provided good classification accuracy for predicting IADL capacity.
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Affiliation(s)
- Peter Karzmark
- a Department of Neurology and Neurological Sciences, Stanford Health Care , Palo Alto , California , USA
| | - Gayle K Deutsch
- a Department of Neurology and Neurological Sciences, Stanford Health Care , Palo Alto , California , USA
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20
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Durant J, Berg JL, Banks SJ, Miller JB. Comparing the test of practical judgment with the neuropsychological assessment battery judgment subtest in a neurodegenerative disease clinic population. APPLIED NEUROPSYCHOLOGY-ADULT 2017; 25:489-496. [PMID: 28605212 DOI: 10.1080/23279095.2017.1329147] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Abstract
The Test of Practical Judgment (TOP-J) and the Judgment subtest from the Neuropsychological Assessment Battery (NAB-JDG) are both brief interview-based measures that assess judgment. This study compared estimates of judgment obtained from these measures in a neurodegenerative disease population. Records from 61 referrals seen for neuropsychological evaluation in a neurodegenerative disorders clinic were reviewed. Measures of interest included the TOP-J and NAB-JDG. Concordance correlation coefficients (CCC) and root mean square differences (RMSD) were calculated between judgment T-scores. Discrepancy scores were calculated by subtracting NAB-JDG scores from TOP-J scores. CCC showed poor agreement between the judgment measures, with evidence of fixed bias, such that the NAB-JDG systematically generates higher scores than the TOP-J. This fixed bias was present whether NAB-JDG scores are demographically adjusted or unadjusted. There was no evidence of proportional bias. In a neurodegenerative disease clinic population, the TOP-J and NAB-JDG provide estimates of judgment ability that are systematically different. These two measures may be assessing different aspects within the larger construct of judgment and the inconsistency between measures would contraindicate using them interchangeably. Clinicians will need to carefully consider patient characteristics, clinical needs, and review specific item content when selecting between these measures.
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Affiliation(s)
- January Durant
- a Cleveland Clinic Lou Ruvo Center for Brain Health , Las Vegas , Nevada , USA
| | - Jody-Lynn Berg
- a Cleveland Clinic Lou Ruvo Center for Brain Health , Las Vegas , Nevada , USA
| | - Sarah Jane Banks
- a Cleveland Clinic Lou Ruvo Center for Brain Health , Las Vegas , Nevada , USA
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21
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Buczylowska D, Daseking M, Petermann F. Age-related differences in the predictive ability of executive functions for intelligence. ZEITSCHRIFT FUR NEUROPSYCHOLOGIE 2016. [DOI: 10.1024/1016-264x/a000179] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Abstract
Abstract. The Executive Functions Module of the Neuropsychological Assessment Battery (NAB) and the Wechsler Adult Intelligence Scale – Fourth Edition (WAIS-IV) were used to investigate age-related differences in the predictability of intelligence with executive functions. The NAB subtests age and sex better predicted the WAIS-IV index scales and the Full Scale IQ in the older than in the younger age group, with total variance explained up to 75 % in 60- to 88-year-olds and up to 46 % in 18- to 59-year-olds. The NAB subtests Categories and Word Generation were most frequently included, whereas Letter Fluency was least frequently included in the best-fitting models of WAIS-IV prediction. Mazes predicted better in the younger age group, whereas Judgment predicted better in the older age group.
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Affiliation(s)
- Dorota Buczylowska
- Zentrum für Klinische Psychologie und Rehabilitation, Universität Bremen, Germany
| | - Monika Daseking
- Zentrum für Klinische Psychologie und Rehabilitation, Universität Bremen, Germany
| | - Franz Petermann
- Zentrum für Klinische Psychologie und Rehabilitation, Universität Bremen, Germany
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22
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Buczylowska D, Petermann F. Age-related commonalities and differences in the relationship between executive functions and intelligence: Analysis of the NAB executive functions module and WAIS-IV scores. APPLIED NEUROPSYCHOLOGY-ADULT 2016; 24:465-480. [DOI: 10.1080/23279095.2016.1211528] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Affiliation(s)
- Dorota Buczylowska
- Center for Clinical Psychology and Rehabilitation, University of Bremen, Bremen, Germany
| | - Franz Petermann
- Center for Clinical Psychology and Rehabilitation, University of Bremen, Bremen, Germany
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23
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Grills CE, Armistead-Jehle P. Performance validity test and neuropsychological assessment battery screening module performances in an active-duty sample with a history of concussion. APPLIED NEUROPSYCHOLOGY-ADULT 2016; 23:295-301. [DOI: 10.1080/23279095.2015.1079713] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
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Gavett BE, Vudy V, Jeffrey M, John SE, Gurnani AS, Adams JW. The δ latent dementia phenotype in the uniform data set: Cross-validation and extension. Neuropsychology 2014; 29:344-52. [PMID: 25151112 DOI: 10.1037/neu0000128] [Citation(s) in RCA: 36] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022] Open
Abstract
OBJECTIVE Royall and colleagues identified a latent dementia phenotype, "δ", reflecting the "cognitive correlates of functional status." We sought to cross-validate and extend these findings in a large clinical case series of adults with and without dementia. METHOD A confirmatory factor analysis (CFA) model for δ was fit to National Alzheimer's Coordinating Center data (n = 26,068). Factor scores derived from δ were compared with the Clinical Dementia Rating Sum of Boxes (CDR-SB) and to clinically diagnosed dementia. A longitudinal parallel-process growth model compared changes in δ with changes in CDR-SB over 6 annual evaluations. RESULTS The CFA model fit well; CFI = 0.971, RMSEA = 0.070. Factor scores derived from δ discriminated between demented and nondemented participants with an area under the curve of .96. The growth model also fit well, CFI = 0.969, RMSEA = 0.032. CONCLUSIONS The δ construct represents a novel approach to measuring dementia-related changes and has potential to improve cognitive assessment of neurodegenerative diseases.
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Affiliation(s)
- Brandon E Gavett
- Department of Psychology, University of Colorado, Colorado Springs
| | - Vanessa Vudy
- Department of Psychology, University of Colorado, Colorado Springs
| | - Mary Jeffrey
- Department of Psychology, University of Colorado, Colorado Springs
| | - Samantha E John
- Department of Psychology, University of Colorado, Colorado Springs
| | - Ashita S Gurnani
- Department of Psychology, University of Colorado, Colorado Springs
| | - Jason W Adams
- Department of Psychology, University of Colorado, Colorado Springs
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25
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MacDougall EE, Mansbach WE. The Judgment Test of the Neuropsychological Assessment Battery (NAB): psychometric considerations in an assisted-living sample. Clin Neuropsychol 2013; 27:827-39. [PMID: 23570279 DOI: 10.1080/13854046.2013.786759] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
Abstract
A total of 82 older adults recruited from assisted-living facilities completed the Judgment subtest of the Neuropsychological Assessment Battery. The internal consistency reliability of Judgment scores in this sample, as estimated by Cronbach's α, was .83. Significant and strong Judgment score correlations with measures of general cognitive functioning and instrumental activities of daily living provided evidence of construct validity. Furthermore, participants who exhibited the capacity to consent to the evaluation performed significantly better on the Judgment subtest than did participants who did not exhibit consent capacity. Finally, Judgment scores predicted a significant proportion of variance in both instrumental and basic activities of daily living over and above the variance accounted for by scores on measures of general cognitive functioning and executive functioning. This study presents promising preliminary evidence of the incremental validity of Judgment subtest scores for predicting both basic and instrumental activities of daily living in an assisted-living sample.
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