Online Clinical Consensus Diagnosis of Dementia: Development and Validation

doi:10.1111/jgs.16736

. 2020 Aug;68 Suppl 3(Suppl 3):S54-S59.

doi: 10.1111/jgs.16736.

Online Clinical Consensus Diagnosis of Dementia: Development and Validation

Jinkook Lee^{1

2}, Mary Ganguli³, Albert Weerman¹, Sandy Chien¹, Dong Young Lee⁴, Mathew Varghese⁵, Aparajit B Dey⁶

Affiliations

¹ Center for Economic and Social Research, University of Southern California, Los Angeles, California, USA.
² Department of Economics, University of Southern California, and RAND Corporation, Santa Monica, California, USA.
³ Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
⁴ Department of Psychiatry, Seoul National University, Seoul, South Korea.
⁵ Department of Psychiatry, National Institute of Mental Health and Neuroscience, Bengaluru, India.
⁶ Department of Geriatric Medicine, All India Institute of Medical Sciences, New Delhi, India.

PMID: 32815604
PMCID: PMC7513553
DOI: 10.1111/jgs.16736

Free PMC article

Online Clinical Consensus Diagnosis of Dementia: Development and Validation

Jinkook Lee et al. J Am Geriatr Soc. 2020 Aug.

Free PMC article

. 2020 Aug;68 Suppl 3(Suppl 3):S54-S59.

doi: 10.1111/jgs.16736.

Authors

Jinkook Lee^{1

2}, Mary Ganguli³, Albert Weerman¹, Sandy Chien¹, Dong Young Lee⁴, Mathew Varghese⁵, Aparajit B Dey⁶

Affiliations

¹ Center for Economic and Social Research, University of Southern California, Los Angeles, California, USA.
² Department of Economics, University of Southern California, and RAND Corporation, Santa Monica, California, USA.
³ Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
⁴ Department of Psychiatry, Seoul National University, Seoul, South Korea.
⁵ Department of Psychiatry, National Institute of Mental Health and Neuroscience, Bengaluru, India.
⁶ Department of Geriatric Medicine, All India Institute of Medical Sciences, New Delhi, India.

PMID: 32815604
PMCID: PMC7513553
DOI: 10.1111/jgs.16736

Abstract

Objectives: To introduce cost-effective expert clinical diagnoses of dementia into population-based research using an online platform and to demonstrate their validity against in-person clinical assessment and diagnosis.

Design: The online platform provides standardized data necessary for clinicians to rate participants on the Clinical Dementia Rating (CDR^® ). Using this platform, clinicians diagnosed 60 patients at a range of CDR levels at two clinical sites. The online consensus diagnosis was compared with in-person clinical consensus diagnosis.

Setting: All India Institute of Medical Sciences (AIIMS), Delhi, and National Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru, India.

Participants: Thirty patients each at AIIMS and NIMHANS with equal numbers of patients previously independently rated in person by experts as CDR is 0 (cognitively normal), CDR is 0.5 (mild cognitive impairment), and CDR is 1 or greater (dementia).

Measurements: Multiple clinicians independently rate each participant on each CDR domain using standardized data and expert clinical judgment. The overall summary CDR is calculated by algorithm. When there are discrepancies among clinician ratings, clinicians discuss the case through a virtual consensus conference and arrive at a consensus overall rating.

Results: Online clinical consensus diagnosis based on standardized interview data provides consistent clinical diagnosis with in-person clinical assessment and consensus diagnosis (κ coefficient = 0.76).

Conclusion: A web-based clinical consensus platform built on the Harmonized Diagnostic Assessment of Dementia for the Longitudinal Aging Study in India interview data is a cost-effective way to obtain reliable expert clinical judgments. A similar approach can be used for other epidemiological studies of dementia. J Am Geriatr Soc 68:S54-S59, 2020.

Keywords: Clinical Dementia Rating; Harmonized Cognitive Assessment Protocol; Longitudinal Aging Study in India; clinical judgment; population-based research.

PubMed Disclaimer

Conflict of interest statement

Conflict of Interest: The authors have no conflicts of interest to declare.

Figures

**Figure 1.**
Online consensus site screen 1. ADL, activity of daily living; BP, blood pressure; CESD, Center for Epidemiological Studies-Depression; CSI-D, Community Screening Interview for Dementia; DAD, Diagnostic Assessment of Dementia; IADL, instrumental ADL; ID, identifier; IQCODE, Informant Questionnaire on Cognitive Decline in the Elderly; R, respondent.

**Figure 2.**
Online clinical consensus diagnosis process.

See this image and copyright information in PMC

Comment in

New Insights and Knowledge on Cognition and Dementia from Population-Based Cohort of Older Adults in India.
Kenny RA. Kenny RA. J Am Geriatr Soc. 2020 Aug;68 Suppl 3(Suppl 3):S1-S2. doi: 10.1111/jgs.16733. J Am Geriatr Soc. 2020. PMID: 32815601 Free PMC article. No abstract available.

Cited by

MALDI-TOF MS combined with AUC method for tigecycline susceptibility testing in Escherichia coli.
Yan Z, Li J, Hu Y, Zhang Y, Wu Y, Ju X, Cai C, Chen G, Sun C, Zhang R. Yan Z, et al. JAC Antimicrob Resist. 2024 Mar 7;6(2):dlad119. doi: 10.1093/jacamr/dlad119. eCollection 2024 Apr. JAC Antimicrob Resist. 2024. PMID: 38455378 Free PMC article.
Prevalence of DSM-5 mild and major neurocognitive disorder in India: Results from the LASI-DAD.
Gross AL, Nichols E, Angrisani M, Ganguli M, Jin H, Khobragade P, Langa KM, Meijer E, Varghese M, Dey AB, Lee J. Gross AL, et al. PLoS One. 2024 Feb 7;19(2):e0297220. doi: 10.1371/journal.pone.0297220. eCollection 2024. PLoS One. 2024. PMID: 38324518 Free PMC article.
A guide for researchers seeking training in retrospective data harmonization for population neuroscience studies of Alzheimer's disease and related dementias.
Shaaban CE, Tudorascu DL, Glymour MM, Cohen AD, Thurston RC, Snyder HM, Hohman TJ, Mukherjee S, Yu L, Snitz BE. Shaaban CE, et al. Front Neuroimaging. 2022;1:978350. doi: 10.3389/fnimg.2022.978350. Epub 2022 Sep 26. Front Neuroimaging. 2022. PMID: 37464990 Free PMC article.
Feasibility of an online consensus approach for the diagnosis of cognitive impairment and dementia in rural South Africa.
Bassil DT, Farrell MT, Weerman A, Guo M, Wagner RG, Brickman AM, Glymour MM, Langa KM, Manly JJ, Tipping B, Butler I, Tollman S, Berkman LF. Bassil DT, et al. Alzheimers Dement (Amst). 2023 Apr 4;15(2):e12420. doi: 10.1002/dad2.12420. eCollection 2023 Apr-Jun. Alzheimers Dement (Amst). 2023. PMID: 37025188 Free PMC article.
Deep phenotyping and genomic data from a nationally representative study on dementia in India.
Lee J, Petrosyan S, Khobragade P, Banerjee J, Chien S, Weerman B, Gross A, Hu P, Smith JA, Zhao W, Aksman L, Jain U, Shanthi GS, Kurup R, Raman A, Chakrabarti SS, Gambhir IS, Varghese M, John JP, Joshi H, Koul PA, Goswami D, Talukdar A, Mohanty RR, Yadati YSR, Padmaja M, Sankhe L, Rajguru C, Gupta M, Kumar G, Dhar M, Jovicich J, Ganna A, Ganguli M, Chatterjee P, Singhal S, Bansal R, Bajpai S, Desai G, Bhatankar S, Rao AR, Sivakumar PT, Muliyala KP, Sinha P, Loganathan S, Meijer E, Angrisani M, Kim JK, Dey S, Arokiasamy P, Bloom DE, Toga AW, Kardia SLR, Langa K, Crimmins EM, Dey AB. Lee J, et al. Sci Data. 2023 Jan 20;10(1):45. doi: 10.1038/s41597-023-01941-6. Sci Data. 2023. PMID: 36670106 Free PMC article.

See all "Cited by" articles

References

1. Weir DR, Wallace RB, Langa KM, et al. Reducing case ascertainment costs in U.S. population studies of Alzheimerʼs disease, dementia, and cognitive impairment—part 1. Alzheimers Dement. 2011;7(1):94–109. - PMC - PubMed
1. Morris JC. The clinical dementia rating (CDR): current version and scoring rules. Neurology. 1993;43(11):2412–2414. - PubMed
1. John SE, Gurnani AS, Bussell C, Saurman JL, Griffin JW, Gavett BE. The effectiveness and unique contribution of neuropsychological tests and the δ latent phenotype in the differential diagnosis of dementia in the uniform data set. Neuropsychology. 2016;30:946–960. - PMC - PubMed
1. Gavett BE, Vudy V, Jeffrey M, John SE, Gurnani A, Adams J. The δ latent dementia phenotype in the NACC UDS: cross-validation and extension. Neuropsychology. 2015;29:344–352. - PMC - PubMed
1. Royall DR, Palmer RF, Markides KS. Exportation and validation of latent constructs for dementia case-finding in a Mexican-American population-based cohort. J Gerontol B Psychol Sci Soc Sci. 2017;72:947–955. - PMC - PubMed

Publication types

Actions
Actions

MeSH terms

Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions

Grants and funding

LinkOut - more resources

Full Text Sources
Medical
- MedlinePlus Health Information

[1] Weir DR, Wallace RB, Langa KM, et al. Reducing case ascertainment costs in U.S. population studies of Alzheimerʼs disease, dementia, and cognitive impairment—part 1. Alzheimers Dement. 2011;7(1):94–109. - PMC - PubMed

[2] Weir DR, Wallace RB, Langa KM, et al. Reducing case ascertainment costs in U.S. population studies of Alzheimerʼs disease, dementia, and cognitive impairment—part 1. Alzheimers Dement. 2011;7(1):94–109. - PMC - PubMed

[3] Morris JC. The clinical dementia rating (CDR): current version and scoring rules. Neurology. 1993;43(11):2412–2414. - PubMed

[4] Morris JC. The clinical dementia rating (CDR): current version and scoring rules. Neurology. 1993;43(11):2412–2414. - PubMed

[5] John SE, Gurnani AS, Bussell C, Saurman JL, Griffin JW, Gavett BE. The effectiveness and unique contribution of neuropsychological tests and the δ latent phenotype in the differential diagnosis of dementia in the uniform data set. Neuropsychology. 2016;30:946–960. - PMC - PubMed

[6] John SE, Gurnani AS, Bussell C, Saurman JL, Griffin JW, Gavett BE. The effectiveness and unique contribution of neuropsychological tests and the δ latent phenotype in the differential diagnosis of dementia in the uniform data set. Neuropsychology. 2016;30:946–960. - PMC - PubMed

[7] Gavett BE, Vudy V, Jeffrey M, John SE, Gurnani A, Adams J. The δ latent dementia phenotype in the NACC UDS: cross-validation and extension. Neuropsychology. 2015;29:344–352. - PMC - PubMed

[8] Gavett BE, Vudy V, Jeffrey M, John SE, Gurnani A, Adams J. The δ latent dementia phenotype in the NACC UDS: cross-validation and extension. Neuropsychology. 2015;29:344–352. - PMC - PubMed

[9] Royall DR, Palmer RF, Markides KS. Exportation and validation of latent constructs for dementia case-finding in a Mexican-American population-based cohort. J Gerontol B Psychol Sci Soc Sci. 2017;72:947–955. - PMC - PubMed

[10] Royall DR, Palmer RF, Markides KS. Exportation and validation of latent constructs for dementia case-finding in a Mexican-American population-based cohort. J Gerontol B Psychol Sci Soc Sci. 2017;72:947–955. - PMC - PubMed

Save citation to file

Email citation

Add to Collections

Add to My Bibliography

Your saved search

Create a file for external citation management software

Your RSS Feed

Online Clinical Consensus Diagnosis of Dementia: Development and Validation

Affiliations

Online Clinical Consensus Diagnosis of Dementia: Development and Validation

Authors

Affiliations

Abstract

Conflict of interest statement

Figures

Comment in

Similar articles

Cited by

References

Publication types

MeSH terms

Grants and funding

LinkOut - more resources

Full Text Sources

Medical

Abstract

Conflict of interest statement

Figures

Comment in

Similar articles

Cited by

References

Publication types

MeSH terms

Related information

Grants and funding

LinkOut - more resources

Full Text Sources

Medical