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Evaluation of a research diagnostic algorithm for DSM-5 neurocognitive disorders in a population-based cohort of older adults

BACKGROUND: There is little information on the application and impact of revised criteria for diagnosing dementia and mild cognitive impairment (MCI), now termed major and mild neurocognitive disorders (NCDs) in the DSM-5. We evaluate a psychometric algorithm for diagnosing DSM-5 NCDs in a community...

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Autores principales: Eramudugolla, Ranmalee, Mortby, Moyra E., Sachdev, Perminder, Meslin, Chantal, Kumar, Rajeev, Anstey, Kaarin J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5336665/
https://www.ncbi.nlm.nih.gov/pubmed/28259179
http://dx.doi.org/10.1186/s13195-017-0246-x
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author Eramudugolla, Ranmalee
Mortby, Moyra E.
Sachdev, Perminder
Meslin, Chantal
Kumar, Rajeev
Anstey, Kaarin J.
author_facet Eramudugolla, Ranmalee
Mortby, Moyra E.
Sachdev, Perminder
Meslin, Chantal
Kumar, Rajeev
Anstey, Kaarin J.
author_sort Eramudugolla, Ranmalee
collection PubMed
description BACKGROUND: There is little information on the application and impact of revised criteria for diagnosing dementia and mild cognitive impairment (MCI), now termed major and mild neurocognitive disorders (NCDs) in the DSM-5. We evaluate a psychometric algorithm for diagnosing DSM-5 NCDs in a community-dwelling sample, and characterize the neuropsychological and functional profile of expert-diagnosed DSM-5 NCDs relative to DSM-IV dementia and International Working Group criteria for MCI. METHODS: A population-based sample of 1644 adults aged 72–78 years was assessed. Algorithmic diagnostic criteria used detailed neuropsychological data, medical history, longitudinal cognitive performance, and informant interview. Those meeting all criteria for at least one diagnosis had data reviewed by a neurologist (expert diagnosis) who achieved consensus with a psychiatrist for complex cases. RESULTS: The algorithm accurately classified DSM-5 major NCD (area under the curve (AUC) = 0.95, 95% confidence interval (CI) 0.92–0.97), DSM-IV dementia (AUC = 0.91, 95% CI 0.85–0.97), DSM-5 mild NCD (AUC = 0.75, 95% CI 0.70–0.80), and MCI (AUC = 0.76, 95% CI 0.72–0.81) when compared to expert diagnosis. Expert diagnosis of dementia using DSM-5 criteria overlapped with 90% of DSM-IV dementia cases, but resulted in a 127% increase in diagnosis relative to DSM-IV. Additional cases had less severe memory, language impairment, and instrumental activities of daily living (IADL) impairments compared to cases meeting DSM-IV criteria for dementia. DSM-5 mild NCD overlapped with 83% of MCI cases and resulted in a 19% increase in diagnosis. These additional cases had a subtly different neurocognitive profile to MCI cases, including poorer social cognition. CONCLUSION: DSM-5 NCD criteria can be operationalized in a psychometric algorithm in a population setting. Expert diagnosis using DSM-5 NCD criteria captured most cases with DSM-IV dementia and MCI in our sample, but included many additional cases suggesting that DSM-5 criteria are broader in their categorization. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13195-017-0246-x) contains supplementary material, which is available to authorized users.
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spelling pubmed-53366652017-03-07 Evaluation of a research diagnostic algorithm for DSM-5 neurocognitive disorders in a population-based cohort of older adults Eramudugolla, Ranmalee Mortby, Moyra E. Sachdev, Perminder Meslin, Chantal Kumar, Rajeev Anstey, Kaarin J. Alzheimers Res Ther Research BACKGROUND: There is little information on the application and impact of revised criteria for diagnosing dementia and mild cognitive impairment (MCI), now termed major and mild neurocognitive disorders (NCDs) in the DSM-5. We evaluate a psychometric algorithm for diagnosing DSM-5 NCDs in a community-dwelling sample, and characterize the neuropsychological and functional profile of expert-diagnosed DSM-5 NCDs relative to DSM-IV dementia and International Working Group criteria for MCI. METHODS: A population-based sample of 1644 adults aged 72–78 years was assessed. Algorithmic diagnostic criteria used detailed neuropsychological data, medical history, longitudinal cognitive performance, and informant interview. Those meeting all criteria for at least one diagnosis had data reviewed by a neurologist (expert diagnosis) who achieved consensus with a psychiatrist for complex cases. RESULTS: The algorithm accurately classified DSM-5 major NCD (area under the curve (AUC) = 0.95, 95% confidence interval (CI) 0.92–0.97), DSM-IV dementia (AUC = 0.91, 95% CI 0.85–0.97), DSM-5 mild NCD (AUC = 0.75, 95% CI 0.70–0.80), and MCI (AUC = 0.76, 95% CI 0.72–0.81) when compared to expert diagnosis. Expert diagnosis of dementia using DSM-5 criteria overlapped with 90% of DSM-IV dementia cases, but resulted in a 127% increase in diagnosis relative to DSM-IV. Additional cases had less severe memory, language impairment, and instrumental activities of daily living (IADL) impairments compared to cases meeting DSM-IV criteria for dementia. DSM-5 mild NCD overlapped with 83% of MCI cases and resulted in a 19% increase in diagnosis. These additional cases had a subtly different neurocognitive profile to MCI cases, including poorer social cognition. CONCLUSION: DSM-5 NCD criteria can be operationalized in a psychometric algorithm in a population setting. Expert diagnosis using DSM-5 NCD criteria captured most cases with DSM-IV dementia and MCI in our sample, but included many additional cases suggesting that DSM-5 criteria are broader in their categorization. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13195-017-0246-x) contains supplementary material, which is available to authorized users. BioMed Central 2017-03-04 /pmc/articles/PMC5336665/ /pubmed/28259179 http://dx.doi.org/10.1186/s13195-017-0246-x Text en © The Author(s). 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Eramudugolla, Ranmalee
Mortby, Moyra E.
Sachdev, Perminder
Meslin, Chantal
Kumar, Rajeev
Anstey, Kaarin J.
Evaluation of a research diagnostic algorithm for DSM-5 neurocognitive disorders in a population-based cohort of older adults
title Evaluation of a research diagnostic algorithm for DSM-5 neurocognitive disorders in a population-based cohort of older adults
title_full Evaluation of a research diagnostic algorithm for DSM-5 neurocognitive disorders in a population-based cohort of older adults
title_fullStr Evaluation of a research diagnostic algorithm for DSM-5 neurocognitive disorders in a population-based cohort of older adults
title_full_unstemmed Evaluation of a research diagnostic algorithm for DSM-5 neurocognitive disorders in a population-based cohort of older adults
title_short Evaluation of a research diagnostic algorithm for DSM-5 neurocognitive disorders in a population-based cohort of older adults
title_sort evaluation of a research diagnostic algorithm for dsm-5 neurocognitive disorders in a population-based cohort of older adults
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5336665/
https://www.ncbi.nlm.nih.gov/pubmed/28259179
http://dx.doi.org/10.1186/s13195-017-0246-x
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