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Identifying dementia using medical data linkage in a longitudinal cohort study: Lothian Birth Cohort 1936

BACKGROUND: The Lothian Birth Cohort 1936 (LBC1936) is a longitudinal study of ageing with well-characterised assessments, but until now, it has relied on self-report or proxies for dementia such as cognitive tests. Our aims were twofold: a) to describe a framework for identifying dementia in a coho...

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Autores principales: Mullin, Donncha S., Stirland, Lucy E., Buchanan, Emily, Convery, Catherine-Anne, Cox, Simon R., Deary, Ian J., Giuntoli, Cinzia, Greer, Holly, Page, Danielle, Robertson, Elizabeth, Shenkin, Susan D., Szalek, Anna, Taylor, Adele, Weatherdon, Georgina, Wilkinson, Tim, Russ, Tom C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10152609/
https://www.ncbi.nlm.nih.gov/pubmed/37127606
http://dx.doi.org/10.1186/s12888-023-04797-7
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author Mullin, Donncha S.
Stirland, Lucy E.
Buchanan, Emily
Convery, Catherine-Anne
Cox, Simon R.
Deary, Ian J.
Giuntoli, Cinzia
Greer, Holly
Page, Danielle
Robertson, Elizabeth
Shenkin, Susan D.
Szalek, Anna
Taylor, Adele
Weatherdon, Georgina
Wilkinson, Tim
Russ, Tom C.
author_facet Mullin, Donncha S.
Stirland, Lucy E.
Buchanan, Emily
Convery, Catherine-Anne
Cox, Simon R.
Deary, Ian J.
Giuntoli, Cinzia
Greer, Holly
Page, Danielle
Robertson, Elizabeth
Shenkin, Susan D.
Szalek, Anna
Taylor, Adele
Weatherdon, Georgina
Wilkinson, Tim
Russ, Tom C.
author_sort Mullin, Donncha S.
collection PubMed
description BACKGROUND: The Lothian Birth Cohort 1936 (LBC1936) is a longitudinal study of ageing with well-characterised assessments, but until now, it has relied on self-report or proxies for dementia such as cognitive tests. Our aims were twofold: a) to describe a framework for identifying dementia in a cohort study. b) to report the age-specific incidence and prevalence of all-cause dementia and dementia subtypes in 865 individuals in the LBC1936. METHODS: Electronic Health Records (EHR) of all participants were reviewed, and relevant information was extracted to form case vignettes for everyone with any record of cognitive dysfunction. The EHR data sources include hospital and clinic letters, general practitioner and hospital referrals, prescribed medications, imaging and laboratory results. Death certificate data were obtained separately. Clinician assessments were performed when there was concern about a participant's cognition. A diagnosis of probable dementia, possible dementia, or no dementia was agreed upon by a consensus diagnostic review board, comprised of a multidisciplinary team of clinical dementia experts who reviewed case vignettes and clinician assessment letters. For those with probable dementia, a subtype was also determined, where possible. We compared the agreement between our newly ascertained dementia diagnoses with the existing self-reported dementia diagnoses. RESULTS: Self-reported dementia diagnoses were positive in only 17.8% of ascertained dementia diagnoses. The EHR review identified 163/865 (18.8%) individuals as having cognitive dysfunction. At the consensus diagnostic review board, 118/163 were diagnosed with probable all-cause dementia, a prevalence of 13.6%. Age-specific dementia prevalence increased with age from 0.8% (65–74.9 years) to 9.93% (85–89.9 years). Prevalence rates for women were higher in nearly all age groups. The most common subtype was dementia due to Alzheimer disease (49.2%), followed by mixed Alzheimer and cerebrovascular disease (17.0%), dementia of unknown or unspecified cause (16.1%), and dementia due to vascular disease (8.5%). CONCLUSIONS: We present a robust systematic framework and guide for other cohort teams wanting to ascertain dementia diagnoses. The newly ascertained dementia diagnosis provides vital data for further analyses of LBC1936 to allow exploration of lifecourse predictors of dementia. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12888-023-04797-7.
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spelling pubmed-101526092023-05-03 Identifying dementia using medical data linkage in a longitudinal cohort study: Lothian Birth Cohort 1936 Mullin, Donncha S. Stirland, Lucy E. Buchanan, Emily Convery, Catherine-Anne Cox, Simon R. Deary, Ian J. Giuntoli, Cinzia Greer, Holly Page, Danielle Robertson, Elizabeth Shenkin, Susan D. Szalek, Anna Taylor, Adele Weatherdon, Georgina Wilkinson, Tim Russ, Tom C. BMC Psychiatry Research BACKGROUND: The Lothian Birth Cohort 1936 (LBC1936) is a longitudinal study of ageing with well-characterised assessments, but until now, it has relied on self-report or proxies for dementia such as cognitive tests. Our aims were twofold: a) to describe a framework for identifying dementia in a cohort study. b) to report the age-specific incidence and prevalence of all-cause dementia and dementia subtypes in 865 individuals in the LBC1936. METHODS: Electronic Health Records (EHR) of all participants were reviewed, and relevant information was extracted to form case vignettes for everyone with any record of cognitive dysfunction. The EHR data sources include hospital and clinic letters, general practitioner and hospital referrals, prescribed medications, imaging and laboratory results. Death certificate data were obtained separately. Clinician assessments were performed when there was concern about a participant's cognition. A diagnosis of probable dementia, possible dementia, or no dementia was agreed upon by a consensus diagnostic review board, comprised of a multidisciplinary team of clinical dementia experts who reviewed case vignettes and clinician assessment letters. For those with probable dementia, a subtype was also determined, where possible. We compared the agreement between our newly ascertained dementia diagnoses with the existing self-reported dementia diagnoses. RESULTS: Self-reported dementia diagnoses were positive in only 17.8% of ascertained dementia diagnoses. The EHR review identified 163/865 (18.8%) individuals as having cognitive dysfunction. At the consensus diagnostic review board, 118/163 were diagnosed with probable all-cause dementia, a prevalence of 13.6%. Age-specific dementia prevalence increased with age from 0.8% (65–74.9 years) to 9.93% (85–89.9 years). Prevalence rates for women were higher in nearly all age groups. The most common subtype was dementia due to Alzheimer disease (49.2%), followed by mixed Alzheimer and cerebrovascular disease (17.0%), dementia of unknown or unspecified cause (16.1%), and dementia due to vascular disease (8.5%). CONCLUSIONS: We present a robust systematic framework and guide for other cohort teams wanting to ascertain dementia diagnoses. The newly ascertained dementia diagnosis provides vital data for further analyses of LBC1936 to allow exploration of lifecourse predictors of dementia. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12888-023-04797-7. BioMed Central 2023-05-01 /pmc/articles/PMC10152609/ /pubmed/37127606 http://dx.doi.org/10.1186/s12888-023-04797-7 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Mullin, Donncha S.
Stirland, Lucy E.
Buchanan, Emily
Convery, Catherine-Anne
Cox, Simon R.
Deary, Ian J.
Giuntoli, Cinzia
Greer, Holly
Page, Danielle
Robertson, Elizabeth
Shenkin, Susan D.
Szalek, Anna
Taylor, Adele
Weatherdon, Georgina
Wilkinson, Tim
Russ, Tom C.
Identifying dementia using medical data linkage in a longitudinal cohort study: Lothian Birth Cohort 1936
title Identifying dementia using medical data linkage in a longitudinal cohort study: Lothian Birth Cohort 1936
title_full Identifying dementia using medical data linkage in a longitudinal cohort study: Lothian Birth Cohort 1936
title_fullStr Identifying dementia using medical data linkage in a longitudinal cohort study: Lothian Birth Cohort 1936
title_full_unstemmed Identifying dementia using medical data linkage in a longitudinal cohort study: Lothian Birth Cohort 1936
title_short Identifying dementia using medical data linkage in a longitudinal cohort study: Lothian Birth Cohort 1936
title_sort identifying dementia using medical data linkage in a longitudinal cohort study: lothian birth cohort 1936
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10152609/
https://www.ncbi.nlm.nih.gov/pubmed/37127606
http://dx.doi.org/10.1186/s12888-023-04797-7
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