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Protocol for validating an algorithm to identify neurocognitive disorders in Canadian Longitudinal Study on Aging participants: an observational study

INTRODUCTION: In population-based research, disease ascertainment algorithms can be as accurate as, and less costly than, performing supplementary clinical examinations on selected participants to confirm a diagnosis of a neurocognitive disorder (NCD), but they require cohort-specific validation. To...

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Autores principales: Mayhew, Alexandra J, Hogan, David, Raina, Parminder, Wolfson, Christina, Costa, Andrew P, Jones, Aaron, Kirkland, Susan, O'Connell, Megan, Taler, Vanessa, Smith, Eric E, Liu-Ambrose, Teresa, Ma, Jinhui, Thompson, Mary, Wu, Changbao, Chertkow, Howard, Griffith, Lauren E
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10626860/
https://www.ncbi.nlm.nih.gov/pubmed/37914306
http://dx.doi.org/10.1136/bmjopen-2023-073027
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author Mayhew, Alexandra J
Hogan, David
Raina, Parminder
Wolfson, Christina
Costa, Andrew P
Jones, Aaron
Kirkland, Susan
O'Connell, Megan
Taler, Vanessa
Smith, Eric E
Liu-Ambrose, Teresa
Ma, Jinhui
Thompson, Mary
Wu, Changbao
Chertkow, Howard
Griffith, Lauren E
author_facet Mayhew, Alexandra J
Hogan, David
Raina, Parminder
Wolfson, Christina
Costa, Andrew P
Jones, Aaron
Kirkland, Susan
O'Connell, Megan
Taler, Vanessa
Smith, Eric E
Liu-Ambrose, Teresa
Ma, Jinhui
Thompson, Mary
Wu, Changbao
Chertkow, Howard
Griffith, Lauren E
author_sort Mayhew, Alexandra J
collection PubMed
description INTRODUCTION: In population-based research, disease ascertainment algorithms can be as accurate as, and less costly than, performing supplementary clinical examinations on selected participants to confirm a diagnosis of a neurocognitive disorder (NCD), but they require cohort-specific validation. To optimise the use of the Canadian Longitudinal Study on Aging (CLSA) to understand the epidemiology and burden of NCDs, the CLSA Memory Study will validate an NCD ascertainment algorithm to identify CLSA participants with these disorders using routinely acquired study data. METHODS AND ANALYSIS: Up to 600 CLSA participants with equal numbers of those likely to have no NCD, mild NCD or major NCD based on prior self-reported physician diagnosis of a memory problem or dementia, medication consumption (ie, cholinesterase inhibitors, memantine) and/or self-reported function will be recruited during the follow-up 3 CLSA evaluations (started August 2021). Participants will undergo an assessment by a study clinician who will also review an informant interview and make a preliminary determination of the presence or absence of an NCD. The clinical assessment and available CLSA data will be reviewed by a Central Review Panel who will make a final categorisation of participants as having (1) no NCD, (2) mild NCD or, (3) major NCD (according to fifth version of the Diagnostic and Statistical Manual of Mental Disorders criteria). These will be used as our gold standard diagnosis to determine if the NCD ascertainment algorithm accurately identifies CLSA participants with an NCD. Weighted Kappa statistics will be the primary measure of agreement. Sensitivity, specificity, the C-statistic and the phi coefficient will also be estimated. ETHICS AND DISSEMINATION: Ethics approval has been received from the institutional research ethics boards for each CLSA Data Collection Site (Université de Sherbrooke, Hamilton Integrated Research Ethics Board, Dalhousie University, Nova Scotia Health Research Ethics Board, University of Manitoba, McGill University, McGill University Health Centre Research Institute, Memorial University of Newfoundland, University of Victoria, Élisabeth Bruyère Research Institute of Ottawa, University of British Columbia, Island Health (Formerly the Vancouver Island Health Authority, Simon Fraser University, Calgary Conjoint Health Research Ethics Board). The results of this work will be disseminated to public health professionals, researchers, health professionals, administrators and policy-makers through journal publications, conference presentations, publicly available reports and presentations to stakeholder groups.
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spelling pubmed-106268602023-11-07 Protocol for validating an algorithm to identify neurocognitive disorders in Canadian Longitudinal Study on Aging participants: an observational study Mayhew, Alexandra J Hogan, David Raina, Parminder Wolfson, Christina Costa, Andrew P Jones, Aaron Kirkland, Susan O'Connell, Megan Taler, Vanessa Smith, Eric E Liu-Ambrose, Teresa Ma, Jinhui Thompson, Mary Wu, Changbao Chertkow, Howard Griffith, Lauren E BMJ Open Epidemiology INTRODUCTION: In population-based research, disease ascertainment algorithms can be as accurate as, and less costly than, performing supplementary clinical examinations on selected participants to confirm a diagnosis of a neurocognitive disorder (NCD), but they require cohort-specific validation. To optimise the use of the Canadian Longitudinal Study on Aging (CLSA) to understand the epidemiology and burden of NCDs, the CLSA Memory Study will validate an NCD ascertainment algorithm to identify CLSA participants with these disorders using routinely acquired study data. METHODS AND ANALYSIS: Up to 600 CLSA participants with equal numbers of those likely to have no NCD, mild NCD or major NCD based on prior self-reported physician diagnosis of a memory problem or dementia, medication consumption (ie, cholinesterase inhibitors, memantine) and/or self-reported function will be recruited during the follow-up 3 CLSA evaluations (started August 2021). Participants will undergo an assessment by a study clinician who will also review an informant interview and make a preliminary determination of the presence or absence of an NCD. The clinical assessment and available CLSA data will be reviewed by a Central Review Panel who will make a final categorisation of participants as having (1) no NCD, (2) mild NCD or, (3) major NCD (according to fifth version of the Diagnostic and Statistical Manual of Mental Disorders criteria). These will be used as our gold standard diagnosis to determine if the NCD ascertainment algorithm accurately identifies CLSA participants with an NCD. Weighted Kappa statistics will be the primary measure of agreement. Sensitivity, specificity, the C-statistic and the phi coefficient will also be estimated. ETHICS AND DISSEMINATION: Ethics approval has been received from the institutional research ethics boards for each CLSA Data Collection Site (Université de Sherbrooke, Hamilton Integrated Research Ethics Board, Dalhousie University, Nova Scotia Health Research Ethics Board, University of Manitoba, McGill University, McGill University Health Centre Research Institute, Memorial University of Newfoundland, University of Victoria, Élisabeth Bruyère Research Institute of Ottawa, University of British Columbia, Island Health (Formerly the Vancouver Island Health Authority, Simon Fraser University, Calgary Conjoint Health Research Ethics Board). The results of this work will be disseminated to public health professionals, researchers, health professionals, administrators and policy-makers through journal publications, conference presentations, publicly available reports and presentations to stakeholder groups. BMJ Publishing Group 2023-11-01 /pmc/articles/PMC10626860/ /pubmed/37914306 http://dx.doi.org/10.1136/bmjopen-2023-073027 Text en © Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) .
spellingShingle Epidemiology
Mayhew, Alexandra J
Hogan, David
Raina, Parminder
Wolfson, Christina
Costa, Andrew P
Jones, Aaron
Kirkland, Susan
O'Connell, Megan
Taler, Vanessa
Smith, Eric E
Liu-Ambrose, Teresa
Ma, Jinhui
Thompson, Mary
Wu, Changbao
Chertkow, Howard
Griffith, Lauren E
Protocol for validating an algorithm to identify neurocognitive disorders in Canadian Longitudinal Study on Aging participants: an observational study
title Protocol for validating an algorithm to identify neurocognitive disorders in Canadian Longitudinal Study on Aging participants: an observational study
title_full Protocol for validating an algorithm to identify neurocognitive disorders in Canadian Longitudinal Study on Aging participants: an observational study
title_fullStr Protocol for validating an algorithm to identify neurocognitive disorders in Canadian Longitudinal Study on Aging participants: an observational study
title_full_unstemmed Protocol for validating an algorithm to identify neurocognitive disorders in Canadian Longitudinal Study on Aging participants: an observational study
title_short Protocol for validating an algorithm to identify neurocognitive disorders in Canadian Longitudinal Study on Aging participants: an observational study
title_sort protocol for validating an algorithm to identify neurocognitive disorders in canadian longitudinal study on aging participants: an observational study
topic Epidemiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10626860/
https://www.ncbi.nlm.nih.gov/pubmed/37914306
http://dx.doi.org/10.1136/bmjopen-2023-073027
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