Adding Recognition Discriminability Index to the Delayed Recall Is Useful to Predict Conversion from Mild Cognitive Impairment to Alzheimer's Disease in the Alzheimer's Disease Neu...

Autores
Russo, María Julieta; Campos, Jorge; Vázquez, Silvia; Sevlever, Gustavo; Allegri, Ricardo Francisco
Año de publicación
2017
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Background: Ongoing research is focusing on the identification of those individuals with mild cognitive impairment (MCI) who are most likely to convert to Alzheimer's disease (AD). We investigated whether recognition memory tasks in combination with delayed recall measure of episodic memory and CSF biomarkers can predict MCI to AD conversion at 24-month follow-up. Methods: A total of 397 amnestic-MCI subjects from Alzheimer's disease Neuroimaging Initiative were included. Logistic regression modeling was done to assess the predictive value of all RAVLT measures, risk factors such as age, sex, education, APOE genotype, and CSF biomarkers for progression to AD. Estimating adjusted odds ratios was used to determine which variables would produce an optimal predictive model, and whether adding tests of interaction between the RAVLT Delayed Recall and recognition measures (traditional score and d-prime) would improve prediction of the conversion from a-MCI to AD. Results: 112 (28.2%) subjects developed dementia and 285 (71.8%) subjects did not. Of the all included variables, CSF Aβ1-42 levels, RAVLT Delayed Recall, and the combination of RAVLT Delayed Recall and d-prime were predictive of progression to AD (χ2 = 38.23, df = 14, p < 0.001). Conclusions: The combination of RAVLT Delayed Recall and d-prime measures may be predictor of conversion from MCI to AD in the ADNI cohort, especially in combination with amyloid biomarkers. A predictive model to help identify individuals at-risk for dementia should include not only traditional episodic memory measures (delayed recall or recognition), but also additional variables (d-prime) that allow the homogenization of the assessment procedures in the diagnosis of MCI.
Fil: Russo, María Julieta. Fundación para la Lucha Contra las Enfermedades Neurológicas de la Infancia. Instituto de Investigaciones Neurológicas "Raúl Carrea"; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Campos, Jorge. Fundación para la Lucha Contra las Enfermedades Neurológicas de la Infancia. Instituto de Investigaciones Neurológicas "Raúl Carrea"; Argentina
Fil: Vázquez, Silvia. Fundación para la Lucha Contra las Enfermedades Neurológicas de la Infancia. Instituto de Investigaciones Neurológicas "Raúl Carrea"; Argentina
Fil: Sevlever, Gustavo. Fundación para la Lucha Contra las Enfermedades Neurológicas de la Infancia. Instituto de Investigaciones Neurológicas "Raúl Carrea"; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Allegri, Ricardo Francisco. Fundación para la Lucha Contra las Enfermedades Neurológicas de la Infancia. Instituto de Investigaciones Neurológicas "Raúl Carrea"; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Materia
ALZHEIMER'S DISEASE
DISEASE PROGRESSION
MEMORY
MILD COGNITIVE IMPAIRMENT
RECOGNITION DISCRIMINABILITY
SIGNAL DETECTION THEORY
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/40823
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/40823
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Adding Recognition Discriminability Index to the Delayed Recall Is Useful to Predict Conversion from Mild Cognitive Impairment to Alzheimer's Disease in the Alzheimer's Disease Neuroimaging InitiativeRusso, María JulietaCampos, JorgeVázquez, SilviaSevlever, GustavoAllegri, Ricardo FranciscoALZHEIMER'S DISEASEDISEASE PROGRESSIONMEMORYMILD COGNITIVE IMPAIRMENTRECOGNITION DISCRIMINABILITYSIGNAL DETECTION THEORYhttps://purl.org/becyt/ford/3.2https://purl.org/becyt/ford/3Background: Ongoing research is focusing on the identification of those individuals with mild cognitive impairment (MCI) who are most likely to convert to Alzheimer's disease (AD). We investigated whether recognition memory tasks in combination with delayed recall measure of episodic memory and CSF biomarkers can predict MCI to AD conversion at 24-month follow-up. Methods: A total of 397 amnestic-MCI subjects from Alzheimer's disease Neuroimaging Initiative were included. Logistic regression modeling was done to assess the predictive value of all RAVLT measures, risk factors such as age, sex, education, APOE genotype, and CSF biomarkers for progression to AD. Estimating adjusted odds ratios was used to determine which variables would produce an optimal predictive model, and whether adding tests of interaction between the RAVLT Delayed Recall and recognition measures (traditional score and d-prime) would improve prediction of the conversion from a-MCI to AD. Results: 112 (28.2%) subjects developed dementia and 285 (71.8%) subjects did not. Of the all included variables, CSF Aβ1-42 levels, RAVLT Delayed Recall, and the combination of RAVLT Delayed Recall and d-prime were predictive of progression to AD (χ2 = 38.23, df = 14, p < 0.001). Conclusions: The combination of RAVLT Delayed Recall and d-prime measures may be predictor of conversion from MCI to AD in the ADNI cohort, especially in combination with amyloid biomarkers. A predictive model to help identify individuals at-risk for dementia should include not only traditional episodic memory measures (delayed recall or recognition), but also additional variables (d-prime) that allow the homogenization of the assessment procedures in the diagnosis of MCI.Fil: Russo, María Julieta. Fundación para la Lucha Contra las Enfermedades Neurológicas de la Infancia. Instituto de Investigaciones Neurológicas "Raúl Carrea"; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Campos, Jorge. Fundación para la Lucha Contra las Enfermedades Neurológicas de la Infancia. Instituto de Investigaciones Neurológicas "Raúl Carrea"; ArgentinaFil: Vázquez, Silvia. Fundación para la Lucha Contra las Enfermedades Neurológicas de la Infancia. Instituto de Investigaciones Neurológicas "Raúl Carrea"; ArgentinaFil: Sevlever, Gustavo. Fundación para la Lucha Contra las Enfermedades Neurológicas de la Infancia. Instituto de Investigaciones Neurológicas "Raúl Carrea"; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Allegri, Ricardo Francisco. Fundación para la Lucha Contra las Enfermedades Neurológicas de la Infancia. Instituto de Investigaciones Neurológicas "Raúl Carrea"; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFrontiers Research Foundation2017-03info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/40823Russo, María Julieta; Campos, Jorge; Vázquez, Silvia; Sevlever, Gustavo; Allegri, Ricardo Francisco; Adding Recognition Discriminability Index to the Delayed Recall Is Useful to Predict Conversion from Mild Cognitive Impairment to Alzheimer's Disease in the Alzheimer's Disease Neuroimaging Initiative; Frontiers Research Foundation; Frontiers in Aging Neuroscience; 9; MAR; 3-2017; 1-71663-4365CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.3389/fnagi.2017.00046info:eu-repo/semantics/altIdentifier/url/https://www.frontiersin.org/articles/10.3389/fnagi.2017.00046/fullinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:41:43Zoai:ri.conicet.gov.ar:11336/40823instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 09:41:44.089CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Adding Recognition Discriminability Index to the Delayed Recall Is Useful to Predict Conversion from Mild Cognitive Impairment to Alzheimer's Disease in the Alzheimer's Disease Neuroimaging Initiative
title Adding Recognition Discriminability Index to the Delayed Recall Is Useful to Predict Conversion from Mild Cognitive Impairment to Alzheimer's Disease in the Alzheimer's Disease Neuroimaging Initiative
spellingShingle Adding Recognition Discriminability Index to the Delayed Recall Is Useful to Predict Conversion from Mild Cognitive Impairment to Alzheimer's Disease in the Alzheimer's Disease Neuroimaging Initiative
Russo, María Julieta
ALZHEIMER'S DISEASE
DISEASE PROGRESSION
MEMORY
MILD COGNITIVE IMPAIRMENT
RECOGNITION DISCRIMINABILITY
SIGNAL DETECTION THEORY
title_short Adding Recognition Discriminability Index to the Delayed Recall Is Useful to Predict Conversion from Mild Cognitive Impairment to Alzheimer's Disease in the Alzheimer's Disease Neuroimaging Initiative
title_full Adding Recognition Discriminability Index to the Delayed Recall Is Useful to Predict Conversion from Mild Cognitive Impairment to Alzheimer's Disease in the Alzheimer's Disease Neuroimaging Initiative
title_fullStr Adding Recognition Discriminability Index to the Delayed Recall Is Useful to Predict Conversion from Mild Cognitive Impairment to Alzheimer's Disease in the Alzheimer's Disease Neuroimaging Initiative
title_full_unstemmed Adding Recognition Discriminability Index to the Delayed Recall Is Useful to Predict Conversion from Mild Cognitive Impairment to Alzheimer's Disease in the Alzheimer's Disease Neuroimaging Initiative
title_sort Adding Recognition Discriminability Index to the Delayed Recall Is Useful to Predict Conversion from Mild Cognitive Impairment to Alzheimer's Disease in the Alzheimer's Disease Neuroimaging Initiative
dc.creator.none.fl_str_mv Russo, María Julieta
Campos, Jorge
Vázquez, Silvia
Sevlever, Gustavo
Allegri, Ricardo Francisco
author Russo, María Julieta
author_facet Russo, María Julieta
Campos, Jorge
Vázquez, Silvia
Sevlever, Gustavo
Allegri, Ricardo Francisco
author_role author
author2 Campos, Jorge
Vázquez, Silvia
Sevlever, Gustavo
Allegri, Ricardo Francisco
author2_role author
author
author
author
dc.subject.none.fl_str_mv ALZHEIMER'S DISEASE
DISEASE PROGRESSION
MEMORY
MILD COGNITIVE IMPAIRMENT
RECOGNITION DISCRIMINABILITY
SIGNAL DETECTION THEORY
topic ALZHEIMER'S DISEASE
DISEASE PROGRESSION
MEMORY
MILD COGNITIVE IMPAIRMENT
RECOGNITION DISCRIMINABILITY
SIGNAL DETECTION THEORY
purl_subject.fl_str_mv https://purl.org/becyt/ford/3.2
https://purl.org/becyt/ford/3
dc.description.none.fl_txt_mv Background: Ongoing research is focusing on the identification of those individuals with mild cognitive impairment (MCI) who are most likely to convert to Alzheimer's disease (AD). We investigated whether recognition memory tasks in combination with delayed recall measure of episodic memory and CSF biomarkers can predict MCI to AD conversion at 24-month follow-up. Methods: A total of 397 amnestic-MCI subjects from Alzheimer's disease Neuroimaging Initiative were included. Logistic regression modeling was done to assess the predictive value of all RAVLT measures, risk factors such as age, sex, education, APOE genotype, and CSF biomarkers for progression to AD. Estimating adjusted odds ratios was used to determine which variables would produce an optimal predictive model, and whether adding tests of interaction between the RAVLT Delayed Recall and recognition measures (traditional score and d-prime) would improve prediction of the conversion from a-MCI to AD. Results: 112 (28.2%) subjects developed dementia and 285 (71.8%) subjects did not. Of the all included variables, CSF Aβ1-42 levels, RAVLT Delayed Recall, and the combination of RAVLT Delayed Recall and d-prime were predictive of progression to AD (χ2 = 38.23, df = 14, p < 0.001). Conclusions: The combination of RAVLT Delayed Recall and d-prime measures may be predictor of conversion from MCI to AD in the ADNI cohort, especially in combination with amyloid biomarkers. A predictive model to help identify individuals at-risk for dementia should include not only traditional episodic memory measures (delayed recall or recognition), but also additional variables (d-prime) that allow the homogenization of the assessment procedures in the diagnosis of MCI.
Fil: Russo, María Julieta. Fundación para la Lucha Contra las Enfermedades Neurológicas de la Infancia. Instituto de Investigaciones Neurológicas "Raúl Carrea"; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Campos, Jorge. Fundación para la Lucha Contra las Enfermedades Neurológicas de la Infancia. Instituto de Investigaciones Neurológicas "Raúl Carrea"; Argentina
Fil: Vázquez, Silvia. Fundación para la Lucha Contra las Enfermedades Neurológicas de la Infancia. Instituto de Investigaciones Neurológicas "Raúl Carrea"; Argentina
Fil: Sevlever, Gustavo. Fundación para la Lucha Contra las Enfermedades Neurológicas de la Infancia. Instituto de Investigaciones Neurológicas "Raúl Carrea"; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Allegri, Ricardo Francisco. Fundación para la Lucha Contra las Enfermedades Neurológicas de la Infancia. Instituto de Investigaciones Neurológicas "Raúl Carrea"; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
description Background: Ongoing research is focusing on the identification of those individuals with mild cognitive impairment (MCI) who are most likely to convert to Alzheimer's disease (AD). We investigated whether recognition memory tasks in combination with delayed recall measure of episodic memory and CSF biomarkers can predict MCI to AD conversion at 24-month follow-up. Methods: A total of 397 amnestic-MCI subjects from Alzheimer's disease Neuroimaging Initiative were included. Logistic regression modeling was done to assess the predictive value of all RAVLT measures, risk factors such as age, sex, education, APOE genotype, and CSF biomarkers for progression to AD. Estimating adjusted odds ratios was used to determine which variables would produce an optimal predictive model, and whether adding tests of interaction between the RAVLT Delayed Recall and recognition measures (traditional score and d-prime) would improve prediction of the conversion from a-MCI to AD. Results: 112 (28.2%) subjects developed dementia and 285 (71.8%) subjects did not. Of the all included variables, CSF Aβ1-42 levels, RAVLT Delayed Recall, and the combination of RAVLT Delayed Recall and d-prime were predictive of progression to AD (χ2 = 38.23, df = 14, p < 0.001). Conclusions: The combination of RAVLT Delayed Recall and d-prime measures may be predictor of conversion from MCI to AD in the ADNI cohort, especially in combination with amyloid biomarkers. A predictive model to help identify individuals at-risk for dementia should include not only traditional episodic memory measures (delayed recall or recognition), but also additional variables (d-prime) that allow the homogenization of the assessment procedures in the diagnosis of MCI.
publishDate 2017
dc.date.none.fl_str_mv 2017-03
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/40823
Russo, María Julieta; Campos, Jorge; Vázquez, Silvia; Sevlever, Gustavo; Allegri, Ricardo Francisco; Adding Recognition Discriminability Index to the Delayed Recall Is Useful to Predict Conversion from Mild Cognitive Impairment to Alzheimer's Disease in the Alzheimer's Disease Neuroimaging Initiative; Frontiers Research Foundation; Frontiers in Aging Neuroscience; 9; MAR; 3-2017; 1-7
1663-4365
CONICET Digital
CONICET
url http://hdl.handle.net/11336/40823
identifier_str_mv Russo, María Julieta; Campos, Jorge; Vázquez, Silvia; Sevlever, Gustavo; Allegri, Ricardo Francisco; Adding Recognition Discriminability Index to the Delayed Recall Is Useful to Predict Conversion from Mild Cognitive Impairment to Alzheimer's Disease in the Alzheimer's Disease Neuroimaging Initiative; Frontiers Research Foundation; Frontiers in Aging Neuroscience; 9; MAR; 3-2017; 1-7
1663-4365
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.3389/fnagi.2017.00046
info:eu-repo/semantics/altIdentifier/url/https://www.frontiersin.org/articles/10.3389/fnagi.2017.00046/full
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Frontiers Research Foundation
publisher.none.fl_str_mv Frontiers Research Foundation
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.070432

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