Analysis of individual alpha frequency in a large cohort from a tertiary memory center

Background and Purpose Precise and timely diagnosis is crucial for the optimal use of emerging disease‐modifying treatments for Alzheimer disease (AD). Electroencephalography (EEG), which is noninvasive and cost‐effective, can capture neural abnormalities linked to various dementias. This study expl...

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Published inEuropean journal of neurology Vol. 31; no. 10; pp. e16424 - n/a
Main Authors Cecchetti, Giordano, Agosta, Federica, Canu, Elisa, Basaia, Silvia, Rugarli, Giulia, Curti, Davide G., Coraglia, Federico, Cursi, Marco, Spinelli, Edoardo G., Santangelo, Roberto, Caso, Francesca, Fanelli, Giovanna Franca, Magnani, Giuseppe, Filippi, Massimo
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Published England John Wiley & Sons, Inc 01.10.2024
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Abstract Background and Purpose Precise and timely diagnosis is crucial for the optimal use of emerging disease‐modifying treatments for Alzheimer disease (AD). Electroencephalography (EEG), which is noninvasive and cost‐effective, can capture neural abnormalities linked to various dementias. This study explores the use of individual alpha frequency (IAF) derived from EEG as a diagnostic and prognostic tool in cognitively impaired patients. Methods This retrospective study included 375 patients from the tertiary Memory Clinic of IRCCS San Raffaele Hospital, Milan, Italy. Participants underwent clinical and neuropsychological assessments, brain imaging, cerebrospinal fluid biomarker analysis, and resting‐state EEG. Patients were categorized by amyloid status, the AT(N) classification system, clinical diagnosis, and mild cognitive impairment (MCI) progression to AD dementia. IAF was calculated and compared among study groups. Receiver operating characteristic (ROC) analysis was used to calculate its discriminative performance. Results IAF was higher in amyloid‐negative subjects and varied significantly across AT(N) groups. ROC analysis confirmed IAF's ability to distinguish A–T–N– from the A+T+N+ and A+T–N+ groups. IAF was lower in AD and Lewy body dementia patients compared to MCI and other dementia types, with moderate discriminatory capability. Among A+ MCI patients, IAF was significantly lower in those who converted to AD within 2 years compared to stable MCI patients and predicted time to conversion (p < 0.001, R = 0.38). Conclusions IAF is a valuable tool for dementia diagnosis and prognosis, correlating with amyloid status and neurodegeneration. It effectively predicts MCI progression to AD, supporting its use in early, targeted interventions in the context of disease‐modifying treatments.
AbstractList Background and Purpose Precise and timely diagnosis is crucial for the optimal use of emerging disease‐modifying treatments for Alzheimer disease (AD). Electroencephalography (EEG), which is noninvasive and cost‐effective, can capture neural abnormalities linked to various dementias. This study explores the use of individual alpha frequency (IAF) derived from EEG as a diagnostic and prognostic tool in cognitively impaired patients. Methods This retrospective study included 375 patients from the tertiary Memory Clinic of IRCCS San Raffaele Hospital, Milan, Italy. Participants underwent clinical and neuropsychological assessments, brain imaging, cerebrospinal fluid biomarker analysis, and resting‐state EEG. Patients were categorized by amyloid status, the AT(N) classification system, clinical diagnosis, and mild cognitive impairment (MCI) progression to AD dementia. IAF was calculated and compared among study groups. Receiver operating characteristic (ROC) analysis was used to calculate its discriminative performance. Results IAF was higher in amyloid‐negative subjects and varied significantly across AT(N) groups. ROC analysis confirmed IAF's ability to distinguish A–T–N– from the A+T+N+ and A+T–N+ groups. IAF was lower in AD and Lewy body dementia patients compared to MCI and other dementia types, with moderate discriminatory capability. Among A+ MCI patients, IAF was significantly lower in those who converted to AD within 2 years compared to stable MCI patients and predicted time to conversion (p < 0.001, R = 0.38). Conclusions IAF is a valuable tool for dementia diagnosis and prognosis, correlating with amyloid status and neurodegeneration. It effectively predicts MCI progression to AD, supporting its use in early, targeted interventions in the context of disease‐modifying treatments.
Precise and timely diagnosis is crucial for the optimal use of emerging disease-modifying treatments for Alzheimer disease (AD). Electroencephalography (EEG), which is noninvasive and cost-effective, can capture neural abnormalities linked to various dementias. This study explores the use of individual alpha frequency (IAF) derived from EEG as a diagnostic and prognostic tool in cognitively impaired patients.BACKGROUND AND PURPOSEPrecise and timely diagnosis is crucial for the optimal use of emerging disease-modifying treatments for Alzheimer disease (AD). Electroencephalography (EEG), which is noninvasive and cost-effective, can capture neural abnormalities linked to various dementias. This study explores the use of individual alpha frequency (IAF) derived from EEG as a diagnostic and prognostic tool in cognitively impaired patients.This retrospective study included 375 patients from the tertiary Memory Clinic of IRCCS San Raffaele Hospital, Milan, Italy. Participants underwent clinical and neuropsychological assessments, brain imaging, cerebrospinal fluid biomarker analysis, and resting-state EEG. Patients were categorized by amyloid status, the AT(N) classification system, clinical diagnosis, and mild cognitive impairment (MCI) progression to AD dementia. IAF was calculated and compared among study groups. Receiver operating characteristic (ROC) analysis was used to calculate its discriminative performance.METHODSThis retrospective study included 375 patients from the tertiary Memory Clinic of IRCCS San Raffaele Hospital, Milan, Italy. Participants underwent clinical and neuropsychological assessments, brain imaging, cerebrospinal fluid biomarker analysis, and resting-state EEG. Patients were categorized by amyloid status, the AT(N) classification system, clinical diagnosis, and mild cognitive impairment (MCI) progression to AD dementia. IAF was calculated and compared among study groups. Receiver operating characteristic (ROC) analysis was used to calculate its discriminative performance.IAF was higher in amyloid-negative subjects and varied significantly across AT(N) groups. ROC analysis confirmed IAF's ability to distinguish A-T-N- from the A+T+N+ and A+T-N+ groups. IAF was lower in AD and Lewy body dementia patients compared to MCI and other dementia types, with moderate discriminatory capability. Among A+ MCI patients, IAF was significantly lower in those who converted to AD within 2 years compared to stable MCI patients and predicted time to conversion (p < 0.001, R = 0.38).RESULTSIAF was higher in amyloid-negative subjects and varied significantly across AT(N) groups. ROC analysis confirmed IAF's ability to distinguish A-T-N- from the A+T+N+ and A+T-N+ groups. IAF was lower in AD and Lewy body dementia patients compared to MCI and other dementia types, with moderate discriminatory capability. Among A+ MCI patients, IAF was significantly lower in those who converted to AD within 2 years compared to stable MCI patients and predicted time to conversion (p < 0.001, R = 0.38).IAF is a valuable tool for dementia diagnosis and prognosis, correlating with amyloid status and neurodegeneration. It effectively predicts MCI progression to AD, supporting its use in early, targeted interventions in the context of disease-modifying treatments.CONCLUSIONSIAF is a valuable tool for dementia diagnosis and prognosis, correlating with amyloid status and neurodegeneration. It effectively predicts MCI progression to AD, supporting its use in early, targeted interventions in the context of disease-modifying treatments.
Precise and timely diagnosis is crucial for the optimal use of emerging disease-modifying treatments for Alzheimer disease (AD). Electroencephalography (EEG), which is noninvasive and cost-effective, can capture neural abnormalities linked to various dementias. This study explores the use of individual alpha frequency (IAF) derived from EEG as a diagnostic and prognostic tool in cognitively impaired patients. This retrospective study included 375 patients from the tertiary Memory Clinic of IRCCS San Raffaele Hospital, Milan, Italy. Participants underwent clinical and neuropsychological assessments, brain imaging, cerebrospinal fluid biomarker analysis, and resting-state EEG. Patients were categorized by amyloid status, the AT(N) classification system, clinical diagnosis, and mild cognitive impairment (MCI) progression to AD dementia. IAF was calculated and compared among study groups. Receiver operating characteristic (ROC) analysis was used to calculate its discriminative performance. IAF was higher in amyloid-negative subjects and varied significantly across AT(N) groups. ROC analysis confirmed IAF's ability to distinguish A-T-N- from the A+T+N+ and A+T-N+ groups. IAF was lower in AD and Lewy body dementia patients compared to MCI and other dementia types, with moderate discriminatory capability. Among A+ MCI patients, IAF was significantly lower in those who converted to AD within 2 years compared to stable MCI patients and predicted time to conversion (p < 0.001, R = 0.38). IAF is a valuable tool for dementia diagnosis and prognosis, correlating with amyloid status and neurodegeneration. It effectively predicts MCI progression to AD, supporting its use in early, targeted interventions in the context of disease-modifying treatments.
Background and PurposePrecise and timely diagnosis is crucial for the optimal use of emerging disease‐modifying treatments for Alzheimer disease (AD). Electroencephalography (EEG), which is noninvasive and cost‐effective, can capture neural abnormalities linked to various dementias. This study explores the use of individual alpha frequency (IAF) derived from EEG as a diagnostic and prognostic tool in cognitively impaired patients.MethodsThis retrospective study included 375 patients from the tertiary Memory Clinic of IRCCS San Raffaele Hospital, Milan, Italy. Participants underwent clinical and neuropsychological assessments, brain imaging, cerebrospinal fluid biomarker analysis, and resting‐state EEG. Patients were categorized by amyloid status, the AT(N) classification system, clinical diagnosis, and mild cognitive impairment (MCI) progression to AD dementia. IAF was calculated and compared among study groups. Receiver operating characteristic (ROC) analysis was used to calculate its discriminative performance.ResultsIAF was higher in amyloid‐negative subjects and varied significantly across AT(N) groups. ROC analysis confirmed IAF's ability to distinguish A–T–N– from the A+T+N+ and A+T–N+ groups. IAF was lower in AD and Lewy body dementia patients compared to MCI and other dementia types, with moderate discriminatory capability. Among A+ MCI patients, IAF was significantly lower in those who converted to AD within 2 years compared to stable MCI patients and predicted time to conversion (p < 0.001, R = 0.38).ConclusionsIAF is a valuable tool for dementia diagnosis and prognosis, correlating with amyloid status and neurodegeneration. It effectively predicts MCI progression to AD, supporting its use in early, targeted interventions in the context of disease‐modifying treatments.
Author Curti, Davide G.
Rugarli, Giulia
Santangelo, Roberto
Magnani, Giuseppe
Cursi, Marco
Caso, Francesca
Filippi, Massimo
Spinelli, Edoardo G.
Fanelli, Giovanna Franca
Canu, Elisa
Agosta, Federica
Basaia, Silvia
Coraglia, Federico
Cecchetti, Giordano
AuthorAffiliation 5 Neurorehabilitation Unit IRCCS San Raffaele Scientific Institute Milan Italy
3 Neuroimaging Research Unit, Division of Neuroscience IRCCS San Raffaele Scientific Institute Milan Italy
1 Neurology Unit IRCCS San Raffaele Scientific Institute Milan Italy
4 Vita‐Salute San Raffaele University Milan Italy
2 Neurophysiology Service IRCCS San Raffaele Scientific Institute Milan Italy
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– name: 3 Neuroimaging Research Unit, Division of Neuroscience IRCCS San Raffaele Scientific Institute Milan Italy
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Issue 10
Keywords differential diagnosis
Alzheimer disease
individual alpha frequency
EEG
biomarkers
Language English
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This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
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Snippet Background and Purpose Precise and timely diagnosis is crucial for the optimal use of emerging disease‐modifying treatments for Alzheimer disease (AD)....
Precise and timely diagnosis is crucial for the optimal use of emerging disease-modifying treatments for Alzheimer disease (AD). Electroencephalography (EEG),...
Background and PurposePrecise and timely diagnosis is crucial for the optimal use of emerging disease‐modifying treatments for Alzheimer disease (AD)....
SourceID pubmedcentral
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SourceType Open Access Repository
Aggregation Database
Index Database
Publisher
StartPage e16424
SubjectTerms Abnormalities
Alzheimer disease
Alzheimer's disease
Biomarkers
Cerebrospinal fluid
Cognitive ability
Cost analysis
Dementia
Dementia and Cognitive Disorders
Dementia disorders
Diagnosis
differential diagnosis
EEG
Electroencephalography
individual alpha frequency
Lewy bodies
Memory
Neurodegenerative diseases
Neuroimaging
Patients
Short Communication
Title Analysis of individual alpha frequency in a large cohort from a tertiary memory center
URI https://onlinelibrary.wiley.com/doi/abs/10.1111%2Fene.16424
https://www.ncbi.nlm.nih.gov/pubmed/39087560
https://www.proquest.com/docview/3107150229
https://www.proquest.com/docview/3086958044
https://pubmed.ncbi.nlm.nih.gov/PMC11414804
Volume 31
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