Evidence map›Paper›PMID 39087560›Full record

ArticleEuropean journal of neurology2024

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

Giordano Cecchetti, Federica Agosta, Elisa Canu, Silvia Basaia, Giulia Rugarli, Davide G Curti, Federico Coraglia, Marco Cursi, Edoardo G Spinelli, Roberto Santangelo and 4 more

Abstract read
In one paragraph

Article in European journal of neurology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Giordano CecchettiNeurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.ORCID 0000-0002-6544-410X
Federica AgostaNeurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.ORCID 0000-0003-3121-4979
Elisa CanuNeuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.ORCID 0000-0001-5804-3378
Silvia BasaiaNeuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.ORCID 0000-0002-0722-6243
Giulia RugarliNeurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.
Davide G CurtiNeurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.
Federico CoragliaVita-Salute San Raffaele University, Milan, Italy.
Marco CursiNeurophysiology Service, IRCCS San Raffaele Scientific Institute, Milan, Italy.ORCID 0000-0002-7928-0417
Edoardo G SpinelliNeurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.ORCID 0000-0003-1492-7221
Roberto SantangeloNeurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.ORCID 0000-0002-8760-2703
Francesca CasoNeurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.
Giovanna Franca FanelliNeurophysiology Service, IRCCS San Raffaele Scientific Institute, Milan, Italy.
Giuseppe MagnaniNeurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.
Massimo FilippiNeurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.ORCID 0000-0002-5485-0479

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

Alzheimer DiseaseCognitive DysfunctionAgedAged, 80 and overAlpha RhythmCohort StudiesDisease ProgressionElectroencephalographyFemaleHumansMaleMiddle AgedRetrospective StudiesTertiary Care CentersAlzheimer diseasebiomarkersdifferential diagnosisEEGindividual alpha frequency

Identifiers

PMID39087560
PMCPMC11414804

What Socratic holds

Textmetadata
LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.