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Record W2042944220 · doi:10.1177/1533317513507373

Neuropsychiatric Symptoms and Regional Neocortical Atrophy in Mild Cognitive Impairment and Alzheimer’s Disease

2013· article· en· W2042944220 on OpenAlexfundno aff
Michael S. Rafii, Curtis Taylor, Hyun T. Kim, Rahul S. Desikan, Adam Fleisher, David Katibian, James Brewer, Anders M. Dale, Paul Aisen

Bibliographic record

VenueAmerican Journal of Alzheimer s Disease & Other Dementias® · 2013
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsnot available
FundersNational Institute on AgingCanadian Institutes of Health Research
KeywordsAtrophyPsychosisPsychologyAntipsychoticFrontal lobeNeuroimagingTemporal lobeMagnetic resonance imagingNeuroscienceSchizophrenia (object-oriented programming)MedicinePsychiatryInternal medicineEpilepsyRadiology

Abstract

fetched live from OpenAlex

BACKGROUND: To assess the relationship between regional neocortical atrophy and psychotic symptoms in adults with mild cognitive impairment (MCI) and Alzheimer's disease (AD). METHODS: Rates of change in regional neocortical atrophy as measured by longitudinal magnetic resonance imaging scans and the occurrence of psychotic symptoms and/or the long-term use of antipsychotic medications in 389 outpatients with MCI or AD in Alzheimer's Disease Neuroimaging Initiative. RESULTS: Atrophy rate of 3 specific neocortical regions, lateral frontal, lateral parietal, and anterior cingulate gyrus, was significantly associated with the onset of psychosis including delusions, agitation, wandering, and hallucinations and/or the need for chronic antipsychotic medications. Atrophy rate of the lateral frontal lobe correlated most significantly with onset of psychotic symptoms or need for chronic antipsychotic medications. CONCLUSIONS: Psychosis was associated with volume loss in specific regions of the lateral frontal and parietal lobes as well as anterior cingulate gyrus.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.050
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.017
GPT teacher head0.297
Teacher spread0.280 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations44
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueAmerican Journal of Alzheimer s Disease & Other Dementias®Same topicDementia and Cognitive Impairment ResearchFrench-language works237,207