MétaCan
Menu
← Back to cohort
Record W4385659891 · doi:10.1192/j.eurpsy.2023.416

Comparing the distribution of neuropsychiatric symptoms among individuals with depression and mild cognitive impairment

2023· article· en· W4385659891 on OpenAlexaffabout
Alvin Keng, Daniel Kapustin, Clement Ma, Kathleen Bingham, Corinne E. Fischer, L. Mah, Damien Gallagher, Meryl A. Butters, Christopher R. Bowie, Aristotle N. Voineskos, Ariel Graff, Alastair J. Flint, Nathan Herrmann, Bruce G. Pollock, Benoit H. Mulsant, Tarek K. Rajji, Sanjeev Kumar

Bibliographic record

VenueEuropean Psychiatry · 2023
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsUniversity Health NetworkCentre for Addiction and Mental HealthBaycrest HospitalSunnybrook HospitalUniversity of Toronto
Fundersnot available
KeywordsApathyMajor depressive disorderDepression (economics)DementiaNeurocognitivePsychologyPsychiatryClinical psychologyDisinhibitionCognitionMedicineInternal medicineDisease

Abstract

fetched live from OpenAlex

Introduction Neuropsychiatric symptoms (NPS) are common during the course of neurocognitive disorders. NPS have been previously reported in early and late stages of Alzheimer’s Disease. However, our understanding of NPS in high-risk states for dementia such as mild cognitive impairment (MCI) and major depressive disorder (MDD) is poor. Objectives To compare the frequency and factor structure of neuropsychiatric symptoms among individuals with Mild Cognitive Impairment (MCI), Major Depressive Disorder (MDD) in remission, and comorbid MCI and MDD (in remission) (MCI-D). Methods We used baseline data from the Prevention of Alzheimer’s Dementia with Cognitive Remediation Plus Transcranial Direct Current Stimulation in Mild Cognitive Impairment and Depression (PACt-MD) study, a multicenter trial across five academic sites in Toronto, Canada (clinical trial No. NCT0238667). We used ANOVA or χ2-test to compare frequency of NPS across groups. We used factor analysis of Neuropsychiatric Inventory Questionnaire (NPI-Q) items in the three groups. Results We included 374 participants with a mean age of 72.0 years (SD = 6.3). In the overall sample, at least one NPS was present in 64.2% participants, and 36.1 % had at least moderate severity NPS (36.1%). Depression (54%, χ2 < 0.001) and apathy (28.7%, χ2=0.002) were more prevalent in the MCI-D group as compared to MCI and MDD groups. In factor analysis, NPS grouped differently in MCI, MDD, and MCI-D groups. A “psychotic” subgroup emerged among MCI and MCI-D, but not in MDD. Night-time behaviors and disinhibition grouped differently across all three groups. Conclusions Prevalence of NPS seems higher in persons with MCI-D as compared to those with only MCI or MDD. The factor structure of NPS differed between MCI, MDD, and MCI-D groups. Future studies should investigate the association of NPS factors with cognition, function, and illness biomarkers. Disclosure of Interest None Declared

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
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 head0.013
GPT teacher head0.276
Teacher spread0.262 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueEuropean Psychiatry→Same topicDementia and Cognitive Impairment Research→French-language works237,207→