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Record W4401528435 · doi:10.1016/j.addbeh.2024.108132

Predictive factors of cognitive impairment in alcohol use disorder inpatients

2024· article· en· W4401528435 on OpenAlexaboutno aff
Marie-Astrid Gautron, Virgile Clergue‐Duval, Janice Chantre, Michel Lejoyeux, Pierre A. Geoffroy

Bibliographic record

VenueAddictive Behaviors · 2024
Typearticle
Languageen
FieldMedicine
TopicAlcoholism and Thiamine Deficiency
Canadian institutionsnot available
Fundersnot available
KeywordsCognitive impairmentAlcohol use disorderCognitionPsychologyClinical psychologyPsychiatryAlcoholMedicine

Abstract

fetched live from OpenAlex

BACKGROUND: Cognitive impairments are common in patients with AUD and worsen the prognosis of addiction management. There are no clear guidelines for screening cognitive impairments in hospitalized patients with AUD. METHODS: Fifty-seven patients with an AUD history who were admitted to an acute hospital and assessed by the addiction care team were included. Those patients were screened for cognitive impairments using the Montreal Cognitive Assessment (MoCA) test. We collected clinical information regarding addiction history, comorbidities, and current treatments. Chi-square tests, t-tests, and Mann-Whitney tests were performed to determine factors associated with a pathological MoCA score (<26). RESULTS: A pathological MoCA score was positively associated with spatial-temporal disorientation, difficulty in recalling addiction history, patient underreporting of AUD and a date of last alcohol consumption lower than 11 days ago, and negatively associated with a reason for hospitalization due to alcohol-related health issues. No medication was associated with cognitive impairments. CONCLUSIONS: Clinical elements from assessment by the addiction care team allow for relevant indication for screening cognitive impairments.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.851

Codex and Gemma teacher scores by category

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

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 head0.027
GPT teacher head0.316
Teacher spread0.290 · 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.

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

Citations5
Published2024
Admission routes1
Has abstractyes

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