MétaCan
Menu
Back to cohort
Record W4392204799 · doi:10.30834/kjp.36.2.2024.366

Cognitive dysfunction in male inpatients with alcohol dependence: A comparative cross-sectional study from South India

2024· article· en· W4392204799 on OpenAlexaboutno aff
K. P. Rajula, Dev Narayan

Bibliographic record

VenueKerala Journal of Psychiatry · 2024
Typearticle
Languageen
FieldMedicine
TopicBlood Pressure and Hypertension Studies
Canadian institutionsnot available
Fundersnot available
KeywordsCross-sectional studyMedicineAlcoholCognitive impairmentCognitionPsychologyEnvironmental healthPsychiatryClinical psychologyGerontologyChemistryPathology

Abstract

fetched live from OpenAlex

Background: Alcohol is the most widely used psychoactive substance worldwide. More than 50% of alcohol dependent subjects can have alterations in cognitive functions. Cognitive dysfunction interferes with treatment and increases the risk of relapse in alcohol dependence; hence, its identification has potential therapeutic implications. We compared the cognitive dysfunction in alcohol dependent inpatients with controls. Methods: This hospital-based cross-sectional comparative study was conducted in a tertiary center in South India. The study population consisted of 76 consenting male psychiatry inpatients of the age group 18-65 years with alcohol dependence who did not have delirium, while 76 caregivers who accompanied patients to the hospital and were not dependent on alcohol were the controls. The severity of alcohol dependence in the study group was assessed using the Short Alcohol Dependence Data Questionnaire (SADD), and the cognitive functions of both groups were evaluated by the Montreal Cognitive Assessment (MoCA). Results: The prevalence of cognitive impairment was higher in the study group than in controls (96.1% vs. 36.8%, p = 0.001). Conclusion: There is a significantly greater cognitive impairment in those with alcohol dependence compared to those without. Evaluating alcohol dependent patients for cognitive impairment can have important therapeutic and prognostic implications.

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 score0.007
Threshold uncertainty score0.461

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.046
GPT teacher head0.341
Teacher spread0.295 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueKerala Journal of PsychiatrySame topicBlood Pressure and Hypertension StudiesFrench-language works237,207