MétaCan
Menu
Back to cohort

Screening the cognitive impairment among older outpatient population of a general hospital and comparison of the MoCA and MMSE tests

2021· article· en· W3209023600 on OpenAlexaboutno aff
StamatinaTolia, Maria Karanikola, Klimentini Karageorgiou, Giorgos Alevizopoulos

Bibliographic record

VenueInternational Journal of Psychiatry Research · 2021
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsnot available
Fundersnot available
KeywordsMontreal Cognitive AssessmentMedicineCognitionRating scaleDepression (economics)Cognitive impairmentMini–Mental State ExaminationPopulationPhysical therapyGerontologyClinical psychologyPsychiatryPsychologyDevelopmental psychologyEnvironmental health

Abstract

fetched live from OpenAlex

Objectives: To examin the random non- clinically recognized cognitive impairment of 300 individuals admitted to a general hospital, to determine the sensitivity and specificity of the Montreal Cognitive Assessment scale (MoCA) as a screening tool in Greek elder population. To investigate the predictive value of sociodemographic- health variables on participants’ performance. Methods: MoCA was used as the essential cognitive assessment tool and after, the Mini Mental State Examination scale (MMSE) was administered. IPAQ scale evaluated physical activity and Hamilton Depression rating scale was used to identify patients with depression and exclude them. Results: Mean age was 65.4 years. Comorbidities were present in 76.7%. Agreement between the results of MMSE and MoCA test was found in 43.3% of the cases. Subjects with moderate or high physical activity levels had 48% lower odds for having cognitive impairment. Conclusion: Education and physical activity enhance the prevention of cognitive decline. MoCA test demonstrated a superior sensitivity to detect mild cognitive impairment.

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)0.001
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 score0.214

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.000
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 head0.033
GPT teacher head0.409
Teacher spread0.376 · 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
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Psychiatry ResearchSame topicDementia and Cognitive Impairment ResearchFrench-language works237,207