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Record W2108432874

Standardized Mini-Mental State Examination. Use and interpretation.

2001· article· en· W2108432874 on OpenAlexaff
Andrea Vertesi, Judith A. Lever, D. William Molloy, B Sanderson, Irene Tuttle, Laura Pokoradi, Elaine Principi

Bibliographic record

VenuePubMed · 2001
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsHome and Community Care Support Services
Fundersnot available
KeywordsDementiaMedicineCognitionVascular dementiaMini–Mental State ExaminationMEDLINEDepression (economics)PsychiatryDementia with Lewy bodiesClinical psychologyDiseaseGerontologyPathology
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVE: To review administration of the Standardized Mini-Mental State Examination (SMMSE) for dementia and depression and to evaluate how well it interprets older people's cognitive function. QUALITY OF EVIDENCE: Literature from January 1990 to December 1999 was searched via MEDLINE using the MeSH headings Alzheimer Disease, Vascular Dementia, Lewy Bodies, and Depression. Several studies have described the reliability and validity of the SMMSE. MAIN MESSAGE: The SMMSE, a standardized approach to scoring and interpreting older people's cognitive function, provides a global score of cognitive ability that correlates with daily function. Careful interpretation of results of the SMMSE, together with history and physical assessment, can assist in differential diagnosis of cognitive impairment resulting from Alzheimer's disease, vascular dementia, dementia with Lewy bodies, or depression. Repeated measurements can be used to assess change over time and response to treatment. CONCLUSION: The SMMSE is a valuable tool for family doctors who are often the first medical professionals to identify changes in patients' cognitive function. The SMMSE requires little time to complete and is a key component of a comprehensive dementia workup. Determining whether a patient has dementia is important because there are now effective medications that are most beneficial if started early.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.641
Threshold uncertainty score0.287

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 integrity0.0000.000
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 head0.026
GPT teacher head0.284
Teacher spread0.257 · 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

Citations194
Published2001
Admission routes1
Has abstractyes

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