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Record W2794105178 · doi:10.1590/0004-282x20180005

Association between executive and food functions in the acute phase after stroke

2018· article· en· W2794105178 on OpenAlexaboutno aff
Aline Mansueto Mourão, Laélia Cristina Caseiro Vicente, Mery Natali Silva Abreu, Tatiana Simões Chaves, Romeu Vale Sant’Anna, Marcela Aline Fernandes Braga, Fidel Meira, Leonardo Cruz de Souza, Aline Silva de Miranda, Milene Alvarenga Rachid, Antônio Lúcio Teixeira

Bibliographic record

VenueArquivos de Neuro-Psiquiatria · 2018
Typearticle
Languageen
FieldHealth Professions
TopicDysphagia Assessment and Management
Canadian institutionsnot available
FundersFundação de Amparo à Pesquisa do Estado de Minas Gerais
KeywordsModified Rankin ScaleStroke (engine)MedicineExecutive functionsCognitionAssociation (psychology)Executive dysfunctionPhysical medicine and rehabilitationPsychologyInternal medicinePsychiatryIschemic strokeNeuropsychology

Abstract

fetched live from OpenAlex

Purpose To investigate potential associations among executive, physical and food functions in the acute phase after stroke. Methods This is a cross-sectional study that evaluated 63 patients admitted to the stroke unit of a public hospital. The exclusion criteria were other neurological and/or psychiatric diagnoses. The tools for evaluation were: Mini-Mental State Examination and Frontal Assessment Battery for cognitive functions; Alberta Stroke Program Early CT Score for quantification of brain injury; National Institutes of Health Stroke Scale for neurological impairment; Modified Rankin Scale for functionality, and the Functional Oral Intake Scale for food function. Results The sample comprised 34 men (54%) and 29 women with a mean age of 63.6 years. The Frontal Assessment Battery was significantly associated with the other scales. In multivariate analysis, executive function was independently associated with the Functional Oral Intake Scale. Conclusion Most patients exhibited executive dysfunction that significantly compromised oral intake.

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 score0.110
Threshold uncertainty score0.610

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 studies0.0010.000
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 head0.035
GPT teacher head0.388
Teacher spread0.352 · 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

Citations4
Published2018
Admission routes1
Has abstractyes

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