MétaCan
Menu
Back to cohort

Rastreio Cognitivo em Adultos com Esclerose Múltipla

2023· article· pt· W4389164678 on OpenAlexaboutno aff
Clarice Maria Siqueira Falcão Wanderley, Larissa Nadjara Alves Almeida, Bianca Etelvina Santos de Oliveira, Ivonaldo Leidson Barbosa Lima

Bibliographic record

VenueRevista Contexto & Saúde · 2023
Typearticle
Languagept
FieldComputer Science
TopicHealthcare during COVID-19 Pandemic
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPsychologyMedicinePhilosophy

Abstract

fetched live from OpenAlex

Objetivo: Analisar o desempenho de adultos com Esclerose Múltipla (EM) em rastreio cognitivo e observar a correlação entre a idade e as habilidades cognitivas. Métodos: É uma pesquisa descritiva, observacional, transversal e quantitativa. Foi realizada com 27 indivíduos com diagnóstico médico de EM: 22 mulheres, 5 homens, com idades entre 20 e 60 anos. A coleta dos dados foi realizada por meio de três instrumentos: Montreal Cognitive Assessment (Moca); Bateria Breve de rastreio cognitivo e um Protocolo de identificação pessoal. A análise dos dados foi realizada de forma quantitativa, descritiva e inferencial. Aplicou-se o teste de Mann-Whitney e correlação de Spearman, com significância de p<0,05. Resultados: A maioria dos participantes apresentou queixas de memória e dificuldades nas provas de subtração e evocação tardia. Verificou-se que houve correlação negativa entre a idade e o desempenho nas provas de rastreio cognitivo. Os participantes foram divididos em dois grupos de acordo com o escore do Moca e foram observadas diferenças estatísticas na memória incidental (p=0,049), memória imediata (p=0,019), memória tardia (p=0,007), no desenho do relógio (p=0,037), na fluência verbal semântica (p=0,008), repetição de dígitos (p=0,006), na subtração (p=0,026), linguagem (p=0,001), fluência verbal fonêmica (p=0,05), abstração (p=0,019), evocação tardia (p<0,001) e no escore total do Moca (p<0,001). Conclusão: Quanto maior a idade do paciente com esclerose múltipla, pior o funcionamento cognitivo, principalmente da memória e das funções executivas.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.109
GPT teacher head0.374
Teacher spread0.265 · 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 source (direct Gemma or distilled Codex), 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
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueRevista Contexto & SaúdeSame topicHealthcare during COVID-19 PandemicFrench-language works237,207