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Record W7074652649

Sintomas negativos na esquizofrenia refratária e super-refratária

2004· article· pt· W7074652649 on OpenAlexaboutno aff

Bibliographic record

VenueAmericanae (AECID Library) · 2004
Typearticle
Languagept
FieldEconomics, Econometrics and Finance
TopicDiverse Scientific and Economic Studies
Canadian institutionsnot available
Fundersnot available
KeywordsQuality of life (healthcare)Schizophrenia (object-oriented programming)Quality (philosophy)MEDLINE
DOInot available

Abstract

fetched live from OpenAlex

Os sintomas negativos têm sido apontados como grande causa de sobrecarga nos pacientes esquizofrênicos, apesar dos recentes avanços no tratamento. Este estudo teve por objetivo investigar a correlação entre os sintoma s negativos e a qualidade de vida, em pacientes esquizofrênicos refratários e super-refratários. Cento e dois pacientes que preenchiam os critérios DSM-IV para esquizofrenia foram observados durante seis meses. Os pacientes foram divididos de acordo com critérios pré-estabelecidos, em três grupos: não refratários (N=22), refratários (N= 47) e super-refratários (N= 31), A psicopatologia foi avaliada por meio da Escala para Avaliação da Síndrome Positiva e Negativa (PANSS), Entrevista para Síndrome Deficitária (SDS) e Escala de Calgary para Depressão na Esquizofrenia. A qualidade de vida foi medida pela Escala de Qualidade de Vida (QV) . Os super-refratários tiveram os menores escores de QV, quando comparados ao grupo não refratário (p < 0,05). Não houve diferenças significativas nos escores médios de QV entre os refratários e superrefratários. Pacientes não refratários apresentaram menos sintomas negativos e melhores escores de QV. Os sintomas negativos tiveram uma correlação negativa com a qualidade de vida. Pacientes super-refratários, com mais sintomas negativos, tenderam a ter os menores escores de qualidade de vida

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.109
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.003
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0400.058

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 head0.021
GPT teacher head0.197
Teacher spread0.176 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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
Published2004
Admission routes1
Has abstractyes

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