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Conhecer para cuidar: prevalência e fatores associados às Infecções Sexualmente Transmissíveis em imigrantes de Goiás

2023· article· pt· W4390682148 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueRevista da Escola de Enfermagem da USP · 2023
Typearticle
Languagept
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsMedicineHuman immunodeficiency virus (HIV)DemographyGynecologyVirologySociology

Abstract

fetched live from OpenAlex

RESUMO Objetivo: Estimar a prevalência de Infecções Sexualmente Transmissíveis (IST) em imigrantes e refugiados residentes na região metropolitana de Goiânia, Goiás. Método: Trata-se de um estudo transversal e analítico. A coleta de dados foi realizada no período de julho de 2019 a janeiro de 2020 e integraram a amostra 308 imigrantes e refugiados. Todos foram entrevistados face-a-face e testados para HIV, Sífilis e Hepatite B, por meio de testes rápidos. Resultados: A prevalência geral para alguma das IST investigadas foi de 8,8% (IC95% 6,0% – 12,3%), sendo 5,8% (IC95% 3,6% – 8,9%) para Hepatite B, 2,3% para Sífilis (IC95% 1,00% – 4,4%) e 0,7% para HIV (IC95% 0,1% – 2,1%). A análise múltipla, por regressão logística, mostrou que as variáveis sexo masculino (OR = 2,7) e tempo de moradia no Brasil (OR = 2,6) foram associadas significativamente às IST (p < 0,05). Conclusão: Os resultados deste estudo sugerem que as IST são um problema de saúde em imigrantes/refugiados, que parecem ser exacerbadas com o tempo de migração no país. Políticas públicas que garantam a assistência à saúde dessa população devem ser consideradas.

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.

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)0.004
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, 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 score0.106
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.004

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 head0.066
GPT teacher head0.392
Teacher spread0.326 · 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