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Record W2286618824 · doi:10.1016/j.rpped.2015.12.006

Impacto da vacina varicela nas taxas de internações relacionadas à varicela: revisão de dados mundiais

2016· review· pt· W2286618824 on OpenAlexaboutno aff
Maki Hirose, Alfredo Elias Gilio, Ângela Espósito Ferronato, Selma Lopes Betta Ragazzi

Bibliographic record

VenueRevista Paulista de Pediatria · 2016
Typereview
Languagept
FieldMedicine
TopicHerpesvirus Infections and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineHumanities

Abstract

fetched live from OpenAlex

Descrever o impacto da vacina varicela nas taxas de internações hospitalares associadas à varicela nos países que adotaram a vacinação universal contra a doença. Identificaram‐se países que adotaram a vacinação universal contra varicela pelo site http://apps.who.int/immunization_monitoring/globalsummary/schedules da Organização Mundial de Saúde e selecionaram‐se os artigos no Pubmed que descrevem a variação (pré/pós‐vacinal) nas taxas de internações relacionadas à varicela desses países, com auxílio das palavras chaves: “varicella”, “vaccination/vaccine” e “children” (ou) “hospitalization”. Incluíram‐se publicações em inglês entre janeiro de 1995 e maio de 2015. Foram identificados 24 países com vacinação universal contra a varicela e 28 artigos que descrevem o impacto da vacina nas internações associadas à varicela em sete países. Os EUA tiveram 81,4%‐99,2% de redução na taxa de internação em crianças menores de quatro anos, após 6‐14 anos do início da vacinação universal (1995), com cobertura vacinal de 90%; Uruguai: 94% de queda (crianças de 1‐4 anos) em 6 anos, cobertura vacinal de 90%; Canadá: 93% de redução (1‐4 anos) em 10 anos, cobertura de 93%; Alemanha: 62,4% de redução (1‐4 anos) em 8 anos, cobertura de 78,2%; Austrália: queda de 76,8% (1‐4 anos) em 5 anos, cobertura de 90%; Espanha: 83,5% de queda (<5 anos) em 4 anos, cobertura de 77,2%; e Itália: queda entre 69,7%‐73,8% (população geral), cobertura de 60%‐95%. As publicações revelaram variação no percentual de queda na hospitalização por varicela após a vacinação universal nos países pesquisados; os resultados provavelmente dependem do tempo decorrido após introdução da vacinação universal, diferenças na faixa etária estudada, critérios de internação, cobertura vacinal e estratégia de vacina, não permitindo comparação direta entre os dados. to describe the impact of varicella vaccination on varicella‐related hospitalization rates in countries that implemented universal vaccination against the disease. we identified countries that implemented universal vaccination against varicella at the http://apps.who.int/immunization_monitoring/globalsummary/schedules site of the World Health Organization and selected articles in Pubmed describing the changes (pre/post‐vaccination) in the varicella‐related hospitalization rates in these countries, using the Keywords “varicella”, “vaccination/vaccine” and “children” (or) “hospitalization”. Publications in English published between January 1995 and May 2015 were included. 24 countries with universal vaccination against varicella and 28 articles describing the impact of the vaccine on varicella‐associated hospitalizations rates in seven countries were identified. The US had 81.4% ‐99.2% reduction in hospitalization rates in children younger than four years after 6‐14 years after the onset of universal vaccination (1995), with vaccination coverage of 90%; Uruguay: 94% decrease (children aged 1‐4 years) in six years, vaccination coverage of 90%; Canada: 93% decrease (age 1‐4 years) in 10 years, coverage of 93%; Germany: 62.4% decrease (age 1‐4 years) in 8 years, coverage of 78.2%; Australia: 76.8% decrease (age 1‐4 years) in 5 years, coverage of 90%; Spain: 83.5% decrease (age <5 years) in four years, coverage of 77.2% and Italy 69.7% ‐73.8% decrease (general population), coverage of 60%‐95%. The publications showed variations in the percentage of decrease in varicella‐related hospitalization rates after universal vaccination in the assessed countries; the results probably depend on the time since the implementation of universal vaccination, differences in the studied age group, hospital admission criteria, vaccination coverage and strategy, which does not allow direct comparison between data.

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)0.005
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.861
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.004
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0060.003
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0070.008

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 head0.031
GPT teacher head0.347
Teacher spread0.316 · 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
GenreReview

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

Citations27
Published2016
Admission routes1
Has abstractyes

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