Adaptação transcultural e validação da Hamilton Early Warning Score para o Brasil
Bibliographic record
Abstract
RESUMO Objetivo Adaptar transculturalmente e validar, para a língua portuguesa, a Hamilton Early Warning Score para detectar a deterioração clínica em serviços de emergência. Método Estudo metodológico compreendendo as etapas de tradução, síntese, retrotradução, comitê de especialistas (n=13), pré-teste, envio e análise das propriedades de medidas em uma amostra composta por 188 pacientes. Comparou-se a Canadian Acute Scale Triage com a Hamilton Early Warning Score. Foram utilizados o Coeficiente Kappa Ponderado, Coeficiente de Correlação Intraclasse e de Pearson, Regressão Logística Binária e a Área Sob a Curva Receiver Operating Characteristic para a análise dos dados. Resultados A Hamilton Early Warning Score apresentou confiabilidade excelente, ou seja, α=0,924 (p<0,001). A validade de construto identificou correlação forte e negativa r=-0,75 e a preditiva apresentou um odds ratio de 1,63, IC 95% (1,358-1,918) (p<0,001). Conclusão A Hamilton Early Warning Score em português é válida e confiável para reconhecer pacientes em condição de deterioração clínica em serviços de emergência.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.044 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".