Cross-cultural adaptation and validation of the Hamilton Early Warning Score for Brazil
Bibliographic record
Abstract
OBJECTIVE: Cross-culturally adapt and validate, for Portuguese, the Hamilton Early Warning Score to detect clinical deterioration in emergency services. METHOD: Methodological study comprising the stages of translation, synthesis, back translation, expert committee (n=13), pre-test, submission, and analysis of the measurement properties in a sample of 188 patients. The Canadian Acute Scale Triage was compared with the Hamilton Early Warning Score. The Weighted Kappa Coefficient, Intraclass and Pearson Correlation Coefficient, Binary Logistic Regression and the Area Under the Receiver Operating Characteristic Curve were used for data analysis. RESULTS: The Hamilton Early Warning Score showed excellent reliability, α=0.924 (p<0.001). The construct validity identified a strong and negative correlation r=-0.75 and the predictive one presented an odds ratio of 1.63, 95% CI (1.358-1.918) (p<0.001). CONCLUSION: The Hamilton Early Warning Score in Portuguese is valid and reliable to recognize patients in a condition of clinical deterioration in emergency services.
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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 | 0.022 | 0.047 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".