NEWS2 Is Superior to qSOFA in Detecting Sepsis with Organ Dysfunction in the Emergency Department
Why this work is in the frame
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Bibliographic record
Abstract
Early administration of antibiotics is associated with better survival in sepsis, thus screening and early detection for sepsis is of clinical importance. Current risk stratification scores used for bedside detection of sepsis, for example Quick Sequential Organ Failure Assessment (qSOFA) and National Early Warning Score 2 (NEWS2), are primarily validated for death and intensive care. The primary aim of this study was to compare the diagnostic accuracy of qSOFA and NEWS2 for a composite outcome of sepsis with organ dysfunction, infection-related mortality within <72 h, or intensive care due to an infection. Retrospective analysis of data from two prospective, observational, multicentre, convenience trials of sepsis biomarkers at emergency departments were performed. Cohort A consisted of 526 patients with a diagnosed infection, 288 with the composite outcome. Cohort B consisted of 645 patients, of whom 269 had a diagnosed infection and 191 experienced the composite outcome. In Cohort A and B, NEWS2 had significantly higher area under receiver operating characteristic curve (AUC), 0.80 (95% CI 0.75–0.83) and 0.70 (95% CI 0.65–0.74), than qSOFA, AUC 0.70 (95% CI 0.66–0.75) and 0.62 (95% CI 0.57–0.67) p < 0.01 and, p = 0.02, respectively for the composite outcome. NEWS2 was superior to qSOFA for screening for sepsis with organ dysfunction, infection-related mortality or intensive care due to an infection both among infected patients and among undifferentiated patients at emergency departments.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it