Effect of measuring vital signs on recognition and treatment of septic children
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: A majority of children presenting with sepsis do not receive adequate fluid resuscitation and have a delay in antibiotic administration despite recommendations from the Surviving Sepsis Campaign. The objective of this study was to evaluate the association of measuring a complete set of five vital signs in the emergency department (ED) with recognition and treatment of septic children presenting to the ED. METHODS: Records of 218 patients aged 1 month to 17 years treated between February 2011 and December 2011 in a single academic centre with clinical criteria of sepsis, severe sepsis or septic shock were retrospectively evaluated. The presence or absence of complete vital signs was analyzed in relation to timing of fluid resuscitation, and if antibiotics were given in the first hour of medical evaluation. RESULTS: Seventy-six per cent of children who had all five vital signs measured in the ED received fluid resuscitation in the first hour after medical evaluation as opposed to 61% of those who had an incomplete set of vital signs (P<0.04). Twenty per cent of children who had all five vital signs measured received antibiotics in the first hour as opposed to 9% in children who had fewer vital signs measured (P<0.02). CONCLUSION: In our study population, the measurement of all vital signs in the ED, including blood pressure, was associated with faster administration of antibiotics and improved compliance with existing fluid bolus recommendations, which may have been the result of better recognition of sepsis in children through vital signs measurement.
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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 | 0.003 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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 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".