Introduction of a comprehensive management protocol for severe sepsis is associated with sustained improvements in timeliness of care and survival
Bibliographic record
Abstract
INTRODUCTION: Mortality from severe sepsis can be improved by timely diagnosis and treatment. This study investigates the effectiveness of a comprehensive management protocol for recognition and initial treatment of severe sepsis that spans from the emergency department (ED) to the intensive care unit. METHODS: Interventions included development of a management algorithm including early goal-directed therapy, a computerised physician order entry set for suspected sepsis, introduction of invasive haemodynamic monitoring and antibiotics stocked in the ED, and an extensive education campaign involving ED nurses and physicians. MAIN RESULTS: In the 6 months after introduction of the protocol, 37 patients who had severe sepsis were identified in the ED. Compared to a randomly selected group of 37 patients who had severe sepsis and who were transferred directly to the intensive care unit before introduction of the protocol, significant improvements were observed in mean time to initiation of early goal-directed therapy (3.2 vs 10.4h, p=0.001) and to achievement of resuscitation goals (10.4 vs 30.1h, p=0.007). There was a trend towards more rapid administration of antibiotics (1.4 vs 2.7h, p=0.06). This was associated with a decrease in crude hospital mortality rate from 51.4% to 27.0% (absolute risk reduction=24%, 95% CI 3% to 47%). Improvements were sustained in the follow-up audit at 16 months. CONCLUSIONS: Introduction of a comprehensive management protocol to address early recognition and management of severe sepsis in the ED is associated with sustained improvements in processes of care.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".