Early drotrecogin alpha (activated) administration in severe sepsis is associated with lower mortality: a retrospective analysis of the Canadian ENHANCE cohort
Bibliographic record
Abstract
INTRODUCTION: Early multimodal treatment of severe sepsis, including the use of drotrecogin alfa (activated) (DrotAA) when indicated, is considered essential for optimum outcome. However, predicting which infected patients will progress to severe sepsis and the need for aggressive intervention continues to be problematic. We therefore wished to explore whether there were any potential early markers that might predict improved survival in response to early use of DrotAA in patients with severe sepsis. In particular, in the dynamic setting of severe sepsis, we postulated that changes in markers reflecting evolving rather than baseline clinical status might guide therapy. METHODS: Data on a cohort of 305 Canadian patients from the open label ENHANCE trial of DrotAA in severe sepsis was retrospectively analyzed to search for potential clinical predictors of outcome in severe sepsis. Patients received a 96-hour infusion of DrotAA and were followed for 28 days. The association between time to treatment and mortality within subgroups defined by dynamic changes in various potential markers was explored. RESULTS: Mortality at 28 days was 22.6% and the variables of age, time to treatment, and early changes in serum creatinine and platelet count were identified by logistic regression as independent predictors of mortality. Across all age ranges, 28-day mortality was lower when DrotAA was administered within 24 hours of first sepsis-induced organ dysfunction compared to administration after 24 hours for both subgroups of patients defined by changes in platelet count and creatinine within the first day. CONCLUSIONS: These findings suggest that when indicated, treatment with DrotAA should be initiated as soon as possible, regardless of age. TRIAL REGISTRATION: Previous trial registration number: NCT00568893.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".