Drotrecogin alfa (activated): does current evidence support treatment for any patients with severe sepsis?
Bibliographic record
Abstract
Two international multicentre randomised controlled trials of drotrecogin alfa (activated) (DrotAA), the Recombinant Human Activated Protein C Worldwide Evaluation of Severe Sepsis (PROWESS) and Administration of Drotrecogin Alfa (Activated) in Early Stage Severe Sepsis (ADDRESS) trials, have produced inconsistent results. When 28-day mortality data from these trials for patients with severe sepsis and at high risk of death are pooled using a standard random-effects meta-analysis technique, there is no statistically significant survival benefit (for patients with Acute Physiology and Chronic Health Evaluation (APACHE II) scores of 25 or more), or a borderline significant benefit (for patients with multi-organ failure). We argue that two important methodological issues might explain the disparate results between the two trials. These issues centre on early trial stopping, which exaggerates treatment effects, and reliance on subgroup analyses, which for DrotAA yields inconsistent results across different definitions of high risk. These concerns call into question the effectiveness of DrotAA in any patients with severe sepsis. Consequently, further randomised trials of this agent in prospectively defined high-risk patients are required to clarify its role in the management of severe sepsis.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".