Recombinant human activated protein C for severe sepsis in neonates
Bibliographic record
Abstract
BACKGROUND: Sepsis is a common problem in both preterm and term infants. Although the overall incidence of neonatal sepsis has declined over the past decade, mortality remains high. Recombinant human activated protein C (rhAPC) has been shown to possess a broad spectrum of activity modulating coagulation and has been shown in septic adults to reduce mortality. In septic children, an open label study has shown similar pharmacokinetics, adverse reaction profile and frequency as in adults with severe sepsis. OBJECTIVES: To determine whether treatment with rhAPC will reduce mortality and/or morbidity in neonates with severe sepsis. SEARCH STRATEGY: Searches were carried out in July 2005 by the review authors independently of MEDLINE (1966 to July 2005), EMBASE (1980 to July 2005), CINAHL (1982 to July 2005), the Cochrane Central Register of Controlled Trials (CENTRAL, The Cochrane Library, Issue 3, 2005), abstracts of annual meetings of the Pediatric Academic Societies and Society for Pediatric Research which were published in Pediatric Research from 1980, and contacts were made with subject experts. Doctoral dissertations, theses and the Science Citation Index for articles on activated protein C were searched from 1980. No language restriction was applied. SELECTION CRITERIA: Studies were included if they were randomized or quasi-randomized trials, assessing the efficacy of rhAPC compared to placebo or no intervention as an adjunct to antibiotic therapy of suspected or confirmed severe sepsis in term and preterm infants less than 28 days old. Eligible trials were required to report treatment effects on at least one of the following outcomes: all cause mortality during initial hospital stay, neurological development and neurodevelopmental assessment at two years of age or later, length of hospital stay, duration of ventilation, chronic lung disease in survivors, periventricular leukomalacia, intraventricular hemorrhage, necrotizing enterocolitis, bleeding, and any other adverse events. DATA COLLECTION AND ANALYSIS: Both review authors independently evaluated the papers for inclusion criteria and quality, and abstracted information for the outcomes of interest. Differences were resolved by mutual discussion. The statistical methods were to include relative risk, risk difference, number needed to treat to benefit or number needed to treat to harm for dichotomous and weighed mean difference for continuous outcomes reported with 95% confidence intervals. A fixed effects model was to be used for meta-analysis. Heterogeneity tests, including the I(2) statistic, were to be performed to assess the appropriateness of pooling the data. MAIN RESULTS: No eligible trials were identified. AUTHORS' CONCLUSIONS: Despite the scientific rationale for its use, there are insufficient data to support the use of rhAPC for the management of severe sepsis in newborn infants. There is a need for large well-designed trials to elucidate the effectiveness of rhAPC to reduce mortality and adverse outcomes in neonates with severe sepsis. The results of such trials would guide clinical practice. Currently, a cautious approach to the use of rhAPC is warranted due to the high incidence of bleeding with its use; especially as severe sepsis in preterm infants is commonly associated with bleeding problems and intraventricular hemorrhage. Its use is not recommended outside of randomized controlled trials.
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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 | 0.006 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".