Perioperative antibiotics in pediatric cardiac surgery: protocol for a systematic review
Bibliographic record
Abstract
BACKGROUND: Post-operative infections in pediatric cardiac surgery are an ongoing clinical challenge, with rates between 1 and 20%. Perioperative antibiotics remain the standard for prevention of surgical-site infections, but the type of antibiotic and duration of administration remain poorly defined. Current levels of practice variation through informal surveys are very high. Rates of antibiotic-resistant organisms are increasing steadily around the world. METHODS/DESIGN: We will identify all controlled observational studies and randomized controlled trials examining prophylactic antibiotic use in pediatric cardiac surgery. Data sources will include MEDLINE, EMBASE, CENTRAL, and proceedings from recent relevant scientific meetings. For each included study, we will conduct duplicate independent data extraction, risk of bias assessment, and evaluation of quality of evidence using the GRADE approach. DISCUSSION: We will report the results of this review in agreement with the PRISMA statement and disseminate our findings at relevant critical care and cardiology conferences and through publication in peer-reviewed journals. We will use this systematic review to inform clinical guidelines, which will be disseminated in a separate stand-alone publication. STUDY REGISTRATION NUMBER: PROSPERO CRD42016052978C.
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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 | 0.048 | 0.079 |
| Meta-epidemiology (narrow) | 0.006 | 0.005 |
| Meta-epidemiology (broad) | 0.020 | 0.016 |
| Bibliometrics | 0.012 | 0.013 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.060 | 0.006 |
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".