Prophylactic Antibiotics for Prevention of Infective Endocarditis or Bacteremia in Pediatric Patients With Congenital Heart Disease Undergoing Dental Procedures: Systematic Review
Bibliographic record
Abstract
AIM: To assess the effectiveness of prophylactic antibiotics in preventing infective endocarditis (IE) after dental procedures in pediatric patients with congenital heart disease. METHODS: Six electronic databases and grey literature were searched for randomized controlled trials (RCTs), case-control studies, and cohort studies in pediatric patients who received antibiotic prophylaxis (AP) before any dental procedure compared to pediatric patients undergoing the same procedures without AP to prevent IE and/or bacteremia. The Newcastle-Ottawa scale was used to evaluate the internal validity of the included studies. The Grading of Recommendations Assessment, Development, and Evaluation (GRADE) was used to assess the certainty of evidence. RESULTS: 1774 studies were screened after duplicate removal. Three case-control studies met the inclusion criteria and were included. One study evaluated IE as an outcome, whereas the other two studies evaluated bacteremia after dental procedures. Meta-analysis could not be conducted for IE, whereas pooling results were attempted for two studies evaluating bacteremia as an outcome. The odds of IE after a dental procedure within the last 6 months with AP were higher than without AP (Odds ratio: 3.44, 95% CI: 0.93, 12.65, p = 0.06) in the only study. However, AP was effectively able to reduce bacteremia after dental procedures in two studies that evaluated bacteremia (Pooled odds ratio: 0.24, 95% CI: 0.14, 0.42, p < 0.05). CONCLUSIONS: The GRADE evidence was very low to conclude that prophylactic antibiotics might have a role in preventing IE or bacteremia in children with congenital cardiac diseases due to insufficient studies.
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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 | 0.005 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.009 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".