Systemic antibiotic prophylaxis (any regimen; topical therapy excluded) administered before and/or after tooth extraction vs placebo: Adverse effects
- Population
- Patients undergoing tooth extraction (all 18 included trials: healthy patients undergoing impacted third molar/wisdom tooth extraction)
- Intervention
- Systemic antibiotic prophylaxis (any regimen; topical therapy excluded) administered before and/or after tooth extraction
- Comparison
- placebo
- Outcome
- Adverse effects
Systemic antibiotic prophylaxis (any regimen; topical therapy… probably leads to higher adverse effects compared with placebo (moderate certainty).
What each review found
Current versions only| Finding | Effect | Studies | GRADE certainty |
|---|---|---|---|
Systemic antibiotic prophylaxis (any regimen; topical therapy excluded) administered before and/or after tooth extraction vs Placebo Adverse effects · Patients undergoing tooth extraction (all 18 included trials: healthy patients undergoing impacted third molar/wisdom… · mean 7 days Systemic antibiotic prophylaxis (any regimen; topical therapy… probably leads to higher adverse effects compared with placebo (moderate certainty). Antibiotics to prevent complications following tooth extractions (2012) · Cochrane All outcomesearlier version CD003811.PUB2, superseded | RR 1.98 [1.10, 3.59] | 5 studies · 930 participants | Moderate |
Findings are shown side by side, never pooled across reviews.
The reviews
| Review | Searched up to | Included studies | AMSTAR 2 |
|---|---|---|---|
| Antibiotics to prevent complications following tooth extractions 2021 · Cochrane All outcomes | 2020-04 | Not listed | Not assessed |
Related questions
The same intervention and outcome, asked in another population or against another comparator.
- Systemic antibiotic prophylaxis (any regimen; topical therapy excluded) administered before and/or after tooth extraction vs placebo · People undergoing tooth extraction (21 of 23 trials: healthy patients undergoing… · 1 review
How reviews are matched to this question
Reviews word the same question differently. Four decision models (TypeSafe's Jev, Liquid AI's d1-ultra, SubQ Snap and Baseten's Elephant) judged each wording of the population, intervention, comparator and outcome against the others; two wordings count as the same when at least three of them agree and none clearly disagrees, and findings count as this question only when all four elements match. Timing, setting and subgroup never split a question: they are shown on each finding.