Over-Prescription of Antibiotics for Pulpitis: A Systematic Review and Meta-Analysis of Cross-Sectional Surveys
Bibliographic record
Abstract
Background: Pulpitis requires operative dental treatment, and antibiotics are not indicated. Nevertheless, inappropriate antibiotic prescribing persists worldwide. This systematic review and meta-analysis evaluated the prevalence of antibiotic prescription for pulpitis among dentists. Methods: A systematic search of MEDLINE/PubMed, Web of Science, Scopus, Embase, and ProQuest (2015–2025) was performed according to PRISMA guidelines. Observational studies reporting the proportion of dentists prescribing systemic antibiotics for pulpitis were included. Random-effects meta-analyses estimated pooled prevalence for all clinicians, general dental practitioners (GDPs), and endodontists (ENs). Risk of bias was assessed using a modified Newcastle–Ottawa Scale, and certainty of evidence was rated with GRADE. Results: Twelve cross-sectional studies met the inclusion criteria, including 3189 dentists. The overall pooled prevalence of antibiotic prescribing for pulpitis was 19.2% (95% CI: 10.4–32.6%), with very high heterogeneity (I2 = 98%). GDPs exhibited significantly higher prescribing rates (26.9%, 95% CI: 14.9–43.5%; I2 = 98%) compared with ENs (5.1%, 95% CI: 1.2–19.2%; I2 = 92%). Sensitivity analysis excluding two high-prevalence studies reduced the pooled estimate to 13.3% (95% CI: 8.0–21.3%) but heterogeneity remained substantial (I2 = 95%). Most studies showed moderate-to-high risk of bias, and the certainty of evidence was graded as very low due to inconsistency, indirectness, imprecision, and potential publication bias. Conclusions: Approximately one in five dentists prescribe antibiotics for pulpitis, despite strong guideline recommendations against their use. However, certainty of evidence was very low. Marked variability across regions and clinical profiles highlights persistent gaps in diagnostic accuracy, access to emergency dental care, and antibiotic stewardship. Targeted education, improved urgent care pathways, and strengthened antimicrobial stewardship programs are needed to reduce unnecessary antibiotic use in pulpitis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".