Antibiotic Over-Prescription by Dentists in the Treatment of Apical Periodontitis: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
After pulp infection and necrosis, the passage of microbial antigens into the periapical space causes apical periodontitis (AP). Most of the clinical forms of AP can be managed without prescribing antibiotics, only with root canal treatment and abscess drainage or, where appropriate, tooth extraction. However, the scientific literature provides evidence of inappropriate antibiotic prescriptions by dentists in the management of apical disease. OBJECTIVES: The aim of this systematic review and meta-analysis was to analyze the global pattern of antibiotic prescription in the treatment of apical disease. METHODS: PRISMA Guidelines were followed to carry out this systematic review. The research question was as follows: What is the pattern of antibiotic prescription by dentists in the treatment of the different clinical forms of apical periodontitis? A systematic search was conducted on MEDLINE/PubMed, Wiley Online Database, Web of Science and Scopus. All studies reporting data about the pattern of antibiotic prescription by dentists in the treatment of apical disease were included. The meta-analyses were calculated using the Open Meta Analyst version 10.10 software. Random-effects meta-analyses were performed. The risk of bias was assessed using the Newcastle-Ottawa Scale. The certainty of evidence was assessed using GRADE. RESULTS: The search strategy identified 96 articles and thirty-nine cross-sectional studies fulfilled the inclusion criteria. The overall percentage of antibiotic prescriptions by dentists in cases of symptomatic AP was 25.8%, and 31.5% in cases of asymptomatic AP with sinus tract present. The percentage of dentists prescribing antibiotics in cases of acute apical abscess with no/mild symptoms was 47.7%, whereas, in cases of acute apical abscess with moderate/severe symptoms, 88.8% of dentists would prescribe antibiotics. Endodontists prescribe antibiotics at a lower rate than general practitioners. The total risk of bias was considered moderate, and the final rating for the certainty of the evidence was low. CONCLUSIONS: Dentists worldwide are over-prescribing antibiotics in the management of apical disease. It is necessary to improve antibiotic prescribing habits in the treatment of endodontic infections, as well as educational initiatives to encourage the rational and appropriate prescription of antibiotics in periapical diseases.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.008 | 0.004 |
| 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".