Antibiotic Use in Dental Implant Procedures: A Systematic Review and Meta-Analysis

Abstract

Background and Objectives: This project was developed from anecdotal evidence of varied practices around antibiotic prescribing in dental procedures. The aim of the study was to ascertain if there is evidence to support whether antibiotic (AB) use can effectively reduce postoperative infections after dental implant placements (DIPs). Materials and Methods: Following PRISMA-P© methodology, a systematic review of randomised controlled clinical trials was designed and registered on the PROSPERO© database. Searches were performed using PubMed^®, Science Direct^® and the Cochrane© Database, plus the bibliographies of studies identified. The efficacy of prophylactic antibiotics, independent of the regimen used, versus a placebo, control or no therapy based on implant failure due to infection was the primary measured outcome. Secondary outcomes were other post-surgical complications due to infection and AB adverse events. Results: Twelve RCTs were identified and analysed. Antibiotic use was reported to be statistically significant in preventing infection (p < 001). The prevention of complications was not statistically significant (p = 0.96), and the NNT was >5 (14 and 2523 respectively), which indicates that the intervention was not sufficiently effective to justify its use. The occurrence of side effects was not statistically significant (p = 0.63). NNH was 528 indicating that possible harm caused by the use of ABs is very small and does not negate the AB use when indicated. Conclusion: The routine use of prophylactic antibiotics to prevent infection in dental implant placement was found to be not sufficiently effective to justify routine use. Clear clinical assessment pathways, such as those used for medical conditions, based on the patients' age, dental risk factors, such as oral health and bone health, physical risk factors, such as chronic or long-term conditions and modifiable health determinants, such as smoking, are required to prevent the unnecessary use of antibiotics.

Keywords: antibiotic prophylaxis in dentistry; dental implant failure; dental implant placement; pre-operative antibiotics and post-operative complications.

Figure 1

PRISMA flowchart showing the article selection process.

Figure 2

CONSORT diagram.

Figure 3

Forest plot of comparison between AB and placebo, which gives a summary estimate (centre of diamond) and its 95% confidence interval CI (width of diamond) for the number of failed implants by implant. Statistical method: Mantel-Haenszel with fixed-effect model [25,26,27,29,31,32,34,36].

Figure 4

Forest plot of comparison between AB and placebo, which gives the summary estimate (centre of diamond) and its 95% confidence interval CI (width of diamond) based on implant failure by patients. Statistical method: Mantel-Haenszel with fixed-effect model [25,31,32,33,34,36].

Figure 5

Forest plot of comparison between AB and placebo, which gives the summary estimate (centre of diamond) and its 95% confidence interval CI (width of diamond) based on postoperative complications. Statistical method: Mantel-Haenszel with fixed-effect model [26,29,31,32,36].

Figure 6

Forest plot of comparison between AB and placebo, which gives the summary estimate (centre of diamond) and its 95% confidence interval CI (width of diamond) based on postoperative adverse events. Statistical method: Mantel-Haenszel with fixed effect model [26,29,31,32,36].

Figure 7

Risk of bias graph: review of authors’ judgments on each risk of bias item presented as percentages across all included studies. Green denotes features at a low risk of bias, red denotes a feature at a high risk of bias, and yellow denotes features at an unclear risk of bias.

Figure 8

Each risk of bias item for each included study. Green denotes features at a low risk of bias, red denotes a feature at a high risk of bias, and yellow denotes features at an unclear risk of bias (Abu-Ta’a [32], Anitua [26], Caiazzo [25], Durand [29], Esposito [36], Esposito [31], Kashani [34], Khoury [35], Laskin [37], Nolan [33], Payer [28], Tan [27]).