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Background:
Systematic Review

Comparative Efficacy of Different Amoxicillin Dosing Regimens in Preventing Early Implant Failure—A Systematic Review with Network Meta-Analysis

by
Lee Wen Tan
1,
Yan Er Ng
1,
Koay Chun Giok
1,
Sajesh K. Veettil
2 and
Rohit Kunnath Menon
3,4,*
1
School of Dentistry, International Medical University, Kuala Lumpur 57000, Malaysia
2
Research Associate, Department of Pharmacotherapy, College of Pharmacy, University of Utah, Salt Lake City, UT 81142, USA
3
Prosthodontics, School of Dentistry, Ajman University, Ajman 346, United Arab Emirates
4
Center of Medical and Bio-Allied Health Sciences Research, Ajman University, Ajman 346, United Arab Emirates
*
Author to whom correspondence should be addressed.
Antibiotics 2023, 12(3), 512; https://doi.org/10.3390/antibiotics12030512
Submission received: 5 February 2023 / Revised: 23 February 2023 / Accepted: 28 February 2023 / Published: 3 March 2023
(This article belongs to the Special Issue The Application of Antibiotic Therapy in Oral Surgery and Dental Implant Procedures)
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Abstract

:
This systematic review and network meta-analysis aimed to assess the comparative efficacy and safety of antibiotics to prevent early implant failure in patients undergoing dental implant surgery. Methods: The review was registered in PROSPERO [CRD42022319385]. A search was conducted for trials published in Medline, Cochrane, PubMed, and Scopus. A network meta-analysis was performed on the data from randomized controlled trials. Agents were ranked according to their effectiveness based on outcomes (implant failure, prosthetic failure, postsurgical complications, and adverse effects) using the surface under the cumulative ranking [SUCRA]. Results: A total of 15 articles were included in the quantitative analysis. When compared to the placebo, 2 g of amoxicillin given 1 h preoperatively (RR = 0.42 (95%CI: 0.27, 0.67)), 2 g of amoxicillin given 1 h preoperatively with postoperative 500 mg thrice for 5 days (RR = 0.36 (95%CI: 0.15, 0.87)), and post-operative amoxicillin with clavulanic acid 625 mg 3 times daily for 5 days (RR = 0.38 (95%CI: 0.16, 0.90)) were effective in reducing early implant failures. In addition, 2 g of amoxicillin given 1 h preoperatively (RR = 0.42 (95%CI: 0.25, 0.73)) was the only protocol that was significant in the pairwise meta-analysis results. However, sensitivity analysis, which excluded trials with a high risk of bias, showed that none of the protocols were statistically significant in reducing early implant failure. Conclusions: A single 2 g dose of preoperative amoxicillin significantly reduces early implant failure in healthy individuals. More high-quality trials are required to establish this recommendation, as the quality of this evidence is weak.

1. Introduction

Dental implant failure may occur before prosthetic loading (early) due to inadequate osseointegration or after loading (late) [1,2]. Early implant failures may be due to impaired healing due to the micromovement of components, impaired bone quality, contamination of the implant surface, mechanical factors, or patient-related factors like smoking [3,4,5,6,7,8,9]. Osseointegration of dental implants requires meticulous oral hygiene practices with chlorhexidine rinses as an adjunctive measure to promote healing and prevent infection [10,11]. Systemic antibiotics are routinely prescribed in implant surgery with the goal of preventing infection and, consequently, early implant failures [12]. Amoxicillin is the preferred antibiotic, and a single preoperative dose of amoxicillin has been deemed as effective in reducing implant failure rates [13,14]. However, a standardized protocol for the administration of amoxicillin has not yet been established, prompting researchers to suggest further research to establish one [15,16]. The establishment of a standardized protocol is essential to avoid the overuse of antibiotics and their associated detrimental effects, including antibiotic resistance [17]. The long-term impact of amoxicillin on the oral microbiome has been recognized previously by next-generation sequencing research [18,19]. Even though recent systematic reviews suggest the use of preoperative antibiotics for the prevention of early implant failures, there is no conclusive evidence on the type, dose, timing, and duration of antibiotic treatment [15,16,20]. Moreover, current evidence is inconclusive on the harm-benefit aspect of antibiotic treatment for dental implant surgery [21,22]. Unlike conventional pairwise meta-analysis, network meta-analysis (NMA) enables investigators to combine direct and indirect evidence to establish comparative efficacy and acceptability across a network of randomized controlled trials (RCTs) of all interventions until now. Choosing the most efficacious antibiotic regimen for preventing early implant failure is an important consideration in dentistry. Hence, this study aims to perform a NMA to assess the comparative effectiveness of interventions used to prevent early implant failure. This study aims to recommend an appropriate antibiotic dosage regime that is significant in preventing early implant failure while justifying the impact on the oral microbiome and the risk of antibiotic resistance [23].

2. Materials and Methods

A systematic review of randomized controlled trials comparing interventions for the prevention of early implant failure in patients undergoing dental implant surgery was undertaken according to the general principles outlined in The Cochrane Handbook for Systematic Reviews of Interventions and reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) extension statement for NMA [24,25]. The proposal for this systematic review was registered in the PROSPERO registry [CRD42022319385]. We identified relevant studies through a systematic search of Medline, Cochrane, PubMed, and Scopus. In addition, published systematic reviews were searched for relevant randomized controlled trials.

2.1. Search Strategy and Study Selection

A search of human studies in these databases from inception through 6 October, 2022, was performed by using subject headings and free text terms. Three sets of search terms were combined: terms for implant failure, terms for the relevant intervention (systemic antibiotics), and a search filter to identify randomized controlled trials. We developed the search strategy for MEDLINE and modified it for other databases. In vitro studies, studies that were not in English, animal studies, summary reviews, systematic reviews, and articles with unclear data were not included. Two of the authors performed the search within the mentioned databases.

2.2. Outcomes of Interest

Studies included were randomized controlled trials (RCTs) that met the following inclusion criteria: participants will be anyone undergoing dental implant surgery; interventions are systemic antibiotics; comparisons are placebo, no treatment, or any other active intervention; and the primary outcome is early implant failure. Secondary outcomes are surgical site infection and adverse effects. The criteria for early implant failure deployed by the studies selected were instability of implant [26,27,28,29,30], removal of implant due to infection [31,32,33], removal of implant for any reason from implant placement to abutment connection or prosthetic treatment [34], mobility of implant or removal due to pain or infection [35,36], presence of mobility or infection or instability of implant [37,38], and the presence of mobility of implant [39,40]. There was a high degree of heterogeneity across all the studies in the case definition of early implant failure.

2.3. Data Extraction and Quality Assessment

Two authors independently screened titles and abstracts for eligible studies, followed by full-text reading. Ineligible studies were excluded from full-text review, and the reasons for exclusion were documented. Data was extracted independently and in duplicate by the three reviewers and entered into a data extraction form created following The Cochrane Handbook of Systematic Reviews of Interventions guidelines [24]. If multiple publications of the same trial were retrieved, only the most recent relevant data will be included from these publications. The data from RCTs were separated into the following sections: study characteristics, population characteristics, intervention characteristics, and outcome definitions and measures. For all outcomes, the initial number of participants randomized to each trial arm was used, and analyses were performed irrespective of how the authors of the original trials had analyzed the data (intention-to-treat principle). Two reviewers independently assessed the risk of bias (RoB) within each study by using the revised Cochrane risk of bias tool (RoB 2.0) [41]. Reviewers resolved disagreements through discussion.

2.4. Data Synthesis and Statistical Analysis

Data was analyzed according to the intention to treat the principle as a primary analysis. Risk ratios and 95% confidence intervals was used as summary statistics. For direct comparisons, a standard pairwise meta-analysis was performed by using a random effects (DerSimonian and Laird) model [24]. If a direct comparison was based on two or more studies, heterogeneity between trials was assessed using I2 statistics; an I2 estimate ≥50% is interpreted as evidence of substantial levels of heterogeneity [24]. A random-effects network meta-analysis (frequentist approach) using either a consistency or an inconsistency model was applied to synthesize the available evidence by combining direct and indirect evidence from different studies [42,43]. The network inconsistency assumption, which refers to a disagreement between the direct and indirect estimates, was evaluated using a global inconsistency test by fitting design-by-treatment into the inconsistency model [44,45]. The probability of each treatment was estimated as being the best to construct rankograms (a relative ranking of interventions) and their surface area under the cumulative ranking (SUCRA) [46]. Publication bias was examined with a comparison-adjusted funnel plot [47]. For statistical analysis and graph generation, Stata version 15.0 (StataCorp, College Station, TX, USA) was utilized [46]. To assess the robustness of our primary efficacy outcomes, we performed multiple pre-specified sensitivity analyses by restricting studies with low risk of bias.

3. Results

A total of 1076 articles were initially identified, and 342 duplicates were removed. A total of 710 articles were excluded by screening the titles and abstracts. A total of 24 articles were assessed by full-text reading, and finally 15 articles were included in the quantitative synthesis (Table 1). The PRISMA flow diagram is shown in Figure 1.
The different dosing regimens of antibiotics varied from 1 h preoperatively to postoperatively for 7 days, and the time of evaluations following treatment ranged from 2 days to the 8th week for adverse effects and postsurgical complications, and from 10 days to 6 months for implant failure. A table that summarizes all of the abbreviations used in this current study can be accessed in Supplementary Table S1.
The quality assessment of each study using the RoB assessment tool is provided in Supplementary Table S2, and the reasons for the exclusion of four articles from the full text review are provided in Supplementary Table S3. Nine trials were evaluated to be at high RoB [26,27,31,34,35,36,37,39,40]; two studies were graded with some concerns [32,33]; and the remaining four studies had low bias [28,29,30,38].

3.1. Implant Failure (per Patient Data)

A total of 12 randomized control trials comparing 11 interventions (Figure 2) were included in the NMA, which is expressed as the risk ratio (RR) of implant failure per patient when treatment was given as compared to a placebo. When compared to the placebo, protocols POST2 (RR = 0.38(95%CI: 0.16, 0.90)), PRE1 (RR = 0.42(95%CI: 0.27, 0.67)), and PREPO9 (RR = 0.36(95%CI: 0.15, 0.87)) were statistically proven to be significant in preventing implant failure at the patient level. The protocol PREPO9 ranked first (SUCRA 66.3), followed by POST2 (SUCRA 64.0), and lastly PRE1 (SUCRA 59.6) in preventing implant failure.
Table 2 summarizes the relative risk (RR) and the ranking of the treatment options. Figure 3 shows the SUCRA ranking curves for each protocol.
The direct and network estimates for the efficacy of these agents are shown in Figure 4.
Pairwise meta-analysis was conducted for studies with direct comparisons, as shown in Supplementary Figure S1. It was shown that the intervention PRE1 (RR = 0.42(95%CI: 0.25, 0.73)) was statistically significant in preventing implant failure.
A sensitivity analysis was performed due to the high number of studies susceptible to a high risk of bias, as shown in Supplementary Figure S2. The analysis demonstrated no statistically significant protocols, as seen in Supplementary Table S3.

3.2. Implant Failure (per Implant)

Eleven randomized control trials investigating nine interventions were analyzed to assess the efficacy of a preoperative antibiotic in preventing implant failure per implant. The network plot derived is shown in Figure 5. The network estimates that only protocol PRE1 (RR = 0.49 (95%CI: 0.26, 0.92)) is statistically significant in preventing implant failure.
Table 3 summarizes the RR and the SUCRA ranking of the treatment options, while statistically significant differences are listed in the league table (Figure 6).
The ranking of the efficacy of the interventions was based on SUCRA, and protocol PREPO7 ranked the highest. Only protocol PRE1 was statistically significant. The SUCRA ranking curves for each protocol are presented in Figure 7. These direct and network estimates of implant failure (implant) are presented in Figure 6.
Pairwise meta-analysis revealed no significant results, as shown in Supplementary Figure S3.

3.3. Prevention of Prosthetic Failure

Three randomized control trials investigating two protocols were analyzed to assess the efficacy of the preoperative antibiotic in preventing prosthetic failure. The network plot derived is shown in Supplementary Figure S4. The network estimates show that, compared to the placebo, none of the protocols were estimated to be statistically significant. Supplementary Table S4 and Supplementary Figure S5 summarize the RR and the SUCRA ranking of the treatment options. The league table is depicted in Supplementary Figure S6.
The ranking of the efficacy of the interventions was based on SUCRA, and protocol PRE1 ranked the highest, followed by protocol PREPO5. No protocols were statistically significantly more effective compared to the placebo. A pairwise meta-analysis was conducted for studies with direct comparison and is shown in Supplementary Figure S7. No protocols were statistically significant.

3.4. Postsurgical Complications

A total of twelve RCTs investigating 10 interventions have reported postsurgical complications, and a network plot was formed among those studies as shown in Supplementary Figure S8. Based on the NMA, no protocols were statistically significantly effective compared to placebo/no treatment. The SUCRA ranking curve for each protocol is presented in Supplementary Figure S9.
The ranking of the efficacy of the interventions was based on SUCRA, and protocol PREPO7 ranked the highest. The least effective protocol was POST1. No protocols were statistically significantly effective compared to the placebo. Supplementary Table S5 summarizes the RR and the SUCRA ranking of the treatment options.
Based on the SUCRA rank and curve, PREPO7 ranked first while POST1 ranked last in preventing postsurgical complications. Supplementary Figure S10 depicts the league table. For studies with direct comparisons, a pairwise meta-analysis was performed, as shown in Supplementary Figure S11. No protocols were statistically significant.

3.5. Adverse Effects

A total of nine RCTs investigating seven interventions reported adverse effects, and a network plot was formed of these studies as shown in Supplementary Figure S12. Based on the NMA, none of the protocols are statistically significant. The direct and network estimates for the side effects of these protocols are shown in Supplementary Table S6.
Based on the SUCRA ranking curve (Supplementary Figure S13), protocol PRE1 ranked first while PREPO2 ranked last in reported adverse effects to antibiotics. Supplementary Figure S14 depicts the league table for adverse effects. A pairwise meta-analysis was conducted for studies with direct comparison and is shown in Supplementary Figure S15. No protocols were statistically significant.
There was no inconsistency found for any outcome of the network meta-analysis (Supplementary Table S7). Based on the comparison-adjusted funnel plot graph, publication bias could be detected for RCTs investigating protocols for implant failure (patient), implant failure (implant), and post-surgical complications (Supplementary Figures S16, S17, and S19). No publication bias was observed for prosthetic failure or adverse effects (Supplementary Figures S18 and S20).

4. Discussion

A total of nine out of fifteen randomized controlled trials were deemed to have a high risk of bias using the Cochrane’s Collaboration Tool for assessing risk of bias [41]. Assessors can only predict the susceptibility of a trial to bias, but it will not be known with precision whether there was actual bias during the trial [48]. The inclusion of studies with a high susceptibility to biases without any appropriate handling or additional sensitivity analyses can subject the meta-analysis to being skewed towards favorable or unfavorable outcomes [49]. Thus, this systematic review with network meta-analysis has included a sensitivity analysis with the exclusion of studies with a high risk of bias to justify the results and provide a recommendation for the use of antibiotics in preventing early implant failure.
The results of this network meta-analysis have aligned with previous analyses [16,50,51,52]. Administration of 2 g of amoxicillin 1 h before the surgery had the most significant effect on preventing implant failure across the eleven trials analyzed. Canullo et al. have found that preoperative administration of antibiotics has an associated higher implant survival rate at early stages [51]. This finding is also supported by Roca-Millan et al., Salgado-Peralvo et al., Romandini et al., and Esposito et al. [12,16,50,51]. However, the best antibiotic dosage for short-term prophylaxis remains unknown, and there is insufficient evidence to justify a targeted dosage for short-term prophylaxis. This is shown by the sensitivity analysis, which indicated no significant statistical difference in protocols deployed after the exclusion of studies susceptible to high risk of bias. Furthermore, there was a high degree of heterogeneity in the antibiotic protocols used across the fifteen trials. For example, El-Kholey et al. utilized a 1 g dose of amoxicillin 1 h before surgery protocol, while Nolan et al. used a 3 g dose of amoxicillin instead [27,39]. The majority of studies have included a 2 g dose of amoxicillin 1 h preoperatively with a varied postoperative protocol as shown in Table 1 [28,29,30,32,33,35,36,37,38,40]. Two trials did not report the criteria used for implant failure [32,33]. The definition of implant failure varied from instability when tested with a manual wrench, to mobility of implant, and the presence of any infection.
Three trials reported the criteria for prosthetic failure, which is when the clinician is unable to place the prostheses on the abutment or secondary to implant failure [35,37,38]. No interventions were significant as compared to no intervention in the prevention of prosthetic failure. Esposito et al. found that the use of antibiotic prophylaxis had only marginal differences compared with no prophylaxis in the prevention of prosthetic failure [52].
The results show that none of the antibiotic protocols are statistically significant in the prevention of postsurgical complications. Postsurgical complications have been reported to occur in up to 10% of patients receiving dental implants. Two thirds of the infected implants have to be removed because they do not respond to mechanical or drug therapy [53]. Esposito et al. and Ata-Ali et al. have found that antibiotic prophylaxis does not present statistically significant differences in the prevention of postoperative complications such as infection of the implant [52,54]. Furthermore, this current analysis is also in line with the findings of these previous reviews, which recommend against the use of antibiotics for the purpose of preventing postoperative complications.
This meta-analysis demonstrates that there were no statistically significant differences in adverse effects reported by the nine trials [28,30,31,33,35,36,37,38,40]. Common adverse effects of amoxicillin are gastrointestinal upset, nausea, and vomiting [55]. The greatest concern with the use of antibiotics is anaphylaxis, which can progress to death for the patient, and the increase in antibiotic-resistant strains of bacteria in the oral microbiome of the patient [56,57,58]. In addition to that, resistance to beta-lactams is more prevalent when compared to metronidazole, as demonstrated by Koukos et al. [59]. One study has shown that the use of antibiotic prophylaxis from a patient’s perspective is cost-effective since administration of preoperative antibiotics does have protective effects on preventing early implant failure [60]. However, caution has to be exercised in providing antibiotic prophylaxis from the healthcare perspective, as the emergence of resistant bacteria leads to a significant increase in treatment costs [60]. The development of antibiotic-resistant bacteria along with risks of hypersensitivity outweighs its protective effect against early implant failure.
The limitations of the current study are the low number of trials with low bias and the high heterogeneity of the antibiotic protocols used. The majority of the interventions varied by duration, dosage, and type of antibiotic. This complicates the analysis, and a standardized selection of protocol should be employed in future trials to determine the best dosage, timing, and type of antibiotic. The authors recommend that future studies be aimed at comparing varied doses of preoperative antibiotic prophylaxis. A different class of antibiotic, such as metronidazole, in the prevention of early implant failure would also be worth investigating due to the anaerobic nature of the microbiome associated with implant failure.

5. Conclusions

A single dose of 2 g of preoperative amoxicillin significantly reduces early implant failure in healthy individuals. However, more high-quality trials are required to establish this recommendation as the quality of the evidence is weak.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/antibiotics12030512/s1, Figure S1: Pairwise meta-analysis: Implant failure (per patient data); Figure S2: Sensitivity Analysis Network Plot: Implant failure (per patient data); Figure S3: Sensitivity Analysis Network Plot: Implant failure (per implant data); Figure S4: Network plot: Prosthetic failure (Patient); Figure S5: SUCRA ranking curve for Prosthetic Failure (Patient); Figure S6: League table for Prosthetic Failure (Patient); Figure S7: Pairwise meta-analysis for Prosthetic Failure (Patient); Figure S8: Network plot: Postsurgical Complications; Figure S9: SUCRA ranking curve for Postsurgical Complications; Figure S10: League table for Postsurgical Complication; Figure S11: Pairwise meta-analysis for Postsurgical complications; Figure S12: Network plot: Adverse Effect; Figure S13: SUCRA ranking curve for Adverse Effect; Figure S14: League table for Adverse Effect; Figure S15: Pairwise meta-analysis for Adverse Effects; Figure S16: Comparison-adjusted funnel plot for Implant failure (Patient); Figure S17: Comparison-adjusted funnel plot for Implant failure (per implant data); Figure S18: Comparison-adjusted funnel plot for prosthetic failure; Figure S19: Comparison-adjusted funnel plot for postsurgical complications; Figure S20: Comparison-adjusted funnel plot for adverse effects; Table S1: Abbreviations; Table S2: Risk of bias assessment of included studies; Table S3: Results of network meta-analysis from sensitivity analysis: implant failure (per patient data); Table S4: Results of network meta-analysis: Prosthetic failure (Patient); Table S5: Results of network meta-analysis: Postsurgical Complications; Table S6: Results of network meta-analysis: adverse effect; Table S7: Network consistency for implant failure (patient), implant failure (implant), prosthetic failure (patient), postsurgical complications and adverse effects. References [26,27,28,29,30,31,32,33,34,35,36,37,38,39,40] are cited in Supplementary Materials.

Author Contributions

Conceptualization, L.W.T., Y.E.N. and R.K.M. methodology, S.K.V. and R.K.M.; software, S.K.V.; validation, L.W.T., Y.E.N. and R.K.M.; formal analysis, S.K.V.; investigation, L.W.T., Y.E.N. and R.K.M.; resources, S.K.V. and R.K.M.; data curation, L.W.T., Y.E.N. and K.C.G.; writing—original draft preparation, L.W.T., Y.E.N.; K.C.G. and R.K.M.; writing—review and editing, L.W.T., Y.E.N., K.C.G., S.K.V. and R.K.M.; visualization, S.K.V.; supervision, R.K.M.; project administration, R.K.M. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data provided in the supplementary material.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Staedt, H.; Rossa, M.; Lehmann, K.M.; Al-Nawas, B.; Kämmerer, P.W.; Heimes, D. Potential risk factors for early and late dental implant failure: A retrospective clinical study on 9080 implants. Int. J. Implant. Dent. 2020, 6, 81. [Google Scholar] [CrossRef]
  2. Zhu, Y.; Zheng, X.; Zeng, G.; Xu, Y.; Qu, X.; Zhu, M.; Lu, E. Clinical efficacy of early loading versus conventional loading of dental implants. Sci. Rep. 2015, 5, 15995. [Google Scholar] [CrossRef] [Green Version]
  3. Esposito, M.; Thomsen, P.; Ericson, L.E.; Lekholm, U. Histopathologic observations on early oral implant failures. Int. J. Oral Maxillofac. Implant. 1999, 14, 798–810. [Google Scholar]
  4. Alsaadi, G.; Quirynen, M.; Komárek, A.; Van Steenberghe, D. Impact of local and systemic factors on the incidence of oral implant failures, up to abutment connection. J. Clin. Periodontol. 2007, 34, 610–617. [Google Scholar] [CrossRef]
  5. De Jonge, L.T.; Leeuwenburgh, S.C.G.; Wolke, J.G.C.; Jansen, J.A. Organic–Inorganic Surface Modifications for Titanium Implant Surfaces. Pharm. Res. 2008, 25, 2357–2369. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  6. Raghavendra, S.; Wood, M.C.; Taylor, T.D. Early wound healing around endosseous implants: A review of the literature. Int. J. Oral Maxillofac. Implant. 2005, 20, 425–431. [Google Scholar]
  7. Esposito, M.; Hirsch, J.-M.; Lekholm, U.; Thomsen, P. Biological factors contributing to failures of osseointegrated oral implants, (II). Etiopathogenesis. Eur. J. Oral Sci. 1998, 106, 721–764. [Google Scholar] [CrossRef] [PubMed]
  8. Mohajerani, H.; Roozbayani, R.; Taherian, S.; Tabrizi, R. The Risk Factors in Early Failure of Dental Implants: A Retrospective Study. J. Dent. 2017, 18, 298–303. [Google Scholar]
  9. Le Guéhennec, L.; Soueidan, A.; Layrolle, P.; Amouriq, Y. Surface treatments of titanium dental implants for rapid osseointegration. Dent. Mater. 2007, 23, 844–854. [Google Scholar] [CrossRef] [PubMed]
  10. Ciancio, S.G.; Lauciello, F.; Shibly, O.; Vitello, M.; Mather, M. The Effect of an Antiseptic Mouthrinse on Implant Maintenance: Plaque and Peri-Implant Gingival Tissues. J. Periodontol. 1995, 66, 962–965. [Google Scholar] [CrossRef]
  11. Raszewski, Z.; Nowakowska, D.; Więckiewicz, W.; Nowakowska-Toporowska, A. The Effect of Chlorhexidine Disinfectant Gels with Anti-Discoloration Systems on Color and Mechanical Properties of PMMA Resin for Dental Applications. Polymers 2021, 13, 1800. [Google Scholar] [CrossRef]
  12. Roca-Millan, E.; Estrugo-Devesa, A.; Merlos, A.; Jané-Salas, E.; Vinuesa, T.; López-López, J. Systemic Antibiotic Prophylaxis to Reduce Early Implant Failure: A Systematic Review and Meta-Analysis. Antibiotics 2021, 10, 698. [Google Scholar] [CrossRef]
  13. Sánchez, F.R.; Arteagoitia, I.; Teughels, W.; Andres, C.R.; Quirynen, M. Antibiotic dosage prescribed in oral implant surgery: A meta-analysis of cross-sectional surveys. PLoS ONE 2020, 15, e0236981. [Google Scholar] [CrossRef]
  14. Sánchez, F.R.; Arteagoitia, I.; Andres, C.R.; Bruers, J. Antibiotic prophylaxis prescribing habits in oral implant surgery in the Netherlands: A cross-sectional survey. BMC Oral Health 2019, 19, 281. [Google Scholar] [CrossRef] [Green Version]
  15. Kim, A.S.; Abdelhay, N.; Levin, L.; Walters, J.D.; Gibson, M.P. Antibiotic prophylaxis for implant placement: A systematic review of effects on reduction of implant failure. Br. Dent. J. 2020, 228, 943–951. [Google Scholar] [CrossRef] [PubMed]
  16. Romandini, M.; De Tullio, I.; Congedi, F.; Kalemaj, Z.; D’Ambrosio, M.; Laforí, A.; Quaranta, C.; Buti, J.; Perfetti, G. Antibiotic prophylaxis at dental implant placement: Which is the best protocol? A systematic review and network meta-analysis. J. Clin. Periodontol. 2019, 46, 382–395. [Google Scholar] [CrossRef] [PubMed]
  17. Schultz, L.; Lowe, T.J.; Srinivasan, A.; Neilson, D.; Pugliese, G. Economic Impact of Redundant Antimicrobial Therapy in US Hospitals. Infect. Control. Hosp. Epidemiol. 2014, 35, 1229–1235. [Google Scholar] [CrossRef]
  18. Lazarevic, V.; Manzano, S.; Gaïa, N.; Girard, M.; Whiteson, K.; Hibbs, J.; François, P.; Gervaix, A.; Schrenzel, J. Effects of amoxicillin treatment on the salivary microbiota in children with acute otitis media. Clin. Microbiol. Infect. 2013, 19, e335–e342. [Google Scholar] [CrossRef] [Green Version]
  19. Ready, D.; Lancaster, H.; Qureshi, F.; Bedi, R.; Mullany, P.; Wilson, M. Effect of Amoxicillin Use on Oral Microbiota in Young Children. Antimicrob. Agents Chemother. 2004, 48, 2883–2887. [Google Scholar] [CrossRef] [Green Version]
  20. Singh Gill, A.; Morrissey, H.; Rahman, A. A Systematic Review and Meta-Analysis Evaluating Antibiotic Prophylaxis in Dental Implants and Extraction Procedures. Medicina 2018, 54, 95. [Google Scholar] [CrossRef] [Green Version]
  21. Park, A.; Tennant, M.; Walsh, L.J.; Kruger, E. Is there a consensus on antibiotic usage for dental implant placement in healthy patients? Aust. Dent. J. 2017, 63, 25–33. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  22. Øen, M.; Leknes, K.N.; Lund, B.; Bunæs, D.F. The efficacy of systemic antibiotics as an adjunct to surgical treatment of peri-implantitis: A systematic review. BMC Oral Health 2021, 21, 666. [Google Scholar] [CrossRef] [PubMed]
  23. Menon, R.K.; Gomez, A.; Brandt, B.W.; Leung, Y.Y.; Gopinath, D.; Watt, R.M.; Crielaard, W.; Nelson, K.E.; Botelho, M.G. Long-term impact of oral surgery with or without amoxicillin on the oral microbiome-A prospective cohort study. Sci. Rep. 2019, 9, 18761. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  24. Higgins, J.P.T.; Thomas, J.; Chandler, J.; Cumpston, M.; Li, T.; Page, M.J.; Welch, V.A. (Eds.) Cochrane Handbook for Systematic Reviews of Interventionsversion; 6.3 (Updated February 2022); Cochrane: London, UK, 2022; Available online: www.training.cochrane.org/handbook (accessed on 6 October 2022).
  25. Hutton, B.; Salanti, G.; Caldwell, D.M.; Chaimani, A.; Schmid, C.H.; Cameron, C.; Ioannidis, J.P.A.; Straus, S.; Thorlund, K.; Jansen, J.P.; et al. The PRISMA Extension Statement for Reporting of Systematic Reviews Incorporating Network Meta-analyses of Health Care Interventions: Checklist and Explanations. Ann. Intern. Med. 2015, 162, 777–784. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  26. Payer, M.; Tan, W.C.; Han, J.; Ivanovski, S.; Mattheos, N.; Pjetursson, B.E.; Zhuang, L.; Fokas, G.; Wong, M.C.M.; Acham, S.; et al. The effect of systemic antibiotics on clinical and patient-reported outcome measures of oral implant therapy with simultaneous guided bone regeneration. Clin. Oral Implant. Res. 2020, 31, 442–451. [Google Scholar] [CrossRef] [Green Version]
  27. El-Kholey, K. Efficacy of two antibiotic regimens in the reduction of early dental implant failure: A pilot study. Int. J. Oral Maxillofac. Surg. 2014, 43, 487–490. [Google Scholar] [CrossRef] [PubMed]
  28. Momand, P.; Becktor, J.P.; Naimi-Akbar, A.; Tobin, G.; Götrick, B. Effect of antibiotic prophylaxis in dental implant surgery: A multicenter placebo-controlled double-blinded randomized clinical trial. Clin. Implant. Dent. Relat. Res. 2022, 24, 116–124. [Google Scholar] [CrossRef]
  29. Tan, W.C.; Ong, M.; Han, J.; Mattheos, N.; Pjetursson, B.E.; Tsai, A.Y.-M.; Sanz, I.; Wong, M.C.; Lang, N.P.; on Behalf of the ITI Antibiotic Study Group. Effect of systemic antibiotics on clinical and patient-reported outcomes of implant therapy—A multicenter randomized controlled clinical trial. Clin. Oral Implant. Res. 2013, 25, 185–193. [Google Scholar] [CrossRef]
  30. Anitua, E.; Aguirre, J.J.; Gorosabel, A.; Barrio, P.; Errazquin, J.M.; Román, P.; Pla, R.; Carrete, J.; De Petro, J.; Orive, G. A multicentre placebo-controlled randomised clinical trial of antibiotic prophylaxis for placement of single dental implants. Eur. J. Oral Implant. 2009, 2, 283–292. [Google Scholar]
  31. Abu-Ta’A, M.; Quirynen, M.; Teughels, W.; Van Steenberghe, D. Asepsis during periodontal surgery involving oral implants and the usefulness of peri-operative antibiotics: A prospective, randomized, controlled clinical trial. J. Clin. Periodontol. 2008, 35, 58–63. [Google Scholar] [CrossRef]
  32. Tabrizi, R.; Mobin, F.; Dehghanpour, M.; Torabi, Z.S. Comparison of three antibiotic protocols for prevention of infection in dental implant surgery: A randomized clinical trial. J. Cranio-Maxillofac. Surg. 2022, 50, 293–297. [Google Scholar] [CrossRef] [PubMed]
  33. Andrade, N.K.; Ramacciato, J.C.; De Carvalho, P.S.P.; Groppo, F.C.; Motta, R.H.L. Evaluation of two amoxicillin protocols for antibiotic prophylaxis in implant placement surgeries. RGO Rev. Gaúch. Odontol. 2017, 65, 249–253. [Google Scholar] [CrossRef] [Green Version]
  34. Kashani, H.; Hilon, J.; Rasoul, M.H.; Friberg, B. Influence of a single preoperative dose of antibiotics on the early implant failure rate. A randomized clinical trial. Clin. Implant. Dent. Relat. Res. 2019, 21, 278–283. [Google Scholar] [CrossRef] [PubMed]
  35. Arduino, P.G.; Tirone, F.; Schiorlin, E.; Esposito, M. Single preoperative dose of prophylactic amoxicillin versus a 2-day postoperative course in dental implant surgery: A two-centre randomised controlled trial. Eur. J. Oral Implant. 2015, 8, 143–149. [Google Scholar]
  36. Karaky, A.E.; Sawair, F.A.; Al-Karadsheh, O.A.; Eimar, H.A.; Algarugly, S.A.; Baqain, Z. Antibiotic prophylaxis and early dental implant failure: A quasi-random controlled clinical trial. Eur. J. Oral Implant. 2011, 4, 31–38. [Google Scholar]
  37. Esposito, M.; Cannizzaro, G.; Bozzoli, P.; Consolo, U.; Felice, P.; Ferri, V.; Landriani, S.; Leone, M.; Magliano, A.; Pellitteri, G.; et al. Efficacy of prophylactic antibiotics for dental implants: A multicentre placebo-controlled randomised clinical trial. Eur. J. Oral Implant. 2008, 1, 23–31. [Google Scholar]
  38. Esposito, M.; Cannizzaro, G.; Bozzoli, P.; Checchi, L.; Ferri, V.; Landriani, S.; Leone, M.; Todisco, M.; Torchio, C.; Testori, T.; et al. Effectiveness of prophylactic antibiotics at placement of dental implants: A pragmatic multicentre placebo-controlled randomised clinical trial. Eur. J. Oral Implant. 2010, 3, 135–143. [Google Scholar]
  39. Nolan, R.; Kemmoona, M.; Polyzois, I.; Claffey, N. The influence of prophylactic antibiotic administration on post-operative morbidity in dental implant surgery. A prospective double blind randomized controlled clinical trial. Clin. Oral Implant. Res. 2014, 25, 252–259. [Google Scholar] [CrossRef]
  40. Caiazzo, A.; Casavecchia, P.; Barone, A.; Brugnami, F. A Pilot Study to Determine the Effectiveness of Different Amoxicillin Regimens in Implant Surgery. J. Oral Implant. 2011, 37, 691–696. [Google Scholar] [CrossRef]
  41. Higgins, J.P.T.; Altman, D.G.; Gøtzsche, P.C.; Jüni, P.; Moher, D.; Oxman, A.D.; Savović, J.; Schulz, K.F.; Weeks, L.; Sterne, J.A.C.; et al. The Cochrane Collaboration’s tool for assessing risk of bias in randomised trials. BMJ 2011, 343, d5928. [Google Scholar] [CrossRef] [Green Version]
  42. Hoaglin, D.C.; Hawkins, N.; Jansen, J.P.; Scott, D.A.; Itzler, R.; Cappelleri, J.C.; Boersma, C.; Thompson, D.; Larholt, K.M.; Diaz, M.; et al. Conducting Indirect-Treatment-Comparison and Network-Meta-Analysis Studies: Report of the ISPOR Task Force on Indirect Treatment Comparisons Good Research Practices: Part 2. Value Health 2011, 14, 429–437. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  43. Caldwell, D.M.; Ades, T.; Higgins, J. Simultaneous comparison of multiple treatments: Combining direct and indirect evidence. BMJ 2005, 331, 897–900. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  44. Higgins, J.P.T.; Jackson, D.; Barrett, J.K.; Lu, G.; Ades, A.E.; White, I.R. Consistency and inconsistency in network meta-analysis: Concepts and models for multi-arm studies. Res. Synth. Methods 2012, 3, 98–110. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  45. Veroniki, A.A.; Vasiliadis, H.S.; Higgins, J.P.; Salanti, G. Evaluation of inconsistency in networks of interventions. Int. J. Epidemiol. 2013, 42, 332–345. [Google Scholar] [CrossRef] [Green Version]
  46. Chaimani, A.; Higgins, J.P.T.; Mavridis, D.; Spyridonos, P.; Salanti, G. Graphical Tools for Network Meta-Analysis in STATA. PLoS ONE 2013, 8, e76654. [Google Scholar] [CrossRef] [Green Version]
  47. Salanti, G.; Ades, A.E.; Ioannidis, J.P. Graphical methods and numerical summaries for presenting results from multiple-treatment meta-analysis: An overview and tutorial. J. Clin. Epidemiol. 2011, 64, 163–171. [Google Scholar] [CrossRef]
  48. Harvey, L.A.; Dijkers, M.P. Should trials that are highly vulnerable to bias be excluded from systematic reviews? Spinal Cord 2019, 57, 715–716. [Google Scholar] [CrossRef] [Green Version]
  49. Chan, J.S.K.; Harky, A. The importance of risk of bias assessment in meta-analyses: Does controlling heterogeneity suffice? Eur. J. Cardio-Thoracic Surg. 2020, 58, 1102–1107. [Google Scholar] [CrossRef]
  50. Salgado-Peralvo, A.-O.; Mateos-Moreno, M.-V.; Velasco-Ortega, E.; Peña-Cardelles, J.-F.; Kewalramani, N. Preventive antibiotic therapy in bone augmentation procedures in oral implantology: A systematic review. J. Stomatol. Oral Maxillofac. Surg. 2021, 123, 74–80. [Google Scholar] [CrossRef]
  51. Canullo, L.; Troiano, G.; Sbricoli, L.; Guazzo, R.; Laino, L.; Caiazzo, A.; Pesce, P. The Use of Antibiotics in Implant Therapy: A Systematic Review and Meta-Analysis with Trial Sequential Analysis on Early Implant Failure. Int. J. Oral Maxillofac. Implant. 2020, 35, 485–494. [Google Scholar] [CrossRef]
  52. Esposito, M.; Grusovin, M.G.; Worthington, H.V. Interventions for replacing missing teeth: Antibiotics at dental implant placement to prevent complications. Cochrane Database Syst. Rev. 2013, 2013, CD004152. [Google Scholar] [CrossRef]
  53. Camps-Font, O.D.; Figueiredo, R.D.; Valmaseda-Castellón, E.D.; Gay-Escoda, C.M. Postoperative Infections After Dental Implant Placement: Prevalence, Clinical Features, and Treatment. Implant. Dent. 2015, 24, 713–719. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  54. Ata-Ali, J.; Ata-Ali, F. Do antibiotics decrease implant failure and postoperative infections? A systematic review and meta-analysis. Int. J. Oral Maxillofac. Surg. 2014, 43, 68–74. [Google Scholar] [CrossRef] [PubMed]
  55. Akhavan, B.J.; Khanna, N.R.; Vijhani, P. Amoxicillin. In StatPearls; StatPearls Publishing: Treasure Island, FL, USA, 2022. [Google Scholar]
  56. Ahmad, N.; Saad, N. Effects of Antibiotics on Dental Implants: A Review. J. Clin. Med. Res. 2012, 4, 1–6. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  57. Ireland, R.S.; Palmer, N.O.; Lindenmeyer, A.; Mills, N. An investigation of antibiotic prophylaxis in implant practice in the UK. Br. Dent. J. 2012, 213, E14. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  58. Carmona, I.T.; Dios, P.D.; Scully, C. Efficacy of Antibiotic Prophylactic Regimens for the Prevention of Bacterial Endocarditis of Oral Origin. J. Dent. Res. 2007, 86, 1142–1159. [Google Scholar] [CrossRef]
  59. Koukos, G.; Papadopoulos, C.; Tsalikis, L.; Sakellari, D.; Arsenakis, M.; Konstantinidis, A. Prevalence of Antibiotic Resistance Genes in Subjects with Successful and Failing Dental Implants. A Pilot Study. Open Dent. J. 2015, 8, 257–263. [Google Scholar] [CrossRef] [Green Version]
  60. Zhurakivska, K.; Russo, L.L.; Muzio, L.L.; Caponio, V.C.A.; Laino, L.; Arena, C.; Cirillo, N.; Troiano, G. Antibiotic prophylaxis at the time of dental implant placement: A cost-effectiveness analysis. BMC Health Serv. Res. 2022, 22, 1073. [Google Scholar] [CrossRef]
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Figure 1. PRISMA flow diagram summarizing the study selection process for eligible trials. * Databases from which records were identified. ** Explanation of records excluded: two summary reviews; one with unclear data; and one that did not report the outcomes.
Figure 1. PRISMA flow diagram summarizing the study selection process for eligible trials. * Databases from which records were identified. ** Explanation of records excluded: two summary reviews; one with unclear data; and one that did not report the outcomes.
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Figure 2. Network plot: implant failure (per patient). Abbreviations: PLA = placebo/no antibiotics; PRE1 = 2 g amox 1 h pre-op; PRE3 = 3 g amox 1 h pre-op; POST1 = 2 g amox immediately post-op; POST2 = post-op amox with clavulanic acid 625 mg 3 times daily for 5 days; POST3 = 500 mg q 8 h for 5 days post-op/postoperative amox 1 g twice a day for 1 week after surgery; PREPO1 = 2 g amox pre-op and 500 mg amox post-op for 3 days; PREPO2 = 2 g amox 1 h pre-op followed by 500 mg three times for 7 days; PREPO3 = 2 g amox 1 h pre-op, 500 mg q 8 h for 5 days; PREPO5 = 2 g amox pre-op and 1 g amox postoperative, and 1 g twice a day for 2 days later; PREPO7 = 1 g amox 1 h pre-op and 500 mg 4x daily for 2 days post-op; PREPO9 = 2 g amox 1 h pre-op, followed by postoperative 500 mg thrice for 5 days.
Figure 2. Network plot: implant failure (per patient). Abbreviations: PLA = placebo/no antibiotics; PRE1 = 2 g amox 1 h pre-op; PRE3 = 3 g amox 1 h pre-op; POST1 = 2 g amox immediately post-op; POST2 = post-op amox with clavulanic acid 625 mg 3 times daily for 5 days; POST3 = 500 mg q 8 h for 5 days post-op/postoperative amox 1 g twice a day for 1 week after surgery; PREPO1 = 2 g amox pre-op and 500 mg amox post-op for 3 days; PREPO2 = 2 g amox 1 h pre-op followed by 500 mg three times for 7 days; PREPO3 = 2 g amox 1 h pre-op, 500 mg q 8 h for 5 days; PREPO5 = 2 g amox pre-op and 1 g amox postoperative, and 1 g twice a day for 2 days later; PREPO7 = 1 g amox 1 h pre-op and 500 mg 4x daily for 2 days post-op; PREPO9 = 2 g amox 1 h pre-op, followed by postoperative 500 mg thrice for 5 days.
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Figure 3. SUCRA ranking curve in implant failure (per patient). Abbreviations: PRE1 = 2 g amox 1 h pre-op; PRE3 = 3 g amox 1 h pre-op; POST1 = 2 g amox immediately post-op; POST2 = post-op amox with clavulanic acid 625 mg 3 times daily for 5 days; POST3 = 500 mg q 8 h for 5 days post-op/postoperative amox 1 g twice a day for 1 week after surgery; PREPO1 = 2 g amox pre-op and 500 mg amox post-op for 3 days; PREPO2 = 2 g amox 1 h pre-op followed by 500 mg three times for 7 days; PREPO3 = 2 g amox 1 h pre-op, 500 mg q 8 h for 5 days; PREPO5 = 2 g amox pre-op and 1 g amox postoperative, and 1 g twice a day for 2 days later; PREPO7 = 1 g amox 1 h pre-op and 500 mg 4x daily for 2 days post-op; PREPO9 = 2 g amox 1 h pre-op, followed by postoperative 500 mg thrice for 5 days.
Figure 3. SUCRA ranking curve in implant failure (per patient). Abbreviations: PRE1 = 2 g amox 1 h pre-op; PRE3 = 3 g amox 1 h pre-op; POST1 = 2 g amox immediately post-op; POST2 = post-op amox with clavulanic acid 625 mg 3 times daily for 5 days; POST3 = 500 mg q 8 h for 5 days post-op/postoperative amox 1 g twice a day for 1 week after surgery; PREPO1 = 2 g amox pre-op and 500 mg amox post-op for 3 days; PREPO2 = 2 g amox 1 h pre-op followed by 500 mg three times for 7 days; PREPO3 = 2 g amox 1 h pre-op, 500 mg q 8 h for 5 days; PREPO5 = 2 g amox pre-op and 1 g amox postoperative, and 1 g twice a day for 2 days later; PREPO7 = 1 g amox 1 h pre-op and 500 mg 4x daily for 2 days post-op; PREPO9 = 2 g amox 1 h pre-op, followed by postoperative 500 mg thrice for 5 days.
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Figure 4. League table for implant failure (per patient).
Figure 4. League table for implant failure (per patient).
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Figure 5. Network plot: implant failure (per implant). Abbreviations: PLA = placebo/no antibiotics; PRE1 = 2 g amox 1 h pre-op; POST2 = post-op amox with clavulanic acid 625 mg 3 times daily for 5 days; POST3 = 500 mg q 8 h for 5 days post-op/postoperative amox 1 g twice a day for 1 week after surgery; PREPO1 = 2 g amox pre-op and 500 mg amox post-op for 3 days; PREPO3 = 2 g amox 1 h pre-op, 500 mg q 8 h for 5 days; PREPO5 = 2 g amox pre-op and 1 g amox postoperative, and 1 g twice a day for 2 days later; PREPO7 = 1 g amox 1 h pre-op and 500 mg 4x daily for 2 days post-op; PREPO8 = 2 g amox 1 h pre-op, followed by postoperative 1 g amox twice a day for 7 days; PREPO9 = 2 g amox 1 h pre-op, followed by postoperative 500 mg thrice for 5 days.
Figure 5. Network plot: implant failure (per implant). Abbreviations: PLA = placebo/no antibiotics; PRE1 = 2 g amox 1 h pre-op; POST2 = post-op amox with clavulanic acid 625 mg 3 times daily for 5 days; POST3 = 500 mg q 8 h for 5 days post-op/postoperative amox 1 g twice a day for 1 week after surgery; PREPO1 = 2 g amox pre-op and 500 mg amox post-op for 3 days; PREPO3 = 2 g amox 1 h pre-op, 500 mg q 8 h for 5 days; PREPO5 = 2 g amox pre-op and 1 g amox postoperative, and 1 g twice a day for 2 days later; PREPO7 = 1 g amox 1 h pre-op and 500 mg 4x daily for 2 days post-op; PREPO8 = 2 g amox 1 h pre-op, followed by postoperative 1 g amox twice a day for 7 days; PREPO9 = 2 g amox 1 h pre-op, followed by postoperative 500 mg thrice for 5 days.
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Figure 6. League table for implant failure (per implant).
Figure 6. League table for implant failure (per implant).
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Figure 7. SUCRA ranking curve for implant failure (per implant).
Figure 7. SUCRA ranking curve for implant failure (per implant).
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Table
Table 1. Characteristics of included studies.
Table 1. Characteristics of included studies.
Author (Year) Study Design Sample Size Study Comparison Time of Evaluation * Outcome: Implant Failure (Patient) * Outcome: Implant Failure (Implant) * Outcome: Prosthetic Failure (Patient) * Outcome: Prosthetic Failure (Implant) * Outcome: Adverse Effect * Outcome: Postsurgical Complication
Momand et al. (2022) [28] Double-blinded, RCT 473 PRE1, PLA Postsurgical complication and adverse effect: 14 days; implant: 3–6 months 6/238; 7/235 8/373; 8/384 nil nil 0/238; 0/235 2/238; 5/235
Reza Tabrizi et al. (2022)
[32]		 Single-blind, single center clinical trial RCT 450 PRE1,
PREPO3, and POST3		 Three months 0/150; 2/150; 1/150 0/150; 2/150; 1/150 nil nil nil 9/150; 11/150; 7/150
Payer et al. (2020) [26] RCT 236 PREPO1, PLA Twelve weeks 3/117; 1/119 3/117; 1/119 nil nil nil nil
Kashani et al. (2019) [34] Randomized clinical trial 447 PRE1, PLA Four months 11/223; 29/224 12/535; 32/428 nil nil nil nil
Andrade et al. (2017)
[33]		 RCT 66 PRE1,
PREPO2		 One, two, three, and seventh day postop, as well as 3 months 0/35; 3/31 nil nil nil 0/35; 4/31 nil
Arduino et al. (2015) [35] Two centered RCT 343 PRE1,
PREPO5		 Postsurgical complication: 7 days, implant: 1–2 months 5/166; 5/177 5/278; 8/289 0/166; 2/177 0/not stated; 4/not stated 0/166; 3/177 6/166; 4/177
Rory Nolan et al. (2014)
[39]		 Double-blinded RCT 55 PLA, PRE3 Postsurgical complication: 7 days, implant: 3–4 months 0/27; 5/28 nil nil nil nil 0/27; 2/28
El-Kholey et al. (2014) [27] Pilot study 80 PRE2,
PREPO6		 Implant failure and postsurgical complications 0/40; 0/40; 0/47; 0/43 nil nil nil 3/40; 1/40
Tan, Wan Ching et al. (2014) [29] Multicenter RCT 329 PLA, PRE1,
PREPO1, and POST1		 Eight weeks 0/81; 0/82; 0/86; 1/80 nil nil nil nil 0/81; 1/82; 1/86; 0/80
Ashraf Abukaraky (2011) [36] Quasi-random controlled clinical trial 240 PRE1,
PREPO9, and POST2		 One week, one month, and the beginning of the prosthetic stage (after 3–4 months) 12/73; 11/79; 13/88 14/210; 13/266; 15/290 nil nil 0/73; 2/79; 0/88 1/73; 3/79; 1/88
Caiazzo, Alfonso (2011) [40] Prospective, con- trolled, and randomized clinical study 100 PLA, PRE1,
PREPO8, and POST3		 Postsurgical complications and adverse effects: first, second, fourth, and eighth week. Implant: 3 months nil 0/35; 0/36; 0/48;2/29 nil nil 0/25; 0/25; 0/25; 0/25 0/25; 0/25; 0/25; 0/25
Esposito, Marco et al. (2010) [38] Pragmatic multicenter placebo-controlled randomized clinical trial 506 PLA, PRE1 First and second weeks, and the fourth month 5/252; 12/254 7/489; 13/483 4/252; 10/254 nil 0/252; 0;254 8/252; 11/254
Anitua, Eduardo (2009) [30] Double-blinded RCT 105 PLA, PRE1 Three days, ten days, one month, and three months 2/52; 2/53 2/52; 2/53 nil nil 0/52; 0/53 6/52; 6/53
Abu-Ta’a et al. (2008) [31] RCT 80 PLA,
PREPO7		 Ten days 0/40; 3/40 0/128; 5/119 nil nil 0/40; 0/40 1/40; 4/40
Esposito, Marco et al. (2008) [37] Double-blinded RCT 316 PLA, PRE1 One week, two weeks, and four months 2/158; 8/158 nil 2/158;4/158 2/not stated; 4/not stated 1/158; 1/158 7/158; 4/158
Abbreviations: PLA = placebo/no antibiotics; PRE1 = 2 g amox 1 h pre-op; PRE3 = 3 g amox 1 h pre-op; POST1 = 2 g amox immediately post-op; POST2 = post-op amox with clavulanic acid 625 mg 3 times daily for 5 days; POST3 = 500 mg q 8 h for 5 days post-op/postoperative amox 1 g twice a day for 1 week after surgery; PREPO1 = 2 g amox pre-op and 500 mg amox post-op for 3 days; PREPO2 = 2 g amox 1 h pre-op followed by 500 mg three times for 7 days; PREPO3 = 2 g amox 1 h pre-op, 500 mg q 8 h for 5 days; PREPO5 = 2 g amox pre-op and 1 g amox postoperative, and 1 g twice a day for 2 days later; PREPO7 = 1 g amox 1 h pre-op and 500 mg 4x daily for 2 days post-op; PREPO9 = 2 g amox 1 h pre-op, followed by postoperative 500 mg thrice for 5 days. * The numbers x/xxx in the column denote the number of outcomes reported/the sample size in that group.
Table
Table 2. Results of network meta-analysis: implant failure (per patient).
Table 2. Results of network meta-analysis: implant failure (per patient).
Treatment Implant Failure (Patient)
Relative Risk (95% CI) p-Value SUCRA Rank (Score)
POST1 0.47 (0.02; 10.74) 0.640 7 (55.1)
POST2 0.38 (0.16; 0.90) 0.028 * 4 (64.0)
POST3 1.28 (0.05; 32.30) 0.879 8 (35.6)
PRE1 0.42 (0.27; 0.67) 0 * 6 (59.6)
PRE3 0.11 (0; 1.92) 0.132 1 (82.4)
PREPO1 1.42 (0.22; 8.96) 0.704 9 (26.9)
PREPO2 3.37 (0.17; 65.03) 0.421 11 (18.1)
PREPO3 2.14 (0.10; 45.74) 0.626 10 (24.6)
PREPO5 0.40 (0.10; 1.47) 0.170 5 (60.6)
PREPO7 0.14 (0; 2.67) 0.193 2 (77.1)
PREPO9 0.36 (0.15; 0.87) 0.024 * 3 (66.3)
Note: presence of (*) and texts in red indicate statistically significant protocols. Abbreviations: PRE1 = 2 g amox 1 h pre-op; PRE3 = 3 g amox 1 h pre-op; POST1 = 2 g amox immediately post-op; POST2 = post-op amox with clavulanic acid 625 mg 3 times daily for 5 days; POST3 = 500 mg q8h for 5 days post-op/postoperative amox 1 g twice a day for 1 week after surgery; PREPO1 = 2 g amox pre-op and 500 mg amox post-op for 3 days; PREPO2 = 2 g amox 1 h pre-op followed by 500 mg three times for 7 days; PREPO3 = 2 g amox 1 h pre-op, 500 mg q8h for 5 days; PREPO5 = 2 g amox pre-op and 1 g amox postoperative, and 1 g twice a day for 2 days later; PREPO7 = 1 g amox 1 h pre-op and 500 mg 4x daily for 2 days post-op; PREPO9 = 2 g amox 1 h pre-op, followed by postoperative 500 mg thrice for 5 days.
Table
Table 3. Results of network meta-analysis: implant failure (per implant).
Table 3. Results of network meta-analysis: implant failure (per implant).
Treatment Implant Failure (Per Implant)
Relative Risk (95% CI) p-Value SUCRA Rank (Score)
POST2 0.38 (0.11,1.31) 0.127 4 (62.6)
POST3 0.43 (0.04,4.16) 0.468 5 (56.3)
PRE1 0.49 (0.26,0.92) 0.027 * 6 (54.2)
PREPO1 3.05 (0.28,33.09) 0.359 9 (11.8)
PREPO3 0.99 (0.07,13.61) 0.998 8 (34.4)
PREPO5 0.76 (0.17,3.39) 0.721 7 (38.1)
PREPO7 0.08 (0,1.68) 0.106 1 (85.0)
PREPO8 0.23 (0.01,4.84) 0.346 2 (68.3)
PREPO9 0.36 (0.10,1.25) 0.110 3 (64.3)
Note: presence of (*) and text in red indicate statistically significant protocols. Abbreviations: PRE1 = 2 g amox 1 h pre-op; POST2 = post-op amox with clavulanic acid, 625 mg 3 times daily for 5 days; POST3 = 500 mg q 8 h for 5 days post-op/postoperative amox, 1 g twice a day for 1 week after surgery; PREPO1 = 2 g amox pre-op and 500 mg amox post-op for 3 days; PREPO3 = 2 g amox 1 h pre-op,500 mg q 8 h for 5 days; PREPO5 = 2 g amox pre-op and 1 g amox postoperative, and 1 g twice a day for 2 days later; PREPO7 = 1 g amox 1 h pre-op and 500 mg 4x daily for 2 days post-op; PREPO8 = 2 g amox 1 h pre-op, followed by postoperative 1 g amox twice a day for 7 days; PREPO9 = 2 g amox 1 h pre-op, followed by postoperative 500 mg thrice for 5 days.
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Tan, L.W.; Ng, Y.E.; Giok, K.C.; Veettil, S.K.; Menon, R.K. Comparative Efficacy of Different Amoxicillin Dosing Regimens in Preventing Early Implant Failure—A Systematic Review with Network Meta-Analysis. Antibiotics 2023, 12, 512. https://doi.org/10.3390/antibiotics12030512

AMA Style

Tan LW, Ng YE, Giok KC, Veettil SK, Menon RK. Comparative Efficacy of Different Amoxicillin Dosing Regimens in Preventing Early Implant Failure—A Systematic Review with Network Meta-Analysis. Antibiotics. 2023; 12(3):512. https://doi.org/10.3390/antibiotics12030512

Chicago/Turabian Style

Tan, Lee Wen, Yan Er Ng, Koay Chun Giok, Sajesh K. Veettil, and Rohit Kunnath Menon. 2023. "Comparative Efficacy of Different Amoxicillin Dosing Regimens in Preventing Early Implant Failure—A Systematic Review with Network Meta-Analysis" Antibiotics 12, no. 3: 512. https://doi.org/10.3390/antibiotics12030512

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