Influence of Systemic Conditions on the Incidence of Periimplant Pathology: A Case-Control Study

Impact of diabetes mellitus on the poor prognosis in patients with osseointegrated dental implants: a meta-analysis of observational studies

This meta-analysis aimed to explore the correlation between diabetes mellitus (DM) and peri-implant diseases in patients with osseointegrated dental implants. Relevant studies were searched in multiple databases from the available date of inception through 26 August 2021. The odds ratios (ORs) were used as the effect indicator for measurement data, and each effect size was given estimates and 95% confidence intervals (CIs). Begg's test was used for publication bias. Twenty-one observational studies with 24,953 participants were selected. No significant association was shown between DM and peri-implant mucositis (OR: 0.739, 95% CI: 0.394-1.383, P = 0.344). The results demonstrated that the risk of peri-implantitis was higher in DM than in non-DM (OR: 1.553, 95% CI: 1.084-2.226, P = 0.016). Smokers had higher risk of peri-implantitis than non-smoking patients (OR: 1.754, 95% CI: 1.620-1.899, P < 0.001). In addition, no significant association was shown between DM and peri-implantitis among non-smokers. The association between periodontal history (OR: 2.538, 95% CI: 0.814-7.921, P = 0.109), poor plaque control (OR: 1.700, 95% CI: 0.334-8.648, P = 0.523) and peri-implantitis was not statistically significant. No publication bias was observed for each outcome. DM increases the risk of poor outcomes in osseointegrated dental implant patients. The findings of the present study further elucidate the need for longitudinal investigations regarding risk variables that affects peri-implant tissues.

The effect of adjuvant oral irrigation on self-administered oral care in the management of peri-implant mucositis: A randomized controlled clinical trial

OBJECTIVES

This single-blinded randomized clinical trial evaluated the effect of adjuvant oral irrigation in addition to self-administered oral care on prevalence and severity of peri-implant mucositis.

MATERIAL & METHODS

After randomization, patients suffering from peri-implant mucositis were assigned to the following: Group 1 (control) received oral hygiene instruction following a standardized protocol, including a sub- and supramucosal mechanical debridement. Group 2 and 3 additionally were instructed to use an oral irrigator with either water or 0.06% CHX solution. One implant per patient was considered for examination. Clinical examinations included Probing Depth, Bleeding on Probing (BOP-positive sites), and Modified Plaque and Gingival Index. A surrogate variable (mucositis severity score) was applied measuring severity of disease. Statistical analysis included linear regression models and sensitivity analysis.

RESULTS

Sixty periodontally healthy patients were examined for presence and severity of peri-implant mucositis. 70% of all patients reached complete resolution of disease after 12 weeks. The prevalence of peri-implant mucositis after 12 weeks was 50% in group 1, 35% in group 2, and 5% in group 3. Average BOP-positive sites were reduced in all groups after 12 weeks (mean change from baseline: group 1: -1.5; group 2: -1.8; group 3: -2.3).

CONCLUSION

Within the limits of the study, adjuvant use of an oral irrigator with 0.06% CHX in addition to mechanical biofilm removal and oral hygiene instruction can reduce the presence and severity of peri-implant mucositis after 12 weeks.

The Microbiome of Peri-Implantitis: A Systematic Review and Meta-Analysis

This review aimed to systematically compare microbial profiles of peri-implantitis to those of periodontitis and healthy implants. Therefore, an electronic search in five databases was conducted. For inclusion, studies assessing the microbiome of peri-implantitis in otherwise healthy patients were considered. Literature was assessed for consistent evidence of exclusive or predominant peri-implantitis microbiota. Of 158 potentially eligible articles, data of 64 studies on 3730 samples from peri-implant sites were included in this study. Different assessment methods were described in the studies, namely bacterial culture, PCR-based assessment, hybridization techniques, pyrosequencing, and transcriptomic analyses. After analysis of 13 selected culture-dependent studies, no microbial species were found to be specific for peri-implantitis. After assessment of 28 studies using PCR-based methods and a meta-analysis on 19 studies, a higher prevalence of Aggregatibacter actinomycetemcomitans and Prevotella intermedia (log-odds ratio 4.04 and 2.28, respectively) was detected in peri-implantitis biofilms compared with healthy implants. Actinomyces spp., Porphyromonas spp. and Rothia spp. were found in all five pyrosequencing studies in healthy-, periodontitis-, and peri-implantitis samples. In conclusion, the body of evidence does not show a consistent specific profile. Future studies should focus on the assessment of sites with different diagnosis for the same patient, and investigate the complex host-biofilm interaction.

Epidemiology and risk factors of peri-implantitis: A systematic review

The purpose of this systematic review and meta-analysis was to assess the prevalence, incidence and risk factors of peri-implantitis in the current literature. An electronic search was performed to identify publications from January 1980 until March 2016 on 9 databases. The prevalence and incidence of peri-implantitis were assessed in different subgroups of patients and the prevalences were adjusted for sample size (SSA) of studies. For 12 of 111 identified putative risk factors and risk indicators, forest plots were created. Heterogeneity analysis and random effect meta-analysis were performed for selected potential risk factors of peri-implantitis. The search retrieved 8357 potentially relevant studies. Fifty-seven studies were included in the systematic review. Overall, the prevalence of peri-implantitis on implant level ranged from 1.1% to 85.0% and the incidence from 0.4% within 3 years, to 43.9% within 5 years, respectively. The median prevalence of peri-implantitis was 9.0% (SSA 10.9%) for regular participants of a prophylaxis program, 18.8% (SSA 8.8%) for patients without regular preventive maintenance, 11.0% (SSA 7.4%) for non-smokers, 7.0% (SSA 7.0%) among patients representing the general population, 9.6% (SSA 9.6%) for patients provided with fixed partial dentures, 14.3% (SSA 9.8%) for subjects with a history of periodontitis, 26.0% (SSA 28.8%) for patients with implant function time ≥5 years and 21.2% (SSA 38.4%) for ≥10 years. On a medium and medium-high level of evidence, smoking (effect summary OR 1.7, 95% CI 1.25-2.3), diabetes mellitus (effect summary OR 2.5; 95% CI 1.4-4.5), lack of prophylaxis and history or presence of periodontitis were identified as risk factors of peri-implantitis. There is medium-high evidence that patient's age (effect summary OR 1.0, 95% CI 0.87-1.16), gender and maxillary implants are not related to peri-implantitis. Currently, there is no convincing or low evidence available that identifies osteoporosis, absence of keratinized mucosa, implant surface characteristics or edentulism as risk factors for peri-implantitis. Based on the data analyzed in this systematic review, insufficient high-quality evidence is available to the research question. Future studies of prospective, randomized and controlled type including sufficient sample sizes are needed. The application of consistent diagnostic criteria (eg, according to the latest definition by the European Workshop on Periodontology) is particularly important. Very few studies evaluated the incidence of peri-implantitis; however, this study design may contribute to examine further the potential risk factors.

Association between diabetes mellitus/hyperglycaemia and peri-implant diseases: Systematic review and meta-analysis

AIM

This systematic review investigates whether hyperglycaemia/diabetes mellitus is associated with peri-implant diseases (peri-implant mucositis and peri-implantitis).

MATERIALS AND METHODS

Electronic and manual literature searching was conducted. An a priori case definition for peri-implantitis was used as an inclusion criterion to minimize risk of bias. The Newcastle-Ottawa Scale was used for quality assessment; random effect models were applied; and results were reported according to the PRISMA Statement.

RESULTS

Twelve studies were eligible for qualitative and seven of them for quantitative analyses. Meta-analyses detected the risk of peri-implantitis was about 50% higher in diabetes than in non-diabetes (RR = 1.46; 95% CI: 1.21-1.77 and OR = 1.89; 95% CI: 1.31-2.46; z = 5.98; p < .001). Importantly, among non-smokers, those with hyperglycaemia had 3.39-fold higher risk for peri-implantitis compared with normoglycaemia (95% CI: 1.06-10.81). Conversely, the association between diabetes and peri-implant mucositis was not statistically significant (RR = 0.92; 95% CI: 0.72-1.16 and OR = 1.06; 95% CI: 0.84-1.27; z = 1.06, p = .29).

CONCLUSIONS

Within its limits that demand great caution when interpreting its findings, this systematic review suggests that diabetes mellitus/hyperglycaemia is associated with greater risk of peri-implantitis, independently of smoking, but not with peri-implant mucositis.

Risk Factors for Implant Failure and Peri-Implant Pathology in Systemic Compromised Patients

PURPOSE

To identify the possible risk factors for implant failure and peri-implant pathology in a population of systemically compromised patients.

MATERIALS AND METHODS

This retrospective clinical study included a total of 721 systemically compromised patients (422 women, 299 men), with an average age of 51 years (range: 20 to 87) rehabilitated with dental implants. The average follow-up time was 7.3 years. The patients' demographic variables (age and gender) and clinical variables (implant location, type of implant surface, and systemic conditions) were recorded. Outcome measures were implant failure and peri-implant pathology. Binary logistic regression models were performed to investigate the effect of the patients' demographic and clinical characteristics on the dependent variables implant failure and peri-implant pathology. A linear regression model was performed to correlate the patient's characteristics with the number of failed implants. Odds ratios (OR) with 95% confidence intervals and corresponding levels of significance were estimated for each variable.

RESULTS

Multivariate logistic regression disclosed increased age (patients over 40 years of age) as a risk factor for implant failure (OR = 2.63) and hepatitis as a risk factor for peri-implant pathology (OR = 3.74). Multivariate linear regression disclosed rheumatologic and cardiac diseases to be correlated with a higher number of failed implants.

CONCLUSIONS

Within the limitations of this study, the results suggest no absolute contraindications for implant rehabilitation in a population of systemically compromised patients. Nevertheless, this study suggests that increasing age, rheumatological condition, cardiovascular condition, and hepatitis should be considered when performing implant-supported rehabilitations due to their negative influence on the outcome.

Attributable fractions, modifiable risk factors and risk stratification using a risk score for peri-implant pathology

PURPOSE

This study aimed to estimate the impact of risk factors for peri-implant pathology, to identify potentially modifiable factors, and to evaluate the accuracy of the risk algorithm, risk scores and risk stratification.

METHODS

This retrospective case-control study with 1275 patients (255 cases; 1020 controls) retrieved a model according to the predictors: history of Periodontitis, bacterial plaque, bleeding, bone level, lack of passive fit or non-optimal screw joint, metal-ceramic restoration, proximity to other implants/teeth, and smoking habits. Outcome measures were the attributable fraction; the positive and negative likelihood ratios at different disease cut-off points illustrated by the area under the curve statistic.

RESULTS

Six predictors may be modified or controlled directly by either the patient or the clinician, accounting for a reduction in up to 95% of the peri-implant pathology cases. The positive and negative likelihood ratios were 9.69 and 0.13, respectively; the area under the curve was 0.96; a risk score was developed, making the complex statistical model useful to clinicians.

CONCLUSIONS

Based on the results, six predictors for the incidence of peri-implant pathology can be modified to significantly improve the outcome. It was possible to stratify patients per risk category according to the risk score, providing a tool for clinicians to support their decision-making process.