Dental Implant Sites in Healthy versus Diabetic Subjects: A Two-Year Clinical and Bacteriological Assessment

Abstract

The aim of this study was to analyze by Real-Time Polymerase Chain Reaction (PCR) possible differences in periimplant microbiota of patients without significant systemic diseases versus patients affected by non-insulin-dependent diabetes mellitus (NIDDM), both treated with dental implants with the same implant-abutment system. Patients suffering from NIDDM, and those with no history of major systemic diseases, treated with dental implants at the Prosthodontics Operative Unit of “Sapienza” University of Rome in the period February 2009 - March 2010 were considered. Clinical parameters as well as microbiological profile were evaluated for each implant site at 3, 6,12, and 24 month follow-up. Crevicular fluid was collected for microbial sampling and analyzed by Real-Time PCR in order to identify the possible presence of Aggregatibacter actinomycetemcomitans, Porphyromonas gingivalis, Tannerella forsythia, Treponema denticola, Fusobacterium nucleatum and Prevotella intermedia. Eight patients suffering from NIDDM and 22 with no history of major systemic diseases were included in the present investigation, each having received one to three dental implants. All the implants had been loaded 3 months after surgery, and the average follow-up after implant placement was 26.37±3.86. Clinical parameters showed no noticeable difference between the two groups, except for the Implant Stability Quotient (ISQ) that showed significantly lower values in NIDDM patients. A slightly higher amount of the considered pathogenic bacteria were retrieved in samples collected from patients with NIDDM (7.38×105) in comparison with those of healthy subjects (6.78×105), though the differences were below statistical significance. Within the limitations of the present study, a slight correlation was empirically detected between gene expression profiles of microbial populations and history of NIDDM, which however remained below the statistical significance. Further well-designed clinical studies may be useful to conclusively clarify the impact of subgingival microflora on the increased susceptibility of diabetic patients to periimplantitis.

Effects of diabetes/hyperglycemia on peri‐implant biomarkers and clinical and radiographic outcomes in patients with dental implant restorations: A systematic review and meta‐analysis

“…( p < .01; Figure 4b). Seven studies (Al‐Askar et al, 2018; Alrabiah et al, 2018; Al‐Sowygh et al, 2018; Bignozzi et al, 2013; Dŏgan et al, 2015; Tatarakis et al, 2014; Venza et al, 2010) reported the PD value, and meta‐analysis results showed a significant increase in PD of the DM/HG group than the healthy group ( p = .01; Figure 4c). Interestingly, a significant difference was observed between the two groups in the meta‐analysis results regarding MBL, which was extracted from seven studies ( p < .01; Figure 4d; Al‐Askar et al, 2018; Alrabiah et al, 2018; Al‐Sowygh et al, 2018; Bignozzi et al, 2013; Dŏgan et al, 2015; Tatarakis et al, 2014; Venza et al, 2010).…”

“…Titles and abstracts of eligible articles were screened, leaving 42 studies for full‐text review and evaluation. At this stage, 32 studies were excluded (Table S2) and 10 remained eligible for inclusion in this review (Al‐Askar et al, 2018; Alrabiah et al, 2018; Al‐Sowygh et al, 2018; Bignozzi et al, 2013; Conte et al, 2015; Dŏgan et al, 2015; Gauthami et al, 2019; Ghiraldini et al, 2016; Tatarakis et al, 2014; Venza et al, 2010; Figure 1).…”

“…Implant survival rates were reported by five prospective studies (Bignozzi et al, 2013; Dŏgan et al, 2015; Gauthami et al, 2019; Ghiraldini et al, 2016; Tatarakis et al, 2014) with a maximum follow‐up time of 24 months, with all of them reporting a survival rate of 100%. Three studies (Bignozzi et al, 2013; Gauthami et al, 2019; Ghiraldini et al, 2016) performed the resonance frequency analysis by measuring the implant stability quotient (ISQ) with Osstell® (Integration Diagnostics AB, Göteborg, Sweden). The meta‐analysis results showed a significant decrease of ISQ in the DM/HG group than in the healthy group ( p = .04; Figure 4a).…”

“…The meta‐analysis results showed a significant decrease of ISQ in the DM/HG group than in the healthy group ( p = .04; Figure 4a). Six studies (Al‐Askar et al, 2018; Alrabiah et al, 2018; Al‐Sowygh et al, 2018; Bignozzi et al, 2013; Dŏgan et al, 2015; Tatarakis et al, 2014) reported BOP% with a significantly higher BOP% observed in the DM/HG group than in the healthy group. ( p < .01; Figure 4b).…”