Title Dental Implants have similar failure rates in uncontrolled diabetic and well controlled diabetic patients
Clinical Question With dental implants, do patients with uncontrolled diabetes experience higher failure rates than patients with well controlled diabetes?
Clinical Bottom Line Patients with uncontrolled diabetes do not experience significantly higher implant failure rates than patients with well controlled diabetes
Best Evidence  
PubMed ID Author / Year Patient Group Study type
(level of evidence)
27435008Shi, et al. 2016Meta Analysis included 252 patients and 587 implants. 136 patients had well controlled diabetes and 116 had poorly controlled diabetesMeta-Analysis
Key results This Meta-analysis included 7 studies, with a total of 252 patients and 587 dental implants. Relative risk ratios and confidence intervals were pooled to analyze the effect of glycemic levels on dental implants. Heterogeneity of the studies was tested using I2 tests. I2 value was 0 (P = .437) between studies. Since Heterogeneity was low, a fixed effects model was used. The pooled RR in the early failure subgroup was 0.817 (95% CI, 0.096-6.927; P = .853, fixed-effects model) and was 0.572 (95% CI, 0.206-1.586; P = .283) in the late failure subgroup. The total rate of implant failure was 5.32% in uncontrolled diabetics versus 3.15% in well controlled diabetics. Researchers used a pooled analysis to evaluate if failure was more likely in patients with uncontrolled diabetics and found that patients with uncontrolled diabetes were no more likely than patients with well controlled diabetes to have a higher rate of implant failure (RR = 0.620; 95% CI, 0.225-1.705; P = .354).
Evidence Search “uncontrolled diabetes and dental implants”
Comments on
The Evidence
Strict inclusion and exclusion criteria were applied for this meta-analysis, with seven studies included in the analysis. The authors included both prospective and retrospective studies. Retrospective studies allow more opportunities for bias, with one main issue being selection bias. Use of these types of studies in a meta-analysis results in less reliable pooled data. The follow up period for these studies ranged from 4 months to 12 years. 5 studies had a follow up period of at least one year. The lack of longer follow up periods in most of the studies makes the result of the meta-analysis more questionable. It should also be noted that none of the studies controlled for variables like smoking, or a previous history of periodontal disease. These confounding factors could have a significant impact on the results of the pooled data. Additionally, the values for HBA1C of the well-controlled (>8.0%) and poorly controlled diabetics (<7.0%) overlapped. One study used FGP instead of HBA1C to determine if a patient was a well-controlled diabetic. Lastly, the lack of heterogeneity between studies (I2 = 0, P =.437) suggests that the results should be interpreted with great caution. In future meta-analyses, inclusion criteria for studies selected should address controlling for confounding variables and should include a longer follow up period to assess implant success.
Applicability It is estimated that 9.3% of the world’s population (463 million people) have diabetes. This number is expected to increase, making it important for clinicians to understand the implications of placing implants in diabetic patients. Implants are becoming an increasingly popular option for tooth replacement. Providers must continue to follow up with patients after the placement of implants to assess their long-term sustainability. Placement of an implant in a poorly controlled diabetic is still contraindicated, therefore glycemic control should be closely followed in diabetic patients by monitoring HBA1C, blood sugar levels and current medications.
Specialty (Public Health) (Oral Medicine/Pathology/Radiology) (General Dentistry) (Oral Surgery) (Prosthodontics) (Restorative Dentistry)
Keywords dental implants, diabetes, hyperglycemic, meta analysis
ID# 3454
Date of submission 12/09/2020
E-mail cara.pocano@cuanschutz.edu
Author Cara Pocano
Co-author(s) e-mail
Faculty mentor Ethelyn Thomason
Faculty mentor e-mail Ethelyn.thomason@cuanschutz.edu
Basic Science Rationale
(Mechanisms that may account for and/or explain the clinical question, i.e. is the answer to the clinical question consistent with basic biological, physical and/or behavioral science principles, laws and research?)
None available
Comments and Evidence-Based Updates on the CAT
None available