Francisco Salvado

Dental implants in diabetic patients: retrospective cohort study reporting on implant survival and risk indicators for excessive marginal bone loss at 5 years

More studies evaluating the outcome of dental implant restorations in diabetics are needed. To investigate the outcome of immediate function implant rehabilitations in diabetic patients. This retrospective cohort study included 70 diabetic patients (type 1 = six patients; type 2 = 64 patients; 33 females and 37 males, mean age=59 years), rehabilitated with 352 implants. Primary outcome measure was implant survival estimated at 5 years through the Kaplan-Meier product limit estimator using the patient as unit of analysis (first implant failure as reference); secondary outcome measures were marginal bone loss and biological complications. Risk indicators associated with bone loss >2·0 mm were tested in a multivariate logistic regression model. The level of significance considered was 5%. Seven patients were lost to follow-up (10%). Seven patients lost ten implants rendering a global implant cumulative survival rate for diabetic patients of 89·8% (type 1 = 80·0%; type 2 = 90·5%). The average (95% confidence interval) marginal bone loss at 1 and 5 years was 1·64 mm (0·00;3·32) and 2·55 mm (1·38;3·72) for type 1 diabetic patients, 0·79 mm (0·59;1·00) and 1·45 mm (1·09;1·82) for type 2 diabetic patients and 0·88 mm (0·65;1·10) and 1·56 mm (1·21;1·91) overall. Biological complications occurred in seven patients. Female gender (OR = 28·1) and smoking habits (OR = 10·3) were risk indicators for marginal bone loss >2·0 mm at 5 years when controlled for other variables of interest. Implant rehabilitations represent a valid treatment for diabetic patients, with a good risk/benefit ratio. Female gender and smoking habits were risk indicators for a higher marginal bone resorption at 5 years.

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.