As the most common complication of oral implants, peri-implantitis may affect the success rate of oral implants. So, correct and deep understanding of peri-implantitis is particularly important. In order to avoid the occurrence of peri-implantitis, it is very important to predict the probability of peri-implantitis preoperatively based on patient case data, so as to make personalized diagnosis and treatment plan for each patient, and ensure the long-term survival rate and success rate of implantation.
Smoking, diabetes, severe periodontitis, lager implant diameter and poor oral hygiene are important risk factors of peri-implantitis. We also established a novel and accurate predictive model for the occurrence of peri-implantitis in managing patients with chronic periodontitis. The use of these parameters, in the form of a predictive model, has the potential to improve decision-making in the application of the treatment plan.
Some research compared both showed there was no statistical difference about the soft tissue around implant and alveolar bone absorption between smokers and non-smokers, and the implant success and survival rate can amount to 100%.9,10 But the overwhelming consensus was that smokers have a higher rate of implant failure than nonsmokers. Vervaeke reported that implant bone loss in smokers was 1.18mm higher than that in non-smokers.11 A meta- analysis including 13 studies (478 smokers vs 1207 non-smokers) showed that smoking increased implant bone loss by 0.164 mm per year.12 Smoking not only increases the risk of post-implant infection and marginal bone loss, but also changes in peri-implant tissue and flora, which in turn increases the risk of peri-implant inflammation and implant failure, resulting in reduced survival.13,14 Some authors suggest that the controversy between smoking and peri-implantitis may be related to differences in the definition of how much smokers smoke in the study. In this study, smokers were defined as having more than 10 cigarettes a day. The incidence of peri-implantitis was 42.1% (40/95) in smokers and 9.3% (55/591) in nonsmokers. (P<0.05) Although smoking is not an absolute contraindication to dental implant treatment, some studies have shown that smoking can increase the activity of argininase in saliva, thereby reducing the production of nitric oxide and causing local blood circulation disturbance, thus increasing the susceptibility to bacterial infection. In addition, smoking can inhibit the gene expression of bone salivary protein and osteocalcin, reduce the number of osteoblasts on titanium implants, down-regulate osteoblasts, and affect the implant-bone interface binding, resulting in implant failure.15,16 So, we suggested that patients with chronic periodontitis should try to quit smoking or strictly control the amount of smoking.
Ting showed that diabetes patients with poor control were considered to be at high risk of peri-implantitis.17 Similarly, Monje found that the risk of peri-implantitis in diabetes patients was about 50% higher than that in non- diabetes patients. And, even among non-smokers, the risk of peri-implantitis was 3.39 times higher in those with high blood sugar than in those with normal blood sugar.18 Continuously unstable hyperglycemia delayed wound healing and increased peri-implant soft tissue inflammation by reducing the expression of growth factors in wound fluid and epithelial reformation.19 It has been widely recognized that diabetes is a relative contraindication to dental implant therapy. Therefore, strict control and maintenance of blood glucose level can maintain aesthetic and functional stability of implants.
Roccuzzo reported a study including 112 patients and divided them into periodontal health group, moderate and severe periodontitis group. After 10 years, they returned to the three groups and measured the implant marginal bone loss of, which were 0.75±0.88mm, 1.14±1.11mm and 0.98±1.2mm, respectively, and the difference was statistically significant.20 The results of this study showed that there were statistical differences in peri-implantitis among patients with different severity degrees of periodontitis. Occurrence of peri-implantitis in the severe group and moderate group was significantly greater than that in the mild group, indicating that patients in the severe group and moderate group were more prone to get peri-implantitis than those in the mild group.
Currently, there is no standard definition for the classification of implant diameter size. Rodrigo should the incidence of periimplantitis in narrow implants (>3.5mm) was as high as 95.1%, with a statistically significant difference. An animal study by Morelli confirmed that narrow implants (3.3 mm and 4.1 mm) showed a tendency to induce peri-implantitis more easily than standard implants (3.8 mm and 4.1mm).21 In addition, with regard to wide-diameter implants, Flanagan believed that the diameter of implants should be controlled within 4.7mm. Diameters larger than 5mm are more likely to increase the risk of peri-implantitis, because larger diameters may lead to poor blood supply around implants and further affect osseointegration. Moreover, the risk of peri-implantitis increased significantly with implant diameter increasing (RR=1.6/ mm, P<0.01).22,23 However, Shi evaluated 98 narrow implants (3.3mm), of which only 8 were diagnosed with peri-implantitis, showing no statistical difference, suggesting that narrow implants can be a predictable clinical treatment option.24 Hattingh reported a prospective study of 51 wider-diameter (>6mm) implants with a mean follow-up of 23 months, showing almost no marginal bone loss.25 We suggest that there is controversy regarding the relationship between implant diameter and peri-implantitis. The risk of peri-implantitis is increased by the relative thinness of labial-bucolic bone after wide-diameter implants and the resorption of alveolar bone during implant union healing. However, wide diameter implants have advantages in stress distribution, which can improve the stress distribution in the cortical bone region, while narrow implants tend to be more prone to stress concentration. In conclusion, bone stress should be kept within the physiological range in order to prevent pathological implant overload.
Patients do not pay attention to plaque control will lead to plaque accumulation around the implant, plaque, calculus and other long-term retention without timely cleaning, oral pathogenic bacteria will act on the gum around the implant, accelerate the secretion of inflammatory mediators. Make gum cannot fit closely, the impact of biology closed, eventually lead to peri-implantitis. The results show that good oral hygiene is beneficial to the stability of the implant, may improve the success rate of implant prosthesis.
The oral health status of patients with periodontitis were generally poor. There were a large number of subgingival free plaque and attached plaque under the periodontal pocket, which was difficult to completely eradicate. Especially, the number of bacteria in the oral cavity of patients with poor oral health self-maintenance ability was several times higher than that of healthy individuals. Therefore, clinicians should strengthen oral hygiene education for patients, especially those with a history of periodontitis, guide patients to develop the habit of brushing and gargle.
We determined the factors that can predict the occurrence of peri-implantitis in managing patients with chronic periodontitis. This model can be useful to guide dentists to improve decision-making and anticipating the outcome based on patient characteristics. Smoking, diabetes, severe periodontitis, lager implant diameter and poor oral hygiene are important risk factors increasing the odds. The predictive model was reasonable and accurate and need to be verified in a prospective study.
Our study should be considered in the context of several notable strengths. First, this study is the first, to our knowledge, that provides a predictive model analyzing the independent influencing factors of peri-implantitis by logistic regression, and also offers a framework to select patients suitable for implant prosthesis. Dentists can assess these factors to get a nice doctor-patient communication and a personalized treatment plan for each patient. Second, we conducted a rigorous and precise statistical analysis to guarantee the comprehensiveness. Our multiple stepwise logistic regression model analysis was reasonable, and the model was accurate (the overall accuracy was 87.2%) in predicting the likelihood of occurrence of peri-implantitis, according to the strict diagnostic criteria at 5 years follow-up, high AUC for ROC. Third, because of its intuitionism, visualization and simplicity, this model may become one of the important auxiliary tools for clinical decision-making in the future.
There were also shortcomings in this study. First, the sample size of this study is limited, which may affect the study results to some extent. Second, the selection of cases in this study was limited, whether to perform bone augmentation and maxillary sinus lift had not been collected, and further analysis is needed in the later studies. Thirdly, this was a retrospective study mainly based on clinical case data and oral imaging data. The prediction model obtained in this study has only been tested in only one center, and larger multi-center studies and prospective studies are needed to support and optimize our prediction model in the later stage.