Patient factors related to early implant failures in the edentulous jaw: A large retrospective case-control study

Analysis of risk factors related to early implant failure: A retrospective study

STATEMENT OF PROBLEM

Factors influencing early implant failure (failure during the healing period) in the rehabilitation and restoration of oral function in partially edentulous patients are unclear.

PURPOSE

The purpose of this clinical study was to investigate several factors that may be associated with early implant failure.

MATERIAL AND METHODS

This retrospective study was conducted on 3247 implants in 2061 patients between 2009 and 2022. Patient-related and surgery-related factors, including smoking; sex; diabetes; bone grafting; implant length, diameter, and design; adjacent teeth; and insertion torque, were manually retrieved and analyzed. Using univariate and multivariate analyses, a generalized estimating equation (GEE) model with chi-squared tests was employed to evaluate factors related to early implant failure (the failure before restoration) (α=.05).

RESULTS

The mean ±standard deviation age of the study patients was 49.2 ±15.0 years (range 18 to 91). Ninety-nine implants (3.05%) failed during the healing period. Three factors were statistically significant regarding early implant failure: smoking (odds ratio [OR]=1.92, P=.008), implant design (tapered implants) (OR=1.84, P=.007), and implant length <10 mm (OR=2.98, P=.011). Factors including diabetes, bone grafting, anatomic location, adjacent teeth (endodontic therapy in the adjacent teeth and the distance between implant and adjacent teeth), healing method, and insertion torque did not exhibit a statistically significant higher early implant failure rate. Ninety-three sites with failed implants received new implants, and 6 of these 93 implants failed during the healing period.

CONCLUSIONS

Within the limitation of sample size, smokers, implant length (<10 mm), and implant design (tapered implant) exhibited higher risk of early implant failure in this retrospective study. Implant insertion torque, healing method, adjacent teeth, and diabetes did not significantly influence the risk of early implant failure.

Are Allergy-Induced Implant Failures Actually Hypersensitivity Reactions to Titanium? A Literature Review

PURPOSE

This literature review was performed to assess whether implant failures are associated with titanium allergy.

MATERIALS AND METHODS

An electronic search of the MEDLINE/PubMed, Cochrane Library, and Scopus databases up to April 2021 was conducted, and the obtained articles were independently assessed by two reviewers. Articles describing cases of implant failure in which the cause of implant failure was only identified as allergy were included.

RESULTS

Twelve studies were included. Eight studies identified Ti allergy by clinical examinations, of which four used patch tests, three used the lymphocyte transformation test (LTT)/memory lymphocyte immunostimulation assay (MELISA), and one used both tests. Nine studies reported cases of titanium hypersensitivity in combination with other systemic allergy-related disorders, with eight cases also showing positive results for Ni, Hg, Cr, and Co hypersensitivity. Ten papers reported the improvement of symptoms after the removal of the Ti implants and their replacement with zirconia implants, and two of these papers showed good results.

CONCLUSION

Cases of probable titanium allergy included those with true titanium allergies and those with a potentially different cause. However, the differentiation of these cases is difficult. Since no definitive method has been established for diagnosing titanium allergy, a comprehensive diagnosis based on the clinical course and clinical examination using a patch test/LTT/MELISA is necessary. Implant treatment should be performed with caution in patients with any preoperative allergies.

COVID-19 as a factor associated with early dental implant failures: A retrospective analysis

OBJECTIVES

To analyze the effect of COVID-19 on early implant failures and identify potential risk factors for early implant failure, concerning patient- and implant-related factors.

MATERIALS AND METHODS

This retrospective study is based on 1228 patients who received 4841 implants between March 11, 2020, and April 01, 2022, at Erciyes University Faculty of Dentistry. COVID-19, age and gender of patients, smoking, diabetes, irradiation, chemotherapy, osteoporosis, the implant system, location, and characteristics of implants were recorded. At the implant level, univariate and multivariate generalized estimating equation (GEE) logistic regression was used to examine the effect of explanatory variables on early implant failure.

RESULTS

The early implant failure rate was 3.1% at the implant level and 10.4% at the patient level. Smokers showed a significantly higher incidence of early implant failures compared to nonsmokers. (odds ratio (OR; 95% CI): 2.140 (1.438-3.184); p < 0.001). Short implants (≤8 mm) had a higher risk of early implant failure than long implants (≥12 mm) (OR (95% CI): 2.089 (1.290-3.382); p = 0.003).

CONCLUSIONS

COVID-19 had no significant effect on early implant failure. Smoking and short implants were associated with a higher risk for early implant failures.

Predicting the Risk of Dental Implant Loss Using Deep Learning

AIM

To investigate the feasibility of predicting dental implant loss risk with deep learning (DL) based on preoperative cone-beam computed tomography.

MATERIALS AND METHODS

Six hundred and three patients who underwent implant surgery (279 high-risk patients who did and 324 low-risk patients who did not experience implant loss within 5 years) from January 2012 to January 2020 were enrolled. Three models, a logistic regression clinical model (CM) based on clinical features, a DL model based on radiography features, and an integrated model (IM) developed by combining CM with DL, were developed to predict the 5-year implant loss risk. The area under the receiver operating characteristic curve (AUC) was used to evaluate the model performance. Time to implant loss was considered for both groups, and Kaplan-Meier curves were created and compared by the log-rank test.

RESULTS

The IM exhibited the best performance in predicting implant loss risk [AUC = 0.90, 95% confidence interval (CI) 0.84-0.95], followed by the DL model (AUC = 0.87, 95% CI 0.80-0.92) and the CM (AUC = 0.72, 95% CI 0.63-0.79).

CONCLUSION

Our study offers preliminary evidence that both the DL model and IM performed well in predicting implant fate within 5 years and thus may greatly facilitate implant practitioners in assessing preoperative risks.

Ipriflavone suppresses NLRP3 inflammasome activation in host response to biomaterials and promotes early bone healing

AIM

Emerging studies have shown that immune response to biomaterial implants plays a central role in bone healing. Ipriflavone is clinically used for osteoporosis. However, the mechanism of ipriflavone in immune response to implants in early stages of osseointegration remains unclear. In this study, we aimed to investigate the potential role of ipriflavone in early bone healing process and uncover the underlying mechanism.

MATERIALS AND METHODS

We carried out histological examination as well as analysis of proinflammatory cytokines and NLRP3 inflammasome activation in a tibial implantation mouse model with intra-peritoneal injection of ipriflavone. In addition, we explored the mechanism of ipriflavone in the regulation of NLRP3 inflammasome activation in macrophages.

RESULTS

In vivo, ipriflavone ameliorated host inflammatory response related to NLRP3 inflammasome activation at implantation sites, characterized by reductions of inflammatory cell infiltration and proinflammatory cytokine interleukin-1β levels. Ipriflavone treatment also showed beneficial effects on early osseointegration. Further investigations of the molecular mechanism showed that the suppression of NLRP3 inflammasome acts upstream of NLRP3 oligomerization through abrogating the production of reactive oxygen species.

CONCLUSIONS

These results revealed an anti-inflammatory role of ipriflavone in NLRP3 inflammasome activation through improving mitochondrial function. This study provides a new strategy for the development of immune-regulated biomaterials and treatment options for NLRP3-related diseases.

Effects of Dicationic Imidazolium-Based Ionic Liquid Coatings on Oral Osseointegration of Titanium Implants: A Biocompatibility Study in Multiple Rat Demographics

Dicationic imidazolium-based ionic liquids with amino acid anions, such as IonL-phenylalanine (IonL-Phe), have been proposed as a multifunctional coating for titanium (Ti) dental implants. However, there has been no evaluation of the biocompatibility of these Ti coatings in the oral environment. This study aims to evaluate the effects of IonL-Phe on early healing and osseointegration of Ti in multiple rat demographics. IonL-Phe-coated and uncoated Ti screws were implanted into four demographic groups of rats to represent biological variations that could affect healing: young males (YMs) and females (YFs), ovariectomized (OVXFs) females, and old males (OMs). Samples underwent histopathological and histomorphometric analysis to evaluate healing at 7 and 30 days around IonL-coated and uncoated Ti. The real-time quantitative polymerase chain reaction was also conducted at the 2- and 7-day YM groups to evaluate molecular dynamics of healing while the IonL-Phe was present on the surface. IonL-coated and uncoated implants demonstrated similar histological signs of healing, while coated samples’ differential gene expression of immunological and bone markers was compared with uncoated implants at 2 and 7 days in YMs. While YMs presented suitable osseointegration for both uncoated and IonL-Phe-coated groups, decreased success rate in other demographics resulted from lack of supporting bone in YFs and poor bone quality in OVXFs and OMs. Overall, it was found that IonL-coated samples had increased bone-to-implant contact across all demographic groups. IonL-Phe coating led to successful osseointegration across all animal demographics and presented the potential to prevent failures in scenarios known to be challenged by bacteria.