Potential risk factors for early and late dental implant failure: a retrospective clinical study on 9080 implants

Patients, who received dental implants for different reasons within a defined period of 10 years (2002-2012) participated in the present study. The patients included are a subsample of all patients treated within the dental practice. Two hundred sixty-six patients, with a total of 351 implants that failed within the observation period, were analyzed retrospectively regarding the implants’ survival time and conditions. The patients’ medical records were checked for potential risk factors and, in case of further questions, the patients or their family doctors were consulted. A total of 9080 cases fitted the inclusion criteria: Homogeneity was ensured by using the same implant system (helical HiTec Tapered Self Thread implant, Hi-Tec Implants, Herzlia, Israel) inserted by the same dentists (S.H. and R.M.) in one practice. HiTec Tapered Self Thread implants are titanium implants designed with a tapered body and v-shaped threads. The apex is dome shaped and contains grooves. A hexagonal internal connection is placed within the straight head [30].

Special interest was directed toward the analysis of implant failures. Implant failure was defined in case of high implant mobility and/or pain or infection (including peri-implant radiolucency). Implants showing those signs were removed. Besides, a lost implant was defined to be an implant failure as well. The data was pseudonymized—therefore, no approval by the ethics commission was needed.

The implants were placed under aseptic conditions after professional tooth cleaning and—if necessary—periodontal treatments according to the manufacturer’s specifications (see Table 1). Before preparing the implantation site, augmentation techniques were performed depending on the patients’ characteristics. Teeth were removed and the bone was allowed to heal for 8 to 16 weeks. The protocol was performed depending on the patient’s health, clinical situation, and bone quality and quantity. The basic surgical protocol was to place implants and abutments at once (1-stage) when treating patients in the—especially maxillary—front tooth area (n = 81). A 2-staged surgery was the basic protocol for posteriorly placed implants (n = 230). Prosthetic loading was conducted according to surgical standards (hygiene, precision, soft tissue management) and after a latency of either three to 4 months in implants placed within the mandible or 4 to 6 months in implants inserted within the maxilla. After the insertion of the two-piece implants, titanium abutments with fixed partial dentures were utilized. It was taken care that static and dynamic occlusion was checked intensively.

All patients were followed up by the dentist in charge for a mean of 5.42 years (min. = 1 month, max. = 120 months, SD = 20.76 months) or until the implant failed/was removed. Patients who missed the follow-up appointments or left the practice within a period of 2 years were excluded from the study. Radiographs were taken preoperatively and directly after surgery. Clinical evaluations including soft tissue quality, healing at the implant site, implant stability, and periodontal status were conducted after 6 months. One year after surgery, radiographs were taken to evaluate bone resorption and quality. In case of adequate healing and implant stability, clinical evaluations were done every 6 months; if there was any sign of pain, infection, healing delay, or implant instability, recall intervals were shorter.

Dental implant failure (DIF) was recorded and subdivided into groups of early and late events. Early DIF was defined as high implant mobility and/or pain or infection (including peri-implant radiolucency) within a period of 6 months after implantation. Besides, a lost implant within this period was defined to be an early implant failure as well. The occurrence of pathological radiological or clinical characteristics and the loss of an implant beginning after a latency of 6 months was termed as late DIF. The patients’ gender and age as well as the implant location and geometric features (diameter and length) were collected and ranked. Furthermore, the occurrence of systemic diseases was analyzed as potential risk factors.

In addition to the calculated overall implant survival (as ratio between implants in situ and failed implants), the incidence of potential risk factors was compared between the group with early and late DIF. A differentiation between risk factors on patient level (each patient as the statistical unit with patients presenting or not presenting implant failure) and implant level was done. As the data contained nominal variables, Pearson’s chi-Square (χ²) test was performed to check the correlation between the variables. As chi-square test lacks standardization, correlative measures like Phi (Φ) contingency coefficient (four fields table) and Cramers V (≥ 4 cases) were used to demonstrate the strength of association between the groups. A value of ≥ 0.1 was defined as a low association, a value of ≥0 .3 up to < 0.5 as medium strength of association, and a value ≥ 0.5 as a strong association between the groups. Metric variables were analyzed using the binary and multivariate logistic regression analysis and categorized regarding their odds ratio (OR). The data is displayed as OR with a confidence interval (CI). The statistical analyses were performed using SPSS version 24 for Windows (IBM, Armonk, New York). A p value ≤ 0.05 was termed significant.

Within this study, 9080 dental implants were analyzed regarding their survival time. Patients who received dental implants within the defined period of time were followed up for a mean of 5.42 years (min. = 1 month, max. = 120 months, SD = 20.76 months) or until the implant failed/was removed. In total, 351/9080 implants failed among 266 patients. This corresponds to a survival rate of 96.13% (survival analysis see Fig. 1). Early dental implant failure occurred with a rate of 83.48% (n = 293), whereas late failure exhibited a 16.52% rate of occurrence (n = 58). One implant/patient was lost in 76.3% of cases (n = 203), whereas 23.7% of patients showed several implant losses.

The total study population showed a mean age of 61.5 years (min. = 21, max. = 88, SD = 20.5). Both early and late DIF occurred most in patients of 60 to 70 years (see Fig. 2). The contingency analysis could display a statistically significant correlation between patients younger and older than 60 years, and the measured event (χ² = 5.743, p = 0.017, Φ = 0.147).

Males showed a higher incidence (n = 142, 56.7%) of implant failures than females (n = 124, 43.3%) without significant differences between groups. Even if early and late DIF accumulated among male patients (male patients early DIF: n = 116, 43.61% and late DIF: n = 26, 9.77%; female patients early DIF: n = 102, 38.35%, late DIF n = 22, 8.27%), no statistically significant correlation between the patients’ gender and the measured event was seen (χ² = 0.014, p = 0.904, Φ = 0.007).

A total of 178 implants (50.7%) in 136 patients inserted in the maxilla and 173 implants (49.3%) in 130 patients inserted in the mandible failed within the observation period. Early failure of implants inserted into the mandible was seen in 118 patients (44.36%), whereas maxillary placed implants failed in 100 patients (37.59%). Late DIF occurred thrice as often in the maxilla (n = 36, 13.53% versus n = 12, 4.51% in the mandible). The contingency analysis displayed a statistically significant correlation (χ² = 13.358, p < 0.001) with a medium strength of association (Φ = 0.224).

Implants located in the frontal area (central incisor to canine) failed in 92 patients (34.59%), implants inserted in the posterior area of the jaw (1st premolar to 2nd molar) in 174 patients (65.41%). Early DIF occurred more often in patients with posteriorly placed implants with a frequency of 52.63% (n = 140) in comparison to implants located in the front tooth area (n = 78, 29.32%). In accordance, late DIF was more frequent in patients with posteriorly placed implants (front: n = 14, 5.26% and posterior: n = 34, 12.78%). Here, the contingency analysis displayed no statistically significant correlation (χ² = 6.635, p = 0.383, Φ = 0.053) between the groups.

A total of 9080 implants were inserted during the observation period. Ten percent (n = 908) had a length of 8 mm and smaller, 53% measured 10 mm (n = 4812), 35% 1.5 mm (n = 3178), and 2% of implants showed lengths of 13 mm and larger (n = 182). In general, an accumulation of DIF could be observed for implants measuring 10 mm in length (failed ratio: n = 185, 52.7%; total ratio: 31/4812), and 3.75 mm in diameter (failed ratio: n = 132, 37.6%; total ratio: 132/3360). Two thousand five hundred forty-two implants of 3.3 mm in diameter were inserted during the observation period (28%). Implants of 3.75 mm were inserted more frequently (n = 3360, 37%) than implants of 4.2 mm (n = 2270, 25%) and lager (n = 908, 10%). Early DIF occurred more often in implants measuring 10 mm (n = 134, 38.2%) in comparison to both, smaller and larger implants. Furthermore, a high frequency of late dental implant failure could be recorded in implants of both, 10 mm (n = 51, 14.5%) and 11.5 mm (n = 47, 13.4%) in length (see Fig. 3). The contingency analysis showed a statistically significant correlation (χ² = 13.554, p = 0.004) and a medium strength of association (Cramers V = 0.197) between implant length and dental implant failure. In contrast, groups of different diameters displayed no significant correlation (χ² = 2.510, p = 0.474, Cramers V = 0.085) with a greater incidence of early events in implants of smaller diameter (3.3 mm: n = 72, 20.5%; 3.5 mm: n = 88, 25.1%; 4.2 mm: n = 62, 17.7%) and a maximum frequency of late losses in implants of 3.75 mm (n = 44, 12.5%) (see Fig. 4).

A logistic regression analysis was performed to ascertain the effects of the variables analyzed within this study on early and late DIF. First, a binary logistic regression analysis was performed for the independent variables (see Table 2); thereafter, a multivariate logistic regression analysis was needed to ascertain the effects of each factor (see Table 3). The model for patients related factors (gender, age, jaw, CVD, diabetes mellitus) correctly classified 83.5% of cases with Nagelkerkes’ R² of 0.111, which corresponds to a moderate explanatory power [31]. Analyzing the patient’s gender and age, the regression analysis did not show different probabilities for early or late events between the groups. Maxillary implants showed a reduced likelihood (OR = 0.260; p ˂ 0.001; CI, 0.135–0.501) for early DIF, whereas they were 3.849 times as much as likely to exhibit a late event (OR = 3.849; p ˂ 0.001; CI, 1.995–7.425) compared to implants placed in the mandible. Furthermore, the probabilities for early and late events did not differ between implants located within the anterior or posterior area of the jaw. Neither for diabetes nor for CVD associations with early and late DIF could be seen when comparing to healthy patients. The model for implant-related factors (length, diameter) correctly classified 63.5% of cases with Nagelkerkes’ R² of 0.010, which corresponds to a low explanatory power. Implants of different lengths or diameter could not be associated with an increased likelihood of either early or late DIF.