Dental implants have become a preferred treatment option over the last several decades because of the reduced psychological trauma and the high functional and esthetic treatment outcome when compared to conventional restorative treatments (1, 2). The reported success rates of dental implants range from 96.7% to 97.5% for single implants and 92.5% to 93.6% for fixed partial restorations over a period of 6 to 7 years (3). Although the use of osseointegrated dental implants have become a predictable treatment option, complications leading to implant loss may still occur during loading and maintenance (4). Factors that affect implant survival are diverse and have been associated with patient’s risk factors such as smoking, periodontal disease, periodontal pathogenic bacteria, bone density, systemic diseases and bone atrophy as well as implant micro- and macrostructure and surgical techniques (5, 6).
Implant failures can be divided into early and late based on the time of the failure (4). Early implant failure is usually detected within the first 3-6 months and is characterized by poor osseointegration. Late failure may occur after the implant is osseointegrated and is characterized by inadequate preservation of the bone support. Failed implants are characterized by radiolucency around the entire circumference of the implant with lack of implant-to-bone contact and mobility, while failing implants demonstrate slow and continuous marginal bone loss with absence of clinical mobility (4). Implant failure is a significant concern for patients, implant surgeons and insurance companies and further investigation is required to identify potential factors of implant failure.
The frequency of implant failure and peri-implantitis has been reported in 5% of all placed implants (7). In patients with failed implants, replacement with a new implant is sometimes the only available treatment option for fixed or removable rehabilitation. However, the outcome of implants placed in previously failed implant sites is still unclear (8, 9). In a systematic review of the literature, the survival and success rates of implant placement in previously failed implant sites ranged between 71% and 100% (10). It is of paramount importance to determine the etiology and identify potential factors of implant failure and minimize its occurrence.
Understanding potential risk factors of implant failure prior to the initiation of the treatment may foster long-term implant survival, peri-implant tissue health and implant supported prosthesis survival. It is critical to recognize the risk of implant loss and therefore treatment plan accordingly. Research has revealed that social and environmental parameters play a critical role in general health and health outcomes (11). Seeking health care is also closely related to health insurance status which subsequently affects the treatment outcome (12, 13). In dentistry, it has been demonstrated that individuals with a lower socio-economic status exhibit an increased risk for oral diseases rather than in those with a higher socio-economic status (14). Low socio-economic status and lack of dental insurance are associated with increased dental treatment needs due to lack of oral health knowledge, poor access to dental care or poor oral hygiene habits (14, 15). Moreover, in implant dentistry, infrequent dental care or poor oral hygiene following an implant treatment may affect the long-term treatment outcome. Patient’s socio-economic status and dental insurance have not been examined in the literature as potential risk factors of implant failure. Therefore, the aim of this retrospective case-control study was to examine any potential association between socio-economic status, medical history, tobacco status and dental insurance of patients that experienced implant failure and those who had a successful implant treatment.
MATERIAL AND METHODS
Data for this retrospective case-control study were obtained from the electronic records at the University of Minnesota School of Dentistry for treatment provided between 2010 and 2016 to patients attending the dental clinics. The study was approved by the Institutional Review Board of the University of Minnesota School of Dentistry for medical record chart review. Dental records of patients who had implant placement and implant removal in the dental school were retrieved from the electronic database of the School of Dentistry and were matched for age and gender to reduce any risk of selection bias. Patients had to be at least 18 years of age with complete demographic characteristics and insurance status as well as completely answering the medical history questionnaire. Patient’s chart number, age at the time of the procedure, gender, presence/absence of dental insurance, medical history, tobacco use, ZIP code and type of treatment provided were all included in a datasheet.
The examined systemic medical conditions consisted of self-reported high blood pressure, heart attack, high cholesterol, asthma, diabetes, thyroid disorder, kidney disorder, arthritis, artificial joint, osteoporosis, depression, anxiety, cancer and cancer treatment. Medical history, gender, tobacco use and dental insurance were included as binary parameters. Age at the time of the procedure was included in the analysis as a continuous parameter, while patients were also divided into four sub-study groups in the implant success and the implant failure study groups based on the percentiles of age with <54 years (under the 25th percentile), 54-60 years (25th to 50th percentile), 61-67 years (50th to 75th percentile) or ≥68 years of age (75th percentile and above). Implant location was categorized into arch (maxilla/mandible) and region (anterior/posterior).
Patient ZIP codes were utilized in the study to assess socio-economic status based on the 2010-2014 American Community Survey 5-year estimates of the U.S. Census Bureau. This survey reported that the mean annual household income was estimated to be $90,488.46. Each included patient was classified based on percentiles of income with a low (under the 25th percentile), low to moderate (25th to 50th percentile), moderate to high (50th to 75th percentile) or high socio-economic status (75th percentile and above) if the mean annual household income of the ZIP code where he/she lived was below $68,707, between $68,708 and $85,598, between $85,599 and $103,788 or above $103,789, respectively.
Type of treatment
The type of treatment provided was identified based on the ADA codes: D6010 (surgical placement, endosteal implant) and D6100 (implant removal-failure). All included implants were surgically placed or removed by faculty or residents in the Division of Periodontology, Oral and Maxillofacial surgery, Prosthodontics and Endodontics at the University of Minnesota School of Dentistry. All patients that had implant removal (n=186) were included in the analysis, while patients with a successful implant treatment (n=186) were randomly selected to serve as control.
An inherent problem in retrospective case-control studies is the selection of a comparable control group. The aim is to select individuals with similar distribution of exposure status. The control group in the present study was randomly selected from the same population and was matched for age and gender due to minimize the potential risk of selection bias due to the presence of confounding factors. The data from the included dental charts were collected and recorded in a computer database and analyzed utilizing a statistical program. Descriptive statistics including frequencies, means and standard deviations were calculated for patients’ characteristics. Chi-square tests were performed to assess implant location (arch, region), prevalence of medical conditions, insurance status and socio-economic status in regards to the dependent variable (implant removal). The odds ratios and corresponding p-values for the sample were analyzed by logistic regression analysis. All tests of significance were evaluated at the 0.05 error level with a statistical software program (SPSS v.21.0, IBM, Armonk, NY, USA).
A total of 186 dental records of implant removal were identified in the electronic database of the University of Minnesota School of Dentistry and included in the test group. Records of successful implants placed by residents or faculty members of the University of Minnesota School of Dentistry were initially screened for eligibility based on the inclusion and exclusion criteria of the study and 186 age and gender matched records were randomly selected and included in the control group. Therefore, a total of 372 records of dental implants were included in the final analysis to determine whether dental insurance, socio-economic status, tobacco use and medical conditions are associated with implant failure. The mean age of the included 372 patients was 61.26±11.02 with 23.7% of the population being <54 years of age, 22.8% 54-60 years, 26.6% between 61 and 67 years and 26.9%% ≥68 years. The included population consisted of 52.4% males and 47.6% females.
Insurance status, socio-economic status and tobacco use of the total population and comparison between patients with implant failure and successful implants are shown in Table 1. In regards to the socio-economic status, 26.9% were classified as low, 23.7% as low to moderate, 24.5% as moderate to high and 25.0% as high socio-economic status. The socio-economic status reached the significance level (chi-square test, p=0.021) demonstrating that individuals with high a socio-economic status (≥$103,789) when compared to those with a low socio-economic status are more likely to have a successful implant treatment and less risk of implant removal. Individuals with a low socio-economic status had an odds ratio of 0.469 (logistic regression analysis, 95% CI: 0.237-0.929, p=0.030) for having a successful implant.
* Statistical significant difference between study groups with p-value≤0.05. For dental insurance, socio-economic status, tobacco use, implant location (region and arch), chi-square test was used. Bold values represent statistically significant differences.
With respect to insurance, 48.9% of the population had dental insurance, while 51.1% had no dental insurance. In regards to the treatment outcome, insurance status did not show any significant differences (chi-square test, p=0.300) and both groups (presence or absence of insurance) showed similar treatment outcome. Tobacco use was self-reported by 9.7% of the patients, whereas the majority of the population (90.3%) indicated they did not use tobacco. The majority of the included tobacco users (75%) had implant failure and this was found to be statistically significantly (chi-square test, p=0.002) different compared to individuals who did not use tobacco (47.3%). Tobacco users exhibited a statistically significant (logistic regression analysis, p=0.013) odds ratio of 3.710 (95% CI: 1.319-10.440) of having implant failure. Approximately three quarters of the included implants (78.2%) were in the posterior region and 59.7% in the maxilla, but implant location did not affect significantly the risk of implant failure for region (chi-square test, p=0.102) and for arch (chi-square test, p=0.398).
Prevalence of systemic conditions in the total population and between patients that had an implant failure and a successful implant treatment is shown in Table 2. High blood pressure (29.6%), high cholesterol (24.7%), arthritis (25.3%) and depression (14.0%) were the most commonly self-reported medical diseases. Heart attack (chi-square test, p=0.029) showed statistically significant association with the treatment outcome. In particular, individuals with heart attack were more likely to have a successful implant treatment (78.9%) as compared to individuals with no history of heart attack (48.9%) (chi-square test, p=0.029). None of the other examined systemic disease parameters evaluated were found to be significantly associated with the treatment outcome.
* Statistical significance between study groups with p-value≤0.05. Bold value represents statistically significant differences obtained from chi-square test.
Identification of patient characteristics influencing treatment outcomes may provide valuable information in order to distinguish patients at risk of implant failure from patients with successful treatment response. Recognizing patient-level variables that affects treatment outcomes has the potential to enhance clinical reasoning (16). In this study, we aimed to identify socio-economic parameters, insurance status, medical conditions and history of tobacco use that would have the potential to demonstrate treatment effect modification. We found that individuals with high socio-economic status, tobacco non-users and patients with a history of heart attack were significantly more likely to have a successful implant than those with a low socio-economic status, tobacco users and with no history of heart attack.
In the decision-making process, clinicians may be influenced by characteristics of patients such as age, gender, education level, personality and socio-economic status (17). Socio-economic status was a statistically significant predictor of implant failure and removal. In the present study, individuals with a lower socio-economic status demonstrated a higher risk of experiencing implant failure that led to implant failure. It is noteworthy that individuals of a lower socioeconomic status showed poorer health outcomes as a result of less available resources and the limited access to health care (18). The potential difficulties in attending hygiene appointments or having a comprehensive periodontal examination may explain this finding. An association between socio-economic status and oral health behaviors for tooth brushing ≥3 times/day has been reported in the literature with individuals of high income and education level presenting with odds ratios of 1.264 and 2.686, respectively (19). Less optimal oral hygiene habits may also justify our results. In the present investigation, information about patients’ education level was not available due to the retrospective design of the study. The School of Dentistry at the University of Minnesota does not require information on the level of education received as part of their admission of patients. The effect of socio-economic status in the present study was solely evaluated by neighborhood-level measures that have often been used in the literature (20). We utilized a patient’s zip code as a surrogate measure to determine individual socio-economic status, which has been validated in the past by other epidemiological investigations (21, 22). In the present study, patients with dental insurance exhibited similar implant treatment outcomes when compared to uninsured patients. The presence of dental insurance did not affect the survival of the implants as it was initial hypothesized. This finding may be attributed to the low cost of prophylactic treatments and annual recall appointments which are not deterrent to uninsured patients especially in university dental clinics. Uninsured patients may also be financially capable of paying out of pocket for their dental care as well as following the post-treatment instructions regardless of the presence of dental insurance. To the best of the authors knowledge, this is the first study that has evaluated the effect of insurance status on the outcome of implant treatment.
In the current study, no difference in the survival rate in regards to the implant region and arch could be detected which is in agreement with another retrospective study by Eckert and colleagues who showed that location of implants did not have any effect on implant survival, implant fracture rates, screw loosening or screw fracture (23). Dental implants placed in the maxilla have been associated with a three times higher rate of failures than in the mandible (4). Other reports demonstrated that the posterior maxillary region exhibits the lowest success rate (91.4%) when compared to the anterior maxillary region (97%), posterior mandible (96.3%) and anterior mandible (97.9%) (24).
Underlying systemic diseases may influence implant failure and the risk of peri-implantitis (25). The authors hypothesized that individuals with certain systemic diseases/conditions and tobacco use would be more prone to have implant failure when compared to systemically healthy controls. Systemic conditions that have been associated with implant-related complications include cardiovascular diseases, thyroid disorders, diabetes, hepatitis, HIV, Crohn’s disease, osteoporosis as well as tobacco use (25, 26). However, the degree of severity of a specific disease may be more important than the nature of the systemic disorder. In the present investigation, diabetes was not related to implant failure which may possibly be associated with controlled glycemic levels. Individuals with a history of heart attack were statistically significantly more likely to have a successful implant treatment compared to those without heart attack. This may be attributed to the general lifestyle shifts of patients who underwent heart attack which includes adoption of healthier social habits than prior to the heart attack. Patients may have been recommended by their cardiologists and general medical practitioners to receive dental treatment regularly in order to eliminate any potential risk of general infection. Similar complications and failures of dental implants between medically compromised patients and healthy individuals were reported in a systematic review of the literature revealing the need for larger studies (27). In the current study, tobacco users were 3.710 times more likely to have an implant failure when compared to non-smokers. Smoking is considered one of the major risk factors that impacts the long-term survival of dental implants (25). The association between smoking habits and implant survival has been attributed mainly to its effect on osteogenesis and angiogenesis as well as to behavioral parameters such as smokers’ less optimal oral health, infrequent dental visits and less favorable oral hygiene habits (28-31).
Implant failures in dentistry can be attributed to a variety of conditions or situations. These include loss of osseointegration, poor treatment planning and/or poor surgical experience that lead to positional failure, soft tissue defects and biomechanical failures that include a variety of incidences that range from screw loosening to implant or implant component fracture (32). Due to the retrospective design of the study, data on patients’ oral hygiene habits and plaque control were not available for the analysis. This is a limitation of the study due to the detrimental effect of poor oral hygiene on peri-implant tissue health and implant survival (33, 34). The aftermath of implant removal leads to further cost and additional procedures for the patient as well as a clinician’s frustration. Therefore, appropriate patient selection and proper treatment planning may result in successful long-term dental implants with functional and esthetic implant supported restorations. The identification of parameters that may lead to implant failure is of paramount importance for both clinicians and patients.
Within the limitation of this retrospective case-control study, individuals with high socio-economic status, no history of tobacco use and history of heart attack were more likely to have a successful implant treatment than those with a low socio-economic status, tobacco users and without a history of heart attack. The results of the present study provide valuable information for dental professionals about patient selection for successful implant treatment, but there is lack of evidence to suggest that medical history is associated with implant treatment outcome. Further prospective large scale studies should assess the effect of insurance status, socio-economic status, medical history and tobacco use on the risk of implant failure.