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Dental Theses Penn Dental Medicine

Spring 6-17-2021

INCIDENCE OF DENTAL IMPLANT FAILURE IN ACADEMIC INCIDENCE OF DENTAL IMPLANT FAILURE IN ACADEMIC

SETTING - A CLINICAL RETROSPECTIVE STUDY PART ONE: SETTING - A CLINICAL RETROSPECTIVE STUDY PART ONE:

PATIENT LEVEL PATIENT LEVEL

Reza Hakim Shoushtari University of Pennsylvania, hakimh@upenn.edu

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Recommended Citation Recommended Citation Hakim Shoushtari, Reza, "INCIDENCE OF DENTAL IMPLANT FAILURE IN ACADEMIC SETTING - A CLINICAL RETROSPECTIVE STUDY PART ONE: PATIENT LEVEL" (2021). Dental Theses. 58. https://repository.upenn.edu/dental_theses/58

Retrospective, Case Control study

This paper is posted at ScholarlyCommons. https://repository.upenn.edu/dental_theses/58 For more information, please contact repository@pobox.upenn.edu.

INCIDENCE OF DENTAL IMPLANT FAILURE IN ACADEMIC SETTING - A CLINICAL INCIDENCE OF DENTAL IMPLANT FAILURE IN ACADEMIC SETTING - A CLINICAL RETROSPECTIVE STUDY PART ONE: PATIENT LEVEL RETROSPECTIVE STUDY PART ONE: PATIENT LEVEL

Abstract Abstract Aim:Aim: The aim of this retrospective study was to determine the implant failure rate and associated factors in the academic setting by using electronic health records (Axium) and hard copies of patients who received dental implants at in Penn Dental Medicine (PDM) and at Penn Dental Faculty Ppractices (PDFP) ofat the University of Pennsylvania from 06/01/2016 to 08/31/20192020. In addition, evaluation of electronic health records and hard copies were reviewed for patients who had implants removed due to bone loss or lack of osseointegration atin PDM and Faculty practicesPDFP of the University of Pennsylvania from 06/01/2016 to 02/29/2020. Secondary objective was to investigate the co-contributing factors for implant failure at the patient level.

Method and Material:Method and Material: Electronic health records and hard copies of patients who had implants placed and removed due to bone loss or lack of osseointegration atin PDM and Faculty practicesPDFP of the University of Pennsylvania from 06/01/2016 to 02/29/2020 were analyzed.

Results:Results: Data was evaluated at patient count and implant count for this retrospective study. 1609 patients received implants. 883 patients had implant placement at PDM and 726 patients had implant placement at PDFP. Of the total patients, 3180 implants were placed during the study period. 2162 implants were placed at PDM and 1018 implants were placed at PDFP. The total patient failure rate was 4.97% and the failure rate was of 6.0% and 3.7% for PDM and PDFP, respectively. The total implant failure rate was 3.49% and the implant failure rate was 3.7% and 3% for PDM and PDFP, respectively.

Based on the chi-square test results, patients with bisphosphonate IV+PO (12%, P-value=0.004) were significantly overrepresented in the failure group. In contrast, patients with no bisphosphonate use (4.60%, P-value=0.004) were significantly underrepresented in the failure group.

No overrepresentation (or underrepresentation) of patients with different gender, different age group, diabetes mellitus, history of periodontal disease, current smoking status, penicillin allergy, and recall were noted amongst failures.

Based on the chi-square test, implants for bisphosphonate IV variable (11.5%, P-value=0.025) were significantly overrepresented in the failure group. In contrast, implants for no bisphosphonate use (3.20%, P-value<0.001) were significantly underrepresented in the failure group. No overrepresentation (or underrepresentation) of implants for different gender, different age group, diabetes mellitus, history of periodontal disease, current smoking status, penicillin allergy, and recall was noted amongst failures.

Based on the multivariate conditional logistic regression, estimated odds of implant failure in participants with multiple implants were about three times than the participants with single implant (Adj OR=2.99, P-value=0.002); estimated odds of implant failure for bisphosphonate use of IV and PO was about four times that of the participants with no bisphosphonate use (Adj. OR=4.09, P-value=0.003). Diabetes and history of failed implants did not show any significant association with implant failure (with P-values>0.05).

Conclusion:Conclusion: This study concluded that bisphosphonate use and patients with multiple implants were shown to have a significant contribution to implant failure. There was no difference in the failure rate of patients with different gender, different age group, diabetes mellitus, history of periodontal disease, current smoking status, penicillin allergy, and recallamongst failures. It is important to note that due to limitations and the retrospective nature of this study, only the co-contributing factors were evaluated and not the etiology of the implant failure. To further investigate the etiology, randomized clinical trial should

be conducted.

Degree Type Degree Type Thesis

Degree Name Degree Name MSOB (Master of Science in Oral Biology)

Primary Advisor Primary Advisor Dr. Jonathan Korostoff

Keywords Keywords Retrospective, Implant, Failure, Academic, Control, PDM

Subject Categories Subject Categories Dentistry

Comments Comments Retrospective, Case Control study

This thesis is available at ScholarlyCommons: https://repository.upenn.edu/dental_theses/58

INCIDENCE OF DENTAL IMPLANT FAILURE IN ACADEMIC SETTING - A CLINICAL

RETROSPECTIVE STUDY

PART ONE: PATIENT LEVEL

BY

REZA HAKIM SHOUSHTARI, DMD

A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF

PENNSYLANIA FOR THE DEGREE OF MASTER OF SCIENCE IN ORAL BIOLOGY.

ACKNOWLEDGEMENTS

I would like to thank my beautiful wife and to my wonderful parents for their love and support

during my academic accomplishments and to dedicate this thesis to them

I would like to thank my committee members, Dr. Korostoff, Dr. Fiorellini, Dr. Wang, and Dr.

Gogarnoiu for their help with this project.

I would like to thank all of my other faculties, co-residents, and Penn Periodontics staff, who

were part of my educational journey.

List of Abbreviations

PDM Penn Dental Medicine

PDFP Penn Dental Faculty Practice

OR Odds Ratio

Adj OR Adjusted Odds Ratio

Cl Confidence Interval

IV Intravenous

PO Per Os- Through the mouth

MRONJ Medication Related Osteonecrosis of the Jaw

RANKL Receptor activator of nuclear factor kappa-Β ligand

ADA American Dental Association

SPSS/IBM Software platform for advanced statistical analysis

Abstract

Aim: The aim of this retrospective study was to determine the implant failure rate and associated

factors in the academic setting by using electronic health records (Axium) and hard copies of

patients who received dental implants at Penn Dental Medicine (PDM) and at Penn Dental Faculty

Practice (PDFP) of the University of Pennsylvania from 06/01/2016 to 08/31/2019. In addition,

evaluation of electronic health records and hard copies were reviewed for patients who had

implants removed due to bone loss or lack of osseointegration at PDM and PDFP of the University

of Pennsylvania from 06/01/2016 to 02/29/2020. Secondary objective was to investigate the co-

contributing factors for implant failure at the patient level.

Method and Material: Electronic health records and hard copies of patients who had implants

placed and removed due to bone loss or lack of osseointegration at PDM and PDFP of the

University of Pennsylvania from 06/01/2016 to 02/29/2020 were analyzed.

Results: Data was evaluated at patient count and implant count for this retrospective study. 1609

patients received implants. 883 patients had implant placement at PDM and 726 patients had

implant placement at PDFP. Of the total patients, 3180 implants were placed during the study

period. 2162 implants were placed at PDM and 1018 implants were placed at PDFP. The total

patient failure rate was 4.97% and the failure rate was of 6.0% and 3.7% for PDM and PDFP,

respectively. The total implant failure rate was 3.49% and the implant failure rate was 3.7% and

3% for PDM and PDFP, respectively.

Based on the chi-square test results, patients with bisphosphonate IV+PO (12%, P-value=0.004)

were significantly overrepresented in the failure group. In contrast, patients with no

bisphosphonate use (4.60%, P-value=0.004) were significantly underrepresented in the failure

group.

No overrepresentation (or underrepresentation) of patients with different gender, different age

group, diabetes mellitus, history of periodontal disease, current smoking status, penicillin allergy,

and recall were noted amongst failures.

Based on the chi-square test, implants for bisphosphonate IV variable (11.5%, P-value=0.025)

were significantly overrepresented in the failure group. In contrast, implants for no bisphosphonate

use (3.20%, P-value<0.001) were significantly underrepresented in the failure group. No

overrepresentation (or underrepresentation) of implants for different gender, different age group,

diabetes mellitus, history of periodontal disease, current smoking status, penicillin allergy, and

recall was noted amongst failures.

Based on the multivariate conditional logistic regression, estimated odds of implant failure in

participants with multiple implants were about three times than the participants with single implant

(Adj OR=2.99, P-value=0.002); estimated odds of implant failure for bisphosphonate use of IV

and PO was about four times that of the participants with no bisphosphonate use (Adj. OR=4.09,

P-value=0.003). Diabetes and history of failed implants did not show any significant association

with implant failure (with P-values>0.05).

Conclusion: This study concluded that bisphosphonate use and patients with multiple implants

were shown to have a significant contribution to implant failure. There was no difference in the

failure rate of patients with different gender, different age group, diabetes mellitus, history of

periodontal disease, current smoking status, penicillin allergy, and recall amongst failures. It is

important to note that due to limitations and the retrospective nature of this study, only the co-

contributing factors were evaluated and not the etiology of the implant failure. To further

investigate the etiology, randomized clinical trial should be conducted.

Introduction

The discovery of osseointegration has had a huge impact on implant dentistry for the last 50 years.

This began with Branemark defining osseointegration as a “direct structural and functional contact

between ordered, living bone and the surface of a load-carrying implant”. 1 Furthermore, he

experimented with more than 50 different types of implants and introduced the threaded design of

dental implant to the dental community in the early 1980s and still, this design is widely used to

this day.

According to literature, dental implants have been expanded over the last decade as a valid

replacement of missing teeth. Implant survival rates has been reported in the literature as 91.6%.

1-7

However, not all implants are without failure. Implant failure can be classified as early or late

failure. Early failure is defined when osseointergration has not been established and late failure is

when the established osseointegration is breaking down. Biological, microbiological, and

biomechanical factors can contribute to implant loss; however, the mechanism of early implant

failure is still unclear. 8 However, according to 2017 Workshop, late implant failure is mainly

associated with peri-implantitis, which is characterized by progressive bone loss of supporting

bone. 31

According to Moraschini (20015), osseointegrated implants present high survival rates with

minimal marginal bone resorption in the long term. 9 However, there is strong evidence that there

is an increased risk of developing peri-implantitis in patients with history of periodontitis, poor

oral hygiene, and no regular maintenance. 10,11 Ong et al. (2008) concluded in a literature review

that patients treated for periodontitis may experience more implant loss and complications around

implants than non-periodontitis patients. 12 Moreover, Karoussis et al. (2007) reported that a

history of chronic periodontitis was associated with significantly greater long-term probing depth,

peri-implant marginal bone loss, and peri-implantitis. 13 Furthermore, Baelum and Ellegaard

(2007) concluded 5-year survival rate of implants placed in patients with a history of periodontitis

was similar to that of patients without periodontitis. 14 Heitz-Mayfield (2008) found substantial

evidence that poor oral hygiene, history of periodontitis, and cigarettes smoking were associated

with peri-implantitis, but more studies were needed to confirm these as true factors.15 According

to the most recent studies, there is no conclusive evidence that smoking, diabetes, lack of

keratinized mucosa, excess cement, genetic factors, systemic conditions, occlusal overload, bone

compression, overheating, micro-motion, and biocorosion are risk factors for peri-implantitis.

However, a meta-analysis reported that smokers had a greater risk of implant failure (implant-

related odds ratio [OR] of 2.25) when compared to nonsmokers.16 Biological factors may be

associated with implant failures in smokers such as vasoconstrictive effect of nicotine, impaired

and delayed wound healing, and cytotoxic effect on fibroblasts and other regenerative cells.17, 18

In diabetic patients, a glycemic control is an essential variable in providing the optimal periodontal

and implant treatment. Many studies showed that poor glycemic control has negative impact on

the outcome of the therapy, but more studies are needed to provide a definitive conclusion. 19 In

systematic literature review by Javed (2009), osseointegration can be achieved in patients with

well controlled diabetes.20

In addition to systemic disease, there have been studies that show that medications may have

negative impact on implant survival. According to American Association of Oral and Maxillofacial

Surgeons, bisphosphonate can cause Medication Related Osteonecrosis of the Jaw (MRONJ) and

is usually prescribed for patients with osteoporosis, osteopenia, and cancer.21 In a survey study of

more than 13,000 Kaiser permanent members who were exposed to long term oral bisphosphonates

due to osteoporosis, the prevalence of MRONJ was reported to be 0.1% (10 cases per 10,000).

This number was increased to 0.21% (21 cases per 10,000) in patients receiving oral

bisphosphonate longer than 4 years.22 Another report by Malden and Lopes (2012) from 11 cases

of MRONJ reported in 90,000 patients in southeast Scotland, they reported an incidence of 0.004%

(0.4 cases per 10,000 patient-years of exposure to Alendronate).23 Furthermore, with regards to

MRONJ risk in patients with osteoporosis exposed to IV bisphosphonate or RANKL inhibitors, a

study evaluated patients exposed to yearly Zoledronate for 3 years with the risk for MRONJ of

0.017% (1.7 cases per 10,000 patients). 24 Based on current data, the risk of MRONJ in patients

with osteoporosis who are taking oral or IV bisphosphonates still exists, yet remains very low. 21

With all the limitation regarding the use of oral and IV bisphosphonate, some studies show

bisphosphonates do not reduce the dental implant success rate. 25 In addition, patients with

penicillin allergy have shown a higher risk of implant failure when compared to non-allergic

patients with a risk ratio of 3.84 (95% CI). Patients prescribed clindamycin due to penicillin allergy

had four times earlier implant failure; however, other variables such as location, brand, and

surgeon’s experience could have influenced the results. 26 Another limited evidence in literature

that needs to be investigated is the effect of age and gender on short and long implant survival rate.

Another factor that may influence implant survival is the implant site, position, and bone quality.

Implant treatments require careful planning to achieve prosthetically driven implant surgery.

Furthermore, implant sites may be treated differently due to horizontal and vertical changes after

extraction.27 According to Cochran and Becker et al. (1999), maxillary implants showed lower

survival rate than mandibular implants.28, 29

In addition to anatomical limitations, experience may play a role in early implant failure.

According to Lambert (1997), implants placed by inexperienced resident surgeons failed twice

compared to the ones placed by more experienced resident surgeons with the failure rate being

5.9% for the inexperienced residents and 2.4% for the more experienced residents. The main

difference was noted in the first nine cases but after these nine cases, the failure rate decreased

significantly.30

Furthermore, literature shows that the early failure of implants with bone graft and healing

abutments at the same time (1.1%) was significantly higher than that of the implants with bone

graft and healing abutments separately (0.5%, P=0.039).32 Due to limitations and lack of evidence,

this retrospective study can provide a better understanding of the effect of co-existing factors in

implant survival rates.

The aim of this retrospective study was to determine the implant failure rate and associated factors

in the academic setting by using electronic health records (AxiUm) and hard copies of patients

who received dental implants at Penn Dental Medicine (PDM) and at Penn Dental Faculty Practice

(PDFP) of the University of Pennsylvania from 06/01/2016 to 08/31/2019. Electronic health

records and hard copies of patients who had implants removed due to bone loss or lack of

osseointegration at PDM and PDFP of the University of Pennsylvania from 06/01/2016 to

02/29/2020 were searched and analyzed.

As the primary objective of this study, the failed implants were identified and categorized.

As the secondary objective, data was categorized as patient level and implant level. Patient level

included the patient’s past medical history (diabetes, history of bisphosphonates, smoking, and

penicillin allergy), patient’s age, gender, history of periodontal disease, and implant follow up;

The implant level included implant site, width, length, diameter, manufacturer, surface

characteristics, immediate implant, implants placed in grafted or non-grafted sites, and the

prosthesis type (fixed/removable). The tertiary objective of this study was to assess whether

experience played a role in implant survival rate.

Materials and Methods

This study obtained approval from the institutional review Board of the University of

Pennsylvania. The search involved electronic health records from AxiUm data base software and

hard copies of qualifying patients from PDM and PDFP. Study was conducted by two examiners

(R.H and O.M). Electronic health records and hard copies were searched and analyzed for patients

who received dental implants at PDM and PDFP from 06/01/2016 to 08/31/2019 as well as patients

who had implants removed due to bone loss or lack of osteointegration in both PDM and PDFP

from 06/01/2016 to 02/29/2020. Implant placement (ADA Code D6010) and implant removal

(ADA Code D6100) were checked for the same site in each of these patients. Implant placement

and failure were confirmed by existence of implant checklist and hard copies, ADA code, and

clinical note. Dates of implant placement and removal were documented.

Additional data was extracted from the records for both patient level and implant level. Data was

categorized as implant count and patient count for both PDM and PDFP for patient level and

implant level with timeline A- from 06/01/2016 to 08/31/2019 and timeline B- from 06/01/2016

to 02/29/2020.

With regard to “Implant Count” the following categories were identified for patient level

analysis:

1- Implant placement and implant removal

1-1-Total number of implants placed (D6010) during time line A.

1-2-Total number of implants placed during time line A and removed (D6100) during time line B.

The implants in this category should have had codes D6100 in addition to code D6010 during the

dates mentioned above.

1-3- The number of implants placed (D6010) during time line A in each of the following

categories: female, male, age (18-30 y/o), age (31-50 y/o), age (51-70 y/o), age (70<), diabetes,

smoking, bisphosphonate (IV, oral), and penicillin allergy.

1-4- The number of implants removed (D6100) during time line B in each of the following

categories: female, male, age (18-30 y/o), age (31-50 y/o), age (51-70 y/o), age (70<), diabetes,

smoking, bisphosphonate (IV, oral), and penicillin allergy.

2- Periodontal Disease and follow ups/Periodontal Maintenance

2-1 Total number of implants placed (D6010) during time line A, in patients with history of

periodontal disease (codes D499T2, D499T3, D499T4, D4999.1) within no specific time line

(since the beginning of becoming a patient at PDM).

2-1-1 Total number of implants in category 2-1, in the above patients who have been

coming for their periodontal maintenance (any of the following codes D110, D4910,

D4910.2, D4910.3, D4910.4) during time line B. Furthermore, the number of times these

codes (D110, D4910, D4910.2, D4910.3, D4910.4) were completed was considered to

determine whether the patients were coming for regular maintenance and follow ups or not.

2-2 Total number of implants placed (D6010) during time line A and the implant removed (D6100)

during time line B, in patients who also have a history of periodontal disease (codes D499T2,

D499T3, D499T4, D4999.1) within no specific time line (since the beginning of becoming a

patient at PDM).

2-2-2 Total number of implants in category 2-2, in the above patients who also have been

coming for their periodontal maintenance (any of the following codes D110, D4910,

D4910.2, D4910.3, D4910.4) during time line B. Furthermore, the number of times these

codes (D110, D4910, D4910.2, D4910.3, D4910.4) were completed was considered to

determine whether the patients were coming for regular maintenance and follow ups or not.

3- Recall

3-1 Total number of implants placed (D6010) during time line A and the history of recalls (codes

D110, D4910, D4910.2, D4910.3, D4910.4) during time line B. As well as the number of the times

these codes (D110, D4910, D4910.2, D4910.3, D4910.4) were completed to determine whether

the patients were coming for regular maintenance and follow ups or not.

3-2 Total number of implants received (D6010) during time line A and the implant removed

(D6100) during timeline B, and the history of recalls (codes D110, D4910, D4910.2, D4910.3,

D4910.4) during time line B. Furthermore, the number of the times these codes (D110, D4910,

D4910.2, D4910.3, D4910.4) were completed was considered to determine whether the patients

were coming for regular maintenance and follow ups or not.

With regard to “patient Count” the following categories were identified for patient level analysis:

1- Implant placement and implant removal

1-1-Total number of patients who had implants placed (D6010) during time line A.

1-2-Total number of patients who had implants placed during time line A and removed (D6100)

during time line B. The patients in this category should have had codes D6100 in addition to code

D6010 during the dates mentioned above.

1-3- The number of patients who received implants (D6010) during time line A in each of the

following categories: female, male, age (18-30 y/o), age (31-50 y/o), age (51-70 y/o), age (70<),

diabetes, smoking, bisphosphonate (IV, oral), and penicillin allergy.

1-4- The number of patients who had implants removed (D6100) during time line B in each of the

following categories: female, male, age (18-30 y/o), age (31-50 y/o), age (51-70 y/o), age (70<),

diabetes, smoking, bisphosphonate (IV, oral), and penicillin allergy.

2- Periodontal Disease and follow ups/Periodontal Maintenance

2-1 Total number of patients who received implants (D6010) during time line A, who also have a

history of periodontal disease (codes D499T2, D499T3, D499T4, D4999.1) within no specific time

line (since the beginning of becoming a patient at PDM).

2-1-1 Total number patients in category 2-1, who also have been coming for their

periodontal maintenance (any of the following codes D110, D4910, D4910.2, D4910.3,

D4910.4) during time line B. Furthermore, the number of times these codes (D110, D4910,

D4910.2, D4910.3, D4910.4) were completed was considered to determine whether the

patients were coming for regular maintenance and follow ups or not.

2-2 Total number of patients who received implant (D6010) during time line A and had that

implant removed (D6100) during time line B, who also have a history of periodontal disease (codes

D499T2, D499T3, D499T4, D4999.1) within no specific time line (since the beginning of

becoming a patient at PDM).

2-2-2 Total number patients in category 2-2, who also have been coming for their

periodontal maintenance (any of the following codes D110, D4910, D4910.2, D4910.3,

D4910.4) during time line B. Furthermore, the number of times these codes (D110, D4910,

D4910.2, D4910.3, D4910.4) were completed was considered to determine if they were

coming for regular maintenance and follow ups or not.

3- Recall

3-1 Total number of patients who received implant (D6010) during time line A and their history

of recalls (codes D110, D4910, D4910.2, D4910.3, D4910.4) during time line B. As well as the

number of the times these codes (D110, D4910, D4910.2, D4910.3, D4910.4) were completed (to

determine if they were coming for regular maintenance and follow ups or not).

3-2 Total number of patients who received implant (D6010) during time line A and had the implant

removed (D6100) during timeline B, and their history of recalls (codes D110, D4910, D4910.2,

D4910.3, D4910.4) during time line B. Furthermore, the number of the times these codes (D110,

D4910, D4910.2, D4910.3, D4910.4) were completed was considered to determine whether the

patients were coming for regular maintenance and follow ups or not.

Exclusion criteria included implants placed outside of Penn Dental and removed at Penn Dental,

implants placed or removed at Penn Dental outside of the study timeframe, cases with vague or

ambiguous documentation, and patients younger than 18 years old.

Statistical Analysis

Data were analyzed using SPSS v.24 (IBM Corp. Released 2016. IBM SPSS Statistics for

Windows, Version 24.0. Armonk, NY: IBM Corp.), and Stata v.15 (Stata Corp. 2017. Stata

Statistical Software: Release 15. College Station, TX: Stata Corp LLC.).

A chi-square test was applied to compare the implant failure distribution between the different

categories of potential risk factors (a P-value≤0.05 was considered as significant). The null

hypothesis (𝐻0) was that the implant failure rate is independent from the potential risk factors; i.e.,

the different level of a particular risk factor does not change the implant failure ratio. The Chi-

square test was applied in both patient-level and implant-level.

This was a matched-case-control study with a 1:3 ratio (1 case matched to 3 controls) consisted of

99 patients with implant failure(s) and 297 matched controls. Cases were matched based on age,

gender, site, and trainee-group. The descriptive statistics were first reported to explain the data,

including, number and percentage. The overall incidence of failure was calculated in both patient-

level and implant-level.

We applied a univariate conditional logistic regression as a feature selection method to select the

most relevant factors affecting the implant failure - to be considered in the final multivariate

logistic regression model. Variables with a univariate P-value<0.2 were considered as important

variables and got selected as the covariate for the final multivariate conditional logistic regression.

The multivariate conditional logistic regression was applied to find the potential risk factors

affecting the implant failure and report the odds ratios, called adjusted odds ratio (Adj. ORs).

Covariates with a multivariate P-value≤0.05 were considered as significant potential risk factors.

Twenty-year-old female patient with implant failure #Q was excluded from matching due to not

having a controlled group.

Results

The data and results were analyzed in patient count and implant count:

Patient Count

During the study period a total of 1609 patients received implants, out of which 883 patients

received implants at PDM and 726 patients received implants at PDFP. The total rate of patients

with failed implants was 4.9%. This is the sum of patients with failed implant of 6% and 3.7% for

PDM and PDFP, respectively.

Implant Count

A total of 3180 implants were placed during the study period. 2162 implants were placed at PDM

and 1018 implants were placed at PDFP. The total failed implant rate was 3.4%. This is the sum

of implant failure rate of 3.7% and 3% for PDM and PDFP, respectively.

Based on the chi-square test results in Table 1C, patients with bisphosphonate IV+PO (12%, P-

value=0.004) were significantly overrepresented in the failure group. In contrast, patients with no

bisphosphonate use (4.60%, P-value=0.004) were significantly underrepresented in the failure

group.

No overrepresentation (or underrepresentation) of patients with different gender, different age

group, diabetes mellitus, history of periodontal disease, current smoking status, penicillin allergy,

and recall was noted amongst failures.

Based on the chi-square test results in Table 2C, all of PO+IV bisphosphonate use was statistically

significant (9.80%, P-value <0.001). Implants for bisphosphonate IV variable (11.5%, P-

value=0.025) were significantly overrepresented in the failure group. In contrast, implants for no

bisphosphonate use (3.20%, P-value<0.001) were significantly underrepresented in the failure

group. No overrepresentation (or underrepresentation) of implants for different gender, different

age group, diabetes mellitus, history of periodontal disease, current smoking status, penicillin

allergy, and recall was noted amongst failures.

Conditional Logistic Regression

Based on the frequency distributions of the variables (Table 3A), frequencies of the current

smokers (n=4), subjects with penicillin allergy (n=2), IV bisphosphonate use (n=5), and diabetes

(n=6) were very low, which may result in unreliable odds ratios (ORs) in the conditional logistic

regression.

Matching variables were not considered in the conditional logistic regression model (age, gender,

trainee group). Univariate conditional logistic regression was applied as a variable-selection step.

Variables with a univariate P-value≤0.2 were selected to be entered into the final multivariate

logistics regression model.

Based on the univariate conditional logistic regression results in Table 3B, total implant (OR=3.15,

P-value=0.001), history of periodontal disease (OR=0.68, P-value=0.208), bisphosphonate use

(OR=3.88, P-value=0.003), and diabetes (OR=3.0, P-value=0.178) were selected (with P-

value≤0.2) as the final variables to be entered in the multivariate conditional logistic regression.

Based on the multivariate conditional logistic regression results in Table 3B, estimated odds of

implant failure in participants with multiple implants were about three times than participants with

single implant (Adj OR=2.99, P-value=0.002); estimated odds of implant failure for

bisphosphonate use of IV and PO were about four times than participants with no bisphosphonate

use (Adj. OR=4.09, P-value=0.003). Diabetes and history of failed implants did not show any

significant association with implant failure (with P-values>0.05).

The conditional logistic regression was initially calculated with “Bisphosphonate use” with three

categories (results presented in table 4). However, the odds ratio for the “IV” category became

OR=121.17 due to the sparse data in this category (n=5, refer to Table 3A). Therefore, the model

was re-calculated with “Bisphosphonate use” with two categories.

Tables

Table 1C. Patients with failed implants according to gender, age and past medical histories

(diabetes, bisphosphonates, periodontal disease, and smoking status)

Variable

Patients

Who

Receive

d

Implant

s

Patients

with

Failures

% of

Patients

with

Failures

(Under 𝐻0)

Expected

Patients

with Failures

(Under 𝐻0)

P-

value

Entire sample 1609 80 4.97% - -

Gender

Male 691 28 4.10% 34.9 0.110

Female 892 52 5.80% 45.1 0.108

Unknown 1 0

Age (in years)

18-30 63 1 1.60% 3.1 0.207

31-50 379 12 3.20% 18.8 0.064

51-70 816 48 5.90% 40.6 0.088

70< 351 19 5.40% 17.5 0.667

Diabetes (Type 1 and Type

2) 18 2 11.10% 0.9 0.228

Diabetes Type 1 2 0 0% 0.1 1.000

Diabetes Type 2 16 2 12.50% 0.8 0.164

No diabetes 1591 78 4.90% 79.1 0.228

Bisphosphonates (IV + PO) 75 9 12% 3.7 0.004*

Bisphosphonate IV 14 2 14.30% 7.0 0.107

Bisphosphonate PO 61 7 11.50% 3.0 0.017*

No Bisphosphonates 1534 71 4.60% 76.3 0.004*

Hx of Periodontal Disease 362 16 4.40% 18.0 0.583

No periodontal

disease 1247 64 5.10% 62.0 0.583

Current Smoker 18 1 5.60% 0.9 0.909

Non-smoker 1591 79 5% 79.1 0.909

Penicillin Allergy 16 1 6.20% 0.8 0.813

No penicillin allergy 1593 79 5% 79.2 0.813

Patients with Recall 1236 55 4.40% 61.5 0.079

Non-recall patient 373 25 6.70% 18.5 0.079 * Significant with P-value<0.05. P-values are based on a chi-square test.

Table 2C. Implant’s demographics

Variable

Implan

ts

placed

in

patient

s

Failed

Implants

% of

Failures

(Under

𝑯𝟎)

Expected

Implants

with Failures

(Under 𝑯𝟎)

P-

value

Entire sample 3180 111 3.49%

Gender

Male 1391 40 2.90% 48.6 0.094

Female 1788 71 4.00% 62.4 0.096

Unknown 1 0

Age (in years)

18-30 110 1 0.90% 3.8 0.133

31-50 595 15 2.50% 20.8 0.153

51-70 1787 68 3.80% 62.4 0.273

70< 663 27 4.10% 23.1 0.359

Diabetes (Type 1 and

Type 2) 70 3 4.30% 2.4 0.714

Diabetes Type 1 2 0 0.00% 0.1 1.000

Diabetes Type 2 68 3 4.40% 2.4 0.676

No Diabetes 3110 108 3.50% 3.5 0.714

Bisphosphonates (IV +

PO) 133 13 9.80% 4.6

<0.00

1*

Bisphosphonate

IV 26 3 11.50% 0.9 0.025*

Bisphosphonate

PO 107 10 9.30% 4.6 0.001*

No

Bisphosphonates 3047 98 3.20% 106.4

<0.00

1*

Hx of Periodontal

Disease 730 19 2.60% 25.5 0.136

No periodontal

disease 2450 92 3.80% 85.5 0.136

Current Smoker 33 0 0.00% 1.2 0.272

Non-smoker 3147 111 3.50% 109.8 0.272

Penicillin Allergy 24 2 8.30% 0.8 0.194

No penicillin

allergy 3156 109 3.50% 110.2 0.194

Patients with Recall 2145 74 3.40% 74.9 0.857

Non-recall patient 1035 37 3.60% 36.1 0.857 * Significant with P-value<0.05. P-values are based on a chi-square test.

Table 3A. Frequency of different variables

Variable level Number %

Outcome Fail 99 25.0

Success 297 75.0

Sex Female 252 63.3

Male 144 36.4

Site Max Post 124 31.3

Max Ant 84 21.2

Mand Post 128 32.3

Mand Ant 60 15.2

Arch Mandibular 188 47.5

Maxillary 208 52.5

Location Posterior 252 63.3

Anterior 144 36.4

Trainee group PDM 280 70.7

PDFP 116 29.3

Total Implant Single 117 29.5

Multiple 279 70.5

Smoking No 392 99.0

Yes 4 1.0

Penicillin Allergy No 394 99.5

Yes 2 0.5

History of

Periodontal Diseases

No 307 77.5

Yes 89 22.5

Recall No 138 34.8

Yes 258 65.2

Bisphosphonate use No 370 93.4

IV 5 1.3

PO 21 5.3

Diabetes No 390 98.5

Type II 6 1.5

Table 3B. Results of the univariate and multivariate conditional logistic regression. Variables

with a univariate P-value≤0.2 are selected to be entered into the final multivariate logistics

regression.

Variable Category

Univariate Analysis Multivariate Analysis

OR* 95%

CI

P-

value

Adj

OR**

95%

CI P-value

Total Implant Single ref

Multiple 3.15 1.58-

6.26 0.001

2.99

1.48-

6.02 0.002

Smoking No ref -

Yes 3.0 0.42-

21.29 0.271

-

Penicillin Allergy No ref -

Yes 3.0 0.19-

47.96 0.437

-

History of Periodontal

Disease No ref

Yes 0.68 0.37-

1.24 0.208

0.70

0.37-

1.32 0.267

Recall No ref -

Yes 1.03 0.60-

1.78 0.891

-

Bisphosphonate use No ref

IV & PO 3.88 1.58-

9.54 0.003

4.09

1.61-

10.35 0.003

Diabetes No ref

Type II 3.0 0.60-

14.86 0.178

2.24

0.42-

11.80 0.341

* Odds Ratio

** Adjusted Odds Ratio

Table 4

Variable Category OR* 95% CI P-value

Bisphosphonate use No ref

IV 13.37 1.47-121.17 0.021

PO 2.87 1.06-7.78 0.037

Discussion

Implant failure can be characterized by clinical and radiographic findings such as implant mobility,

suppuration around the implant, implant bone loss, lack of osseointegration, progressive bone

resorption, peri-implantitis, and patient complaint.33 Implant failures have been associated with

multiple factors. These factors include poor bone quality or lack of bone volume, smoking habits,

infection, host response, implant instability, and unfavorable implant loading. 34

Implant failures can be divided into early or late failures. Early failure occurs prior to delivery of

restorative abutment. Late failure happens after implant loading. This recognition is critical to

know for practitioners as the etiology of them are different. 35 In early failure there is inadequate

bone to implant contact due to impaired bone healing and fibrous scar tissue formation instead of

bone apposition. This leads to epithelial down growth or marsupialization that can lead to implant

loss. 36, 37, 38 There have been patient related and implant related factors identified for this early

implant failure such as smoking habit, metabolic disorders, implant features, quality and quantity

of bone, surgery related factors, and the use of grafted bone. 39, 40 The late failures are associated

with overload induced peri-implantitis and plaque induced peri-implantitis.41 In a systematic

review by Berglundh (2002), incidence of early implant loss was reported to be between 0.76%

and 7.47% and late implant loss between 2.1% and 11.3% in studies with 5 to 10 years follow up.

42

This study investigated implant failure co-contributing factors at the patient level. It was noted that

the majority of the implant failures happened prior to final restorative abutment insertion, which

indicates these failures to be categorized as early implant failures. Failure rate in patient level was

found to be equal to 4.97% (95% CI: 3.90, 6.03) while failure rate in implant level was 3.49%

(95% CI: 2.85, 4.13). In this study no overrepresentation (or underrepresentation) of patients with

different gender, different age group, diabetes mellitus, periodontal disease, current smoking

status, penicillin allergy, and recall was noted amongst failures.

Age and Gender

According to our findings, patient demographics such as gender and age were not over or under

represented thus not related to the early implant failure. These results are in agreement with

Steenberghe et al. (2002) that also found no direct correlation of age and gender with early implant

failure.43

History of Periodontal Disease, Recall, Smoking

Heitz-Mayfield (2008) found substantial evidence that poor oral hygiene, history of periodontitis,

and cigarettes smoking were associated with peri-implantitis and limited evidence that poorly

controlled diabetes and alcohol consumption is associated with peri-implantitis, but more studies

are needed to confirm these as true factors.15 Baelum and Ellegaard (2004) found no difference in

a 5-year implant survival rate study in patients with history of periodontitis compared to patients

without it.14 Similarly, Klokkevold and Han (2007) determined that there is no statistically

significant difference for survival rate of implants placed in patients with a history of treated

periodontitis compared to patients with no history of periodontitis (95% and 97.1% respectively).44

This is in accordance to the results of the present study. On the contrary, in a systematic review,

Ong et al. (2008) concluded that patients treated for periodontitis may experience more implant

failure compared to non-periodontitis patients.12 However, evaluating the correlation of

periodontitis or history of recall and implant failure may be better evaluated with late implant

failure as the peri-implantitis takes longer to occur.

Tran et al. (2016) conducted a long-term retrospective study regarding survival of dental implants

placed in grafted and non-grafted sites and found that smoking and lack of professional

maintenance were significantly related to increased implant loss.45 Similarly, a meta-analysis by

Manzano et al. (2016) and a systematic review by Strietzel et al. (2007) concluded that smoking

increases the risk of early implant failure. 46, 47 However, in the present study smoking did not play

a role as a contributing factor for implant failure. This may have been due to small number of

patients who had implant failure with smoking habit, thereby reducing the power of the statistical

analysis. Based on the frequency distributions of the variables (Table 3A), frequencies of the

current smokers (n=4) were very low, which may result in unreliable odds ratios (ORs) in the

conditional logistic regression. Another restrictive factor may have been that the smoking habit

was self-reported and may have been biased. In addition, Sverzut et al (2008) stated that tobacco

alone cannot be considered a risk factor for early implant loss. On the contrary, Alsaadi et al (2007)

reported that smoking may have a dose dependent effect on osseointegration and is associated with

early implant failure. 47, 48

Diabetes Mellitus

Another important factor to consider when implant placement is the presence of diabetes mellitus

and the glycemic status of the patient. Moy et al. (2005) noted that implant failure was significantly

higher among patients who were 60 years or older, smoked, and had a history of diabetes.49 Oates

et al. (2009) reported that alterations with the implant stability due to impaired implant integration

in people with type 2 diabetes mellitus with HbA1c greater or equal to 8.1%, is in direct relation

to their hyperglycemic condition.50 Javed et al. (2009) reported that implant osteointegration can

be reached in patients with well controlled diabetes.20 This is in accordance with the results of this

study that showed no statistically significant difference between implant failure rate of patients

with controlled diabetes compared to patients without diabetes. In the present study, the diabetes

mellitus status was self-reported by patients and implant surgery was done only if diabetes had

been reported to be controlled. The self-reported control of diabetes may have caused bias.

Bisphosphonate

A meta-analysis by Ata-Ali et al. (2014) reported that receiving bisphosphonates does not reduce

the success rate of dental implants, yet such patients are not without complications. Furthermore,

risk evaluation has to be done on an individual basis and there was not enough evidence and studies

included in this report.51 Similarly, in a study by Fugazzottoo et al. (2007), 61 patients with history

of oral bisphosphonate therapy for a mean period of 3.3 years were followed up 12-24 months

after implant placement. The history of oral bisphosphonate use was not found to be a contributing

factor for developmental of osteonecrosis following implant placement either in extractions

sockets with immediate implant placement or in intact ridges. However, they recommended a

larger controlled studies and retrospective reports.52 Furthermore, Jeffcoat (2006) conducted two

controlled clinical studies and found that oral bisphosphonate use was not associated with

occurrence of osteonecrosis of the jaw. 53 On the contrary, Jacobsen et al. (20013) noted that

implants that are placed in the posterior regions have higher risk of development of osteonecrosis

of the jaws. They mentioned that the implant placement as well as the implant by itself can be a

continuous risk factor. 54 Another study by Tam et al. (2012) reported that unusual jaw necrosis

following dental implant placement can be related to oral and/or intravenous bisphosphonate use.

They stated that key factors for successful healing in these situations are collagen graft, resection

of necrotic tissue, and primary closure.55 According to the present study, bisphosphonate use is

associated with implant failure rate (Adj. OR=4.09, P-value=0.003).

Penicillin Allergy

According to a cross sectional study by Salomo-Coll et al. (2018), patients with allergy to

penicillin, who received clindamycin prophylactically and post surgically following implant

surgery, exhibited 3.84 times more implant failure compared to non-allergic patients who received

amoxicillin. However, the authors mentioned that these results could have been influenced by other

factors such as implant brand, surgical skill, and location of the implant.26 The present study did

not show any statistically significant correlation between implant failure rate in patients with

penicillin allergy or non-allergic patients. However, this study evaluated 394 subjects with no

allergy to penicillin and 2 subjects with allergy. This results in an unreliable OR in conditional

logistic regression. Therefore, a bigger sample size is needed in this category to be able to reliably

compare them with each other.

Multiple vs. Single Implant Placement and Provider Expertise

Cluster phenomenon, which is defined as multiple implant failure in the same patient, supports the

evidence that certain characteristics in each individual can influence the early implant failure.

These characteristics can include age, bone quality, taking antidepressants, and bruxism.56, 57

According to an analysis of a large number of clinical follow up studies with Branemark implants,

the failure rate was noted to be 7.7% in a 5 year follow up, excluding grafted sites. They noted

early failure rate of 3.8% and 2% for partially edentulous and fully edentulous, respectively and

total failure rate was 3.4% for partially edentulous and 7.6% for fully edentulous patients. This can

be due to a better patient selection in terms of age, health, and anatomical conditions, as well as

more favorable load distribution. Overall, higher failure rates were observed for overdenture.36, 58

The results of this study showed that patients who received more than one implant either at the

same time or different time periods had statistically significant more implant failure rate compared

to patients who received only one implant (P-value=0.002). This can be due to anatomical

limitations, patient’s overall poor oral hygiene, host response, impaired healing due to undiagnosed

or uncontrolled disease, and the technique sensitivity of the surgery. In other words, placing

multiple implants requires more planning and superior surgical skills. Another factor for the

increase in failure rate may be due to atrophic ridge, which may require additional procedures, and

size and characteristics of the implant. These factors will be discussed more in details in the second

part of this study.

Espositio et al. (1998b) stated experienced dentist may have a better patient and site selection,

better technique, minimal surgical trauma and bacterial contamination, thus have less failures. 58

Traumatic surgery can cause soft tissue encapsulation of the implants. 59 Furthermore, overheating

has been deemed to be the most probable cause of early implant failures. 60

As part of the study design for collecting data with matched-case-control technique with a 1:3

ratio, trainees covariate were matched; therefore, they could not be used as covariate in logistic

regression analysis and there could not be a true comparison of these groups with regard to the

implant failure rate.

Limitations of the study

The findings of this study were subject to some limitations. One of the limitations was that patients’

self-reporting of medical condition and tobacco use may have been subject to their recall bias.

Also, the survival rate of implants that were placed but patient did not come back for follow up is

unknown. Moreover, due to Penn Dental policy, there was access to limited number of the charts

to review for more detailed information. Based on the frequency distributions of the variables

(Table 3A), frequencies of the failed implants in current smokers (n=4), subjects with penicillin

allergy (n=2), bisphosphonate use IV (n=5), and diabetes (n=6) were very low, which may have

resulted in unreliable odds ratios (ORs) in the conditional logistic regression. Thus, it is

recommended to have bigger sample size in each of these categories in the future studies to be able

to have a logistical comparison.

Conclusion

Implant therapy can be a reliable treatment option to replace missing teeth. This retrospective study

investigated early implant failure. The primary objective of this retrospective study was to assess

implant failure rate in academic setting. The total failure rate for PDM and PDFP was within the

reported failure range of the literature. Co-contributing factors were stratified in patient level and

implant level. In this study, the focus was the patient level.

This study concluded that bisphosphonate use and patients with multiple implants were shown to

have a significant contribution to implant failure. There was no difference in the failure rate of

patients with different gender, different age group, diabetes mellitus, periodontal disease, current

smoking status, penicillin allergy, and recall amongst failures.

It is important to note that due to limitations and the retrospective nature of this study, only the co-

contributing factors were evaluated and not the etiology of the implant failure. To investigate the

etiology, randomized clinical trial should be conducted. Yet, the clinicians should be aware of the

increased risk of early implant failure with bisphosphonate use and in cases with multiple implant

therapy.

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