Bruxism and dental implant failures: a multilevel mixed effects parametric survival analysis approach

Journal of

Oral Rehabilitation

Journal of Oral Rehabilitation 2016

Bruxism and dental implant failures: a multilevel mixed effects parametric survival analysis approach B.R. CHRCANOVIC*, J. KISCH†, T. ALBREKTSSON*‡ & A. WENNERBERG*

*Depart-

ment of Prosthodontics, Faculty of Odontology, Malm€o University, Malm€o, †Clinic for Prosthodontics, Centre of Dental Specialist Care, Malm€o and ‡Department of Biomaterials, G€oteborg University, G€oteborg, Sweden

Recent studies have suggested that the insertion of dental implants in patients being diagnosed with bruxism negatively affected the implant failure rates. The aim of the present study was to investigate the association between the bruxism and the risk of dental implant failure. This retrospective study is based on 2670 patients who received 10 096 implants at one specialist clinic. Implant- and patient-related data were collected. Descriptive statistics were used to describe the patients and implants. Multilevel mixed effects parametric survival analysis was used to test the association between bruxism and risk of implant failure adjusting for several potential confounders. Criteria from a recent international consensus (Lobbezoo et al., J Oral Rehabil, 40, 2013, 2) and from the International Classification of Sleep Disorders (International classification of sleep disorders, revised: diagnostic and coding manual, American Academy of Sleep Medicine, Chicago, 2014) were used to define and diagnose the condition. The SUMMARY

Introduction The relationship between bruxism and dental implants outcome has been recently receiving great attention in the literature. The results of a recent meta-analysis on the subject (1) found that the insertion of dental implants in patients being diagnosed with bruxism negatively affected the implant failure rates. However, the authors stressed that the effect size observed was not reliable due to a limited number of published studies, all characterised by a low level of specificity, and most of them dealing with a limited number of cases. © 2016 John Wiley & Sons Ltd

number of implants with information available for all variables totalled 3549, placed in 994 patients, with 179 implants reported as failures. The implant failure rates were 13
0% (24/185) for bruxers and 4
6% (155/3364) for non-bruxers (P < 0
001). The statistical model showed that bruxism was a statistically significantly risk factor to implant failure (HR 3
396; 95% CI 1
314, 8
777; P = 0
012), as well as implant length, implant diameter, implant surface, bone quantity D in relation to quantity A, bone quality 4 in relation to quality 1 (Lekholm and Zarb classification), smoking and the intake of proton pump inhibitors. It is suggested that the bruxism may be associated with an increased risk of dental implant failure. KEYWORDS: dental implant, implant failure, bruxism, multilevel mixed effects parametric survival analysis Accepted for publication 19 August 2016

Another review (2) has concluded that it is unlikely that bruxism would be considered a risk factor for biological complications around dental implant, while there are some suggestions that it may be a risk for mechanical complications. A considering number of clinical trials reported a significant relationship between bruxism and implant failure (3–6). The most recent of them (6) compared 98 bruxers with a matched group and suggested that bruxism may significantly increase both the implant failure rate and the rate of mechanical and technical complications of implant-supported restorations. doi: 10.1111/joor.12431

2

B . R . C H R C A N O V I C et al. As the recognition of conditions that place the patient at a higher risk of failure will allow the surgeon to make informed decisions and refine the treatment plan to optimise the clinical outcome (7), the aim of this retrospective study was to investigate the association between sleep and/or awake bruxism and the risk of dental implant failure, and to describe and compare the group of bruxers with non-bruxers.

Materials and methods Materials See supporting information. Inclusion/exclusion criteria See supporting information. Definitions An implant was considered a failure if presenting signs and symptoms that led to implant removal. Thus, a failed implant in our study is equal to a lost implant. To diagnose patients as bruxers, the authors followed the definition of bruxism proposed by Lobbezoo et al. (8): ‘Bruxism is a repetitive jaw-muscle activity characterised by clenching or grinding of the teeth and/or by bracing or thrusting of the mandible. Bruxism has two distinct circadian manifestations: it can occur during sleep (indicated as sleep bruxism) or during wakefulness (indicated as awake bruxism)’. As reliable and valid diagnostic tools for bruxism are scarce (8), a diagnostic grading system of ‘possible’, ‘probable’ and ‘definite’ sleep or awake bruxism was used, as suggested for clinical and research purposes (9). According to an international consensus (8), ‘possible’ sleep/awake bruxism should be based on self-report, by means of questionnaires and/or the anamnestic part of a clinical examination. ‘Probable’ sleep/awake bruxism should be based on self-report plus the inspection part of a clinical examination. ‘Definite’ sleep bruxism should be based on self-report, a clinical examination, and a polysomnographic recording, preferably along with audio/video recordings. As electromyography and/or polysomnography were not used due to high cost and limited availability, the patients of this study would only fall into the categories ‘possible’ or ‘probable’. Thus, a

patient was considered as presenting bruxism based on self-report of clenching/grinding during sleep/ wakefulness, plus the inspection part of a clinical examination. The patients’ records were scrutinised looking for clinical notes and photographs that would suggest the possible/probable diagnosis of bruxism. All patients who were diagnosed in the records as bruxers were considered for a clinical re-evaluation. The patients were contacted through a telephone call and were asked to attend a follow-up appointment. The patients signed an informed and written consent form approving the participation in the study and were clinically reassessed. The self-conscience of the condition was evaluated with some questions (see supporting information), according to suggestions of a previous study (10). The clinical condition was re-evaluated to assess possible bruxism-related signs and symptoms. The signs and symptoms of bruxism were listed according to the International Classification of Sleep Disorders (11): (i) presence of regular or frequent tooth grinding sounds occurring during sleep, (ii) abnormal tooth wear consistent with above reports of tooth grinding during sleep, (iii) transient morning jaw-muscle pain or fatigue, and/or temporal headache and/or jaw locking on awakening consistent with above reports of tooth grinding during sleep. Moreover, clenching or grinding of the teeth and/or by bracing or thrusting of the mandible during wakefulness was also considered, according to a recent international consensus (8). The clinical examination was carried out by the same trained operator. Data collection See supporting information. Statistical analyses The mean, standard deviation (s.d.) and percentages were presented as descriptive statistics. Differences between implants in bruxers and non-bruxers were compared with the Student’s t-test or Mann–Whitney U-test for continuous variables, depending on the normality, and the Pearson’s chi-squared or Fisher’s exact tests for categorical variables, depending on the expected count of events in a 2 9 2 contingency table. Comparison between bruxers and non-bruxers in terms of demographic systemic conditions and © 2016 John Wiley & Sons Ltd

BRUXISM AND DENTAL IMPLANT FAILURES other factors was made; odds ratios (OR) and their 95% confidence intervals (CI) were computed. Multilevel mixed effects parametric survival analysis (12) was used, a patient-based multilevel analysis, to assess the association between bruxism and dental implant failure, accounting for the fact that repeated observations (several implants) were available for a single patient (cluster effect). Bruxism was set as the exposure variable. Because there was little prior knowledge about the appropriate shape of survival probability, we extended parametric frailty models including five different parametric models (Weibull, Exponential, Log logistic, Log Normal and Gamma) to allow any number of normally distributed random effects. Akaike information criteria (AIC) were used to choose the best fit survival model (13). Bruxism was the exposure variable, and all analyses were adjusted for the following potential confounders: age, gender, implant length, implant diameter, implant surface, implant location, bone augmentation, bone quantity, bone quality, the intake of prophylactic antibiotics, smoking habits, use of snuff, diabetes, asthma, and the intake of antidepressants, antihypertensive drugs, immunosuppressives, antithrombotic agents (antiplatelet, anticoagulant, thrombolytic drugs), antihypercholesterolaemia agents, medicaments to compensate hypothyroidism and PPIs. To verify multicollinearity, a correlation matrix of all of the predictor variables with a significant odds ratio (P-value cut-off point of 0
1) was scanned, to see whether there were some high correlations among the predictors. Collinearity statistics obtaining variance inflation factor (VIF) and tolerance statistic were also performed to detect more subtle forms of multicollinearity. The results of the final model were presented as an estimated hazard ratio (HR) of each significant prognostic variable. Kaplan–Meier survival curves were plotted to describe the cumulative proportion of dental implant failure stratified by the patients’ habits of bruxism (presence/absence), and a comparison among groups was analysed by the log-rank test. The degree of statistical significance was considered P < 0
05. All data were statistically analysed using the software Stata version 14* and SPSS 23 software† .

*StataCorp LP, College Station, TX, USA. †

SPSS Inc., Chicago, IL, USA.

© 2016 John Wiley & Sons Ltd

Results The number of implants with information available for all variables totalled 3549, placed in 994 patients, with 179 implants reported as failures. There were 1777 implants in 478 men (mean age  s.d. 60
4  15
9, min–max 15
9– 90
2) and 1772 implants in 516 women (mean age  s.d. 59
6  15
1, min–max 14
9–90
8). A total of 185 implants were placed in 56 bruxers, whereas 3364 were placed in 938 non-bruxers. The number of implants per patient ranged from 1 to 15 (mean  s.d. 3
57  2
67). The mean  s.d. follow-up time was 2843  2364 days (2654  2325 days for bruxers, 2853  2366 days for non-bruxers; P = 0
426; Mann–Whitney U-test). The implant failure rates were 13
0% (24/185) for bruxers and 4
6% (155/3364) for non-bruxers (P < 0
001; Pearson’s chi-squared test). The 179 failed implants were lost at a mean  s.d. of 1121  1611 days (min– max, 24–9491). Forty-six (25
7%) of 179 failed implants were lost up to the abutment connection procedure or second-stage surgery (one in bruxers, 45 in non-bruxers). Eighty-six (48
0%) of 179 failed implants were lost until 1 year after surgery. All implants were inserted with open flapped surgery. Twenty implants were immediately loaded (two in bruxers, 18 in non-bruxers). Eleven implants were placed in fresh extraction sockets (two in bruxers, nine in non-bruxers). A number of 113 implants were nonsubmerged (six in bruxers, 107 in non-bruxers). The abutment connection surgery was performed after a mean  s.d. healing time of 145  51 and 155  62 days for the bruxers and non-bruxers, respectively (P = 0
012; Mann–Whitney U-test). The comparison between bruxers and non-bruxers in terms of systemic conditions and other factors (Table 1) showed that there were statistically more men than women bruxers. Moreover, shorter and wider implants were more common in bruxers than in non-bruxers, as well as enlarged-surface implants. Bruxers received more implants in the posterior areas of jaws in comparison with non-bruxers. Bone augmentation surgeries were performed more often in bruxers. There were more former smokers, diabetic type 1, people taking antihypercholesterolaemia drugs, antidepressants, PPIs and medicaments to compensate hypothyroidism among bruxers than non-bruxers. There were no statistically significant differences for the other variables (Table 1). Among bruxers, there were no individuals taking bisphosphonates, with

3

4

B . R . C H R C A N O V I C et al. Table 1. Description of the cohort by implants (n = 3549) between bruxers and non-bruxers Variables Age (years) ≤30 30 < x ≤ 60 >60 Gender Male Female Implant length (mm) 6
0–10
0 10
5–14
0 15
0–20
0 Implant diameter (mm) 3
00–3
50 3
70–4
10 4
20–5
00 Implant surface Turned Enlarged Implant location Anterior maxilla Posterior maxilla Anterior mandible Posterior mandible Bone augmentation No Yes Prophylactic antibiotics No Yes Bone quantity† A B C D E Bone quality† 1 2 3 4 Smoking No Yes Former smoker Snuff No Yes Diabetes No Type 1 Type 2

Bruxersn (%)

Non-bruxersn (%)

Odds ratio (95% CI)

P value*

9 (4
9) 77 (41
6) 99 (53
5)

244 (7
3) 1173 (34
9) 1947 (57
9)

1 1
780 (0
880, 3
598) 1
379 (0
688, 2
763)

0
109 0
365

107 (57
8) 78 (42
2)

1670 (49
6) 1694 (50
4)

1 0
719 (0
533, 0
970)

0
031

44 (23
8) 105 (56
8) 36 (19
5)

671 (19
9) 1637 (48
7) 1056 (31
4)

1 0
978 (0
680, 1
407) 0
520 (0
331, 0
816)

0
905 0
004

14 (7
6) 160 (86
5) 11 (5
9)

291 (8
7) 2008 (89
4) 65 (1
9)

1 1
656 (0
946, 2
899) 3
518 (1
527, 8
101)

0
077 0
003

39 (21
1) 146 (78
9)

1563 (46
5) 1801 (53
5)

1 3
249 (2
267, 4
655)