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. 2025 Mar 4;27(2):e70021. doi: 10.1111/cid.70021

Effects of Bone Augmentation on Implant Success and Survival: A Retrospective Analysis With 6‐Year Mean Follow‐Up

Ufuk Tatli 1,2,, Ali Cavana 2, Huseyin Can Tukel 2, Mehmet Emre Benlidayi 2
PMCID: PMC11879386  PMID: 40037311

ABSTRACT

Objective

To compare the clinical, radiographic, esthetic outcomes, and success and survival rates of dental implants placed after bone augmentation techniques.

Methods

This retrospective study included a total of 764 patients receiving 764 dental implants between 2009 and 2019. Four hundred implants were placed without bone augmentation (control), and 364 were placed after bone augmentation. Bone augmentation techniques were guided bone regeneration (GBR), ridge split, and onlay bone grafting. Gingival index (GI), plaque index (PI), probing depth (PD), bleeding on probing (BOP), pink esthetic score (PES) and marginal bone loss (mm) and area (mm2) were measured. The study variables of the implants among augmentation groups were compared statistically.

Results

The mean PI and GI scores, and BOP values of the implants in the augmentation and control groups were comparable (p = 0.365, p = 0.230, and p = 0.371 resp.) The mean PD scores of the implants were 2.82 ± 1.22 in the augmentation and 2.54 ± 1.29 in the control groups; the difference was significant (p = 0.002). The mean vertical bone loss of the implants was 0.78 ± 0.70 in augmentation and 0.82 ± 0.82 in the control groups, which was comparable (p = 0.461). The mean PES total values of the implants were 8.30 ± 1.55 in augmentation and 10.04 ± 2.43 in the control groups; the difference was significant (p < 0.001). There were no significant differences between the augmentation and control groups in implant survival (99.18% vs. 98%, p = 0.228) and success (82.97% vs. 85.50%, p = 0.389) rates. Significant differences in some study variables were observed among the augmentation groups. The survival and success rates of the implants in GBR (99.21% and 85.04%), ridge split (99.19% and 79.68%), onlay (99.12% and 84.21%), and control (98.00% and 85.50%) groups were similar (p = 0.630 and p = 0.479, resp.) in the 6‐year mean follow‐up.

Conclusion

The implants placed in augmented bone showed similar cumulative success and survival rates compared to implants placed in natural bone with a 6‐year mean follow‐up. The augmentation group showed lower esthetic scores. There are some differences in clinical parameters among augmentation groups; however, all the augmentation groups showed similar success and survival rates.

Keywords: bone augmentation, clinical outcomes, dental implant, success rate, survival rate

1. Introduction

Dental implants have become the preferred treatment option for edentulism due to high survival and success rates [1]. Insufficient alveolar bone volume following tooth loss, periodontal disease, oral pathologies, and trauma may prevent prosthetically driven implant placement. In these cases, bone augmentation methods are used for long‐term success in implant treatment. Depending on the extent of the alveolar bone deficiency, different bone augmentation techniques can be performed to provide sufficient bone for implant placement [2, 3, 4, 5]. The success of implant restorations has been evaluated with certain comprehensive success criteria and esthetic assessments [6, 7, 8, 9, 10]. There is no consensus in the literature regarding the survival and success rates of implants placed in augmented and native bone [5, 11, 12, 13, 14]. Moreover, the number of studies comparing the effects of different bone augmentation techniques on implant survival and success rates is quite low, and there is a paucity in the literature on this subject.

The aim of the present retrospective clinical study was to compare the clinical, radiographic, and esthetic outcomes, and success and survival rates of dental implants placed after bone augmentation techniques. The present study was conducted to test the hypothesis that there are no significant differences in implant success and survival rates after frequently used bone augmentation techniques as well as when compared to implants placed in native bone.

2. Material and Methods

2.1. Study Design

The present retrospective study protocol was approved by the Clinical Research Ethics Committee of the Cukurova University Hospital (Meeting no: 89/Decision no: 35). The study was performed in accordance with the guidelines of the Helsinki Declaration. A retrospective chart review was conducted, including patients who received dental implants in the oral and maxillofacial surgery department at Cukurova University School of Dentistry, between May 2009 and January 2019. Patients were given a follow‐up appointment. Following clinical and radiological examinations, patients who met the inclusion criteria were included in the study; written informed consents were obtained, and study data was collected. The implants placed at sites with previous bone augmentation were allocated as the test group. As the control group, data of the implants placed without bone augmentation were recorded. The primary outcome variable of this study was the implant survival rate. The secondary outcomes were peri‐implant bone loss and the implant success rate.

The inclusion criteria for the study were patients over 18 years of age, patients having one of the following bone augmentation surgeries before implant surgery (except ridge split technique); guided bone regeneration (GBR), ridge split, and autogenous block onlay grafting for the augmentation group, patients with post‐loading observation > 1 year, and implants only restored in a conventional (delayed) loading protocol to provide standardization. To prevent the impact of material‐related differences, the patients in whom the same biomaterials were used in bone augmentation procedures were included in the study. Patients having only implant‐supported fixed prosthetic restorations (single crown or bridge) were included in the study. Only one implant per patient was included in the study to standardize the contribution of the patients who had a different number of implants. If the patient had more than one implant, the study implant was randomly allocated using a randomization software (Research Randomizer, version 4.0, www.randomizer.org). Exclusion criteria were the following conditions: patients who were unwilling to participate in the study, implants placed in sites of previously failed implants, patients with poor oral hygiene, patients with a history of periodontal disease, heavy smoker patients (> 10 cigarettes per day), genetic diseases affecting bone metabolism, previous radiotherapy in the head and neck region, uncontrolled metabolic diseases, chronic use of steroids, alcoholism, and drug abuse. Patients who underwent contour augmentation during implant surgery were not included in the control group. Patients who did not participate a minimum of two times (every 6 months) in the supportive peri‐implant maintenance care program were not included in the present study.

Power analysis was performed for the main outcome measure (implant survival in augmented and native bone) considering the data of a previous study [13]. In order to obtain a power of 0.8, 412 implants were required (estimated effect size 0.2), which resulted in at least 206 implants per group.

The study is in compliance with the STROBE guidelines/checklist.

2.2. Surgical Procedures

All bone augmentation procedures and implant surgeries were performed by faculties or postdoctoral residents under the direct supervision of faculties. All the bone augmentation surgeries were performed using particulate bovine‐bone xenograft (Cerabone, Botiss Biomaterials, Berlin, Germany), resorbable collagen membrane (Jason membrane, Botiss Biomaterials, Berlin, Germany), and bone tucks. Autogenous block grafts were harvested from the mandibular ramus region for all onlay block augmentation cases. All ridge split and onlay augmentation techniques were combined with particulate xenograft and resorbable collagen membrane. Dental implants were placed 4–6 months after bone augmentation surgery, except for the ridge split technique in which the implants were placed simultaneously with bone augmentation. The following three dental implant systems used in the oral and maxillofacial surgery clinic and with the largest sample size were included in the study: Biohorizons (Tapered internal implant, bone‐level, internal hex connection, RBR + Laser‐Lok surface, butt‐joint platform) (Birmingham, Alabama, USA), Dentium (Implantium implant, bone‐level, internal conical hex connection, SLA surface, platform switching) (Seoul, South Korea), and Nucleoss (T4 implant, bone level, internal hex connection, SLA surface, platform switching) (İzmir, Turkey). All implant surgeries were performed according to the recommendations of the implant manufacturers. During implant surgery, a one‐stage approach (healing abutment attachment at the time of implant placement) was performed for implants achieving ≥ 35 Ncm insertion torque. The specific surgical protocol including a one‐ or two‐stage approach was not considered in this study. Implant‐supported metal‐ceramic fixed restorations (screw retained or cemented) were delivered 3–4 months after implant placement. The timeline diagram of the study protocol was shown in Figure 1. The patients were included in a supportive peri‐implant maintenance care program involving routine recalls every 6 months for professional cleanings.

FIGURE 1.

FIGURE 1

The timeline diagram of the study protocol.

2.3. Data Collection

Demographic variables including gender, age, smoking status, implant diameter, implant length, implant brand, implant location, and prosthesis type were collected from all patients. Following study variables were collected at the latest follow‐up recall: bleeding on probing (BOP) (Dichotomized, yes/no) within 30 s following probing, modified gingival index (GI) [15], modified plaque index (PI) [16], probing depth (PD) (mm), pink esthetic score (PES) [17], vertical and horizontal marginal bone loss (MBL) (mm) and MBL area (mm2) for mesial and distal sites. Probing depth measures were obtained from mesial and distal midpoints in both facial and palatal aspects of an implant, 4 measurements per implant (mesio‐buccal, disto‐buccal, mesio‐lingual, and disto‐lingual), using a UNC‐15 periodontal probe (Hu‐Friedy, Chicago, IL, USA). The PD was measured from the peri‐implant mucosal margin to the bottom of the sulcus/pocket (mm) with gentle probing. The mean value of 4 measurements was recorded for each implant. All PD measurements were performed by the same experienced investigator who was unaware of the study groups of the individuals. All the clinical measurements were performed by a calibrated examiner (A.C). The 10% of the measurements (randomly selected) were performed two times at an interval of 4 weeks by the same investigator to evaluate the consistency.

The health, success, and survival status of the implants were also measured. The health status of the implants was determined according to the 4‐scale criteria defined by consensus decisions of The International Congress of Oral Implantologists [9] using clinical and radiographic data. Clinical conditions for scale 1 (success, optimum health) are no pain, no mobility, no bleeding and/or exudate on probing, and < 2 mm MBL; clinical conditions for scale 2 (satisfactory survival) are the same as scale 1 and 2–4 mm MBL; clinical conditions for scale 3 (compromised survival) are no mobility, may have pain and exudate, PD > 7 mm, and MBL > 4 mm (less than ½ of implant length); and clinical conditions for scale 4 (failure) are pain, mobility, uncontrolled exudate, MBL > ½ of implant length, or any implant that is no longer in the mouth. The implant survival rate was defined as the percentage of the implants remaining in place and in function at the follow‐up recall. The implant success was considered as a healthy peri‐implant condition and no major prosthetic complication (screw or implant fracture). The implant success rate was defined as the percentage of the implants showing the following success criteria defined by Papaspyridakos et al. [7]: (1) demonstrating the absence of peri‐implant signs of inflammation, (2) no bleeding on probing, (3) PD ≤ 3 mm, (4) bone loss < 2 mm, (5) no major prosthetic complication. These criteria are also in accordance with scale 1 (success) of the consensus decision of the International Congress of Oral Implantologists [9]. The incidence of peri‐implant mucositis and peri‐implantitis was also calculated. The definitions of peri‐implant mucositis and peri‐implantitis were made based on the consensus report of workgroup 4 of the 2017 World Workshop on the Classification of Periodontal and Peri‐implant Diseases and Conditions [18]. The peri‐implant mucositis was diagnosed in the presence of bleeding and/or suppuration on gentle probing with increased probing depth (PD > 4 mm) and absence of bone loss beyond crestal bone level changes resulting from initial bone remodeling. The peri‐implantitis was diagnosed in the presence of bleeding and/or suppuration on gentle probing with increased probing depth (PD ≥ 6 mm) and presence of bone loss (bone levels ≥ 3 mm apical of the most coronal portion of the intra‐osseous part of the implant). The time between implant‐supported restoration delivery and data collection was recorded as follow‐up time.

2.4. Pink Esthetic Score (PES)

In our study, the PES was collected to assess peri‐implant soft‐tissue esthetic as described by Fürhauser et al. [17] Intra‐oral photographs of the implant‐supported restorations were taken using a digital camera (Canon EOS 80D, Canon Inc., Tokyo, Japan) with a twin lite flash and following camera settings: ISO 100, f/22, shutter speed of 1/200 s, 1:3 magnification. The following seven variables of the implant‐supported restorations were evaluated by an experienced faculty (U.T) versus the symmetrical or adjacent reference tooth: mesial papilla, distal papilla, soft‐tissue level, soft‐tissue contour, alveolar process deficiency, soft‐tissue color, and texture. Using a 0‐1‐2 scoring system, 0 being the lowest and 2 being the highest value, mean and total values of the 7 parameters were also recorded for each restoration.

2.5. Radiographic Examination

Peri‐implant marginal bone level was calculated from the implant neck to the crestal bone level using standardized digital periapical radiography. To provide standardization, periapical radiographs were taken with the long‐cone parallel technique with a film holder, perpendicular beam to the implant axis, and all radiographs were taken with the same parameters (60 kVp, 10 mA, and 0.3 s) using digital films (Kavo scan exam, Kavo Dental GmbH, Germany). Radiologic measurements were performed using an image analysis software (Image J, version 1.33u, National Institute of Health, Bethesda, MD, USA). To eliminate the effects of distortion and magnification, the radiographs were digitally calibrated in two dimensions using the known implant diameter and length. The MBL was evaluated in three parameters: vertical MBL, horizontal MBL, and MBL area. Mesial values, distal values, and mean values were measured for all three parameters per implant. First, mesial and distal edges of the implant shoulder were identified and then a line was drawn between the designated two points and used as a landmark line. Vertical MBL was determined by measuring the vertical distance (mm) between this line and the most coronal (first) bone‐to‐implant contact point. Horizontal MBL was determined by measuring the horizontal distance (mm) perpendicular to the implant long axis between the implant neck (landmark line) and the most coronal part of the crestal bone. In other words, horizontal MBL was defined as the horizontal distance from the shoulder of the implant to the internal border of the socket/defect. MBL area was determined by measuring the area (mm2) among horizontal reference point, vertical reference point, and implant neck (Figure 2). Radiographic bone measurements at the time of implant placement were compared with those at the time of the last follow‐up recall, and bone loss was calculated. The mesial, distal, and averaged measurements were recorded. The 10% of the radiographic measurements (randomly selected) were performed two times at an interval of 4 weeks by the same investigator who was unaware of the study groups of the individuals to evaluate the consistency.

FIGURE 2.

FIGURE 2

Measurement of marginal bone loss (MBL). The MBL was evaluated in three parameters: Vertical MBL, horizontal MBL, and MBL area. Vertical MBL was determined by measuring the vertical distance (mm) between the implant neck and the most coronal bone‐to‐implant contact point. Horizontal MBL was determined by measuring the horizontal distance (mm) perpendicular to the implant long axis between the implant neck and the most coronal part of crestal bone. MBL area was determined by measuring the area (mm2) among horizontal reference point, vertical reference point, and implant neck.

2.6. Statistical Analysis

SPSS software (IBM SPSS for Mac, version 29.0.2.0) was used for statistical analysis, and the level of significance was set at p < 0.05. Demographic variables were compared using the t test and chi‐square test. Cronbach's alpha was used to evaluate the consistency in clinical and radiographic measurements. Cronbach's alpha value greater than 0.8 was considered a high level of consistency. Clinical and radiographic variables between the augmentation group and control group were compared using the t test and chi‐square test. Comparison among augmentation groups was made using ANOVA, and a Bonferroni‐corrected post hoc test was used for pairwise comparisons. Chi‐square and Fisher's exact tests were used to compare implant health status, survival, and success rates. Logistic regression was performed to analyze the relationship between variables on the occurrence of peri‐implantitis and failure rates, and to determine the p‐values, the relative risk (odds ratio), and the 95% confidence interval of the variables. Kaplan–Meier survival analysis and the Mantel‐Cox log‐rank test were used to test the difference in cumulative implant survival curves among augmentation techniques.

3. Results

A total of 764 patients, consisting of 382 males and 382 females, with 764 implants (Mean follow‐up period: 5.98 ± 3.07 years, range: 1.25–10 years, median: 4.5 years) were included in the study. Among the implants, 364 were in the bone augmentation group and 400 were in the control group. The clinical and radiographic measurements showed a high level of consistency (Cronbach's alpha values > 0.8). Patient‐ and implant‐related baseline characteristics were presented in Table 1. Regarding baseline characteristics, there were no statistically significant differences between the augmentation and control groups.

TABLE 1.

Patient‐ and implant‐related baseline characteristics.

Characteristics Augmentation (n = 364) Control (n = 400) p
Patient‐related characteristics
Gender (male/female) 180/184 202/198 0.772
Age (mean ± SD) 57.22 ± 10.85 58.18 ± 10.71 0.222
Smoking (smoker/non) 122/242 148/252 0.314
Follow‐up, month (mean ± SD) 72.16 ± 36.75 71.30 ± 36.97 0.747
Implant‐related characteristics
Implant diameter [N (%)] 0.292
Narrow (3.25–3.75 mm) 131 (35.99) 164 (41.00)
Regular (3.8–4.2 mm) 152 (41.76) 147 (36.75)
Wide (4.3–5.8 mm) 81 (22.25) 89 (22.25)
Implant length [N (%)] 0.093
Standard (8–12 mm) 357 (98.08) 384 (96.00)
Short (< 8 mm) 7 (1.92) 16 (4.00)
Implant brand [N (%)] 0.392
Biohorizons 114 (31.32) 122 (30.50)
Dentium 145 (39.83) 145 (36.25)
Nucleoss 105 (28.85) 133 (33.25)
Anatomical location [N (%)] 0.100
Anterior maxilla 54 (14.84) 62 (15.50)
Posterior maxilla 192 (52.75) 179 (44.75)
Anterior mandible 22 (6.04) 37 (9.25)
Posterior mandible 96 (26.37) 122 (30.50)
Type of prosthesis 0.392
Single crown 224 (61.54) 234 (58.50)
Bridge 140 (38.46) 166 (41.50)

Comparison of the study parameters, including clinical, radiographic, and esthetic parameters, as well as health, survival, and success parameters between augmentation and control groups, was shown in Table 2. Regarding clinical parameters, the mean PI scores of the implants were 0.85 ± 0.74 in the augmentation group and 0.81 ± 0.69 in the control group, which was statistically comparable (p = 0.365). The mean GI scores of the implants were 1.61 ± 0.50 in the augmentation group and 1.56 ± 0.53 in the control group, which was statistically comparable (p = 0.230). The mean PD scores of the implants were 2.82 ± 1.22 in the augmentation group and 2.54 ± 1.29 in the control group, and the difference was statistically significant (p = 0.002). Bleeding on probing occurred in 17.03% of the implants in the augmentation group and 14.5% of the implants in the control group, which was statistically comparable (p = 0.371).

TABLE 2.

Comparison of study parameters (mean ± SD) between augmentation and control groups.

Study parameters Augmentation (n = 364) Control (n = 400) p
Clinical parameters
PI 0.85 ± 0.74 0.81 ± 0.69 0.365
GI 1.61 ± 0.50 1.56 ± 0.53 0.230
PD 2.82 ± 1.22 2.54 ± 1.29 0.002
BOP 17.03% (62/364) 14.5% (58/400) 0.371
Radiographic parameters
Mesial vertical MBL (mm) 0.74 ± 0.74 0.78 ± 0.85 0.327
Mesial horizontal MBL (mm) 0.32 ± 0.35 0.37 ± 0.52 0.123
Mesial MBL area (mm2) 0.19 ± 0.43 0.26 ± 0.84 0.188
Distal vertical MBL (mm) 0.82 ± 0.80 0.84 ± 0.91 0.684
Distal horizontal MBL (mm) 0.32 ± 0.34 0.35 ± 0.43 0.334
Distal MBL area (mm2) 0.21 ± 0.53 0.25 ± 0.59 0.402
Mean vertical MBL (mm) 0.78 ± 0.70 0.82 ± 0.82 0.461
Mean horizontal MBL (mm) 0.32 ± 0.28 0.36 ± 0.42 0.144
Mean MBL area (mm2) 0.20 ± 0.40 0.25 ± 0.62 0.197
Esthetic parameters
PES 1 (Mesial papilla) 1.18 ± 0.38 1.48 ± 0.50 < 0.001
PES 2 (Distal papilla) 1.10 ± 0.29 1.35 ± 0.48 < 0.001
PES 3 (Soft tissue margin) 1.18 ± 0.38 1.41 ± 0.49 < 0.001
PES 4 (Soft tissue contour) 1.21 ± 0.40 1.44 ± 0.50 < 0.001
PES 5 (Alveolar process) 1.24 ± 0.43 1.52 ± 0.50 < 0.001
PES 6 (Soft tissue color) 1.31 ± 0.46 1.49 ± 0.50 < 0.001
PES 7 (Soft tissue texture) 1.09 ± 0.29 1.34 ± 0.47 < 0.001
PES mean 1.18 ± 0.22 1.43 ± 0.35 < 0.001
PES total 8.30 ± 1.55 10.04 ± 2.43 < 0.001
Health, success, survival parameters
Health scores (mean ± SD) 1.26 ± 0.62 1.23 ± 0.63 0.569
Cumulative survival rate (%) 99.18 98.00 0.228
Cumulative success rate (%) 82.97 85.50 0.389

Abbreviations: BOP, bleeding on probing; GI, gingival index; MBL, marginal bone loss; PD, probing depth; PES, pink esthetic score; PI, plaque index.

Regarding radiographic parameters, the mean vertical bone loss of the implants was 0.78 ± 0.70 in the augmentation group and 0.82 ± 0.82 in the control group, which was statistically comparable (p = 0.461). The implants placed in augmented and native bone showed comparable results in all radiographic parameters (All p > 0.05, the detailed mean ± standard deviation value and p‐value for each parameter were shown in Table 2).

Considering the esthetic parameters, the mean PES total values of the implants were 8.30 ± 1.55 in the augmentation group and 10.04 ± 2.43 in the control group, and the difference was statistically significant (p < 0.001). The implants placed in augmented bone showed significantly lower PES scores in all aspects compared to those placed in native bone (All p < 0.05, the detailed mean ± standard deviation value and p‐value for each esthetic parameter were shown in Table 2).

In implant health status, mean health scores of augmentation and control groups were 1.26 ± 0.62 and 1.23 ± 0.63, respectively, showing statistically similar results (p = 0.569). In a follow‐up period of up to 10 years (mean 5.98 years), there were no significant differences between augmentation and control groups in implant survival (99.18% vs. 98.00%, p = 0.228) and success (82.97% vs. 85.50%, p = 0.389) rates.

For the detailed analysis of the augmentation techniques, a total of four study groups, including the control group (no augmentation) and three augmentation groups (GBR, ridge split, and onlay) were compared in terms of study parameters. Comparison of PI scores of GBR (0.93 ± 0.69), ridge split (0.95 ± 0.79), onlay (0.67 ± 0.72), and control (0.81 ± 0.69) groups showed statistically significant differences (p = 0.006) (Table 3). In pairwise comparison, the GBR group showed statistically significantly higher PI scores compared to the onlay group (p = 0.026). The ridge split group showed statistically significantly higher PI scores compared to the onlay group (p = 0.013) (Table 4).

TABLE 3.

Comparison of clinical parameters (mean ± SD) among study groups.

Clinical parameters Augmentation procedures p
GBR (n = 127) Ridge split (n = 123) Onlay (n = 114) Control (n = 400)
PI 0.93 ± 0.69 0.95 ± 0.79 0.67 ± 0.72 0.81 ± 0.69 0.006
GI 1.63 ± 0.48 1.70 ± 0.46 1.49 ± 0.55 1.56 ± 0.53 0.010
PD 2.50 ± 1.17 3.08 ± 1.18 2.90 ± 1.25 2.54 ± 1.29 < 0.001
BOP 14.96% (19/127) 20.32% (25/123) 15.79% (18/114) 14.5% (58/400) 0.480

Note: Abbreviations were given in Table 2.

TABLE 4.

Multiple comparison results of the clinical parameters among study groups.

Parameter Group I Group II Mean difference Standard error p 95% CI
PI GBR Ridge split −0.02209 0.08987 1.000 −0.2598, 0.2156
Onlay 0.26247* 0.09166 0.026 0.0200, 0.5049
Control 0.12163 0.07236 0.559 −0.0698, 0.3130
Ridge split Onlay 0.28455* 0.09236 0.013 0.0402, 0.5289
Control 0.14372 0.07325 0.301 −0.0500, 0.3375
Onlay Control −0.14083 0.07543 0.374 −0.3403, 0.0587
GI GBR Ridge split −0.06927 0.06494 1.000 −0.2410, 0.1025
Onlay 0.13869 0.06623 0.220 −0.0365, 0.3139
Control 0.06492 0.05229 1.000 −0.0734, 0.2032
Ridge split Onlay 0.20796* 0.06674 0.011 0.0314, 0.3845
Control 0.13419 0.05293 0.069 −0.0058, 0.2742
Onlay Control −0.07377 0.05450 1.000 −0.2179, 0.0704
PD GBR Ridge split −0.57933* 0.15793 0.002 −0.9971, −0.1616
Onlay −0.39715 0.16106 0.083 −0.8232, 0.0289
Control −0.04241 0.12715 1.000 −0.3787, 0.2939
Ridge split Onlay 0.18218 0.16229 1.000 −0.2471, 0.6115
Control 0.53693* 0.12871 < 0.001 0.1965, 0.8774
Onlay Control 0.35475* 0.13254 0.046 0.0042, 0.7053

Note: Abbreviations were given in Table 2.

*

The mean difference is statistically significant.

Comparison of GI scores of GBR (1.63 ± 0.48), ridge split (1.70 ± 0.46), onlay (1.49 ± 0.55), and control (1.56 ± 0.53) groups showed statistically significant differences (p = 0.010) (Table 3). In pairwise comparison, the ridge split group showed statistically significantly higher GI scores compared to the onlay group (p = 0.011) (Table 4).

Comparison of PD scores of GBR (2.50 ± 1.17), ridge split (3.08 ± 1.18), onlay (2.90 ± 1.25), and control (2.54 ± 1.29) groups showed statistically significant differences (p < 0.001) (Table 3). In pairwise comparison, the ridge split group showed statistically significantly higher PD scores compared to the GBR and control groups (p = 0.002 and p < 0.001, respectively). The onlay group showed statistically significantly higher PD scores compared to the control group (p = 0.046) (Table 4).

Comparison of BOP values of GBR (14.96%), ridge split (20.32%), onlay (15.79%), and control (14.5%) groups showed statistically similar results (p = 0.480) (Table 3).

Comparison of mean vertical bone loss of GBR (0.76 ± 0.72), ridge split (0.80 ± 0.71), onlay (0.78 ± 0.68), and control (0.82 ± 0.82) groups showed statistically similar results (p = 0.877). Comparison of MBL among augmentation groups showed comparable results in all radiographic parameters (All p > 0.05, the detailed mean ± standard deviation value and p‐value for each radiographic parameter were shown in Table 5).

TABLE 5.

Comparison of radiographic parameters (mean ± SD) among study groups.

Radiographic parameters Augmentation procedures p
GBR (n = 127) Ridge split (n = 123) Onlay (n = 114) Control (n = 400)
Mesial vertical MBL (mm) 0.71 ± 0.72 0.76 ± 0.75 0.74 ± 0.75 0.79 ± 0.85 0.738
Mesial horizontal MBL (mm) 0.31 ± 0.33 0.35 ± 0.38 0.31 ± 0.34 0.37 ± 0.52 0.389
Mesial MBL area (mm2) 0.18 ± 0.37 0.20 ± 0.42 0.19 ± 0.49 0.26 ± 0.84 0.619
Distal vertical MBL (mm) 0.82 ± 0.85 0.83 ± 0.80 0.81 ± 0.74 0.85 ± 0.91 0.975
Distal horizontal MBL (mm) 0.32 ± 0.40 0.33 ± 0.29 0.31 ± 0.32 0.35 ± 0.43 0.789
Distal MBL area (mm2) 0.25 ± 0.76 0.20 ± 0.35 0.18 ± 0.35 0.25 ± 0.59 0.661
Mean vertical MBL* (mm) 0.76 ± 0.72 0.80 ± 0.71 0.78 ± 0.68 0.82 ± 0.82 0.877
Mean horizontal MBL (mm) 0.31 ± 0.31 0.34 ± 0.28 0.31 ± 0.26 0.36 ± 0.42 0.460
Mean MBL area (mm2) 0.22 ± 0.50 0.20 ± 0.34 0.19 ± 0.33 0.25 ± 0.62 0.609

Note: Abbreviations were given in Table 2.

Comparison of PES total values of GBR (8.16 ± 1.35), ridge split (8.29 ± 1.60), onlay (8.46 ± 1.71), and control (10.04 ± 2.43) groups showed statistically significant differences (p < 0.001) (Table 6). Comparison of esthetic parameters among study groups showed statistically significantly different results in all PES parameters (All p < 0.05, the detailed mean ± standard deviation value and p‐value for each PES parameter were shown in Table 6). Multiple comparison results of the esthetic parameters among study groups were shown in Table 7. In pairwise comparisons, the control group showed statistically significantly higher scores compared to all augmentation groups (GBR, ridge split, and onlay) in all PES parameters. All augmentation groups (GBR, ridge split, and onlay) showed similar values in all PES parameters (The detailed p‐values for each PES parameter were shown in Table 7).

TABLE 6.

Comparison of esthetic parameters (mean ± SD) among study groups.

Esthetic parameters Augmentation procedures p
GBR (n = 127) Ridge split (n = 123) Onlay (n = 114) Control (n = 400)
PES 1 (Mesial papilla) 1.24 ± 0.43 1.18 ± 0.38 1.11 ± 0.32 1.48 ± 0.50 < 0.001
PES 2 (Distal papilla) 1.04 ± 0.19 1.12 ± 0.33 1.13 ± 0.34 1.35 ± 0.48 < 0.001
PES 3 (Soft tissue margin) 1.14 ± 0.35 1.18 ± 0.38 1.22 ± 0.42 1.41 ± 0.49 < 0.001
PES 4 (Soft tissue contour) 1.18 ± 0.39 1.19 ± 0.40 1.25 ± 0.43 1.44 ± 0.50 < 0.001
PES 5 (Alveolar process) 1.19 ± 0.39 1.24 ± 0.43 1.31 ± 0.46 1.52 ± 0.50 < 0.001
PES 6 (Soft tissue color) 1.31 ± 0.46 1.27 ± 0.44 1.35 ± 0.48 1.49 ± 0.50 < 0.001
PES 7 (Soft tissue texture) 1.07 ± 0.26 1.11 ± 0.32 1.09 ± 0.28 1.34 ± 0.47 < 0.001
PES mean 1.16 ± 0.20 1.18 ± 0.23 1.21 ± 0.24 1.43 ± 0.35 < 0.001
PES total 8.16 ± 1.35 8.29 ± 1.60 8.46 ± 1.71 10.04 ± 2.43 < 0.001

Note: Abbreviations were given in Table 2.

TABLE 7.

Multiple comparison results of the esthetic parameters among study groups.

Parameter Group I Group II Mean difference Standard error p 95% CI
PES 1 GBR Ridge split 0.05736 0.05663 1.000 −0.0924, 0.2072
Onlay 0.12219 0.05775 0.208 −0.0306, 0.2750
Control −0.24128* 0.04559 < 0.001 −0.3619, −0.1207
Ridge split Onlay 0.06483 0.05820 1.000 −0.0891, 0.2188
Control −0.29864* 0.04615 < 0.001 −0.4207, −0.1766
Onlay Control −0.36346* 0.04753 < 0.001 −0.4892, −0.2377
PES 2 GBR Ridge split −0.08258 0.05062 0.619 −0.2165, 0.0513
Onlay −0.09221 0.05163 0.447 −0.2288, 0.0444
Control −0.30813* 0.04076 < 0.001 −0.4159, −0.2003
Ridge split Onlay −0.00963 0.05202 1.000 −0.1472, 0.1280
Control −0.22555* 0.04126 < 0.001 −0.3347, −0.1146
Onlay Control −0.21592* 0.04248 < 0.001 −0.3283, −0.1035
PES 3 GBR Ridge split −0.03713 0.05623 1.000 −0.1859, 0.1116
Onlay −0.07757 0.05735 1.000 −0.2293, 0.0741
Control −0.27327* 0.04527 < 0.001 −0.3930, −0.1535
Ridge split Onlay −0.04044 0.05778 1.000 −0.1933, 0.1124
Control −0.23614* 0.04583 < 0.001 −0.3574, −0.1149
Onlay Control −0.19570* 0.04719 < 0.001 −0.3205, −0.0709
PES 4 GBR Ridge split −0.01402 0.05769 1.000 −0.1666, 0.1386
Onlay −0.06451 0.05884 1.000 −0.2202, 0.0911
Control −0.26390* 0.04645 < 0.001 −0.3868, −0.1410
Ridge split Onlay −0.05049 0.05929 1.000 −0.2073, 0.1063
Control −0.24988* 0.04702 < 0.001 −0.3743, −0.1255
Onlay Control −0.19939* 0.04842 < 0.001 −0.3275, −0.0713
PES 5 GBR Ridge split −0.04680 0.05907 1.000 −0.2031, 0.1095
Onlay −0.11804 0.06025 0.303 −0.2774, 0.0413
Control −0.33102* 0.04756 < 0.001 −0.4568, −0.2052
Ridge split Onlay −0.07125 0.06071 1.000 −0.2318, 0.0893
Control −0.28423* 0.04814 < 0.001 −0.4116, −0.1569
Onlay Control −0.21298* 0.04958 < 0.001 −0.3441, −0.0818
PES 6 GBR Ridge split 0.03869 0.06107 1.000 −0.1228, 0.2003
Onlay −0.04379 0.06229 1.000 −0.2085, 0.1210
Control −0.18791* 0.04917 < 0.001 −0.3180, −0.0578
Ridge split Onlay −0.08258 0.06276 1.000 −0.2486, 0.0834
Control −0.22671* 0.04977 < 0.001 −0.3584, −0.0950
Onlay Control −0.14412* 0.05125 0.030 −0.2797, −0.0085
PES 7 GBR Ridge split −0.04295 0.05026 1.000 −0.1759, 0.0900
Onlay −0.01685 0.05126 1.000 −0.1524, 0.1187
Control −0.27163* 0.04047 < 0.001 −0.3787, −0.1646
Ridge split Onlay 0.02610 0.05165 1.000 −0.1105, 0.1627
Control −0.22868* 0.04096 < 0.001 −0.3370, −0.1203
Onlay Control −0.25478* 0.04218 < 0.001 −0.3664, −0.1432
PES mean GBR Ridge split −0.01991 0.03727 1.000 −0.1185, 0.0787
Onlay −0.04327 0.03801 1.000 −0.1438, 0.0573
Control −0.26967* 0.03001 < 0.001 −0.3490, −0.1903
Ridge split Onlay −0.02335 0.03830 1.000 −0.1247, 0.0780
Control −0.24976* 0.03037 < 0.001 −0.3301, −0.1694
Onlay Control −0.22640* 0.03128 < 0.001 −0.3091, −0.1437
PES total GBR Ridge split −0.13520 0.26068 1.000 −0.8247, 0.5543
Onlay −0.29866 0.26585 1.000 −1.0019, 0.4046
Control −1.88502* 0.20987 < 0.001 −2.4402, −1.3299
Ridge split Onlay −0.16346 0.26789 1.000 −0.8721, 0.5452
Control −1.74982* 0.21245 < 0.001 −2.3118, −1.1879
Onlay Control −1.58636* 0.21877 < 0.001 −2.1650, −1.0077
*

The mean difference is statistically significant.

The detailed distributions of the implants for each augmentation group in all health scales were shown in Table 8. The mean health scores of the GBR (1.20 ± 0.54), ridge split (1.31 ± 0.67), onlay (1.26 ± 0.65), and control (1.23 ± 0.63) groups were statistically comparable (p = 0.557). The distribution of implants in all augmentation groups was also statistically similar in all scales (p = 0.479 for scale 1, p = 0.514 for scale 2, p = 0.133 for scale 3, p = 0.601 for scale 4) (Table 8).

TABLE 8.

Distribution of implants according to the health scales and comparison of the mean health scores (mean ± SD) in different augmentation groups.

Augmentation Health scales Mean health score
Groups 1 2 3 4
GBR (n = 127) 108 (85.04%) 13 (10.23%) 5 (3.94%) 1 (0.79%) 1.20 ± 0.54
Ridge split (n = 123) 98 (79.68%) 13 (10.57%) 11 (8.94%) 1 (0.81%) 1.31 ± 0.67
Onlay (n = 114) 96 (84.21%) 7 (6.14%) 10 (8.77%) 1 (0.88%) 1.26 ± 0.65
Control (n = 400) 342 (85.50%) 31 (7.75%) 19 (4.75%) 8 (2.00%) 1.23 ± 0.63
p 0.479 0.514 0.133 0.601 0.557

Note: Health scales: 1, optimum health; 2, satisfactory survival; 3, compromised survival; 4, failure.

Considering all implants, the rates of peri‐implant mucositis were 10.21% (78/764) and peri‐implantitis was 5.50% (42/764) in a mean follow‐up period of 5.98 years. The incidence of peri‐implant mucositis and peri‐implantitis in each augmentation group was shown in Figure 3. The rates of peri‐implant mucositis were 11.02% (14/127) in GBR, 13.82% (17/123) in ridge split, 11.40% (13/114) in onlay, and 8.50% (34/400) in control groups. The rates of peri‐implant mucositis were statistically comparable among augmentation groups (p = 0.348). The rates of peri‐implantitis were 3.94% in GBR (5/127), 6.5% in ridge split (8/123), 4.39% (5/114) in onlay, and 6.00% (24/400) in control groups. The rates of peri‐implantitis were statistically comparable among augmentation groups (p = 0.729).

FIGURE 3.

FIGURE 3

The incidence of peri‐implant mucositis and peri‐implantitis in different augmentation groups.

In total, 11 out of 764 implants (1.44%) failed; 3 implants (0.82%) were in the augmentation group and 8 (2.00%) implants were in the control group. One implant in the augmentation group (Ridge split group, 9.42 years after loading) and 1 implant in the control group (9.75 years after loading) were lost due to biomechanical complications (implant fracture). The other implants were lost due to biological complications (peri‐implantitis). The significance of study variables for peri‐implantitis and implant failure was shown in Table 9. Considering all patients, peri‐implantitis was significantly related to location (p = 0.031) and prosthesis type (p < 0.001). Implant failure was significantly related to smoking (p = 0.048), location (p = 0.049), and prosthesis type (p = 0.026). The bone augmentation did not show significant effects on the rates of peri‐implantitis (p = 0.523) and implant failure (p = 0.173).

TABLE 9.

Significance of study variables for peri‐implantitis and implant failure.

Variable Peri‐implantitis Failure
Yes No p Yes No p
Gender 0.204 0.362
Male (n = 382) 17 (4.45%) 365 (95.55%) 7 (1.83%) 375 (98.17%)
Female (n = 382) 25 (6.54%) 357 (93.46%) 4 (1.05%) 378 (98.95%)
Smoking 0.167 0.048*
Yes (n = 270) 19 (7.04%) 251 (92.96%) 7 (2.59%) 263 (97.41%)
No (n = 494) 23 (4.66%) 471 (95.34%) 4 (0.81%) 490 (99.19%)
Location 0.031* 0.049*
Maxilla (n = 432) 17 (3.93%) 415 (96.07%) 3 (0.69%) 429 (99.31%)
Mandible (n = 332) 25 (7.53%) 307 (92.47%) 8 (2.41%) 324 (97.59%)
Prosthesis type < 0.001* 0.026*
Crown (n = 458) 12 (2.62%) 446 (97.38%) 3 (0.65%) 455 (99.35%)
Bridge (n = 306) 30 (9.80%) 276 (90.20%) 8 (2.61%) 298 (97.39%)
Augmentation 0.523 0.173
Yes (n = 364) 18 (4.94%) 346 (95.06%) 3 (0.82%) 361 (99.18%)
No (n = 400) 24 (6.00%) 376 (94.00%) 8 (2.00%) 392 (98.00%)
*

Statistically significant.

A multiple logistic regression analysis was performed to determine the effects of significant variables from Table 9 on the outcomes of peri‐implantitis and implant failure. Since patients with missing data were excluded from the study, there was no missing data in the regression model. The evaluated parameters for logistic regression were location (maxilla vs. mandible) and prosthesis type (single crown vs. bridge) for peri‐implantitis. The evaluated parameters were smoking status (yes vs. no), location (maxilla vs. mandible), and prosthesis type (single crown vs. bridge) for implant failure. In this model, the risk of peri‐implantitis was significantly increased in the mandible (OR = 1.92, p = 0.046) and bridge prosthesis (OR = 3.97, p < 0.001). The risk of implant failure was significantly raised in smokers (OR = 3.50, p = 0.049) and bridge prosthesis (OR = 4.10, p = 0.040). The variable location was no longer statistically significant in this model (p = 0.063). After adjusting the model for bone augmentation, only bridge prosthesis increased the risk of peri‐implantitis (OR = 3.97, p < 0.001). In the adjusted model for bone augmentation, smoking (OR = 3.53, p = 0.048) and bridge prosthesis (OR = 4.10, p = 0.040) increased the risk of implant failure (Table 10).

TABLE 10.

Multiple logistic regression with the occurrence of a “peri‐implantitis” and “implant failure” as dependent variables.

Outcome Unadjusted Adjusted a
Variable OR (95% CI) p Variable OR a (95% CI) p
Peri‐implantitis Location Location
Maxilla 1.0 [Reference] Maxilla 1.0 [Reference]
Mandible 1.92 (1.01–3.64) 0.046* Mandible 1.91 (0.98–3.67) 0.054
Prosthesis Prosthesis
Single crown 1.0 [Reference] Single crown 1.0 [Reference]
Bridge 3.97 (1.99–7.89) < 0.001* Bridge 3.97 (1.99–7.87) < 0.001*
Bone Augmentation
No 1.0 [Reference]
Yes 0.97 (0.51–1.87) 0.938
Implant failure Smoking Smoking
No 1.0 [Reference] No 1.0 [Reference]
Yes 3.50 (1.00–12.21) 0.049* Yes 3.53 (1.00–12.34) 0.048*
Location Location
Maxilla 1.0 [Reference] Maxilla 1.0 [Reference]
Mandible 3.57 (0.93–13.70) 0.063 Mandible 3.24 (0.83–12.66) 0.090
Prosthesis Prosthesis
Single crown 1.0 [Reference] Single crown 1.0 [Reference]
Bridge 4.10 (1.07–15.62) 0.040* Bridge 4.10 (1.07–15.62) 0.040*
Bone Augmentation
No 1.0 [Reference]
Yes 1.90 (0.49–7.41) 0.355

Note: The independent variables are “location (maxilla vs mandible)” and “prosthesis type (crown vs. bridge)” for peri‐impantitis; “smoking”, “location (maxilla vs. mandible)”, and “prosthesis type (crown vs. bridge)” for implant failure. Multi‐variable model is adjusted for bone augmentation. Nagelkerke pseudo R 2 is 0.082 for peri‐implantitis and 0.117 for implant failure in unadjusted model. Nagelkerke pseudo R 2 is 0.082 for peri‐implantitis and 0.125 for implant failure in adjusted model.

Abbreviations: CI, confidence interval; OR, odds ratio.

a

Multivariable model adjusted for bone augmentation.

*

Statistically significant.

Cumulative survival rates of the implants in the control (Mean follow‐up: 5.94 ± 3.08 years, median: 4.58 years, range: 1.25–10 years) and augmentation (Mean follow‐up: 6.01 ± 3.06 years, median: 4.29 years, range: 1.25–10 years) groups were shown in Table 11. Three time periods were defined: early‐term (1–3 years), mid‐term (3–5 years), and long‐term (5–10 years). The cumulative survival rates of the implants in the control (98.68%) and augmentation (99.50) groups were statistically comparable up to 5‐year (Mean 3.44 years) follow‐up (p = 0.626). The cumulative survival rates of the control (98.00%) and augmentation (99.18%) groups were statistically comparable up to 10‐year (Mean 5.98 years) follow‐up (p = 0.228). The detailed p values for survival rates within each defined duration and cumulative survival rates were shown in Table 11. The Kaplan–Meier cumulative survival curves of implants in the different augmentation groups were shown in Figure 4. The cumulative survival and success rates of the implants in GBR (99.21% and 85.04%, respectively), ridge split (99.19% and 79.68%, respectively), onlay (99.12% and 84.21%, respectively), and control (98.00% and 85.50%, respectively) groups were statistically similar (p = 0.630 and p = 0.479, respectively) in the 5.98‐year mean follow‐up (Table 12).

TABLE 11.

Cumulative survival rates of implants in the control and augmentation groups up to 10 years.

Year Control (n = 400) Augmentation (n = 364) P1/P2
Implant (n) Failed (n) SR (%) CRS (%) Implant (n) Failed (n) SR (%) CRS (%)
1–3 95 0 100 100 67 0 100.00 100.00 1.000/1.000
3–5 132 3 97.73 98.68 134 1 99.25 99.50 0.368/0.626
5–10 173 5 97.11 98.00 163 2 98.77 99.18 0.449/0.228

Abbreviations: CSR, cumulative survival rate. P1, p‐value for comparison of SR; P2, p‐value for comparison of CSR; SR, survival rate within defined duration.

FIGURE 4.

FIGURE 4

Kaplan–Meier cumulative survival curves up to 10‐year for implants placed in native bone and with different bone augmentation techniques (Log‐rank test = 1.733, df = 3, p = 0.630).

TABLE 12.

Comparison of cumulative implant survival and success rates among augmentation groups.

Implant success Augmentation procedures p
GBR (n = 127) Ridge split (n = 123) Onlay (n = 114) Control (n = 400)
Survival rate (%) 99.21 99.19 99.12 98.00 0.630
Success rate (%) 85.04 79.68 84.21 85.50 0.479

4. Discussion

Alveolar bone atrophy following tooth loss causes difficulties in implant placement and may decrease treatment success. In cases where residual alveolar ridge height and width are insufficient, bone augmentation techniques are used for successful implant treatment. This retrospective clinical study revealed the effects of frequently used bone augmentation techniques on peri‐implant tissues, implant success, and survival rates after a mean follow‐up period of 6 years.

In the present study, the impact of three different bone augmentation techniques on implant treatment was analyzed and compared with implants placed in natural bone under six aspects: clinical, radiographic, esthetic, health status, survival, and success. In our study, while GI, PI, and BOP values were comparable between two groups (augmentation vs. control), statistically significantly increased PD values were measured in the augmentation group compared to the control group. However, a 0.28 mm difference in PD may not be clinically significant.

Peri‐implant bone loss is one of the important parameters to assess implant success. The present study revealed that implants placed in augmented bone showed similar and stable MBL values in vertical, horizontal, and area units compared to those placed in native bone. Moreover, all augmentation groups showed similar results in all radiographic parameters. Usually, vertical bone loss is considered to evaluate implant success and peri‐implant health status. In our study, we also assessed horizontal bone loss and bone loss area. These detailed radiographic parameters could give more information about the extent of the bone loss and might have an impact on clinical practice in terms of treatment strategies for these bone defects.

The implant should have an esthetic restoration in addition to meeting biological success criteria to be assessed as successful. Considering the increasing esthetic expectations of patients today, esthetic criteria have become crucial when assessing success. Fürhauser et al. [17] defined the PES as an objective method to assess peri‐implant soft tissue by evaluating the esthetic appearance of implant‐supported single crowns using 7 parameters. In our study, PES parameters of the implant‐supported restorations were measured to evaluate the esthetic outcomes of bone augmentation methods. In our study, significantly decreased PES scores were observed in all aspects in implants placed in augmented bone compared to those placed in native bone, which meant that peri‐implant gingival tissues had an overall worse esthetic appearance in the augmentation group compared to the control group. Similarly, Romito et al. [19] reported the lowest papilla and alveolar process scores following bone augmentation. In comparison among augmentation techniques, all augmentation groups (GBR, ridge split, and onlay) showed comparable esthetic appearance in all PES parameters. Bone augmentation surgeries should not only be planned to provide a sufficient bone amount for implant placement but also to meet esthetic expectations.

It is a controversial issue whether the survival rates of implants placed in augmented bone are at a similar level to implants placed in native bone. Some studies reported lower survival rates for implants placed in augmented bone compared to those placed in native bone [12, 13, 14, 20, 21]. However, some other studies reported similar survival rates for implants placed in natural and augmented bone [5, 22, 23]. In our study, the overall survival rates of implants placed in native and augmented bone were similar (98.00% and 99.18% respectively) after a mean follow‐up time of 5.98 years.

Most of the previous studies assessed only implant survival rates following bone augmentation [4, 5, 13, 21, 24]. In the literature, there are very few studies that evaluate both the success and survival rates of implants placed after bone augmentation techniques [12, 19, 25, 26, 27]. In our study, both survival and success rates of the implants after bone augmentation techniques were compared. Since there are different recognized success criteria, it is difficult to compare the outcomes with different studies. The major difference among different success criteria is the amount of bone loss. This factor should be kept in mind while interpreting the results. In the present study, the implants with < 2 mm MBL were deemed successful and healthy. Chiapasco et al. [27] reported that cumulative survival and success rates were 98.11% and 85.16%, respectively, in 182 implants following reconstruction with mandibular ramus block graft, after a 10‐year mean follow‐ up. Romito et al. [19] reported that implant survival and success rates were 90.9% and 63.6%, respectively, for 22 implants following onlay grafting with mandibular ramus block graft with a mean follow‐up of 22.6 months. In the present study, we observed comparable results with a success rate of 84.21% and a survival rate of 99.12% in 114 implants following bone augmentation with mandibular ramus block graft after a mean 6.53 years follow‐up. Choi et al. [25] reported the survival rate of 95.9% and the success rate of 89.8% in 49 implants placed after GBR during the mean follow‐up period of 67.5 months. Mordenfeld et al. [28] reported a survival rate of 94.4%–100% and a success rate of 91.7%–97.1% following GBR after 2 years of follow‐up. In our study, we observed similar results with a survival rate of 99.21% and a success rate of 85.04% in 127 implants following GBR after the mean follow‐up period of 6.13 years. Tang et al. [26] reported the cumulative survival rate of 100% and a success rate of 95.6% following the ridge split technique after a mean follow‐up period of 2.8 years. In our study, we observed a similar survival rate (99.19%) but a lower success rate (79.68%) following the ridge split technique after a 5.41 years mean follow‐up.

Our study revealed not only the success and survival rates of the implants, but it also showed different health statuses of the implants, including satisfactory and compromised survival rates. In the present study, the health status of the implants was assessed using the health scale defined in The International Congress of Oral Implantologists Consensus Conference [9]. Our results revealed that augmentation techniques did not have a significant impact on the mean health scores of the implants. Similar implant distributions were observed in all health categories (healthy, satisfactory survival, compromised survival, failure) after different augmentation techniques. The prognosis of the implants in scale 2 (Satisfactory survival) depends on close follow‐up and maintenance protocols. The implants in scale 3 (Compromised survival) require surgical treatments and maintenance protocols to provide soft and hard tissue health. The rates of implants in these health scales for each augmentation group are crucial for informing patients, planning maintenance protocols, and achieving long‐term success. Our results also revealed that all augmentation techniques showed similar peri‐implant mucositis and peri‐implantitis rates with each other and also with the control group. Considering all implants, the rates of peri‐implant mucositis were 10.21% and peri‐implantitis were 5.50% in a mean follow‐up period of 5.98 years in our study. French et al. [21] revealed similar rates and reported that the incidence of peri‐implant mucositis was 12.1% and peri‐implantitis was 3.2% at 6–7 years.

The strengths of our study could be summarized as follows: a total of three different augmentation techniques were assessed and compared; esthetic assessment of peri‐implant tissues was performed; MBL values were shown separately for mesial and distal sites, as well as mean values. In addition, MBL values were calculated not only vertically but also horizontally and in area values; implant survival and success rates were evaluated, as well as implant health status and incidence of peri‐implant mucositis and peri‐implantitis. In our study, strict inclusion criteria were applied: patients with simultaneous augmentation and implant placement were not included (except ridge split technique). We included patients in whom the same biomaterials (bovine xenograft and resorbable collagen membrane) and autogenous graft harvested only from the ramus were used in augmentation procedures. Moreover, the implants restored only with a fixed prosthesis (single crown or bridge) were included in the present study. We believe that these strict criteria increase the standardization and evidence level of our study. The insufficient standardization protocols might be the reason for the controversial results in the literature. Considering the weaknesses of the present study, baseline clinical parameters or values from other follow‐ups were not recorded. However, all bone augmentation surgeries and dental implant treatments were performed following regular pre‐operative phase I periodontal therapy (supragingival mechanical debridement of the entire dentition/implants, localized subgingival instrumentation if needed, and reinforcement of oral hygiene) and only in cases of healthy periodontal conditions. Therefore, we can assume that the patients were healthy and had comparable baseline clinical values. The other weaknesses of our study were that the initial defect type, the amount of bone gained, graft resorption, and the amount of keratinized tissue were not assessed in the present study. Further studies including these parameters can make significant contributions to theliterature.

In summary, dental implants placed in augmented bone showed statistically higher probing depth compared to implants placed in native bone, which might not be clinically significant (0.28 mm difference in mean PD). Augmentation group implants showed lower esthetic scores compared to control group implants. There are some differences in clinical parameters among different augmentation techniques; however, all the augmentation groups showed similar success and survival rates after a mean follow‐up period of 5.98 years.

Author Contributions

Ufuk Tatli: conceived the idea, project administration, analyzed the data, led the writing. Ali Cavana: collected the data, review the literature, writing (review and editing). Huseyin Can Tukel: collected the data, validation, writing (review and editing). Mehmet Emre Benlidayi: methodology, supervision, writing (review and editing).

Conflicts of Interest

The authors declare no conflicts of interest.

Acknowledgments

This research received scientific grant from Cukurova University Scientific Research Projects Department with project number TDH‐2019‐12146. The authors would like to thank to Dr. Shengtong Han from Marquette University School of Dentistry for his contributions in statistical analysis.

Funding: This work was supported by Cukurova University Scientific Research Projects Department with project number TDH‐2019‐12146.

Data Availability Statement

The data of the present study are available from the corresponding author upon reasonable request. The data are not available publicly due to ethical restrictions.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

The data of the present study are available from the corresponding author upon reasonable request. The data are not available publicly due to ethical restrictions.


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