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Article

Survival Analysis of Orthodontic Micro-Implants: A Retrospective Study on the Effects of Patient-Related Factors on Micro-Implant Success

by
Jung-Kwang Lee
1,2,
Nayansi Jha
3,
Yoon-Ji Kim
3,4,* and
Dong-Yul Lee
1,5
1
Graduate School of Medicine, Korea University, Seoul 02481, Republic of Korea
2
Good Will Dental Hospital, Busan 46547, Republic of Korea
3
Graduate School of Medicine, University of Ulsan, Seoul 05505, Republic of Korea
4
Department of Orthodontics, Asan Medical Center, University of Ulsan College of Medicine, Seoul 05505, Republic of Korea
5
Seoul KU Orthodontic Clinic, Seongnam 13618, Republic of Korea
*
Author to whom correspondence should be addressed.
Appl. Sci. 2022, 12(22), 11655; https://doi.org/10.3390/app122211655
Submission received: 14 October 2022 / Revised: 13 November 2022 / Accepted: 15 November 2022 / Published: 16 November 2022
(This article belongs to the Special Issue Clinical Applications of Orthodontic TSADs and CBCT)
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Abstract

:
The purpose of this study was to investigate the effects of patient-related factors such as anteroposterior and vertical skeletal patterns and alveolar bone density on the success rate of micro-implants. Cases of orthodontic micro-implants (n = 404; diameter, 1.6 mm; length, 6 mm) were investigated in 164 patients (127 women, 37 men; mean age, 23.6 ± 5.8 years). Cortical bone thickness and alveolar bone density were measured using diagnostic cone-beam computed tomography to examine their effects on the micro-implant’s survival. Moreover, anteroposterior and vertical facial patterns were considered as independent variables for the success of micro-implants. Marginal survival analysis was performed by analyzing the time from implant placement to the removal of the failed micro-implants, or to the end of treatment for successful micro-implants. Variables including age, sex, implantation side, implantation site, root proximity, and type of loading (immediate vs. delayed) were also assessed. In total, 347 (85.9%) of the 404 micro-implants were successful. The mean loading time was 12.4 ± 4.3 months. Marginal survival analysis showed that the effects of the anteroposterior and vertical facial patterns on the risk of failure were not statistically significant. The factors significantly associated with the micro-implant loading time were cortical bone density, root proximity, and micro-implants replanted in the same site. In conclusion, our findings indicate that anteroposterior and vertical skeletal patterns are not associated with the success of orthodontic micro-implants. Cortical bone density may be associated with the micro-implant’s success.

1. Introduction

Temporary skeletal anchorage devices (TSADs) such as micro-implants are widely used for anchorage control in orthodontics [1,2,3,4]. Traditional anchorage devices such as transpalatal arches have been shown to be insufficient in providing anchorage in vertical and anteroposterior dimensions in premolar extraction cases [5]. Extraoral appliances such as headgears may be used to reinforce anchorage; however, they rely on patient compliance, which can be a problem [6,7].
TSADs have increased the range of biologic tooth movement using orthodontic appliances, altering the principle of “envelop of discrepancy” suggested by Proffit and Ackerman [8]. They can be used for various indications such as incisor retraction, molar intrusion, molar distalization, molar protraction, and the traction of impacted or unerupted teeth [9]. As a result, the need for orthognathic surgery decreased owing to advanced biomechanics for camouflage treatment in severe skeletal malocclusions, such as anterior openbite [10,11], and skeletal Class III malocclusions [12,13]. Additionally, TSADs have provided skeletal anchorage for maxillary expansion [14] and maxillary protraction [15] for patients with skeletal discrepancies.
As micro-implants are used temporarily during orthodontic treatment, their stability relies primarily on mechanical retention rather than osseointegration [16,17]. Previous studies on the factors associated with the success of orthodontic micro-implants are often limited to the biomechanical properties of the local bone required for implantation, such as the cortical bone thickness and the alveolar bone density, and to technical factors related to the implantation procedure, including the use of predrilling, the proximity of the micro-implant to the adjacent roots, the height of the insertion point, and the angle of the placement [18,19,20,21]. As the thickness and volume of the masseter muscle are significantly associated with different patterns of vertical facial growth [22,23], the impact of the masticatory function on bone morphology and its effects on micro-implant success have been evaluated [16,21,24]. However, only a few studies have examined the influence of craniofacial patterns on micro-implant success [25,26,27].
Despite the vast amount of research on factors affecting orthodontic micro-implant success, most of the studies have employed a univariate analysis, which does not consider the effects of other factors that may affect the outcome and lead to inaccurate results. Other studies have employed logistic regression analysis, which does not consider the time factor, which is critical for micro-implant survival. Survival analysis is a statistical method used in biomedical research, wherein the response variable, which is the time until the occurrence of an event of interest, and the survival differences among the groups of patients are tested [28]. The incidence of micro-implant failure is the event of interest in the study of orthodontic micro-implant success, and the probability of failure can be analyzed after adjusting for multiple patient-related factors known as covariates. These covariates can significantly affect the outcome. So far, only a few studies have performed survival analyses to evaluate the success of orthodontic micro-implants [29,30].
The purpose of this study was to investigate the effects of the patient-related factors such as anteroposterior and vertical skeletal patterns and alveolar bone density on the success rate of micro-implants.

2. Materials and Methods

This study was approved by the institutional review board of Korea National Institute for Bioethics Policy (P01-202209-01-035). Due to the retrospective nature of the study, informed consent from the patients was waived. Patients who received orthodontic treatment between March 2014 and April 2020 at the Department of Orthodontics of the Good Will Dental Hospital and those who met the inclusion criteria were included in the study. The analysis included patients who (1) received orthodontic treatment using one or more orthodontic micro-implant screws, (2) underwent cone-beam computed tomography (CBCT) for orthodontic diagnosis, (3) had micro-implants installed in the buccal interdental area of premolars or molars, and (4) had intraoral radiographs taken after application of micro-implants. The exclusion criteria were as follows: (1) presence of chronic disease and ongoing medication, (2) craniofacial syndromes, and (3) micro-implants placed in areas other than the buccal alveolar bone, such as the palate, retromolar area, and the anterior region.
A total of 404 micro-implants (DualTop, Jeil Medical Co., Seoul, Republic of Korea) with a diameter of 1.6 mm and a length of 6 mm were evaluated in 164 orthodontic patients (127 female patients, 37 male patients; mean age, 23.6 ± 5.8 years) (Table 1). The micro-implants were self-tapping implants with tapered shapes.
The mean number of the micro-implants was 2.5 ± 1.2 per patient. The orthodontic micro-implants were placed directly by self-drilling with a hand driver under local anesthesia. All patients were treated using the same right-handed operator (JL) with a clinical experience of more than 15 years. The insertion torque was not recorded. Micro-implants were implanted into the maxillary or mandibular buccal alveolar bone between the first and second premolars, first and second molars, or the second premolar and the first molar on the attached gingival area close to the mucogingival junction. In some patients, orthodontic forces ranging from 50 g to 200 g were applied immediately after the implantation, which was defined as immediate loading. In other patients, orthodontic forces were applied within 2–8 weeks following implantation, which was regarded as delayed loading. Micro-implants that showed inflammation and mobility were regarded as failed micro-implants and were removed. In cases of failed micro-implants, they were replanted in the same position after 2–3 months.
Cortical bone thickness and alveolar bone density were measured using diagnostic CBCT to investigate their effects on micro-implant survival as well as to control for the effects of varying bone thickness and density when assessing the risk of micro-implant failure in patients with varying facial types. CBCT images were obtained using a PaX-Zenith3D machine with the following operational settings: tube voltage, 85 kV; tube current, 6 mA; scan time, 24 s; voxel size, 0.20 mm; field of view, 19 cm × 20 cm. The images were saved as Digital Imaging and Communications in Medicine files, which were then used to reconstruct three-dimensional (3D) images as multiplanar reformatted (MPR) images using InVivoDental software (version 6.0, Anatomage, San Jose, CA, USA).
CBCT images were reoriented using the occlusal plane as the reference plane; this connects the mesiobuccal cusps of the first molars and the right central incisor tip. The site of implantation was located by measuring the distance from the crown tip to the point where the micro-implant enters the alveolar bone intraorally, and the nearest area was located on MPR views of the CBCT images. Cortical and cancellous bone densities were determined on the axial view via measurement in Hounsfield units (HU) on the line bisecting the inter-radicular space; this was achieved by creating a 1.0 mm2 rectangle shape in the cancellous bone and a 2.0 mm2 rectangle shape in the cortical bone around the area of the micro-implant’s placement (Figure 1). The measurements were performed using InVivoDental software.
Root proximity of the micro-implants was investigated on intraoral radiographs taken after implantation. The classification given by Kuroda et al. [19] was used; category I was defined as a micro-implant absolutely separate from the root, category II as the apex of a micro-implant touching the lamina dura, and category III as the body of the screw overlying the lamina dura.

Statistical Analysis

Intra-examiner reliability was assessed for the measurement of cortical bone thickness and cortical and cancellous bone densities. Twenty patients were randomly selected for a second set of measurements performed by the same investigator three weeks after the initial measurements. Inter-examiner reliability was assessed in 20 randomly selected patients whose measurements of cortical bone thickness and bone density were performed by another researcher (NJ). Intraclass correlation coefficients were calculated.
A generalized estimating equation (GEE) model was used to assess the significant factors related to the success of micro-implants; micro-implants that showed neither soft tissue inflammation nor mobility until the end of treatment were regarded as the cases of success. Marginal survival analysis was used to determine the significant factors associated with the survival of the micro-implants until the end of the treatment. Time to event was indicated by the months from the date of implant placement to the date of micro-implant removal for failed micro-implants, and to the end of treatment date for survived micro-implants. Based on the results of the GEE, we fitted a marginal survival model that considered the effects of variables including sex, vertical skeletal pattern (normal-faced, short-faced, and long-faced), extraction vs. non-extraction, cortical bone density, cancellous bone density, type of loading (immediate vs. delayed), root proximity (type I, II, and III, as classified by Kuroda et al. [19]), whether implant position was changed during installation, and whether the micro-implant was replanted after failure.
In addition, the factors associated with loading time, the period during which orthodontic force was applied to the micro-implants for treatment, were assessed using the linear regression analysis.
Statistical analyses were performed with SAS 9.4 for Windows (SAS Institute, Inc., Cary, NC, USA) and R 3.2.3 Survival Package (R Foundation for Statistical Computing, Vienna, Austria). Differences with p values smaller than 0.05 were considered significant.

3. Results

Intra-examiner and inter-examiner reliability for the measurements of cortical bone thickness and alveolar bone density showed intra-class correlation coefficients of 0.94–0.98 and 0.92–0.97, respectively. The overall success rate of the micro-implants was 85.9%; a total of 347 out of 404 micro-implants were used successfully until the end of the treatment. The mean loading time was 12.4 ± 4.3 months. According to the GEE, which compared the factors between the successful and failed micro-implants, the loading protocol (immediate vs. delayed, p < 0.001) and root proximity (p < 0.001) were identified as the significant factors (Table 2).
The micro-implants that were loaded immediately had a greater rate of failure; the micro-implants that had type III in Kuroda’s classification had the greatest failure rate. Contrastingly, cortical bone thickness and bone density did not show significant differences between the successful and failed micro-implants (Table 3).
The marginal survival plot is shown in Figure 2. As a result of the marginal survival analysis, no statistically significant variables were observed.
Variables that showed borderline non-significance (0.05 < p < 0.10) were cortical bone density (p = 0.061), loading protocol (p = 0.066 for immediate loading), and root proximity (p = 0.098 for type II, Table 4).
The results of the regression analysis for the loading time are shown in Table 5. Cortical bone density (p < 0.001), root proximity (p = 0.001 for type III), and micro-implant replacement (p = 0.008) were identified as significant factors in multi-variable analysis.

4. Discussion

Micro-implants are clinically and statistically more effective in reinforcing orthodontic anchorage [31] with a high rate of success ranging from 71.4% to 100% [32]. The micro-implant success rate of 85.9% observed in our study was similar to those obtained in previous studies [32,33,34]. The success rate did not differ significantly according to sex, which is also mostly in line with previous reports [16,26,29,35]. However, Baek et al. [36] have communicated that the success rates are higher in women compared to those in men. Age has been reported as a significant factor affecting micro-implant survival [29]: adolescents have a higher risk of micro-implant failure [37]. However, we did not detect a significant effect of the patients’ age on the success rate in the present study, which may be due to our cohort of young adults with a mean age of 23.6 ± 5.8 years.
The anteroposterior and vertical skeletal patterns had no significant associations with the micro-implant success in this study; previous studies have, however, reported conflicting results. Moon et al. [38], Miyawaki et al. [16], and Kuroda et al. [39] have concluded that anteroposterior skeletal pattern is not associated with the micro-implant success. Baek et al. [36] have reported that the success rate for Class III malocclusion patients is lower compared to Class I and II patients. In contrast, according to Chen et al. [25], patients with a retruded mandible have significantly higher rates of micro-implant failure.
Moon et al. [38] found that patients with larger gonial angles and Frankfort-mandibular plane angles are at a greater risk of micro-implant failure. Similar results have been reported by Miyawaki et al. [16] in a study of 129 miniscrews and concluded that miniscrews placed in patients with a high mandibular plane angle carry a greater risk of failure. Chen et al. [25] also reported a similar tendency for micro-implant failure in patients with a high mandibular plane angle, although this result only trended towards statistical significance. Therefore, thin cortical bone has been suggested as a possible factor responsible for the increased incidence of micro-implant failure in long-faced patients [16], as cortical bone thickness plays an important role in conferring primary stability [40]. Ozdemir et al. [41] reported that patients with a high mandibular plane angle and a decreased cortical bone thickness at the micro-implant sites are at a greater risk of micro-implant failure compared to patients with normal or low mandibular plane angles. Similarly, other studies [42,43] have reported a greater cortical bone thickness in patients with hypodivergent growth patterns, which are considered to be an adaptive response to the increased functional loading. However, our results suggest that cortical bone thickness is not associated with micro-implant success.
Rather than the cortical bone thickness, the cortical bone density was found to be a factor for micro-implant success. Cortical bone density showed statistical significance in the multivariable linear regression model for loading time (p < 0.001) and borderline non-significance (p = 0.061) in the survival analysis. The primary stability of micro-implants is dependent on mechanical retention, and, thus, bone quality is known to be an important factor [43,44,45]. Chugh et al. [43] have reported that stress distribution in alveolar bone is dependent on cortical bone density and thickness. Lee et al. [45] have found a higher success rate for orthodontic micro-implants in patients with high cancellous and total bone densities. As the failure rate is reported to be greater in the mandible than in the maxilla [32], the retromolar area has been suggested as a stable position for the micro-implants in the mandible, showing the greatest cortical bone density in the mesiobuccal site [46].
The timing of the loading had no significant effect on the success rate. Yano et al. [47] observed the screw to bone contact after micro-implant placement and concluded that tapered implants show greater bone contact compared with the straight implants. Moreover, the bone contact shows no difference between immediate loading and delayed loading in the tapered implants. Other factors associated with immediately loaded micro-implants are screw length and rotational moment applied to the micro-implant. Among the immediately loaded micro-implants, those with a length of 3 mm show higher failure rates than those with a length of 6 mm [48]. Cho et al. [49] suggested that a counterclockwise rotational moment applied to micro-implants can increase the risk of failure.
Root proximity has been considered as a significant factor affecting micro-implant stability and success. The classification for root proximity by Kuroda et al. [19] was used in this study, and similar results were obtained. We found that the risk of micro-implant failure was significantly greater for root proximity category II compared to category I, while the hazard ratio for category III patients indicated borderline non-significance.
One of the main limitations of this study was that the sex distribution among the study subjects was uneven, with more female patients than male patients, warranting a further study involving a more representative and inclusive cohort. Another limitation was that the survival analysis identified some variables that were marginally non-significant. Therefore, a further study with a larger sample size is also warranted. Bone density was measured in the CBCT images which do not have a consistent HU, which may be less accurate compared with those using conventional multi-slice CT. Additionally, the patients’ anteroposterior and vertical facial patterns were included as categorical variables using Angle’s classification of Class I, II, and III, and normo-divergent, hypodivergent, and hyper-divergent growth patterns. The incorporation of lateral cephalometric variables into the statistical models may provide a better understanding of craniofacial growth patterns and their possible effects on micro-implant success. Lastly, the variable of insertion torque could not be analyzed due to the retrospective nature of the study. As the insertion torque is a significant factor for micro-implant success [50,51,52], a further prospective study considering the insertion and removal torque is needed.

5. Conclusions

  • Anteroposterior and vertical skeletal patterns are not associated with the success of orthodontic micro-implants;
  • Cortical bone density and root proximity may be associated with the micro-implant’s success.

Author Contributions

Conceptualization, J.-K.L., Y.-J.K. and D.-Y.L.; methodology, J.-K.L., Y.-J.K., N.J. and D.-Y.L.; validation, J.-K.L., Y.-J.K. and D.-Y.L.; formal analysis, J.-K.L., Y.-J.K., N.J. and D.-Y.L.; investigation, J.-K.L., Y.-J.K. and D.-Y.L.; resources, J.-K.L., Y.-J.K. and D.-Y.L.; data curation, J.-K.L., Y.-J.K., N.J. and D.-Y.L.; writing—original draft preparation, J.-K.L., Y.-J.K. and D.-Y.L.; writing—review and editing, Y.-J.K.; supervision, J.-K.L., Y.-J.K. and D.-Y.L. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

This study was approved by the Institutional Review Board of Korea National Institute for Bioethics Policy (P01-202209-01-035).

Informed Consent Statement

Due to the retrospective nature of the study, informed consent from the patients was waived.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

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Applsci 12 11655 g001 550
Figure 1. Measurement of cortical and cancellous bone density in the axial view: (a) Cortical bone density. (b) Cancellous bone density. (c) Cortical bone thickness.
Figure 1. Measurement of cortical and cancellous bone density in the axial view: (a) Cortical bone density. (b) Cancellous bone density. (c) Cortical bone thickness.
Applsci 12 11655 g001
Applsci 12 11655 g002 550
Figure 2. The marginal survival plot showing high overall survival rate for micro-implants.
Figure 2. The marginal survival plot showing high overall survival rate for micro-implants.
Applsci 12 11655 g002
Table
Table 1. Sample characteristics of the study cohort (n = 164).
Table 1. Sample characteristics of the study cohort (n = 164).
MaleFemaleTotal
Number of patients (n)37127164
Age (years; mean ± SD)23.43 ± 4.3723.67 ± 6.1323.62 ± 5.77
Number of micro-implants (n)79325404
Mean number of micro-implants per patient2.14 ± 0.712.56 ± 1.312.46 ± 1.22
Anteroposterior skeletal pattern 1 (n)
Class I 135669
Class II 225779
Class III 21416
Vertical skeletal pattern 2 (n)
Normal 157590
Short 8614
Long 144660
1 Class I, 0° ≤ ANB < 4°; Class II, ANB ≥ 4°; Class III, ANB < 0°. 2 Normal, 31° ≤ SN-GoGn < 39°; Short, SN-GoGn < 31°; Long: SN-GoGn ≥ 39°. SD, standard deviation.
Table
Table 2. Generalized estimating equation model (GEE) to assess the significant factors related to the success of micro-implants.
Table 2. Generalized estimating equation model (GEE) to assess the significant factors related to the success of micro-implants.
Variable SuccessFailureTotalp
n = 347 (85.89%)n = 57 (14.11%)n = 404
Age 23.59(5.91%)24.67(5.72%)23.74(5.89%)0.141
SexM69(19.88%)10(17.54%)79(19.55%)0.728
F278(80.12%)47(82.46%)325(80.45%)
Anteroposterior skeletal patternClass I145(41.79%)26(45.61%)171(42.33%)0.887
Class II174(50.14%)27(47.37%)201(49.75%)
Class III29(8.07%)4(7.02%)32(7.92%)
Vertical facial patternShort31(9.01%)2(3.51%)33(8.23%)0.380
Normal193(56.1%)35(61.4%)228(56.86%)
Long120(34.88%)20(35.09%)140(34.91%)
Position IMx 456217(62.54%)28(49.12%)245(60.64%)0.439
Mx 6714(4.03%)4(7.02%)18(4.46%)
Mn 45691(26.22%)19(33.33%)110(27.23%)
Mn 6725(7.2%)6(10.53%)31(7.67%)
Position IIL-Mx456112(32.28%)9(15.79%)121(29.95%)0.110
L-Mx673(0.86%)2(3.51%)5(1.24%)
L-Mn45648(13.83%)7(12.28%)55(13.61%)
L-Mn6715(4.32%)2(1.75%)16(3.96%)
R-Mx456105(30.26%)19(33.33%)124(30.69%)
R-Mx6711(3.17%)2(3.51%)13(3.22%)
R-Mn45643(12.39%)12(21.05%)55(13.61%)
R-Mn6710(2.88%)5(8.77%)15(3.71%)
Loading protocoldelayed147(42.36%)17(29.82%)164(40.59%)<0.001
immediate200(57.64%)26(45.61%)226(55.94%)
no loading0(0%)14(24.56%)14(3.47%)
Root proximity *I226(65.13%)17(30.36%)243(60.3%)<0.001
II100(28.82%)27(48.21%)127(31.51%)
III21(6.05%)12(21.43%)33(8.19%)
Extraction/non-extractionNon-Ext252(72.62%)44(77.19%)296(73.27%)0.491
Ext95(27.38%)13(22.81%)108(26.73%)
* Root proximity classified by Kuroda et al. [19]. Mx, maxilla; Mn, mandible; 456, between first and second premolars or between second premolar and first molar; 67, between first and second molars; L, left; R, right; Non-Ext, non-extraction; Ext, extraction.
Table
Table 3. Generalized estimating equation model used to assess the effect of bone density on the success of micro-implants.
Table 3. Generalized estimating equation model used to assess the effect of bone density on the success of micro-implants.
GroupsnMeanSDMedianMinimumMaximump *
Cortical bone thickness (mm)Success3471.570.491.520.633.650.821
Failure571.550.531.470.723.05
Total4041.560.51.510.633.65
Cortical bone density (HU *)Success3471325.25545.031014.3174.2104,2040.357
Failure57985.88274.56944.6509.81516.9
Total4041277.325140.331003.9174.2104,204
Cancellous bone density (HU)Success347317.24268.85302.5−495.911360.342
Failure57276.42291.26242−495.9840
Total404311.48272.11282.5−495.91136
* HU, Hounsfield unit.
Table
Table 4. Univariable marginal survival analysis for factors associated with micro-implant success.
Table 4. Univariable marginal survival analysis for factors associated with micro-implant success.
95% CIp
Variables HRLowerUpper
SexM0.9670.6571.4240.866
F1.000
Vertical facial patternShort1.2720.7202.2470.688
Normal1.2850.9221.7920.139
Long1.000
Extaction/non-extractionNon-ext1.2430.8511.8170.260
Ext1.000
Cortical bone density(HU)unit = 10000.9980.9951.0000.061
Cancellous bone density(HU)unit = 100.9970.9921.0030.391
Immediate/delayed loadingdelayed1.000
immediate1.2260.9871.5230.066
Root proximity *I1.000
II0.8380.6791.0330.098
III1.2030.7771.8620.407
Position change **Yes0.9410.7091.2480.673
No1.000
Replacement ***Yes1.3810.9292.0520.111
No1.000
* Root proximity classified by Kuroda et al. [19]. ** Change in implant site during installation. *** Replanted in the same site 2–3 months after failure of micro-implant. HR, hazard ratio; CI, confidence interval.
Table
Table 5. Regression analysis for loading time.
Table 5. Regression analysis for loading time.
UnivariableMultivariable
Variables BetaSEpBetaSEp
SexM0.1811.0080.857
F0.000
Vertical facial patternShort0.0981.3260.941
Normal−1.0410.8450.218
Long0.000
Loading time (month)
Extaction/non-extractionNon-ext−0.8940.9410.342
Ext0.000
Cortical bone density (HU)unit = 10000.0350.005<0.0010.0270.007<0.001
Cancellous bone density (HU)unit = 100.0210.0130.101
Immediate/delayed loadingdelayed0.000 0.000
immediate−0.1510.6850.826−0.1990.6730.767
Root proximity *I0.000 0.000
II−0.8570.6490.098−0.2140.6260.733
III−3.6001.0260.187−3.1960.9810.001
Position change **Yes−1.2831.0780.234
No0.000
Replacement ***Yes−3.8781.5150.011−3.4991.3250.008
No0.000 0.000
* Root proximity classified by Kuroda et al. [19]. ** Change in implant site during installation. *** Replanted in the same site 2–3 months after failure of micro-implant. SE, standard error for beta.
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Lee, J.-K.; Jha, N.; Kim, Y.-J.; Lee, D.-Y. Survival Analysis of Orthodontic Micro-Implants: A Retrospective Study on the Effects of Patient-Related Factors on Micro-Implant Success. Appl. Sci. 2022, 12, 11655. https://doi.org/10.3390/app122211655

AMA Style

Lee J-K, Jha N, Kim Y-J, Lee D-Y. Survival Analysis of Orthodontic Micro-Implants: A Retrospective Study on the Effects of Patient-Related Factors on Micro-Implant Success. Applied Sciences. 2022; 12(22):11655. https://doi.org/10.3390/app122211655

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Lee, Jung-Kwang, Nayansi Jha, Yoon-Ji Kim, and Dong-Yul Lee. 2022. "Survival Analysis of Orthodontic Micro-Implants: A Retrospective Study on the Effects of Patient-Related Factors on Micro-Implant Success" Applied Sciences 12, no. 22: 11655. https://doi.org/10.3390/app122211655

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