Peri‐implant inflammation and marginal bone level changes around dental implants in relation to proximity with and bone level of adjacent teeth

Ng, Kcd; Fan, Mhm; Leung, Ming Chi Terrence; Fokas, George; Mattheos, Nikos

doi:10.1111/adj.12650

Cited by 9 publications

(6 citation statements)

References 40 publications

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“…The study was approved by the Institutional Review Board of the University of Hong Kong/Hospital Authority Hong Kong and the Ethics Committee of the Faculty of Dentistry, University of Hong Kong (reference number: UW 15‐609). Retrospective data were sourced from patients treated by postgraduate students in the Implant Dentistry clinic, The University of Hong Kong (Ng, Fan, Leung, Fokas, & Mattheos, ).…”

Section: Methodsmentioning

confidence: 87%

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Peri‐implant marginal bone loss rate pre‐ and post‐loading: An exploratory analysis of associated factors

Acharya

Leung

et al. 2019

Clinical Oral Implants Res

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Objectives To perform an exploratory analysis of factors influencing annual rates of peri‐implant marginal bone loss (RBL) calculated over different time frames, at implants unaffected by peri‐implantitis. Material and methods A total of 154 implants from 86 patients were reviewed at 1.6–6.8 years after placement. Marginal bone levels (MBL) were assessed on intraoral radiographs at three time‐points: immediately post‐placement, time of loading, and least 1‐year post‐loading. RBLs (mm/year) were computed using these three time frames and corresponding MBL changes as: RBL placement‐loading, RBL loading‐review, RBL placement‐review. Exploratory ordination of three RBLs, corresponding time durations, and 17 background factors were used for visualization. Hierarchical linear mixed‐effects models (MEM) with predictor selection were applied to RBL outcomes. The correlation of actual MBL with MBLs predicted by RBL placement‐loading and RBL loading‐review was tested. Results Median RBL placement‐loading was 0.9 mm/year (IQR = 2.02), loading‐review was 0.06 mm/year (IQR = 0.16), and overall RBL placement‐review was 0.21 mm/year (IQR = 0.33). Among‐patient variance was highest for RBL placement‐loading (SD = 0.66). Longer time predicted lower RBL in all time frames. Shorter time of loading significantly predicted lower RBL placement‐review. Augmentation predicted lower RBL placement‐loading, while anterior location and older age predicted lower RBLs placement‐loading placement‐review. Only MBL projected using RBL placement‐loading significantly correlated with actual MBL. Conclusions Exploratory analysis indicated RBL varied with the time duration used for calculation in pre‐ and post‐loading, and overall periods. In each period, RBL declined with increasing time. Earlier loading predicted lower overall RBL. Higher pre‐loading RBL predicted worse actual bone level.

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Section: Methodsmentioning

confidence: 87%

“…Dimensions of the digitized radiographs were calibrated to account for distortion by using known distance between implant threads and implant diameter. Two examiners were calibrated with six random sets of radiographs with an intraclass correlation coefficients documented as 0.99 and then conducted all measurements (Ng et al, ).…”

Section: Methodsmentioning

confidence: 99%

Peri‐implant marginal bone loss rate pre‐ and post‐loading: An exploratory analysis of associated factors

Acharya

Leung

et al. 2019

Clinical Oral Implants Res

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“…Han et al (2022) found that implant-tooth root proximity (≤ 1 mm) increased the possibility of peri-implantitis and marginal bone loss [32] . A distance of 1.5 mm between the adjacent teeth and implant must be ensured in implantation to avoid complications [33] . However, Galindo et al ( 2016) thought that the clinical performance of the implant would not be in uenced by the distance between adjacent teeth and the implant (distance ≥ 1.5 mm) [34] .…”

Section: Discussionmentioning

confidence: 99%

Analysis of risk factors related to early implant failure: a retrospective study

Lin

Jiang

Ding

2023

Preprint

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Objective This study investigated the factors associated with early implant failure. Material and methods This retrospective study was conducted on 3,247 implants in 2,061 patients. Patient-related and surgery-related factors, including smoking, sex, diabetes, bone grafting, implant length, implant width, implant design, adjacent teeth, and insertion torque, were manually retrieved and analyzed. Using univariate and multivariate analyses, a generalized estimating equation (GEE) model was employed to evaluate factors related to early implant failure. Results The mean age of the patients was 49.2 ± 15.0 (18–91) years. Ninety-nine implants failed during the healing period. Three factors were statistically significant regarding early implant failure: smoking (odds ratio [OR] = 7.060, P = 0.008), implant design (OR = 6.983, P = 0.008), and implant length (OR = 7.500, P = 0.006). Factors including diabetes, bone grafting, location, adjacent teeth (root canal therapy in the adjacent teeth and the distance between the implant and adjacent teeth), healing method, and insertion torque did not exhibit a significantly higher early implant failure rate. Ninety-three sites with failed implants received replantation, and six implants failed during the healing period. Conclusions This retrospective study identified three factors associated with early implant failure: smoking, implant design, and implant length. A prospective study with larger sample size is needed in the future. Clinical relevance: There is fierce debate on the factors influencing early implant failure (failure during the healing period) in the rehabilitation and restoration of oral function in partially edentulous patients.

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“…Ng et al (103) reported that horizontal proximity of implants to adjacent teeth in cases of <1 mm might be considered as a risk factor for PI by increasing the prevalence of inflammation and risk of bone resorption in the interproximal bone area of the adjacent tooth. According to Ng, bone loss caused by implant proximity can result from the lack of access for oral hygiene, as well as from the lack of proper contour of the prosthetic restoration.…”

Section: Implant Installation Positioning and Spacingmentioning

confidence: 99%

Dental implant risk factors for peri-implant disease: a narrative review

Alterman¹,

Jensen²,

Glick³

et al. 2023

Front Oral Maxillofac Med

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Background and Objective: Dental implants have become a leading method to rehabilitate areas of missing teeth. Their success and survival rates, as well as their supporting tissues health, are influenced by various intrinsic and exogenous factors. Each year the total number of implants in function rises with more patients becoming at risk for peri-implantitis (PI). Various treatment modalities have been suggested for PI, varying from minimally invasive methods to extensive regenerative surgeries. In advanced stages of PI, implant removal and reimplantation may be required. There is little long-term data regarding the effectiveness of treatment as counter measure to assure the long-term effectiveness of dental implant therapy. It remains the responsibility of the individual clinician to understand the risk factors involved in development of PI and incorporate mitigation strategies as part of overall patient treatment. The aim of the manuscript is to review the scientific literature regarding risk factors for peri-implant disease (PID). Methods: A comprehensive review of the English literature (published between 2005 and May 2021) was conducted in MEDLINE, PubMed, Cochrane and Google Scholar databases on intra-oral and extra-oral risk factors.

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Peri‐implant inflammation and marginal bone level changes around dental implants in relation to proximity with and bone level of adjacent teeth

Abstract: Proximity of implants to adjacent teeth of <1 mm leads to increased prevalence of inflammation and interproximal bone resorption at the teeth adjacent to bone level implants.

Cited by 9 publications

References 40 publications

Peri‐implant marginal bone loss rate pre‐ and post‐loading: An exploratory analysis of associated factors

Peri‐implant marginal bone loss rate pre‐ and post‐loading: An exploratory analysis of associated factors

Analysis of risk factors related to early implant failure: a retrospective study

Dental implant risk factors for peri-implant disease: a narrative review

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