Proposition of a New Scale for Marginal Bone Loss Prediction Around Dental Implants—A 5-Year Follow-Up of Functional Loaded Implants

<b>Background</b>: Marginal bone loss (MBL) is a condition leading to implant loss and treatment failure. MBL is one of the main complications in dental implantology. The aim of this research is to show the method that can predict bone loss around implants and protect patients from implant loss. <b>Methods</b>: A total of 1026 intraoral standardized radiographs of dental implants were included in this study. A total of 2052 peri-implant jawbone image samples were analyzed in MaZda 4.6 software. A new scale was calculated and described. MBL was measured, and groups of patients were compared. <b>Results:</b> After 3 months of functional loading, the Corticalization Index (CI) was calculated to be 210.70 ± 149.78 and increased after 60 months to 277.88 ± 198.78. In the 60-month observation, MBL was 0.85 mm ± 1.29 mm, and it has been noted that low MBL is associated with CI lower than 300, high MBL with CI higher than 500, and critical high MBL appeared when CI was higher than 1200. <b>Conclusions:</b> Authors created a new scale, and research showed that the specified CI in our scale may predict MBL around dental implants with a five-year forecast horizon. It allows us to implement specific treatment and protect implants from loss.

Authors

Institutions

Publication Details

Journal
Diagnostics
Published
2025-12-06
DOI
https://doi.org/10.3390/diagnostics15243101
Primary Topic
Dental Implant Techniques and Outcomes
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Proposition of a New Scale for Marginal Bone Loss Prediction Around Dental Implants—A 5-Year Follow-Up of Functional Loaded Implants

Tomasz Wach, Grzegorz Trybek, Maciej Sikora, Adam Michcik et al.
Diagnostics
Dental Implant Techniques and Outcomes
article

Proposition of a New Scale for Marginal Bone Loss Prediction Around Dental Implants—A 5-Year Follow-Up of Functional Loaded Implants

Tomasz Wach, Grzegorz Trybek, Maciej Sikora, Adam Michcik, Marcin Kozakiewicz, Piotr Hadrowicz, Piotr Szymor, Raphaël Olszewski, Paulina Pruszyńska
article en

Abstract

<b>Background</b>: Marginal bone loss (MBL) is a condition leading to implant loss and treatment failure. MBL is one of the main complications in dental implantology. The aim of this research is to show the method that can predict bone loss around implants and protect patients from implant loss. <b>Methods</b>: A total of 1026 intraoral standardized radiographs of dental implants were included in this study. A total of 2052 peri-implant jawbone image samples were analyzed in MaZda 4.6 software. A new scale was calculated and described. MBL was measured, and groups of patients were compared. <b>Results:</b> After 3 months of functional loading, the Corticalization Index (CI) was calculated to be 210.70 ± 149.78 and increased after 60 months to 277.88 ± 198.78. In the 60-month observation, MBL was 0.85 mm ± 1.29 mm, and it has been noted that low MBL is associated with CI lower than 300, high MBL with CI higher than 500, and critical high MBL appeared when CI was higher than 1200. <b>Conclusions:</b> Authors created a new scale, and research showed that the specified CI in our scale may predict MBL around dental implants with a five-year forecast horizon. It allows us to implement specific treatment and protect implants from loss.

DiagnosticsVol. 15(24)
Cliniques Universitaires Saint-Luc (BE), Military Hospital (PK), Nicolaus Copernicus University (PL), Medical University of Lodz (PL), Ministry of Interior and Administration (PL), Directorate-General Joint Research Centre (BE), Gdańsk Medical University (PL), Pomeranian Medical University (PL)
Openalex Percentile: Top 46%
Dental Implant Techniques and Outcomes
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.