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1.
The Journal of Korean Academy of Prosthodontics ; : 27-35, 2021.
Article in English | WPRIM | ID: wpr-875394

ABSTRACT

Purpose@#The purpose of this study is to compare the accuracy of digital scans of implants according to different shapes of scanbodies, and to compare the accuracy of library merging according to different oral exposure height. @*Materials and methods@#A master model with a single tooth edentulous site was prepared. For the first experiment, three types of intraoral scanbodies were prepared, divided into three groups, and the following experiments were conducted for each group: An internal hex implant was placed. The master model with the scanbody connected was scanned with a model scanner, and a master reference file (control group) was created. 10 files (experimental group) were created by performing 10 consecutive scans with an intraoral scanner. After superimposing the control and experimental groups, the following values were calculated: 1) Distance deviation of a designated point on the scanbody 2) Angle deviation of the major axis of the scanbody. For the second experiment, the scanbody scan data were prepared in 6 different heights. Library files were merged with each of the scan data. The distance and angular deviation were calculated using the 7 mm scan data as control group. @*Results@#In the first experiment, there were no significant differences between A and B (P=.278), B and C (P=.568), and C and A (P=.711) in the distance deviations. There were no significant differences between A and B (P=.568), B and C (P=.546), and C and A (P=.112) in the angular deviations. Also, the scanbody showed significantly higher library merging accuracy in the groups with high oral exposure height (P<.5). @*Conclusion@#There were no significant differences in scan accuracy according to the different shapes of scanbodies, and the accuracy of library merging increased according to exposure height of the scanbody in the oral cavity.

2.
Journal of Periodontal & Implant Science ; : 207-217, 2016.
Article in English | WPRIM | ID: wpr-173088

ABSTRACT

PURPOSE: The aim of this study is to analyze and visualize the distribution of patients visiting the periodontology department at a dental college hospital, using a geographic information system (GIS) to utilize these data in patient care and treatment planning, which may help to assess the risk and prevent periodontal diseases. METHODS: Basic patient information data were obtained from Dankook University Dental Hospital, including the unit number, gender, date of birth, and address, down to the dong (neighborhood) administrative district unit, of 306,656 patients who visited the hospital between 2007 and 2014. The data of only 26,457 patients who visited the periodontology department were included in this analysis. The patient distribution was visualized using GIS. Statistical analyses including multiple regression, logistic regression, and geographically weighted regression were performed using SAS 9.3 and ArcGIS 10.1. Five factors, namely proximity, accessibility, age, gender, and socioeconomic status, were investigated as the explanatory variables of the patient distribution. RESULTS: The visualized patient data showed a nationwide scale of the patient distribution. The mean distance from each patient's regional center to the hospital was 30.94±29.62 km and was inversely proportional to the number of patients from the respective regions. The distance from a regional center to the adjacent toll gate had various effects depending on the local distance from the hospital. The average age of the patients was 52.41±12.97 years. Further, a majority of regions showed a male dominance. Personal income had inconsistent results between analyses. CONCLUSIONS: The distribution of patients is significantly affected by the proximity, accessibility, age, gender and socioeconomic status of patients, and the patients visiting the periodontology department travelled farther distances than those visiting the other departments. The underlying reason for this needs to be analyzed further.


Subject(s)
Humans , Male , Epidemiology , Geographic Information Systems , Logistic Models , Parturition , Patient Care , Periodontal Diseases , Social Class , Spatial Regression
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