Distribution and clinical characterization of pathogenic bacteria in combined periodontal and endodontic lesions of periodontal origin by digital technology

Author:

Jing Zhixing1,Mi Changjiang1,Zhu Wanchun1

Affiliation:

1. Department of Stomatology , North Sichuan Medical College , Nanchong , Sichuan , , China .

Abstract

Abstract In this paper, the Logistic regression model and χ2 automatic interaction test were used to study the distribution, number, and correlation of common pathogenic bacteria of periodontal origin with combined periodontal and endodontic lesions by sample training, extracting variable characteristics, and then these variables were modeled as characteristic variables of the regression model to test whether the independent variables were significantly correlated with the dependent variables. It is also necessary to perform χ2 automatic interaction test to compare with the normal distribution, and the results are merged into one group if they are the same and not incorporated into one group if they are different. After the merging was completed, the splitting was done. The study group had a detection rate of pathogenic bacteria of 50.70%, while the control group had a detection rate of 12.24%, according to the results. Campylobacter spp. was the main bacteria that infected periodontal pockets in the study group. And Clostridium spp. The root canal specimens were mainly from Corynebacterium spp. and Actinobacillus spp. There was a significant difference between the pathogenic species and the control group P<0.05. Campylobacter spp. was also a risk factor for co-morbidities (P=0.031). Intra-root canal tissue with its subgingival plaque pathogenic bacteria Ef, Pe (Ρ<0.05), Pg, Td, Tf (Ρ<0.01) played a more important role in the development of pulpitis. Before and after clinical treatment, Pgi showed the most significant decrease in bacterial counts (t=2.759, P=0.022).

Publisher

Walter de Gruyter GmbH

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3