Personalized antibiotic selection in periodontal treatment improves clinical and microbiological outputs

FRONTIERS IN CELLULAR AND INFECTION MICROBIOLOGY(2023)

引用 0|浏览1
暂无评分
摘要
IntroductionPeriodontitis is a biofilm-mediated disease that is usually treated by non-surgical biofilm elimination with or without antibiotics. Antibiotic treatment in periodontal patients is typically selected empirically or using qPCR or DNA hybridization methods. These approaches are directed towards establishing the levels of different periodontal pathogens in periodontal pockets to infer the antibiotic treatment. However, current methods are costly and do not consider the antibiotic susceptibility of the whole subgingival biofilm.MethodsIn the current manuscript, we have developed a method to culture subgingival samples ex vivo in a fast, label-free impedance-based system where biofilm growth is monitored in real-time under exposure to different antibiotics, producing results in 4 hours. To test its efficacy, we performed a double-blind, randomized clinical trial where patients were treated with an antibiotic either selected by the hybridization method (n=32) or by the one with the best effect in the ex vivo growth system (n=32).ResultsAntibiotic selection was different in over 80% of the cases. Clinical parameters such as periodontal pocket depth, attachment level, and bleeding upon probing improved in both groups. However, dental plaque was significantly reduced only in the group where antibiotics were selected according to the ex vivo growth. In addition, 16S rRNA sequencing showed a larger reduction in periodontal pathogens and a larger increase in health-associated bacteria in the ex vivo growth group.DiscussionThe results of clinical and microbiological parameters, together with the reduced cost and low analysis time, support the use of the impedance system for improved individualized antibiotic selection.
更多
查看译文
关键词
xCELLigence,biofilms,personalized medicine,periodontitis,oral bacteria,infection,antibiotic treatment,subgingival plaque
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要