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Published on: May 9, 2022
Personalized antibiotic selection in periodontal treatment improves clinical and microbiological outputs
Miglė Žiemytė1, Andrés Lopez-Roldan2, Miguel Carda-Diéguez1
1Genomics & Health Department, Foundation for the Promotion of Health and Biomedical Research of the Valencian Community (FISABIO) Foundation, Valencia, Spain.
Introduction:
Periodontitis 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.
Methods:
In 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).
Results:
Antibiotic 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.
Discussion:
The 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.

