Topical Therapy Failure In Chronic Suppurative Otitis Media Is Due To Persister Cells In Biofilms

Objective: Chronic suppurative otitis media (CSOM) is characterized by a chronically draining middle ear. CSOM is typically treated with multiple courses of antibiotics or antiseptics which are successful in achieving quiescence; however, the disease is prone to relapse. Understanding why these treatment failures occur is essential. Study Design: The minimum inhibitory concentration (MIC), minimal biofilm eradication concentration, and the inhibitory zone were determined for ototopicals and ofloxacin for the laboratory strains and CSOM-derived isolates. The percentage of persister cells and bacterial biofilm formation were measured. Disease eradication was tested in a validated in-vivo model of CSOM after treatment with ofloxacin. Setting: Microbiology Laboratory. Methods: Basic science experiments were performed to measure the effectiveness of a number of compounds against CSOM bacteria in a number of distinct settings. Results: The minimal biofilm eradication concentration is higher than is physiologically achievable with commercial preparations, except for povo-iodine. Clincial isolates of CSOM have equivalent biofilm-forming ability but increased proportions of persister cells. Ofloxacin can convert to inactive disease temporarily but fails to eradicate disease in an in-vivo model. Conclusions: Higher percentages of persister cells in clinical CSOM isolates are associated with resistance to ototopicals. Current ototopicals, except povo-iodine, have limited clinical effectiveness; however, it is unknown what the maximum achievable concentration is and there are ototoxicity concerns. Fluoroquinolones, while successful in producing inactive disease in the short term, have the potential to encourage antimicrobial resistance and disease recalcitrance and do not achieve a permanent remission. Given these limitations, clinicians should consider surgery earlier or use of clinically safe concentrations of povo-iodine earlier into the treatment algorithm.