PROGNOSTIC PARAMETERS OF THE SUSCEPTIBILITY OF STAPHYLOCOCCUS SPP. TO AMINOGLYCOSIDES AND DOXYCYCLINE

Area of Science:

• Microbiology
• Infectious Diseases
• Mathematical Modeling

Background:

• Severe burns are susceptible to Staphylococcus aureus infections.
• Aminoglycoside resistance in S. aureus is a growing clinical concern.
• Predictive modeling is crucial for understanding antimicrobial susceptibility trends.

Purpose of the Study:

• To investigate microbiological resistance patterns of S. aureus clinical isolates.
• To develop mathematical models predicting S. aureus susceptibility to aminoglycosides and doxycycline.
• To inform treatment strategies for severe burn patients.

Main Methods:

• Analysis of 199 S. aureus strains from 435 burn patients (2011-2017).
• Microbiological testing against gentamicin, tobramycin, amikacin, and doxycycline.
• Development of predictive mathematical equations for antimicrobial susceptibility.

Main Results:

• S. aureus susceptibility to gentamicin declined to 42.86% by 2017, with further decrease predicted.
• Tobramycin efficacy showed a rapid decline predicted by mathematical modeling.
• Amikacin efficacy, though declining, was predicted to increase over 60% in 2018.
• Doxycycline susceptibility was 65.38% in 2017, with a predicted gradual decline.

Conclusions:

• Current aminoglycoside efficacy is insufficient for treating S. aureus infections in severe burn patients.
• Doxycycline demonstrates sustained efficacy, supporting its use as a second-line agent.
• Predictive modeling aids in anticipating antimicrobial resistance trends and guiding therapy.