Antibiotic Stewardship and Length of Stay in Osteoarticular Infections: Predictive Modeling and Multivariate Analysis...

Area of Science:

• Infectious Diseases
• Health Economics
• Clinical Informatics

Background:

• Osteoarticular infections (OAIs) necessitate timely, targeted antimicrobial treatment.
• Delays in optimizing antibiotic therapy for OAIs lead to extended hospital stays and increased healthcare expenses.
• Inefficiencies in diagnosis and antibiotic selection contribute to prolonged treatment durations.

Purpose of the Study:

• To evaluate the impact of antibiotic optimization delays and empirical mismatches on length of stay (LOS) and costs in osteoarticular infections.
• To identify factors influencing LOS in OAI patients.
• To model potential cost savings and operational benefits from reducing antibiotic optimization delays.

Main Methods:

• Retrospective analysis of adult OAI admissions from the MIMIC-IV database.
• Definition of mismatch as inactive empirical antibiotics against isolated pathogens.
• Calculation of optimization delay from empirical to first susceptible antibiotic.
• Multivariate log-linear regression to assess LOS determinants.
• Cost modeling using a standardized daily cost estimate.

Main Results:

• Antibiotic mismatch occurred in 13% of 3,093 OAI admissions, with a mean delay of 8.8 days.
• Mismatch increased LOS by approximately 64%, and each day of delay increased LOS by 2.4% (p<0.001).
• Congestive heart failure, chronic kidney disease, and immune deficiency were associated with prolonged LOS.

Conclusions:

• Reducing antibiotic optimization delays offers significant clinical, economic, and operational advantages.
• Rapid diagnostics and predictive analytics can facilitate earlier antibiotic optimization.
• Further research is needed to address culture-negative OAIs to enhance generalizability.