Osteoarticular Infections in MIMIC-IV, A Clinical and Microbiological Analysis

Area of Science:

• Infectious Diseases
• Medical Informatics
• Clinical Epidemiology

Background:

• Osteoarticular infections (OAIs) present significant clinical challenges, exacerbated by increasing antimicrobial resistance.
• Effective management requires understanding inflammatory marker (IM) utilization and comorbidity-specific risks for multidrug-resistant organisms (MDROs).

Purpose of the Study:

• To characterize IM ordering patterns in OAIs using a structured informatics workflow.
• To assess comorbidity-specific infection risks and identify prevalent MDROs.
• To inform the development of diagnostic and therapeutic decision support tools for OAIs.

Main Methods:

• Utilized the MIMIC-IV database for a retrospective analysis.
• Applied a structured informatics workflow to analyze IM ordering, infection risks, and MDRO identification.
• Examined the association between specific comorbidities (immune deficiency, diabetes, sickle cell disease) and OAI prevalence and pathogen profiles.

Main Results:

• Observed overuse of white blood cell (WBC) counts as an inflammatory marker.
• Identified distinct pathogen profiles associated with different comorbidity groups.
• Found increased OAI rates in patients with immune deficiency and diabetes, but not sickle cell disease.

Conclusions:

• Inflammatory marker ordering in OAIs may not be optimal, with potential for overuse of certain tests like WBC counts.
• Comorbidities significantly influence OAI risk and pathogen characteristics, necessitating tailored diagnostic and treatment strategies.
• Informatics-driven analysis of large datasets like MIMIC-IV can reveal critical insights for improving OAI management and combating antimicrobial resistance.