Development and validation of a bedside instrument to predict carbapenem resistance among gram-negative pathogens in...

Area of Science:

• Infectious Diseases
• Clinical Microbiology
• Medical Diagnostics

Background:

• Complicated urinary tract infections (cUTIs) pose significant treatment challenges.
• Carbapenem resistance is a growing threat in managing cUTIs.
• Predictive tools are needed to guide antimicrobial therapy.

Purpose of the Study:

• To develop and validate a bedside instrument for predicting carbapenem resistance.
• To identify key clinical factors associated with carbapenem resistance in cUTIs.

Main Methods:

• Development of a weighted point-based model.
• Inclusion of factors such as facility admission, weight loss, ventilation, age, gender, catheter use, prior antibiotics, and prior carbapenem resistance.
• Assessment of model discrimination using the C statistic.

Main Results:

• The developed model demonstrated good predictive discrimination (C statistic = 0.721).
• Specific weighted points were assigned to various risk factors.
• Factors included demographics, medical history, and prior infection history.

Conclusions:

• A bedside instrument can effectively predict carbapenem resistance in cUTIs.
• The model provides a practical approach for risk stratification.
• Early prediction aids in appropriate antibiotic selection and infection control.