Two-way analysis for detecting factors affecting ventilator-associated pneumonia.

Area of Science:

• Critical Care Medicine
• Epidemiology
• Biostatistics

Background:

• Ventilator-associated pneumonia (VAP) is a significant complication in intensive care units.
• Predicting the clinically required ventilation period for VAP assessment has been a challenge due to lack of predictive models.
• Understanding risk factors is crucial for developing effective VAP prevention strategies.

Purpose of the Study:

• To investigate the
• clinically required ventilation period
• for VAP assessment using rate and failure-time analyses.
• To identify patient and clinical factors associated with VAP development.
• To compare the utility of different statistical models in VAP risk assessment.

Main Methods:

• Retrospective review of 325 patients receiving mechanical ventilatory support.
• Application of logistic regression, Cox proportional hazard model, and Frechet distribution model.
• Comparison of univariate and multivariate analyses to identify time-dependent biases.

Main Results:

• Discrepancies between methods were noted for emergent admissions, with a reduced hazard ratio observed.
• Longer operation time was associated with increased VAP rate in the logistic model.
• Low body mass index significantly increased VAP risk, particularly in female patients (HR, 0.1707).

Conclusions:

• Rate and failure-time analyses yielded similar results for most factors but differed for emergent admissions.
• The findings suggest that different analytical approaches may reveal distinct or obscured factors influencing VAP.
• Low BMI and emergency admission are critical factors to consider in VAP prevention protocols.