Clinical Microbiology and Infection
Clinical Microbiology and Infection
5 years ago

Assessing prediction accuracy for outcomes of ventilator-associated events and infections in critically ill children: A prospective cohort study.

To assess the prediction accuracy of 2008 Center for Disease Control and Prevention (CDC) definitions for ventilator-associated pneumonia (VAP)/ventilator-associated tracheobronchitis (VAT), 2013-CDC definitions for ventilator-associated events (VAE) and a new VAE algorithm (Ped-VAE) in children. Methods Prospective 13-month cohort study at a multidisciplinary Pediatric Intensive Care Unit (PICU). Primary end-points were duration of ventilation episode, PICU/hospitalization length of stay from episode (LOS), and episode mortality. Episodes without VAE (or VAP/VAT) served as comparison groups. Results 108 episodes of ventilation (99 children) with 2,554 ventilator-days were assessed. In episodes not meeting 2008-CDC definitions, a median of 6 ventilator-days (PICU stay 11 days) was documented (with 8 deaths), not significantly different from episodes not meeting VAE or Ped-VAE definitions. Using 2008-CDC criteria, 11 (10.2%) respiratory infections (8 tracheobronchitis) were identified, 7 VAEs using 2013-CDC criteria (6.4%), and 29 (26.8%) using Ped-VAE criteria (RR vs 2008 CDC criteria 2.58 (95%CI 1.36-4.91). In contrast with their comparison groups, episodes meeting 2008-CDC criteria did not significantly predict outcomes, whereas VAEs (only 4 possible VAPs) were associated with significantly more ventilation/PICU LOS (12-day/8-day increase) and 6-fold increase in mortality. Ped-VAE did not increased mortality but it was associated with 4-day increase in ventilation and PICU LOS, with 10 possible VAPs and atelectasis (9/12) as the main pediatric ventilator-associated condition. Conclusions 2008-CDC criteria did not predict outcomes, whereas VAE only identified very severe events. The Ped-VAE algorithm had more accuracy predicting outcomes by characterizing lower oxygenation changes and identifying hypoxemia severity, a major driver for management.

Publisher URL: www.sciencedirect.com/science

DOI: S1198743X17305414

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