Abstract

PURPOSE:

Infections after pediatric cardiac surgery are a common complication, occurring in up to 30% of cases. The purpose of this study was to develop a bedside prediction rule to estimate the risk of a postoperative infection.

METHODS:

All consecutive pediatric cardiac surgery procedures between April 2006 and May 2009 were retrospectively analyzed. The primary outcome variable was any postoperative infection, as defined by the Center of Disease Control (2008). All variables known to the clinician at the bedside at 48 h post cardiac surgery were included in the primary analysis, and multivariable logistic regression was used to construct a prediction rule.

RESULTS:

A total of 412 procedures were included, of which 102 (25%) were followed by an infection. Most infections were surgical site infections (26% of all infections) and bloodstream infections (25%). Three variables proved to be most predictive of an infection: age less than 6 months, postoperative pediatric intensive care unit (PICU) stay longer than 48 h, and open sternum for longer than 48 h. Translation into prediction rule points yielded 1, 4, and 1 point for each variable, respectively. Patients with a score of 0 had 6.6% risk of an infection, whereas those with a maximal score of 6 had a risk of 57%. The area under the receiver operating characteristic curve was 0.78 (95% confidence interval 0.72-0.83).

CONCLUSIONS:

A simple bedside prediction rule designed for use at 48 h post cardiac surgery can discriminate between children at high and low risk for a subsequent infection.