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Bedside prediction rule for infections after pediatric cardiac surgery
Selma O Algra1, Mieke M P Driessen, Alvin W L Schadenberg
1Department of Pediatric Cardiothoracic Surgery, University Medical Center Utrecht, Utrecht, The Netherlands. s.o.algra@umcutrecht.nl
Insights
A new bedside rule helps predict infection risk in children after cardiac surgery. It uses factors like age, PICU stay, and sternum status at 48 hours to identify high-risk patients.
Area of Science:
- Pediatric Surgery
- Infectious Diseases
- Clinical Prediction Models
Background:
- Postoperative infections are a significant complication in pediatric cardiac surgery, affecting up to 30% of patients.
- Accurate risk stratification is crucial for implementing targeted preventive strategies.
Purpose of the Study:
- To develop a simple, bedside prediction rule for estimating the risk of postoperative infection in pediatric cardiac surgery patients.
- To identify key clinical variables available at 48 hours post-surgery that predict infection risk.
Main Methods:
- Retrospective analysis of 412 pediatric cardiac surgery procedures (April 2006 - May 2009).
- Infection defined by CDC criteria (2008).
- Multivariable logistic regression used to construct a prediction rule based on variables available at 48 hours post-surgery.
Main Results:
- 102 (25%) patients developed a postoperative infection.
- Predictive variables for infection: age < 6 months, pediatric intensive care unit (PICU) stay > 48 hours, and open sternum > 48 hours.
- A scoring system was developed, with infection risk ranging from 6.6% (score 0) to 57% (maximal score 6). Area under the ROC curve was 0.78.
Conclusions:
- A bedside prediction rule, applied 48 hours post-cardiac surgery, effectively identifies children at high or low risk of subsequent infection.
- This tool can aid clinicians in managing infection risk in this vulnerable population.
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.
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