A Proposed Clinical Algorithm for Children with Upper Respiratory Illness Undergoing Elective Cardiac Procedures Requiring Anesthesia.
TL;DR
An algorithm emphasizing the severity of respiratory illness, the patient's cardiac physiology, and selective, deliberate viral testing in specific clinical circumstances is proposed, which may reduce postponement of cardiac procedures in this patient population while maintaining favorable clinical outcomes.
Abstract
BackgroundChildren presenting for elective procedures with upper respiratory illness (URI) represent a common clinical dilemma. While several decision algorithms exist to guide perioperative management in the general pediatric surgical population, to our knowledge, no published perioperative decision frameworks specifically address children with congenital heart disease (CHD) presenting for elective procedures with URI, despite their unique physiology and perioperative risk.MethodsA review of the pediatric and congenital cardiac anesthesia literature was performed to evaluate established clinical algorithms used to guide decisions to proceed with elective cases requiring anesthesia in children with URIs. We also reviewed the literature assessing risk associated with URI symptoms in children with CHD undergoing procedures requiring anesthesia.ResultsSeveral clinical algorithms exist to help clinicians decide whether to proceed with elective procedures in children with URI symptoms. These algorithms emphasize symptom severity, comorbid pulmonary disease, and surgical factors when determining whether to proceed with anesthesia. However, no current decision algorithms address pediatric patients with heart disease. Existing algorithms do not account for these patients' diverse cardiac physiologies and risks. We propose an algorithm emphasizing the severity of respiratory illness, the patient's cardiac physiology, and selective, deliberate viral testing in specific clinical circumstances.ConclusionsChildren with cardiac disease undergoing cardiac procedures with URI symptoms represent a unique population not addressed by existing decision algorithms. The proposed algorithm prioritizes clinical examination, the patient's cardiac physiology, and judicious viral testing. This algorithm may reduce postponement of cardiac procedures in this patient population while maintaining favorable clinical outcomes.