NURS-04. NUTRITION RISK CLASSIFICATION AND INTERVENTION DECISION TOOL FOR CHILDREN WITH CENTRAL NERVOUS SYSTEM TUMORS. Issue 2 (22nd June 2018) - Hill, Rachel; Mansell, Mandy; Johnson, Danielle; Hines, Ashleigh
Abstract: During childhood cancer treatment, nutrition screening and timely intervention is vital because malnutrition negatively impacts survival, treatment tolerance, infection risk, quality of life, and cost of care. Though some central nervous system (CNS) tumors present a greater nutritional risk than others, no specific classification system has been published, and there is no standardized decision-making process between institutions or providers. Additionally, despite aggressive efforts, many parents report conflict and guilt when their child experiences anorexia and is unable to maintain an appropriate nutritional status. Early education and the use of a proactive nutrition intervention decision tool could optimize intervention timing, standardize care between patients, and alleviate tension between the parent, patient, and medical team. Based on diagnosis, treatment intensity, and patient-specific characteristics including age, dysphagia, and nutritional status at diagnosis, an algorithm was developed to classify CNS tumor patients into three risk categories (low, intermediate, and high risk for malnutrition). Each category has a unique intervention pathway, including timing of dietitian consult, use of appetite stimulants and high calorie diets and/or supplements, and timing of nutrition support. Discussion points include selecting the most appropriate route of nutrition support when indicated, since surgically-placed feeding devices may potentiate problems during cancer treatment. Additional factors considered are dysphagia, age, expected enteral feeding duration, and nasoenteric feeding tolerance. This decision tool will be piloted to evaluate its utility. Quality of parental education and preparedness for nutrition intervention will be evaluated by a questionnaire. The tool will then be revised and validated.