Background Some critically ill children have malnutrition which may worsen while they are in hospital and delay their return home. They can recover faster when they are given tube feedings to improve their nutrition. Unfortunately, in the hospital these feedings are often interrupted and so these children do not get all the nutrition they need. The usual procedure is to set hourly rates for the tube feedings and to accept that they get less when feedings are interrupted. The researchers would like to test if children are fed better if the bedside nurses were to check the volume provided through the day and then ensure the child gets closer to the prescribed volumes. Aim To determine the feasibility of performing a Randomized Control Trial assessing the use of a Volume-based feeding algorithm in critically ill children admitted to the Alberta Children's Hospital Pediatric Intensive Care Unit (PICU). Objectives 1. Obtain information to inform sample size calculations for nutrition and clinical outcomes for a larger RCT: energy adequacy and protein adequacy, feed tolerance, infections, changes in anthropometric measurements at transitions of care, 28-day ventilator free days, length of stay, 60-day mortality, and 60-day hospital readmission? 2. Assess adherence of medical staff to the study protocol 3. Evaluate the timing of study enrollment and participant allocation 4. Evaluate the proposed deferred consent strategy. Methods The researchers will conduct a randomized control feasibility trial of critically ill children admitted to the Alberta Children's Hospital (ACH) Pediatric Intensive Care unit who require tube feedings. Children will be randomly assigned to the intervention arm (Volume-based algorithm) or the comparison arm (rate-based algorithm). Significance The proposed study will provide evidence of whether a novel approach to feeding critically ill children is feasible during PICU admission. This trial will inform a larger Randomized Control Trial on this topic that will assess if using a Volume-based feeding algorithm will improve outcomes of clinical importance including energy adequacy, protein adequacy, feed tolerance, infections, changes in anthropometric measurements at transitions of care, 28-day ventilator free days, length of stay in PICU and hospital, 60-day mortality, and 60-day hospital readmission.
See this in plain English?
AI-rewrites the medical criteria so a patient or caregiver can understand them. Always confirm with the trial site.
Assess participant enrollment and recruitment will be completed by documenting the number of children who successfully initiate the study protocol.
Timeframe: Up to 12 months
Number of deviations from assigned feeding algorithm.
Timeframe: Up to 12 months
Reason for participant attrition/withdraw from study.
Timeframe: Up to 12 months
Day of participant attrition/withdraw from study.
Timeframe: Up to 12 months
The length of time it takes between randomization of eligible participants to starting the assigned feeding algorithm to obtaining consent/assent.
Timeframe: Up to 12 months
Proportion of eligible subjects who provide consent/assent.
Timeframe: Up to 12 months
10 semi structured qualitative interviews to to assess guardians/caregiver perception and experiences around deferred consent.
Timeframe: Semi-structured interviews will take place after PICU discharge - up to 6 months
10 semi structured qualitative interviews to to assess patient experiences around deferred consent.
Timeframe: Semi-structured interviews will take place after PICU discharge - up to 6 months