Continuous Versus Intermittent Nutrition in Pediatric Intensive Care Patients: Protocol for a Randomized Controlled Trial

Background: Intermittent fasting is a time-restricted feeding strategy with proven health benefits, which is based on multiple metabolic and endocrine changes, in several patient populations and healthy participants. In the pediatric intensive care unit (PICU), artificial feeding is usually administered 24 hours a day, although solid evidence supporting this practice is lacking. This discards the potential benefits of fasting in this population. We hypothesize that intermittent nutrition with a focus on an overnight feeding interruption (intermittent fasting), as compared with 24-hour continuous nutrition, is a feasible and safe strategy, with potential benefits, for critically ill children. Objective: The aim of the Continuous versus Intermittent Nutrition in Pediatric Intensive Care randomized controlled trial (RCT) is to investigate a strategy of intermittent nutrition with a focus on an overnight feeding interruption period versus 24-hour nutrition during the first 14 days in the PICU. Methods: The Continuous versus Intermittent Nutrition in Pediatric Intensive Care study is an investigator-initiated RCT in a tertiary referral PICU. Critically ill children (term newborn to 18 years), expected to stay in the PICU for ≥48 hours, and dependent on artificial nutrition, are eligible for inclusion. This study will randomize critically ill children (n=140) to a continuous versus intermittent nutrition strategy. In both groups, similar daily caloric targets will be prescribed. In the continuous group (control), nutrition will be administered 24 hours a day, with a maximum interruption period of 2 hours. In the intermittent group (intervention), nutrition will be interrupted during an age-dependent overnight fasting period. The study intervention will last until admission day 14, initiation of oral intake, or discharge from the PICU, whichever comes first. The primary outcome is the difference in ketosis between the groups under the condition of noninferiority regarding caloric intake. Secondary outcomes are feeding intolerance; the proportion of severe and resistant hypoglycemic events and severe gastrointestinal complications; and additional observed effects on nutritional intake, circadian rhythm, and clinically relevant outcome measures of the intermittent feeding strategy compared with continuous nutrition. Results: The study was approved by the Dutch national ethical review board in February 2020. The first patient was enrolled on May 19, 2020. By May 2022, a total of 132 patients had been included in the study. Recruitment of the last patient is expected in Q3 2022. Conclusions: Although intermittent fasting has been proven to have many health benefits in both animal and human studies, the feasibility and safety of this strategy in a PICU setting must be investigated. This RCT will help physicians gain more insight into the feasibility, safety, and potential clinical effects of intermittent feeding with overnight fasting in critically ill children

An EEG-based sleep index and supervised machine learning as a suitable tool for automated sleep classification in children

STUDY OBJECTIVES: Although sleep is frequently disrupted in the pediatric intensive care unit (PICU), it's currently not possible to perform real-time sleep monitoring at the bedside. In this study, spectral band powers of electroencephalography (EEG) data are used to derive a simple index for sleep classification.METHODS: Retrospective study at Erasmus MC Sophia Children's Hospital, using hospital-based polysomnography (PSG) recordings obtained in non-critically ill children between 2017 and 2021. Six age categories were defined: 6-12 months, 1-3 years, 3-5 years, 5-9 years, 9-13 years and 13-18 years.UNLABELLED: Candidate index measures were derived by calculating spectral band powers in different frequent frequency bands of smoothed EEG. With the best performing index, sleep classification models were developed for two, three and four states via decision tree and five-fold nested-cross validation. Model performance was assessed across age categories and EEG channels.RESULTS: In total 90 patients with PSG were included, with a mean (standard deviation) recording length of 10.3 (1.1) hours. The best performance was obtained with the gamma to delta spectral power ratio (gamma:delta-ratio) of the F4-A1 and F3-A1 channels with smoothing. Balanced accuracy was 0.88, 0.74 and 0.57 for two, three and four state classification. Across age categories, balanced accuracy ranged between 0.83 - 0.92 and 0.72 - 0.77 for two and three state classification, respectively.CONCLUSIONS: We propose an interpretable and generalizable sleep index derived from single-channel-EEG for automated sleep monitoring at the bedside in non-critically ill children aged 6 months to 18 years, with good performance for two and three state classification.</p