INTRODUCTION

Incidence of malnutrition is 35.5% in our country. It is higher in critically ill children. The adverse effects of chemotherapy, feed intolerance, feeding interruptions, frequent admissions to hospital/icu and overall catabolic state of these children is a deterrent to their nutrition and growth. Nutrition status declines during the icu stay.¹

Malnutrition has been associated with increased morbidity (infections, weakness, prolonged mechanical ventilation, and delayed recovery) as well as increased mortality.

In 2013, the Academy of Nutrition and Dietetics and American Society of Parenteral and Enteral Nutrition (ASPEN) defined paediatric malnutrition as “an imbalance between nutrient requirements and intake, resulting in cumulative deficits of energy, protein or micronutrients that may negatively affect growth, development and other relevant outcomes”.

The European Society for Clinical Nutrition and Metabolism (ESPEN) and the European Society for Pediatrics Gastroenterology, Hepatology and Nutrition (ESPGHAN) recommend nutritional risk screening for hospitalized children during admission, to facilitate the detection of children nutritionally at risk and to allow the physician to make an appropriate nutritional support plan. Even if several pediatric nutritional risk scores are reported in literature, there is no consensus on the “ideal” screening tool and, often, nutritional screening is not yet widely performed.

AIM

To study the nutrition practices in paediatric intensive care unit in terms of timing, dosing and delivery of enteral and parenteral nutrition.

METHODOLOGY

1.    We will commence the study after approval from the Hospital Ethics Committee approval and registration with the Clinical Trials registry of India.

2.    This is a Prospective observational case control study, which will be conducted in ICU in Tata Memorial Hospital.

3.    Nutritional practices will be recorded during the  ICU and patients will be followed up until hospital discharge.

4.    We will also record Nutrition scores, Incidence of malnutrition by anthropometric data. For haematology patients below the age of 5, we will utilise the weight-for-height (WFH) ratio as a means to assess their nutritional status.

5.    For patients aged 5 and above, we rely on the body mass index (BMI) to assess malnutrition. BMI takes into account both weight and height and aids in categorising individuals as underweight, normal weight, overweight, or obese.

6.    We will be measuring the weight of the child on a weighing scale directly or if it’s safe and feasible, indirectly when held by the parent (standing on the weighing scale) by subtracting parent’s weight from total. Children are weighed daily in the wards, so we will obtain the admission weight from there if not feasible in the ICU.

7.    In cases of solid tumor patients, we acknowledge that weight alone may not accurately reflect their nutritional status due to the presence of tumor mass. Therefore, when assessing malnutrition using weight-for-height or BMI, we also incorporate the measurement of mid-upper arm circumference (MUAC) as per Frisancho. MUAC provides additional insights into muscle mass and overall nutritional status. Triceps skin fold (TSF) is measured as per St. Jude children’s Research Hospital algorithm which is defined as TSF < 5^th Percentile as severely depleted, 5-10^thpercentile as moderately depleted and TSF >10^th percentile as adequate.

8.    Anthropometric data will be measured according to latest CDC guidelines as of 2022 under the following headings of – Measuring recumbent length, measuring weight, Arm circumference and skin fold thickness measurements. Measurements will be taken according to techniques mentioned in the National Health and Nutrition Examination Survey (NHANES) by the CDC. Techniques used to obtain accurate anthropometric measurements have been attached to the appendix.

9.    The values obtained will be then analysed using the WHO 2006 and IAP growth charts. Charts have been attached in the appendix.

10. BMI will be calculated using kilograms obtained by weighing the participant and height obtained in metres, and will be then analysed as kg/m2, interpreted as per IAP growth charts.

11. According to the American Association of Pediatrics (AAP), clinically significant weight loss depends on age. Newborns may lose 5% to 10% of their birth weight in the first few days after birth; losses greater than 12% are concerning. In children, unintentional weight loss greater than 5% from baseline may be concerning.

12. The refeeding syndrome appears in patients who have had a reintroduced and/or increased caloric intake. ASPEN proposed the following diagnostic criteria for refeeding syndrome as being, A reduction in serum levels in one or any of the electrolytes, phosphorus, potassium or magnesium by 10–20% (mild refeeding syndrome), 20–30% (moderate refeeding syndrome), or >30% (severe refeeding syndrome), or organ dysfunction results from a decrease in any of these and/or as a result of thiamine deficiency (severe refeeding syndrome). Combined with this occurrence within 5 days of recommencing or significantly increasing energy provision.

13. We will also record Time to initiation of enteral/parenteral nutrition and time to achieve target nutrition goals, Dosing (calories, protein, continuous/ bolus) and route of enteral or parenteral nutrition, Nutrition free days, Incidence of feed intolerance, overfeeding/ refeeding syndrome, PRISM/PIM III scores, acquired nosocomial infections define (VAP/UTI/BSI) etc.

14. As indicators of feeding intolerance, we will look for the following symptoms and signs.

15. Symptoms – Vomiting (altered milk, bile or blood stained).

16. Signs –

1.    Abdominal distention (>2cm increase in abdominal girth from baseline)

2.    Abdominal tenderness

3.    Gastric Residual Volume

4.    Reduced or absent bowel sounds

5.    Systemic signs (bradycardia, shock, apnea, asystole)

Statistical analysis plan

Descriptive statistics will be presented with numbers and proportions and medians and interquartile ranges (IQR) as appropriate. Statistical analysis will be performed using IBM-SPSS version 25.0. Statistical analysis for continuous variables will be performed by using Analysis of Variance (ANOVA) and Chi square test for categorical variables. We will perform Multivariate analysis using the cox regression method to identify independent predictors of mortality and assess correlation of malnutrition with icu Outcomes. The significant level will be set to 5% and all reported p-value will be two sided.