Validation and Impact of Paediatric Malnutrition Screening Tool in Hospitalised Children on Medical Staff Awareness and Health-Related Outcomes
Trial Snapshot
- Phase
- Not Applicable
- Status
- Completed
- Sponsor
- Rabin Medical Center
- Enrollment
- 484
- Locations
- 2
- Primary Endpoint
- Effect of STAMP on staff's awareness to nutritional status
Study Overview
Brief Summary
Children hospitalized due to an acute disease may suffer from acute malnutrition or chronic malnutrition caused by chronic diseases.
We aimed to evaluate the use of the Screening Tool for the Assessment of Malnutrition in Pediatrics (STAMP) among children admitted in a pediatric hospital, and assess its effect on medical staff's awareness to nutritional status and health outcomes at discharge.
Detailed Description
Malnutrition prevalence upon admission to paediatric hospitals remains considerably high, ranging from 7.3 to 17.9% in the developed world with higher prevalence rates in infants and toddlers and particularly high rates for specific medical conditions. Several studies have reported deterioration of nutritional status during hospitalization. Screening children for malnutrition risk is recommended by a number of international organizations such as the American Society for Parenteral and Enteral Nutrition (ASPEN), the European Society for Parenteral and Enteral Nutrition (ESPEN) and the European Society for Paediatric Gastroenterology, Hepatology and Nutrition (ESPGHAN).
Screening Tool for the Assessment of Malnutrition in Pediatrics (STAMP) was chosen for this study because it is highly applicable, frequently used by nurses and has shown high reproducibility, as well as concurrent and predictive validity. The tool was developed by McCarthy et al11 in England. It collects the following information to assess nutritional risk for a patient: discrepancy between the weight and height percentile weight for the age expected nutritional risk caused by clinical diagnosis, recent changes in the appetite. The assessment results are used to define if there is a need for a referral to a full nutritional assessment.
We aimed to evaluate the use of the Screening Tool for the Assessment of Malnutrition in Pediatrics among children admitted in a pediatric hospital, and assess its effect on medical staff's awareness to nutritional status and health outcomes at discharge.
Study Design
- Study Type
- Interventional
- Allocation
- Non Randomized
- Intervention Model
- Parallel
- Primary Purpose
- Supportive Care
- Masking
- None
Eligibility Criteria
- Ages
- 1 Year to 17 Years (Child)
- Sex
- All
- Accepts Healthy Volunteers
- No
Inclusion Criteria
- •patients hospitalized during the study,
- •patients hospitalized for more than 24 hours. The children will be enrolled from 3 internal medicine and surgical departments, children's parents will give their consent and will be able to understand and sign the consent forms
Exclusion Criteria
- •children < 1 year of age,
- •children > 17 years of age,
- •children hospitalized for less than 24 hours,
- •children in the intensive care unit or following hospitalization in the intensive care unit.
- •Statistical analysis for STAMP validation will be performed using Kappa (K) test. Chi square test will be used in order to calculate the effect of STAMP use
Outcomes
Primary Outcomes
Effect of STAMP on staff's awareness to nutritional status
Time Frame: one year
Methods for testing the effect of STAMP tool use on the attitude of the medical staff to the nutritional status, measured by collection of data related to the nutritional status and recording them in the patient's file.
Validity and reliability
Time Frame: one year
The growth chart tables accepted in England, CDC (Centers for Disease Control will be used in order to compare weight and height and generate them into the BMI. The children will be divided into 3 nutritional risk groups: low, moderate and high according to the STAMP toll assessment and the results will be compared to the dietician's complete assessment. Nutritional assessment will include: demographic and medical data, daily nutritional intake, blood tests, anthropometric measurements.
Health outcome at discharge: haemoglobin (g/dl)
Time Frame: One year
Health outcomes on the discharge of the children who are screened by STAMP will be compared to outcomes of children are not. The data for this comparison includes changes in haemoglobin during hospitalisation. Controls are matched by age, gender, and STAMP risk score will be calculated based on the retrieved information from medical files.
Health outcome at discharge: albumin (g/dl)
Time Frame: One year
Health outcomes on the discharge of the children who are screened by STAMP will be compared to outcomes of children are not. The data for this comparison includes changes in albumin levels during hospitalisation. Controls are matched by age, gender, and STAMP risk score will be calculated based on the retrieved information from medical files.
Health outcome at discharge: number of recurrent hospitalisations
Time Frame: One year
Health outcomes on the discharge of the children who are screened by STAMP will be compared to outcomes of children are not. The data for this comparison includes the number of recurrent hospitalisations. Controls are matched by age, gender, and STAMP risk score will be calculated based on the retrieved information from medical files.
Health outcome at discharge: weigh (KG)
Time Frame: one year
Health outcomes on the discharge of the children who are screened by STAMP will be compared to outcomes of children are not. The data for this comparison includes weight changes during hospitalisation measured in Kg. and changes in haemoglobin and albumin levels. Controls are matched by age, gender, and STAMP risk score will be calculated based on the retrieved information from medical files.
Health outcome at discharge: length of stay (number of days)
Time Frame: One year
Health outcomes on the discharge of the children who are screened by STAMP will be compared to outcomes of children are not. The data for this comparison includes length of stay (LOS). Controls are matched by age, gender, and STAMP risk score will be calculated based on the retrieved information from medical files.
Secondary Outcomes
No secondary outcomes reported
Investigators
raanan shamir
Chairman, Institute of Gastroenterology, Nutrition and Liver Diseases
Rabin Medical Center