Improving the Outcomes of Community-based Management of Acute Malnutrition

NCT ID: NCT04582773

Last Updated: 2021-02-02

Basic Information

• Recruitment Status: COMPLETED
• Total Enrollment: 1087 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2019-07-22
• Study Completion Date: 2020-10-30

Brief Summary

Severe acute malnutrition (SAM) affects 16 million children at any one time and is responsible for the deaths of over 500,000 children under 5 years of age each year. Treatment for severe acute malnutrition is based on the Community-based Management of Acute Malnutrition (CMAM) model. The current methods used for detecting high risk children have not prevented 5% mortality observed in regions using this program. The purpose of the study is to provide evidence that objective methods for detecting high risk children can be used to optimize efficiency of Community-based Management of Acute Malnutrition (CMAM) treatment programs and thus improve child health outcomes.

Detailed Description

A prospective observational study in inpatient care within community-based management of acute malnutrition(CMAM) program run by the nongovernmental organization called Alliance for International Medical Action (ALIMA) within the University of Maiduguri Teaching Hospital, Maiduguri, Nigeria

The objectives of the study are to validate the BedsidePEWS scores as a measure of severity of illness in children who are treated as inpatients for severe acute malnutrition and to compare the BedsidePEWS scores with other risk factors associated for mortality and relapse of children with severe acute malnutrition. The design is a prospective observational study of 1000 children admitted as inpatients in a CMAM program in Maidaguri Teaching Hospital in Maidaguri, Nigeria. Data collection (estimated duration 4-5 months) involves vital signs, and risk factor assessment every 12 hours for duration of hospitalization. Blood test for hemoglobin and malaria will be done once upon admission. Outcomes will be measured every 12 hours and include mortality and/or escalation and de-escalation of care. Logistic regression with significance testing will be used to compare BedsidePEWS scores and risk factors between patients and among individual patients within the outcome categories. Exploratory sensitivity analyses will repeat the main logistic regression analyses to evaluate the performance of partial BedsidePEWS score in patients with missing data of 1-3 of the 7 components, by randomly removing 1-3 data elements from the score calculation from patients, and by removing systolic blood pressure from scoring.

Conditions

Severe Acute Malnutrition

Study Design

• Observational Model Type: COHORT
• Study Time Perspective: PROSPECTIVE

Eligibility Criteria

Inclusion Criteria

• Aged 1 to 59 months
• Diagnosed with severe acute malnutrition (criteria for severe acute malnutrition is <3Z Weight for Height Z score, and/or MUAC <115mm, and/or bilateral pitting oedema)
• Meet the criteria for admission into inpatient care (failed appetite test, and/or medical conditions).

Study amendment for inclusion: children with and without severe acute malnutrition admitted to emergency pediatric unit (EPU)

Exclusion Criteria

• Children with congenital anomalies that interfere with feeding (ie. cleft lip and/or palate); previous enrolment in this study.

• Minimum Eligible Age: 1 Month
• Maximum Eligible Age: 59 Months
• Eligible Sex: ALL
• Accepts Healthy Volunteers: No

Sponsors

Alliance for International Medical Action

OTHER

Sponsor Role: collaborator

University of Maiduguri Teaching Hospital

UNKNOWN

Sponsor Role: collaborator

Tampere University

OTHER

Sponsor Role: collaborator

The Hospital for Sick Children

OTHER

Sponsor Role: lead

Responsible Party

Christopher Parshuram

Principal Investigator

Responsibility Role: PRINCIPAL_INVESTIGATOR

Principal Investigators

Chris Parshuram, MD/PHD

Role: PRINCIPAL_INVESTIGATOR

The Hospital for Sick Children

Locations

University of Maiduguri Teaching Hospital

Maiduguri, Borno State, Nigeria

Countries

Nigeria

Other Identifiers

REB1000063224

Identifier Type: -

Identifier Source: org_study_id