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Weight for Height z-score (WHZ) and mid-upper arm circumference (MUAC) have been acknowledged as criteria for the diagnosis severe acute malnutrition (SAM) and the targeting of humanitarian nutrition programmes. However, in the absence of a gold standard allowing to understanding their respective diagnosis performances and limits, the statement of their inconsistencies is triggering the urgent need for relevant and practical diagnosis tools to improve the accuracy of SAM diagnosis in humanitarian settings. The project is co-funded by EU Humanitarian Aid.

What humanitarian need is being addressed?

The diagnosis of children suffering from Severe Acute Malnutrition (SAM): to increase the sensitivity and specificity of diagnostic measures for SAM and identify children who are at highest risk for life-threatening acute and chronic complications.

WHAT IS THE INNOVATIVE SOLUTION?

The solution we want to put in place can be described as novel diagnostic and screening tools relying on the assessment of emerging biomarkers of metabolic deprivation and vulnerability, as a complement or an alternative to anthropometric indicators, for identification, classification, and management of malnourished children in the developing world.

WHAT ARE THE EXPECTED OUTCOMES?

The project is part of a PhD leading to several scientific publications on:

  • Validated anthropometric indicators and confirmation of possible misdiagnosis of SAM made by MUAC or WHZ criteria.
  • Identification of high risk groups within the SAM children based on admission characteristics and treatment response.
  • Documented underlying heterogeneity of the pathophysiology.
  • Generation of new algorithms for the assessment and classification of malnourished children, based on the combined use of emerging biomarkers and anthropometric measures, or on the modification of anthropometric criteria (modified cut-offs for specific categories of children for instance, combination of wasting and stunting, etc…).
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Project Resources

Report Nutrition

Final Report: OptiDiag – Improvements in the diagnosis of child undernutrition through assessment of emerging biomarkers of deprived metabolic status and vulnerability

Latest Updates

Data collection is complete!

14 Aug 2018

It is with great pride that Action Against Hunger can announce the OptiDiag project’s successful on-the-field data collection in Bangladesh, Burkina Faso and Liberia.

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2018Aug

Five Days of Fieldwork (Part 2)

26 Feb 2018

The D4 assay uses a matched pair of antibodies to detect and capture leptin in a biological sample.

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Feb

Five Days of Fieldwork (Part 1)

06 Feb 2018

The team conduct a field test for a diagnostic device that would rapidly test for biomarkers of malnutrition.

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Printable tool enables sensitive diagnostic testing

07 Aug 2017

Project innovation featured in Eureka Alert.

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2017Aug

Starting up the OptiDiag Project

26 May 2016

In short, the OptiDiag project is designed to determine how to best diagnose (and subsequently treat) children suffering from severe acute malnutrition (SAM).

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2016May

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