Biomedical Investigations for Optimized Diagnosis and Monitoring of Severe Acute Malnutrition (SAM): Elucidating the Heterogeneous Diagnosis of SAM by Current Anthropometric Criteria and Moving Beyond

Study Overview
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Brief Summary
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INTRODUCTION In 2014, 50 million children under 5 suffered from acute malnutrition, of which 16 million suffered from SAM, most of them living in sub-Saharan Africa and Southeast Asia. SAM children have higher risk of mortality (relative risk between 5 and 20). It is an underlying factor in over 50% of the 10 - 11 million preventable deaths per year among children under five. At present, 65 countries have implemented WHO recommendations for SAM treatment (both in-patient for complicated cases and outpatient for uncomplicated cases) but these programs have very low coverage, reaching only around 10 - 15 % of SAM children. In 2009 the World Health Organization (WHO) and the United Nations Children's Fund (UNICEF) issued a joint statement in an effort to harmonize the application of anthropometric criteria for SAM diagnosis and monitoring in child aged 6 - 59 months; the statement presents recommended cut-offs, and summarizes the rational for the adoption, of the following two anthropometric criteria: Weight-for-Height Z-Score (WHZ): WHO and UNICEF recommend the use of a cut-off for weight-for-height of below -3 standard deviations (SD) of the WHO standards to identify infants and children as having SAM. Additionally, analysis of existing data show that children with a WHZ < -3 have a highly elevated risk of death. Mid-Upper Arm Circumference (MUAC): WHO standards for the MUAC-for-age show that in a well-nourished population there are very few children aged 6 - 59 months with a MUAC less than 115 mm. Children with a MUAC less than 115 mm have a highly elevated risk of death compared to those who are above. Thus it is recommended to [use] the cut-off point [of] 115 mm to define SAM with MUAC. GENERAL OBJECTIVE To generate new evidence on pathophysiological process, nutritional needs and risks associated with different types of anthropometric deficits in children under 5, in order to optimize the diagnosis and treatment of SAM. SPECIFIC OBJECTIVES To compare nutritional status, metabolism, pathophysiological process and risks in different types of SAM anthropometric diagnosis, with or without concomitant stunting (growth retardation). To analyze the extent to which current SAM treatment is promoting recovery and healthy growth in different categories of children. To evaluate the relevance of current discharge criteria used in nutrition programs and their association with metabolic recovery, in different age groups and among those who are stunted. To test novel rapid tests of emerging biomarkers predicting long-term outcomes and mortality risk in the field. METHODOLOGY A wide range of supplementary information related to nutritional status, body composition, metabolic and immune status, including emerging biomarkers of metabolic deprivation and vulnerability, will be collected besides anthropometry during prospective observational studies. They will be collected with minimum level of invasiveness, compatible with field work requirements in the humanitarian context. Phase 1: Cross-sectional surveys. Phase 2: Prospective cohort studies involving SAM children between 6 months and 5 years old. Children admitted as SAM at the nutrition centers will be enrolled into the cohort. The follow up duration will be at least three months. EXPECTED OUTCOMES Confirmation of current hypotheses related to: possible misdiagnosis of SAM made by MUAC or WHZ criteria, varying degree of severity and need for admission to treatment of the different types of diagnosis, 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. Generation of new treatment paradigms based on the predictive value of biomarkers in combination with traditional anthropometric measures. This will enable us to assess the power of current treatment regimens to promote long-term weight gain and growth and will allow us to tailor treatment to the physiological needs of the child.

Detailed Description
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DIAGNOSTIC DISCREPANCY According to WHO experts, WHZ and MUAC can be used independently to indicate severe acute malnutrition (WH. There is however a significant and sometimes huge discrepancy between these two criteria: they do not usually identify the same children as acutely malnourished; moreover when used as proxy indicator to assess a deteriorating nutritional situation at a population level, these criteria do not report the same level of global acute malnutrition in the same zone. It was reported that only about 40% of SAM cases identified by one indicator are also diagnosed as such by the other. For example, among severely malnourished children hospitalized in rural Kenya, 65.1% (486/746) of the WHZ -3 cases also had a MUAC < 115 mm, whereas 56% (489/873) of the MUAC < 115 mm cases were also identified by WHZ < -3. In that study, 42.9% (489/1140) of the SAM cases were identified by both indicators. The discrepancy between the two indicators can be even more extreme. Fernandez et al. reported that among 34,937 children between the ages of 6 - 59 months from 39 nutritional surveys, 75% of the children with a WHZ < -3 were not identified by a MUAC < 115 mm. In Cambodia, this proportion was above 90%, whereas 80% of MUAC < 115 mm were not detected by WHZ < - 3. Most of the time, caseloads defined by WHZ are much larger than by MUAC, but the contrary may happen as well, especially in the younger age groups. PROGRAMMATIC CONFUSION Such discrepancy generates important programmatic challenges and confusion. On the one hand, a strategy where the diagnosis can be based on either indicator, as recommended by some authors may unduly inflate the workload of nutritional rehabilitation programs, as the most appropriate management of children identified by one indicator and not by the other is uncertain. On the other hand, relying on only one of these indicators, e.g. using only MUAC < 115 mm in community-based programs, may under-detect true acute malnutrition cases and result in missed opportunities to treat a severe condition. In recent years, however, the use of MUAC alone for admission has been discussed, and is increasingly applied in a variety of contexts. In particular, more and more national protocols for SAM management consider MUAC only management as programmatic option. The national guidelines in Bangladesh, for example consider only low MUAC as an admission criterion for uncomplicated SAM management, which by de facto excludes a vast majority of the SAM children, those who have WHZ < - 3 and MUAC ≥ 115mm. Many benefits of using MUAC exist: MUAC is predictive of death, easy to use, acceptable, and favors community-based screening methods. Yet, as these two anthropometric tools select different children for treatment, as outlined above, this complicates the programmatic paradigm shift from admitting children using MUAC < 115 mm and/or WHZ < -3 to a new model admitting children using MUAC < 115 mm only. Depending on context, up to 63-79% of children currently recommended for therapeutic feeding with WHZ < -3 and/or MUAC < 115 mm would not be eligible if using MUAC < 115 mm alone for admission. RATIONALE To inform decision making regarding the use of MUAC as a standalone admission criterion in nutrition programming, more information on the programmatic and clinical implications of using MUAC alone is urgently needed. Despite WHO clearly highlighting the importance of this anthropometric diagnostic heterogeneity, and requesting more investigation, very little has been done so far. Preliminary reports demonstrate demographic and anthropometric differences among children identified by WHZ and MUAC: MUAC is more likely to identify children that are younger, female and with concomitant stunting. These data have been used to suggest a role for MUAC to identify children that are potentially more vulnerable or at a higher risk of death, supporting the transition to a MUAC-only based admission criterion. Recent secondary analysis of the clinical profile and outcomes of SAM children admitted to an outpatient SAM program in Niger infirmed this hypothesis, by showing a similar vulnerability profile in SAM children presenting with a MUAC < 115 mm (with or without concomitant WHZ <- 3) and in SAM children with a MUAC ≥ 115mm, i.e. only with WHZ < -3, who would not be considered for treatment in case of MUAC-only programming. Furthermore, according to this study, and a similar one from a SAM management program in South-Sudan, the anthropometric category of SAM children displaying the highest vulnerability at admission and the worse treatment outcomes are those combining MUAC < 115mm and WHZ < -3. These results are in line with previous observations from an in-patient SAM management program in Kenya. Beyond the investigation of possible variations in mortality risks, all reviews of available evidence on this issue highlight the need for robust research to further investigate the physiological significance of the different anthropometric criteria and to better understand how the clinical status and nutritional needs of the children are addressed over the course of nutritional rehabilitation. A key issue is indeed that these two different indicators identify different populations of children, the reason for which is unknown due to the lack of a gold standard. Current hypotheses to explain the diagnosis discrepancy are that: WHZ<-3 overestimates the diagnosis of acute malnutrition in populations with a slender morphology (i.e. with a low sitting-to-standing-height ratio; SSR) as observed in pastoralists. MUAC at a fixed cut-off overestimate SAM in the younger children, in girls and in the stunted children, and on the contrary underestimates SAM in older, male, and non-stunted children. Young age, being a girl and stunting are indeed factors known to be associated with lower MUAC measurements and were already shown to be independently associated with MUAC diagnosis: lesser levels of acute nutritional deficits and wasting might thus be necessary to reach the 115mm cut-off in these children. These hypotheses have recently been supported by the analysis of the strength of the association between these factors and the diagnosis discrepancy in nutritional cross-sectional surveys. WHZ and MUAC criteria also may identify a separate kind of physiological deficit. It has been hypothesized that this might be related to differing impairments of fat and muscle mass stores, with MUAC reflecting preferentially fat mass for some authors and muscle mass for others. An analysis of body composition in a cohort of Ethiopian infants recently confirmed WHZ as a good marker of tissue masses independent of length, while MUAC appeared more as a composite index of poor growth indexing jointly tissue masses and length. Children identified by different criteria may thus require different treatment, one that is tailored to nutritional deficit. For instance, lower anthropometric response to treatment (lower MUAC gain and weight gain, longer treatment duration and higher proportion of non-responders) has already been observed in younger, stunted girls identified by MUAC. This might be linked to a suboptimal response in less severely wasted children, or might be due to a higher proportion of false positives in this sub-population, or be an indicator that the treatment is less effective or required in such children. Also, a recent meta-analysis of follow-up datasets evidenced a dramatic increase in mortality risk in children combining low WHZ and stunting (MUAC was not factored in). Today, in the absence of a gold standard for SAM, it is difficult to interpret different and often divergent anthropometric diagnoses. Additionally, there is a vital need to better understand if and how far physiological recovery, beyond anthropometric growth (which might be transient or sub-optimal) is achieved under the current SAM management strategy. Moreover, this understanding should encompass the whole population of children affected by anthropometric deficit, beyond just those few complicated cases that reach the hospital for inpatient nutritional rehabilitation. It should also account for potential contextual variation in the link between anthropometry and nutritional status. In order to describe and compare nutritional needs and risks associated with the different types of diagnosis as they are present in the community, we propose to conduct prospective cohort studies of SAM children who will be detected and referred to treatment in the catchment areas of community-based acute malnutrition management programs. Such programs combine both outpatient and inpatient nutritional rehabilitation, and an effective community outreach component. Nutritional needs and risks will be evaluated using a range of indicators: proxy indicators of nutritional, metabolic and immune status, among which several biomarkers whose association with risk of death has been recently evidenced in SAM children; clinical characteristics; and, response to treatment in terms of cure rates, recovery speed, relapse. The indicators necessary to do so must be easy to collect with low invasiveness and should provide reliable information regarding the severity of nutritional status. ISOTOPIC EVALUATION OF HAIR Isotopic analysis of stable carbon and nitrogen in human hair can be investigated and measured throughout the course of nutritional deprivation to reconstruct the onset and duration of undernourishment as well as tracing the temporal evolution of nutritional status. Several studies have revealed that factors like diet, disease and injury can influence nitrogen isotope ratios (d15N) in human tissues. Specifically, d15N values reflect the nitrogen balance of an organism in that during a catabolic state (tissue breakdown) d15N values increase while during an anabolic state (tissue buildup) d15N values decrease. In contrast, carbon isotope ratios (d13C) are shown to decrease during catabolism and increase during anabolism. Thus, during starvation the body becomes enriched in 15N and depleted in 13C at the same time. Since keratin remains unchanged after synthesis, and the speed of hair growth is constant (around 2.5 mm per week), weekly information on protein-energy metabolism can be traced back along the hair follicle, thereby indicating not only the severity of the episode of wasting but also the metabolic effects of the nutritional rehabilitation (on both lipid and protein anabolism). Isotopic evaluation of stable carbon and nitrogen in hair will therefore be used to create a retrospective timeframe of nutritional status and trace the physiological recovery of children during SAM management. LEPTIN AND IL-6 A recent study using non-targeted metabolomics analysis to characterize changes a broad array of hormones, cytokines, growth factors and metabolites during the treatment of SAM has revealed that a major biochemical predictive factor for mortality is low-level leptin. Low leptin and interleukin 6 levels reflect the adequacy of fat stores. Depletion of white adipose stores is postulated to limit the ability of a child to sustain energy production during the course of the illness and thereby increase the child's risk of death. Alternatively, hypoleptinemia may reduce viability affecting glucose and energy homeostasis or immune competence. Leptin and interleukin 6 targeted analysis will therefore be used to create a metabolic profile of SAM patients at presentation and during nutritional rehabilitation, and may predict mortality prior to and during treatment. Dr. Michael Freemark and colleagues at DUMC are currently developing novel point-of-care micro-assays to characterize the hormonal status of leptin and interleukin 6 in SAM children from a single fingerstick that will be piloted. MICRONUTRIENT AND IMMUNE RESPONSE BIOMARKERS Deficiencies of vitamin A and iron are among the most common micronutrient deficiencies related to childhood undernutrition and are both linked to compromised immune function. Manifestations of isolated iron deficiency include anemia, fatigue, impaired cognitive development and reduced growth and physical strength. Vitamin A deficiency contributes to anemia by immobilizing iron in the reticuloendothelial system, reducing hemopoiesis and increasing susceptibility to infections; it is essential for the functioning of the immune system and its deficiency has been clearly shown to be associated with diarrhea and related mortality. Vitamin A deficiency has been evidenced as frequent in SAM children. Vitamin A status, measured by the surrogate marker RBP, has been shown to be low in SAM children and to rise during nutritional rehabilitation. Mean serum vitamin A has been shown to decrease with increasing stunting (HAZ), wasting (WHZ) and underweight (WAZ). Additionally, there are indications that the storage levels of iron in SAM children are increased not decreased, even in the presence of quite severe anemia. However, there is a major lack of evidence on this point; we know that these parameters also need to be adjusted for inflammation biomarker, anemia and malaria, which was not done in the studies mentioned by Golden. Immune response biomarkers like C-reactive protein (CRP) are elevated in SAM children with severe bacterial infections. CRP is therefore a potentially valuable clinical tool for identifying bacterial infections, and recent research has shown that a rapid CRP could be useful in field settings to identify children most at risk for dying, with a relatively good negative predictive value (81% sensitivity, 85% specificity). There is a need to evaluate the relationship between micronutrient status, immune response and anthropometric diagnosis of SAM children at and to examine the extent to which nutritional rehabilitation is effective in treating deficiencies of vitamin A and iron and to prevent deficiencies during catch up growth. An inexpensive and sensitive simple sandwich enzyme-linked immunosorbent assay (ELISA) technique was recently developed to measure indicators of vitamin A and iron deficiency. Due to the low cost, high throughput, and comparability to traditional tests, this procedure has several advantages for assessing vitamin A and iron status on the field. Moreover, it can easily be combined with the measurement of immune response biomarkers like CRP and α1-acid glycoprotein (AGP). CRP, AGP, as well as biomarkers of iron (serum ferritin and serum transferrin receptor) and vitamin A status (serum retinol binding protein) can be assessed in a few drops of capillary blood. CRP and AGP will be used to adjust for the effect of inflammation on the micronutrient status indicators. Inflammation is indeed known to elevate serum ferritin and depress retinol binding protein as part of the biological acute phase response to inflammation. URINE TESTS The presence of ketones in the urine, indicating lipid catabolism (fat tissue disintegration and rapid weight loss) was evidenced during fasting and SAM. Metabolic status for SAM children at the time of enrollment in CMAM has been characterized by ketonemia; yet, lipolysis decreases in response to nutritional rehabilitation suggested by total ketones. Moreover, biomarkers of urinary infections like urinary nitrites and urinary leucocyte esterase (LE) have also been shown to be associated with an increased mortality risk in SAM children. Positive dipstick urinalysis administered as a bedside screening test for either nitrates or LE is associated with a higher case fatality and was shown to be a strong predictor of mortality in children admitted with SAM. Non-sterile urine sample will be also carried out when possible, and these biological parameters will be measured using through the urinary multiple indicator strips (e.g. Roche laboratory, or Combi Screen of Analyticon). BIOELECTRICAL IMPEDANCE (BI) It has been suggested that different anthropometric diagnoses identify children with different body composition, and associated nutritional needs. Restoration of body composition indicates successful management of SAM. Bioelectral impedance (BI) is a safe, rapid and easy technique often used to assess body composition, predicting total body water (TBW) in non-edematous children. It has demonstrated utility for indexing acute changes in hydration in children with SAM during in-patient treatment. This technique could also potentially distinguish tissue versus hydration relates weight catch-up during or post treatment. Lastly, BI analysis may predict survival outcomes for children hospitalized for SAM. BI parameters will therefore be used to describe body composition at admission and the restoration of body composition throughout nutritional recovery. METHODS STUDY DESIGN This study consists of three prospective follow-up studies (Bangladesh, Burkina Faso and Liberia) including cohorts of SAM children between 6 and 59 months of age. Children will be recruited according to the current WHO recommended anthropometric criteria for SAM diagnosis, WHZ and MUAC. Clinical examination, interviews with caregivers and blood and hair samples will be collected at admission and follow-up. Prospective follow-up cohort studies will be nested into currently operational Community-based Management of Acute Malnutrition (CMAM) programs run with the technical support of ACF-France, in hospitals and primary health-care centers involved in SAM management. All participants will be treated according to the standard of care outlined in the national protocol for SAM management of the country; this included a medical examination and standard treatment for infections as well as hospital referral for any complications requiring medical attention. The follow-up duration for enrolled SAM cases will be three months at minimum. Each individual cohort study will last approximately one year. This study design is multi-centric, and will be conducted in Bangladesh, Burkina Faso and Indonesia to account for potential contextual variation in the link between anthropometry and nutritional status. The various biomarkers assessed in this study, alongside anthropometry and clinical characteristics, at admission and follow-up times, can be grouped into the following three main groups: Biomarkers of micronutrient deficiencies: (1) iron status biomarkers like serum ferritin and serum transferrin receptor; (2) vitamin A status biomarkers like retinol binding protein; and (3) vitamin C in the urine. Biomarkers and indicators of body composition and energy metabolism: (1) urinary ketones; (2) natural enrichment of nitrogen and carbon stable isotopes in hair; and (3) circulating leptin and IL-6. Biomarkers of non-specific immune response or urinary infections: (1) c-reactive protein level; (2) urinary nitrites; and (3) urinary leucocytes esterase. QUESTIONNAIRES Data collection sheets, hereafter referred to as case report forms (CRF) will be linked to the patient's information by his or her unique study ID number. All data will be collected by trained ACF research staff. A baseline questionnaire will be administered upon admission by means of a structured interview with the caregiver. The interview content includes socioeconomic indicators, family size, income, expenditure as well as the medical history of the child (including changes in the child's weight, quantity and quality of food consumed and global health status). This questionnaire will include changes in the child's weight, quantity and quality of food consumed and overall health status. At each weekly visit, caregivers will answer a morbidity questionnaire (regarding fever, diarrhea, respiratory infection, and appetite) over the past week. Additionally, the caregiver will be asked to score the child's health status using a visual analog scale (VAS), table 4 the VAS is a psychometric response scale used in questionnaires to measure subjective characteristics or attitudes that cannot otherwise be directly measured (Visual Analog Scale, 2015). The use of a VAS in the assessment of severity of illness has been shown to be a strong predictor of mortality. These data will be compared to the patient's nutritional progress to assess the relationship between maternal health perception and nutritional indicators of recovery. Additional questions will probe adherence to treatment ready-to-use therapeutic food (RUTF) on a weekly basis. ANTHROPOMETRY Weight, height, MUAC, edema, will be measured weekly in all children. Weight will be measured to the nearest 0.1 kg with an electronic SECA scale, which will allow for simultaneous weighing of caregiver and patient. A standard weight of 5-10 kg will be used for daily calibration of the scale, and it will be stabilized on wooden plank to ensure the scale stays in a horizontal position. Length and height will be measured to the nearest 0.1 cm with a UNICEF model wooden height board with graduated index strips in millimeters on each side. A standardized length stick will be used to check the accuracy of the equipment. Children less than 2 years of age will be measured lying down and older children will be measured standing up. In case the age cannot be verified, children less than 87cm will be measured lying down. Children above 2 years of age, or above 87 cm who are not able to stand, will be measured lying, and 0.7 cm will be subtracted the recumbent length during data analysis. MUAC will be measured with a non-stretchable MUAC tape on the left arm to the nearest millimeter. Anthropometry will be measured and recorded twice. Measurements will be repeated by the same person and directly after each other to minimize discomfort for the child. The measurer will read out loud his measurement, which will then be repeated by the assistant who will record the results. In case of large differences between the measurements, the procedure will be repeated. All measuring tools will be calibrated and checked daily for accuracy and replaced if needed. To quantify the inter-measurer error, as part of training and refresher training programs, anthropometry measurements will be repeated by a second person. This procedure will be done on a small sample of children and will take place at the beginning, mid-way and end of the trial. CLINICAL ASSESSMENT AND EDEMA Presence of bilateral pitting edema of nutritional origin will be assessed by applying normal thumb pressure on the tops of both feet for three seconds. In the presence of edema (a remnant impression remains for some time, where the fluid has been temporarily pressed out of the tissue) the same procedure will be repeated on the lower legs, hands. Generalized, severe edema can be observed sacral pad and face (forehead, eyelids). The degree of edema generalization will be recorded according to WHO categorization of edema severity outlined in the guidelines for the management of severe acute malnutrition in children 6 to 59 months of age with edema, presented in table 5. The nurse will conduct a weekly clinical assessment of the child (i.e. temperature, respiratory rate, pulse rate, diarrhea, vomiting, and malaria). Symptoms, diagnosis and treatments prescribed will be recorded. The clinical assessment will also serve to monitor the development of medical complications requiring inpatient care. Any serious adverse effects or development of medical complications will be immediately reported to the study supervisor and the child will be referred for inpatient treatment if necessary. BLOOD SAMPLES AND ANALYSES Since no laboratory in the study area performs all the desired analyses required, the samples must be exported for analysis. A serum sample of 0.5 mL of serum from baseline and at two weeks and two months after nutritional rehabilitation will be sent to Dr. Juergen Ehardt at VitMin Laboratory in Wilstaett, Germany for the following analyses: C-reactive protein (CRP), a1-acid glycoprotein (AGP), Serum ferritin Retinol Binding Protein (RBP) Soluble Transferrin Receptor (sTfR). A duplicate serum sample will be kept in the event that the first sample is lost or destroyed during transport. Serum RBP will be used to assess vitamin A status. Serum ferritin and sTfR will be used to assess iron status. Additionally, the two acute phase reactants, CRP and AGP, will be measured and used to adjust for the effect of inflammation on the micronutrient status indicators. These five proteins will be measured using a specialized ELISA kit which analyses all five components simultaneously. HAIR SAMPLES AND ANALYSES A single lock of 20 - 25 hair follicles will be shaved at the back of the skull at admission and throughout treatment to both retrospectively characterize the nature and magnitude of metabolic deficits at admission; and also the efficacy of treatment in correcting them. Hair samples will be sent to Dr. Jean-Francois Huneau and Dr. Helene Fouillet at the Human Biology and Nutrition Laboratory at AgroParisTech in Paris, France. Hair samples will be sub-sectioned into 2.5 mm samples and analyzed for d13C and d15N through EA-IRM analysis. URINE SAMPLES AND ANALYSES Freshly voided, clean catch urine samples will be tested using reagent test strips (e.g. Multistix) at admission and at the end of treatment to assess biomarkers of urinary infections, urinary nitrites and urinary LE. BIOELECTRICAL IMPEDANCE BI parameters will be measures using a NutriGuard-S (DataInput, Germany) using protocols described elsewhere. Self-adhesive disposable electrodes will be attached to the right hand and foot. Measurements will be taken in triplicate, each spaced 5 minutes apart, while children are supine with limbs abducted from the body. DATA MANAGEMENT AND ANALYSIS DATA MANAGEMENT All questionnaire data and measurements will be measured on paper print-outs. The field supervisor will digitize, back-up and share data with the project coordinator at least weekly. Appropriate consistency checks and completeness rules will be applied to all data templates. Anthropometric measurements will be standardized using the ENA SMART software standardization tools; additionally, regular supervision and refresher training workshops will be organized to maintain the highest quality data. In addition to a digital database, paper forms including the date, the patient's and caregiver's name, study ID, age, length and height at admission will be produced at enrollment. These forms will be kept at each health center and new anthropometric values will be added at each visit to track the child's health progress. Field tables for anthropometric conversion to z-scores will be available at all health centers. To maximize the follow-up rate, all participants will be registered in a digital logbook (for example using Epidata) where each visit will be registered with the date of attendance. Weekly lists of expected participants will be produced and printed for reminder calls. Participants who do not show up at the health center will be contacted per telephone, and if not successful, a team of community health workers will try to trace the family at the home address and encourage them to go to the health center for continuation of the treatment. DATA ANALYSIS All data will be analyzed using STATA Data Analysis and Statistical Software version 13 (StataCorp, College Station; Lakeway, Texas, U.S.A.). ETHICAL CONSIDERATIONS This research protocol will be submitted for ethical clearance to: The Institutional Review Board (IRB) of the Institute of Tropical Medicine Antwerp, Belgium; and The Committee of Medical Ethics (CME) at Antwerp University Hospital, Universitair Ziekenhuis Antwerpen (UZA) and the University of Antwerp, Universiteit Antwerpen (UAntwerp); Context adapted versions of this protocol will be submitted for ethical clearance to: The Comite National d'Ethique pour la Recherche en Sante (CNERS), Burkina Faso The IRB of the University of Liberia - Pacific Institute of Research and Evaluation (UL-PIRE; The National Research Ethics Committee (NERC) at the Bangladesh Medical Research Council (BMRC). CONFLICTS OF INTEREST None of the project affiliates have declared any conflicts of interest.

Official Title
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OptiDiag: Biomedical Investigations for Optimized Diagnosis and Monitoring of Severe Acute Malnutrition (SAM): Elucidating the Heterogeneous Diagnosis of SAM by Current Anthropometric Criteria and Moving Beyond

Conditions
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Severe Acute Malnutrition

Intervention / Treatment
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* Other: Severe Acute Malnutrition


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Diagnosed SAM and eligible for CMAM treatment, defined as: (1) WHZ < -3 and/or MUAC < 115 mm; (2) No bilateral pitting edema; (3) Children without the general danger signs of illness as per the Integrated Management of Childhood Illness (IMCI) guidelines like lethargy, unconsciousness, convulsions or severe vomiting (WHO 2005). Resident of the catchment area at the time of inclusion; and Caretakers consent for the child to participate. Exclusion Criteria: Plans to leave the catchment area within the next 6 months; Known peanut and/or milk allergy; Admitted for SAM treatment within the past 6 months prior to recruitment (including re-admission after default, relapse or medical transfer); Malformations which may affect food intake such as cleft palate, cerebral palsy, Down's syndrome; and, The presence of general danger signs as per the IMCI guidelines.

Ages Eligible for Study
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Minimum Age: 6 Months
Maximum Age: 5 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| OptiDiag-Cohort, Liberia<br>A respresentative population of 275 Liberian children with SAM and admitted to a CMAM/IMAM program supported by Action Against Hunger (75 of which have a MUAC < 115, 75 of which have a WHZ < -3 and 75 of which have both a MUAC < 115 mm and a WHZ < -3). | Other: Severe Acute Malnutrition<br> <br> |
| OptiDiag/MANGO-Cohort, Burkina Faso<br>A respresentative population of 275 Burkinabé children with SAM and admitted to a CMAM/IMAM program supported by Action Against Hunger (75 of which have a MUAC < 115, 75 of which have a WHZ < -3 and 75 of which have both a MUAC < 115 mm and a WHZ < -3). | Other: Severe Acute Malnutrition<br> <br> |
| OptiDiag-cohort, Bangladesh<br>A respresentative population of 275 Bangladeshi children with SAM and admitted to a CMAM/IMAM program supported by Action Against Hunger (75 of which have a MUAC < 115, 75 of which have a WHZ < -3 and 75 of which have both a MUAC < 115 mm and a WHZ < -3). | Other: Severe Acute Malnutrition<br> <br> |

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Leptin | Describe and compare the different types of SAM anthropometric diagnoses based on circulating leptin. | At admission | 
| Stable Isotope Analysis (SIA) | Describe and compare the different types of SAM anthropometric diagnoses based on Stable Isotope Analysis (SIA) | At admission | 
| Clinical Signs | Describe and compare the different types of SAM anthropometric diagnoses based on the severity of clinical signs at admission; these include: dehydration, visible signs of wasting, pulse, signs of micronutrient deficiency, acute resipiratory infections, respiratory rate, temperature, dermatosis and hair changes and diarrhea. | At admission | 
| Micronutrient status | Describe and compare the different types of SAM anthropometric diagnoses based on micronutrient status. | At admission | 
| Bioelectric impedance (BI) | Describe and compare the different types of SAM anthropometric diagnoses based on bioelectric impedance (BI). | At admission | 
| Patient's health and nutritional status (caretaker's perception) | Describe and compare the different types of SAM anthropometric diagnoses based on the caretaker's perception of the patient's health and nutritional status. | At admission | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Stable Isotope Analysis (SIA) | Describe and compare the different types of SAM anthropometric diagnoses based on the history of lipid and protein catabolism (δ13C and δ15N isotopes in hair) reversed throughout nutritional rehabilitation. | At 2 weeks, 4 weeks, 6 weeks & 8 after admission. | 
| Clinical signs: dehydration | Describe and compare the different types of SAM anthropometric diagnoses based on the severity of clinical signs for dehydration at admission and the development of clinical signs of dehydration during treatment. | At 2 weeks & 8 weeks after admission. | 
| Clinical signs: visible wasting | Describe and compare the different types of SAM anthropometric diagnoses based on the severity of clinical signs of visible wasting at admission and the development of clinical signs of visible wasting during treatment. | At 2 weeks & 8 weeks after admission. | 
| Clinical signs: pulse | Describe and compare the different types of SAM anthropometric diagnoses based on the severity of abnormal pulse at admission and the development of abnormal pulse during treatment. | At 2 weeks & 8 weeks after admission. | 
| Clinical signs: micronutrient deficiency | Describe and compare the different types of SAM anthropometric diagnoses based on the severity of clinical signs of micronutrient deficency at admission and the development of clinical signs of micronutrient deficency during treatment. | At 2 weeks & 8 weeks after admission. | 
| Clinical signs: acute respiratory infection | Describe and compare the different types of SAM anthropometric diagnoses based on the severity of clinical signs of acute respiratory infection at admission and the development of clinical signs of acute respiratory infection during treatment. | At 2 weeks & 8 weeks after admission. | 
| Clinical signs: respiratory rate | Describe and compare the different types of SAM anthropometric diagnoses based on the severity of abnormal respiratory rate at admission and the development of clinical signs of abnormal respiratory rate during treatment. | At 2 weeks & 8 weeks after admission. | 
| Clinical signs: temperature | Describe and compare the different types of SAM anthropometric diagnoses based on the severity of abnormal temperature at admission and the development of clinical signs of abnormal temperature during treatment. | At 2 weeks & 8 weeks after admission. | 
| Clinical signs: dermatosis | Describe and compare the different types of SAM anthropometric diagnoses based on the severity of clinical signs of dermatosis at admission and the development of clinical signs of dermatosis during treatment. | At 2 weeks & 8 weeks after admission. | 
| Clinical signs: hair changes | Describe and compare the different types of SAM anthropometric diagnoses based on the severity of clinical signs of hair change (color and consistency) linked to acute malnutrition at admission and the development of clinical signs of of hair change (color and consistency) during treatment. | At 2 weeks & 8 weeks after admission. | 
| Clinical signs: diarrhea | Describe and compare the different types of SAM anthropometric diagnoses based on the severity of diarrhea at admission and the development of diarrhea during treatment. | At 2 weeks & 8 weeks after admission. | 
| Treatment outcomes | Describe and compare the different types of SAM anthropometric diagnoses based on negative and positive treatment outcomes; these include: discharged from program as recovered [mid-upper arm circumference (MUAC) ≥ 125 and weight-for-height Z-score (WHZ) ≥ -2], defaulted from program (caretaker confirmation of unwillingness to participate), death, transfer to an in-patient facility (developement of medical complications as per national protocol, loss of or static weight), transfer to another out-patient facility outside of the program catchment area and facility and non-response to treatment (cure criteria unattained before maximum treatment duration). | Events occuring up to maximum treatment duration as per national protocol (up to 12 weeks in Bangladesh, up to 16 weeks in Burkina Faso, and up to 12 weeks in Liberia). | 
| Early weight gain | Describe and compare the different types of SAM anthropometric diagnoses based on early weight gain. | After 2 weeks and 4 weeks after admission. | 
| Leptin | Describe and compare the different types of SAM anthropometric diagnoses based on circulating leptin | At 2 weeks & 8 weeks after admission. | 
| Micronutrient status | Describe and compare the different types of SAM anthropometric diagnoses based on micronutrient status. | At 2 weeks & 8 weeks after admission. | 
| Patient's health and nutritional status (caretaker's perception) | Describe and compare the different types of SAM anthropometric diagnoses based on the caretaker's perception of the patient's health and nutritional status. | At 2 weeks & 8 weeks after admission. | 
| Bioelectric impedance (BI) | Describe and compare the different types of SAM anthropometric diagnoses based on bioelectric impedance. | At 2 weeks & 8 weeks after admission. | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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Severe Acute Malnutrition