137 research outputs found

    Household-level factors associated with relapse following discharge from treatment for moderate acute malnutrition

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    AbstractFactors associated with relapse among children who are discharged after reaching a threshold denoted ‘recovered’ from moderate acute malnutrition (MAM) are not well understood. The aim of this study was to identify factors associated with sustained recovery, defined as maintaining a mid-upper-arm circumference≥12·5 cm for 1 year after release from treatment. On the basis of an observational study design, we analysed data from an in-depth household (HH) survey on a sub-sample of participants within a larger cluster randomised controlled trial (cRCT) that followed up children for 1 year after recovery from MAM. Out of 1497 children participating in the cRCT, a subset of 315 children participated in this sub-study. Accounting for other factors, HH with fitted lids on water storage containers (P=0·004) was a significant predictor of sustained recovery. In addition, sustained recovery was better among children whose caregivers were observed to have clean hands (P=0·053) and in HH using an improved sanitation facility (P=0·083). By contrast, socio-economic status and infant and young child feeding practices at the time of discharge and HH food security throughout the follow-up period were not significant. Given these results, we hypothesise that improved water, sanitation and hygiene conditions in tandem with management of MAM through supplemental feeding programmes have the possibility to decrease relapse following recovery from MAM. Furthermore, the absence of associations between relapse and nearly all HH-level factors indicates that the causal factors of relapse may be related mostly to the child’s individual, underlying health and nutrition status.</jats:p

    Relapse after severe acute malnutrition: A systematic literature review and secondary data analysis.

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    The objectives of most treatment programs for severe acute malnutrition (SAM) in children focus on initial recovery only, leaving post-discharge outcomes, such as relapse, poorly understood and undefined. This study aimed to systematically review current literature and conduct secondary data analyses of studies that captured relapse rates, up to 18-month post-discharge, in children following recovery from SAM treatment. The literature search (including PubMed and Google Scholar) built upon two recent reviews to identify a variety of up-to-date published studies and grey literature. This search yielded 26 articles and programme reports that provided information on relapse. The proportion of children who relapsed after SAM treatment varied greatly from 0% to 37% across varying lengths of time following discharge. The lack of a standard definition of relapse limited comparability even among the few studies that have quantified post-discharge relapse. Inconsistent treatment protocols and poor adherence to protocols likely add to the wide range of relapse reported. Secondary analysis of a database from Malawi found no significant association between potential individual risk factors at admission and discharge, except being an orphan, which resulted in five times greater odds of relapse at 6 months post-discharge (95% CI [1.7, 12.4], P = 0.003). The development of a standard definition of relapse is needed for programme implementers and researchers. This will allow for assessment of programme quality regarding sustained recovery and better understanding of the contribution of relapse to local and global burden of SAM

    Latent analysis of unmodified biomolecules and their complexes in solution with attomole detection sensitivity

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    The study of biomolecular interactions is central to an understanding of function, malfunction and therapeutic modulation of biological systems, yet often involves a compromise between sensitivity and accuracy. Many conventional analytical steps and the procedures required to facilitate sensitive detection, such as the incorporation of chemical labels, are prone to perturb the complexes under observation. Here we present a 'latent' analysis approach that uses chemical and microfluidic tools to reveal, through highly sensitive detection of a labelled system, the behaviour of the physiologically relevant unlabelled system. We implement this strategy in a native microfluidic diffusional sizing platform, allowing us to achieve detection sensitivity at the attomole level, determine the hydrodynamic radii of biomolecules that vary by over three orders of magnitude in molecular weight, and study heterogeneous mixtures. We illustrate these key advantages by characterizing a complex of an antibody domain in the solution phase and under physiologically relevant conditions.We would like to thank the ERC, BBSRC, Wellcome Trust, Newman Foundation, Winston Churchill Foundation, and Elan Pharmaceuticals for financial support. E.D.G was supported by the MRC (G1002272)
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