44 research outputs found

    Phenotype is sustained during hospital readmissions following treatment for complicated severe malnutrition among Kenyan children : a retrospective cohort study

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    Hospital readmission is common among children with complicated severe acute malnutrition (cSAM) but not well-characterised. Two distinct cSAM phenotypes, marasmus and kwashiorkor, exist, but their pathophysiology and whether the same phenotype persists at relapse are unclear. We aimed to test the association between cSAM phenotype at index admission and readmission following recovery. We performed secondary data analysis from a multicentre randomised trial in Kenya with 1-year active follow-up. The main outcome was cSAM phenotype upon hospital readmission. Among 1,704 HIV-negative children with cSAM discharged in the trial, 177 children contributed a total of 246 readmissions with cSAM. cSAM readmission was associated with age<12 months (p = .005), but not site, sex, season, nor cSAM phenotype. Of these, 42 children contributed 44 readmissions with cSAM that occurred after a monthly visit when SAM was confirmed absent (cSAM relapse). cSAM phenotype was sustained during cSAM relapse. The adjusted odds ratio for presenting with kwashiorkor during readmission after kwashiorkor at index admission was 39.3 [95% confidence interval (95% CI) [2.69, 1,326]; p = .01); and for presenting with marasmus during readmission after kwashiorkor at index admission was 0.02 (95% CI [0.001, 0.037]; p = .01). To validate this finding, we examined readmissions to Kilifi County Hospital, Kenya occurring at least 2 months after an admission with cSAM. Among 2,412 children with cSAM discharged alive, there were 206 readmissions with cSAM. Their phenotype at readmission was significantly influenced by their phenotype at index admission (p < .001). This is the first report describing the phenotype and rate of cSAM recurrence

    New approaches and technical considerations in detecting outlier measurements and trajectories in longitudinal children growth data

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    Background Growth studies rely on longitudinal measurements, typically represented as trajectories. However, anthropometry is prone to errors that can generate outliers. While various methods are available for detecting outlier measurements, a gold standard has yet to be identified, and there is no established method for outlying trajectories. Thus, outlier types and their effects on growth pattern detection still need to be investigated. This work aimed to assess the performance of six methods at detecting different types of outliers, propose two novel methods for outlier trajectory detection and evaluate how outliers affect growth pattern detection. Methods We included 393 healthy infants from The Applied Research Group for Kids (TARGet Kids!) cohort and 1651 children with severe malnutrition from the co-trimoxazole prophylaxis clinical trial. We injected outliers of three types and six intensities and applied four outlier detection methods for measurements (model-based and World Health Organization cut-offs-based) and two for trajectories. We also assessed growth pattern detection before and after outlier injection using time series clustering and latent class mixed models. Error type, intensity, and population affected method performance. Results Model-based outlier detection methods performed best for measurements with precision between 5.72-99.89%, especially for low and moderate error intensities. The clustering-based outlier trajectory method had high precision of 14.93-99.12%. Combining methods improved the detection rate to 21.82% in outlier measurements. Finally, when comparing growth groups with and without outliers, the outliers were shown to alter group membership by 57.9 -79.04%. Conclusions World Health Organization cut-off-based techniques were shown to perform well in few very particular cases (extreme errors of high intensity), while model-based techniques performed well, especially for moderate errors of low intensity. Clustering-based outlier trajectory detection performed exceptionally well across all types and intensities of errors, indicating a potential strategic change in how outliers in growth data are viewed. Finally, the importance of detecting outliers was shown, given its impact on children growth studies, as demonstrated by comparing results of growth group detection

    Biomarkers of post-discharge mortality among children with complicated severe acute malnutrition

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    High mortality after discharge from hospital following acute illness has been observed among children with Severe Acute Malnutrition (SAM). However, mechanisms that may be amenable to intervention to reduce risk are unknown. We performed a nested case-control study among HIV-uninfected children aged 2-59 months treated for complicated SAM according to WHO recommendations at four Kenyan hospitals. Blood was drawn from 1778 children when clinically judged stable before discharge from hospital. Cases were children who died within 60 days. Controls were randomly selected children who survived for one year without readmission to hospital. Untargeted proteomics, total protein, cytokines and chemokines, and leptin were assayed in plasma and corresponding biological processes determined. Among 121 cases and 120 controls, increased levels of calprotectin, von Willebrand factor, angiotensinogen, IL8, IL15, IP10, TNF alpha, and decreased levels of leptin, heparin cofactor 2, and serum paraoxonase were associated with mortality after adjusting for possible confounders. Acute phase responses, cellular responses to lipopolysaccharide, neutrophil responses to bacteria, and endothelial responses were enriched among cases. Among apparently clinically stable children with SAM, a sepsis-like profile is associated with subsequent death. This may be due to ongoing bacterial infection, translocated bacterial products or deranged immune response during nutritional recovery

    Derivation and external validation of a clinical prognostic model identifying children at risk of death following presentation for diarrheal care

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    Diarrhea continues to be a leading cause of death for children under-five. Amongst children treated for acute diarrhea, mortality risk remains elevated during and after acute medical management. Identification of those at highest risk would enable better targeting of interventions, but available prognostic tools lack validation. We used clinical and demographic data from the Global Enteric Multicenter Study (GEMS) to build clinical prognostic models (CPMs) to predict death (in-treatment, after discharge, or either) in children aged ≤59 months presenting with moderate-to-severe diarrhea (MSD), in Africa and Asia. We screened variables using random forests, and assessed predictive performance with random forest regression and logistic regression using repeated cross-validation. We used data from the Kilifi Health and Demographic Surveillance System (KHDSS) and Kilifi County Hospital (KCH) in Kenya to externally validate our GEMS-derived CPM. Of 8060 MSD cases, 43 (0.5%) children died in treatment and 122 (1.5% of remaining) died after discharge. MUAC at presentation, respiratory rate, age, temperature, number of days with diarrhea at presentation, number of people living in household, number of children <60 months old living in household, and how much the child had been offered to drink since diarrhea started were predictive of death both in treatment and after discharge. Using a parsimonious 2-variable prediction model, we achieved an area under the ROC curve (AUC) of 0.84 (95% CI: 0.82, 0.86) in the derivation dataset, and an AUC = 0.74 (95% CI 0.71, 0.77) in the external dataset. Our findings suggest it is possible to identify children most likely to die after presenting to care for acute diarrhea. This could represent a novel and cost-effective way to target resources for the prevention of childhood mortality

    Cessation of exclusive breastfeeding and seasonality, but not small intestinal bacterial overgrowth, are associated with environmental enteric dysfunction: A birth cohort study amongst infants in rural Kenya.

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    Background: Environmental Enteric Dysfunction (EED) is a chronic intestinal inflammatory disorder of unclear aetiology prevalent amongst children in low-income settings and associated with stunting. We aimed to characterise development of EED and its putative risk factors amongst rural Kenyan infants. Methods: In a birth cohort study in Junju, rural coastal Kenya, between August 2015 and January 2017, 100 infants were each followed for nine months. Breastfeeding status was recorded weekly and anthropometry monthly. Acute illnesses and antibiotics were captured by active and passive surveillance. Intestinal function and small intestinal bacterial overgrowth (SIBO) were assessed by monthly urinary lactulose mannitol (LM) and breath hydrogen tests. Faecal alpha-1-antitrypsin, myeloperoxidase and neopterin were measured as EED biomarkers, and microbiota composition assessed by 16S sequencing. Findings: Twenty nine of the 88 participants (33%) that underwent length measurement at nine months of age were stunted (length-for-age Z score <-2). During the rainy season, linear growth was slower and LM ratio was higher. In multivariable models, LM ratio, myeloperoxidase and neopterin increased after cessation of continuous-since-birth exclusive breastfeeding. For LM ratio this only occurred during the rainy season. EED markers were not associated with antibiotics, acute illnesses, SIBO, or gut microbiota diversity. Microbiota diversified with age and was not strongly associated with complementary food introduction or linear growth impairment. Interpretation: Our data suggest that intensified promotion of uninterrupted exclusive breastfeeding amongst infants under six months during the rainy season, where rainfall is seasonal, may help prevent EED. Our findings also suggest that therapeutic strategies directed towards SIBO are unlikely to impact on EED in this setting. However, further development of non-invasive diagnostic methods for SIBO is required. Funding: This research was funded in part by the Wellcome Trust (Research Training Fellowship to RJC (103376/Z/13/Z)). EPKP was supported by the MRC/DfID Newton Fund (MR/N006259/1). JAB was supported by the MRC/DFiD/Wellcome Trust Joint Global Health Trials scheme (MR/M007367/1) and the Bill & Melinda Gates Foundation (OPP1131320). HHU was supported by the NIHR Oxford Biomedical Research Centre (IS-BRC-1215-20008)

    Should first-line empiric treatment strategies cover coagulase-negative staphylococcal infections in severely malnourished or HIV-infected children in Kenya?

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    BACKGROUND: Bloodstream infection is a common cause of morbidity in children aged andlt;5 years in developing countries. In studies reporting bacteremia in Africa, coagulase-negative Staphylococci (CoNS) are commonly isolated. However, it is currently unclear whether children who are highly susceptible to infection because of severe acute malnutrition (SAM) or HIV should be treated with antimicrobials specifically to cover CoNS. We aimed to determine the clinical significance of CoNS amongst children admitted to a rural hospital in Kenya in relation to nutritional and HIV status. METHODS: Systematically collected clinical and microbiological surveillance data from children aged 6-59 months admitted to Kilifi County Hospital (2007-2013) were analysed. Multivariable regression was used to test associations between CoNS isolation from blood cultures and SAM (MUAC andlt;11.5cm or nutritional oedema (kwashiorkor)), and HIV serostatus; and among children with SAM or HIV, associations between CoNS isolation and mortality, duration of hospitalization and clinical features. RESULTS: CoNS were isolated from blood culture in 906/13,315 (6.8%) children, of whom 135/906 (14.9%) had SAM and 54/906 (6.0%) were HIV antibody positive. CoNS isolation was not associated with SAM (MUACandlt;11.5cm (aOR 1.11, 95% CI 0.88-1.40) or kwashiorkor (aOR 0.84, 95% CI 0.48-1.49)), or a positive HIV antibody test (aOR 1.25, 95% CI 0.92-1.71). Among children with SAM or a positive HIV antibody test, CoNS isolation was not associated with mortality or prolonged hospitalization. CONCLUSION: In a large, systematic study, there was no evidence that antimicrobial therapy should specifically target CoNS amongst children with SAM or HIV-infection or exposure

    Changes in susceptibility to life-threatening infections after treatment for complicated severe malnutrition in Kenya

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    Background Goals of treating childhood Severe Acute Malnutrition (SAM), besides anthropometric recovery and preventing short-term mortality, include reducing risks of subsequent serious infections. How quickly and how much the risk of serious illness changes during rehabilitation is unknown, but could inform improving design and scope of interventions. Objective To investigate changes in the risk of life-threatening events (LTEs) in relation to anthropometric recovery from SAM. Design Secondary analysis of a clinical trial including 1,778 HIV-uninfected Kenyan children aged 2-59 months with complicated SAM, enrolled following the inpatient stabilization phase of treatment, and followed for 12 months. The main outcome was LTEs, defined as infections requiring re-hospitalization or causing death. We examined anthropometry measured at months one, three and six after enrolment in relation to LTEs occurring during the 6 months following each of these time points. Results During 12 months, there were 823 LTEs (257 fatal), predominantly severe pneumonia and diarrhea. At months one, three and six, 557(34%), 764(49%) and 842(56%) children had WHZ≥-2 respectively which, compared to WHZ Conclusion Anthropometric response was associated with rapid and substantial reduction risk of LTEs. However, reduction in susceptibility lagged behind anthropometric improvement. Disease events, alongside anthropometric assessment may provide a clearer picture of the effectiveness of interventions. Robust protocols for detecting and treating poor anthropometric recovery, and addressing broader vulnerabilities that complicated SAM indicates may save lives.</p

    Clinical laboratory reference values amongst children aged 4 weeks to 17 months in Kilifi, Kenya: A cross sectional observational study

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    Reference intervals for clinical laboratory parameters are important for assessing eligibility, toxicity grading and management of adverse events in clinical trials. Nonetheless, haematological and biochemical parameters used for clinical trials in sub-Saharan Africa are typically derived from industrialized countries, or from WHO references that are not region-specific. We set out to establish community reference values for haematological and biochemical parameters amongst children aged 4 weeks to 17 months in Kilifi, Kenya. We conducted a cross sectional study nested within phase II and III trials of RTS, S malaria vaccine candidate. We analysed 10 haematological and 2 biochemical parameters from 1,070 and 423 community children without illness prior to experimental vaccine administration. Statistical analysis followed Clinical and Laboratory Standards Institute EP28-A3c guidelines. 95% reference ranges and their respective 90% confidence intervals were determined using non-parametric methods. Findings were compared with published ranges from Tanzania, Europe and The United States. We determined the reference ranges within the following age partitions: 4 weeks to <6 months, 6 months to less than <12 months, and 12 months to 17 months for the haematological parameters; and 4 weeks to 17 months for the biochemical parameters. There were no gender differences for all haematological and biochemical parameters in all age groups. Hb, MCV and platelets 95% reference ranges in infants largely overlapped with those from United States or Europe, except for the lower limit for Hb, Hct and platelets (lower); and upper limit for platelets (higher) and haematocrit(lower). Community norms for common haematological and biochemical parameters differ from developed countries. This reaffirms the need in clinical trials for locally derived reference values to detect deviation from what is usual in typical children in low and middle income countries
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