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In this study from sub-Saharan Africa, children with severe febrile illness and impaired perfusion were randomly assigned to fluid-bolus therapy or no bolus. Albumin or saline boluses significantly increased 48-hour mortality in critically ill children with impaired perfusion. Rapid, early fluid resuscitation in patients with shock, a therapy that is aimed at the correction of hemodynamic abnormalities, is one component of goal-driven emergency care guidelines. This approach is widely endorsed by pediatric life-support training programs, which recommend the administration of up to 60 ml of isotonic fluid per kilogram of body weight within 15 minutes after the diagnosis of shock. 1 Children who do not have an adequate response to fluid resuscitation require intensive care for inotropic and ventilatory support. 1 Substantial improvements in the outcomes of pediatric septic shock have been attributed to this approach. 2 , 3 Nevertheless, evidence regarding . . .

Standardized collection of predictors of pediatric sepsis has enormous potential to increase data compatibility across research studies. The Pediatric Sepsis Predictor Standardization Working Group collaborated to define common data elements for pediatric sepsis predictors at the point of triage to serve as a standardized framework for data collection in resource-limited settings. A preliminary list of pediatric sepsis predictor variables was compiled through a systematic literature review and examination of global guideline documents. A 5-round modified Delphi that involved independent voting and active group discussions was conducted to select, standardize, and prioritize predictors. Considerations included the perceived predictive value of the candidate predictor at the point of triage, intra- and inter-rater measurement reliability, and the amount of time and material resources required to reliably collect the predictor in resource-limited settings. We generated 116 common data elements for implementation in future studies. Each common data element includes a standardized prompt, suggested response values, and prioritization as tier 1 (essential), tier 2 (important), or tier 3 (exploratory). Branching logic was added to the predictors list to facilitate the design of efficient data collection methods, such as low-cost electronic case report forms on a mobile application. The set of common data elements are freely available on the Pediatric Sepsis CoLab Dataverse and a web-based feedback survey is available through the Pediatric Sepsis CoLab. Updated iterations will continuously be released based on feedback from the pediatric sepsis research community and emergence of new information. Routine use of the common data elements in future studies can allow data sharing between studies and contribute to development of powerful risk prediction algorithms. These algorithms may then be used to support clinical decision making at triage in resource-limited settings. Continued collaboration, engagement, and feedback from the pediatric sepsis research community will be important to ensure the common data elements remain applicable across a broad range of geographical and sociocultural settings.

BackgroundThe COVID-19 pandemic has led to an unprecedented global research effort to build a body of knowledge that can inform mitigation strategies. We carried out a bibliometric analysis to describe the COVID-19 research output in Africa in terms of setting, study design, research themes and author affiliation.MethodsWe searched for articles published between 1 December 2019 and 3 January 2021 from various databases including PubMed, African Journals Online, medRxiv, Collabovid, the WHO global research database and Google. All article types and study design were included.ResultsA total of 1296 articles were retrieved. 46.6% were primary research articles, 48.6% were editorial-type articles while 4.6% were secondary research articles. 20.3% articles used the entire continent of Africa as their study setting while South Africa (15.4%) was the most common country-focused setting. The most common research topics include ‘country preparedness and response’ (24.9%) and ‘the direct and indirect health impacts of the pandemic’ (21.6%). However, only 1.0% of articles focus on therapeutics and vaccines. 90.3% of the articles had at least one African researcher as author, 78.5% had an African researcher as first author, while 63.5% had an African researcher as last author. The University of Cape Town leads with the greatest number of first and last authors. 13% of the articles were published in medRxiv and of the studies that declared funding, the Wellcome Trust was the top funding body.ConclusionsThis study highlights Africa’s COVID-19 research and the continent’s existing capacity to carry out research that addresses local problems. However, more studies focused on vaccines and therapeutics are needed to inform local development. In addition, the uneven distribution of research productivity among African countries emphasises the need for increased investment where needed.

Admission records are seldom used in sub-Saharan Africa to delineate hospital catchments for the spatial description of hospitalised disease events. We set out to investigate spatial hospital accessibility for severe malarial anaemia (SMA) and cerebral malaria (CM). Malaria admissions for children between 1 month and 14 years old were identified from prospective clinical surveillance data recorded routinely at four referral hospitals covering two complete years between December 2015 to November 2016 and November 2017 to October 2018. These were linked to census enumeration areas (EAs) with an age-structured population. A novel mathematical-statistical framework that included EAs with zero observations was used to predict hospital catchment for malaria admissions adjusting for spatial distance. From 5766 malaria admissions, 5486 (95.14%) were linked to specific EA address, of which 272 (5%) were classified as cerebral malaria while 1001 (10%) were severe malaria anaemia. Further, results suggest a marked geographic catchment of malaria admission around the four sentinel hospitals although the extent varied. The relative rate-ratio of hospitalisation was highest at <1-hour travel time for SMA and CM although this was lower outside the predicted hospital catchments. Delineation of catchments is important for planning emergency care delivery and in the use of hospital data to define epidemiological disease burdens. Further hospital and community-based studies on treatment-seeking pathways to hospitals for severe disease would improve our understanding of catchments.

Background Hyperlactataemia (HL) is a biomarker of disease severity that predicts mortality in patients with sepsis and malaria. Lactate clearance (LC) during resuscitation has been shown to be a prognostic factor of survival in critically ill adults, but little data exist for African children living in malaria-endemic areas. Methods In a secondary data analysis of severely ill febrile children included in the Fluid Expansion as Supportive Therapy (FEAST) resuscitation trial, we assessed the association between lactate levels at admission and LC at 8 h with all-cause mortality at 72 h (d72). LC was defined as a relative lactate decline ≥ 40% and/or lactate normalisation (lactate < 2.5 mmol/L). Results Of 3170 children in the FEAST trial, including 1719 children (57%) with Plasmodium falciparum malaria, 3008 (95%) had a baseline lactate measurement, 2127 (71%) had HL (lactate ≥ 2.5 mmol/L), and 1179 (39%) had severe HL (≥ 5 mmol/L). Within 72 h, 309 children (10.3%) died, of whom 284 (92%) had baseline HL. After adjustment for potential confounders, severe HL was strongly associated with mortality (Odds Ratio (OR) 6.96; 95% CI 3.52, 13.76, p < 0.001). This association was not modified by malaria status, despite children with malaria having a higher baseline lactate (median 4.6 mmol/L vs 3 mmol/L; p < 0.001) and a lower mortality rate (OR = 0.42; p < 0.001) compared to non-malarial cases. Sensitivity and specificity analysis identified a higher lactate on admission cut-off value predictive of d72 for children with malaria (5.2 mmol/L) than for those with other febrile illnesses (3.4 mmol/L). At 8 h, 2748/3008 survivors (91%) had a lactate measured, 1906 (63%) of whom had HL on admission, of whom 1014 (53%) fulfilled pre-defined LC criteria. After adjustment for confounders, LC independently predicted survival after 8 h (OR 0.24; 95% CI 0.14, 0.42; p < 0.001). Absence of LC (< 10%) at 8 h was strongly associated with death at 72 h (OR 4.62; 95% CI 2.7, 8.0; p < 0.001). Conclusions Independently of the underlying diagnosis, HL is a strong risk factor for death at 72 h in children admitted with severe febrile illnesses in Africa. Children able to clear lactate within 8 h had an improved chance of survival. These findings prompt the more widespread use of lactate and LC to identify children with severe disease and monitor response to treatment. Trial registration ISRCTN69856593 Registered 21 January 2009.

Early rapid fluid resuscitation (boluses) in African children with severe febrile illnesses increases the 48-hour mortality by 3.3% compared with controls (no bolus). We explored the effect of boluses on 48-hour all-cause mortality by clinical presentation at enrolment, hemodynamic changes over the first hour, and on different modes of death, according to terminal clinical events. We hypothesize that boluses may cause excess deaths from neurological or respiratory events relating to fluid overload. Pre-defined presentation syndromes (PS; severe acidosis or severe shock, respiratory, neurological) and predominant terminal clinical events (cardiovascular collapse, respiratory, neurological) were described by randomized arm (bolus versus control) in 3,141 severely ill febrile children with shock enrolled in the Fluid Expansion as Supportive Therapy (FEAST) trial. Landmark analyses were used to compare early mortality in treatment groups, conditional on changes in shock and hypoxia parameters. Competing risks methods were used to estimate cumulative incidence curves and sub-hazard ratios to compare treatment groups in terms of terminal clinical events. Of 2,396 out of 3,141 (76%) classifiable participants, 1,647 (69%) had a severe metabolic acidosis or severe shock PS, 625 (26%) had a respiratory PS and 976 (41%) had a neurological PS, either alone or in combination. Mortality was greatest among children fulfilling criteria for all three PS (28% bolus, 21% control) and lowest for lone respiratory (2% bolus, 5% control) or neurological (3% bolus, 0% control) presentations. Excess mortality in bolus arms versus control was apparent for all three PS, including all their component features. By one hour, shock had resolved (responders) more frequently in bolus versus control groups (43% versus 32%, P <0.001), but excess mortality with boluses was evident in responders (relative risk 1.98, 95% confidence interval 0.94 to 4.17, P = 0.06) and 'non-responders' (relative risk 1.67, 95% confidence interval 1.23 to 2.28, P = 0.001), with no evidence of heterogeneity (P = 0.68). The major difference between bolus and control arms was the higher proportion of cardiogenic or shock terminal clinical events in bolus arms (n = 123; 4.6% versus 2.6%, P = 0.008) rather than respiratory (n = 61; 2.2% versus 1.3%, P = 0.09) or neurological (n = 63, 2.1% versus 1.8%, P = 0.6) terminal clinical events. Excess mortality from boluses occurred in all subgroups of children. Contrary to expectation, cardiovascular collapse rather than fluid overload appeared to contribute most to excess deaths with rapid fluid resuscitation. These results should prompt a re-evaluation of evidence on fluid resuscitation for shock and a re-appraisal of the rate, composition and volume of resuscitation fluids. ISRCTN69856593.

In malaria epidemiology, interpolation frameworks based on available observations are critical for policy decisions and interpreting disease burden. Updating our understanding of the empirical evidence across different populations, settings, and timeframes is crucial to improving inference for supporting public health. Here, via individual-based modeling, we evaluate a large, multicountry, contemporary Plasmodium falciparum severe malaria dataset to better understand the relationship between prevalence and incidence of malaria pediatric hospitalizations - a proxy of malaria severe outcomes- in East-Africa. We find that life-long exposure dynamics, and subsequent protection patterns in children, substantially determine the likelihood of malaria hospitalizations relative to ongoing prevalence at the population level. Unsteady transmission patterns over a lifetime in children -increasing or decreasing- lead to an exponential relationship of hospitalization rates versus prevalence rather than the asymptotic pattern observed under steady transmission. Addressing this increase in the complexity of malaria epidemiology is crucial to update burden assessments via inference models that guide current and future policy decisions. Severe pediatric malaria remains a concern in many countries. Here, the authors use an individual-based modeling approach to evaluate the relationship between malaria prevalence and incidence of malaria pediatric hospitalizations, and show how unsteady transmission patterns affect hospitalization rates.

Severe acute malnutrition (SAM) remains a major cause of admission and inpatient mortality worldwide in children aged less than 5 years. In this study, we explored SAM prevalence and outcomes in children admitted in 13 Kenyan hospitals participating in a Clinical Information Network (CIN). We also describe their immediate in-patient management. We analyzed data for children aged 1-59 months collected retrospectively from medical records after discharge. Mean, median and ranges were used to summarize pooled and age-specific prevalence and mortality associated with SAM. Documentation of key signs and symptoms (S/S) and performance of indicators of quality of care for selected aspects of the WHO management steps were assessed. Logistic regression models were used to evaluate associations between documented S/S and mortality among SAM patients aged 6-59 months. Loess curves were used to explore performance change over time for indicators of selected SAM management steps. 5306/54140 (9.8%) children aged 1-59 months admitted with medical conditions in CIN hospitals between December 2013 and November 2016 had SAM. SAM prevalence identified by clinicians and case fatality varied widely across hospitals with median proportion (range) of 10.1% (4.6-18.2%) and 14.8% (6.0-28.6%) respectively. Seventeen variables were associated with increased mortality. Performance change over time of management steps varied across hospitals and across selected indicators but suggests some effect of regular audit and feedback. Identification of SAM patients, their mortality and adherence to in-patient management recommendations varied across hospitals. An important group of SAM patients are aged less than 6 months. Continued efforts are required to improve management of SAM in routine settings as part of efforts to reduce inpatient mortality.

Sepsis is a life-threatening dysfunction of the immune system leading to multiorgan failure that is precipitated by infectious diseases and is a leading cause of death in children under 5 years of age. It is necessary to be able to identify a sick child at risk of developing sepsis at the earliest point of presentation to a healthcare facility so that appropriate care can be provided as soon as possible. Our study objective was to generate a list of consensus-driven predictor variables for the derivation of a prediction model that will be incorporated into a mobile device and operated by low-skilled healthcare workers at triage. By conducting a systematic literature review and examination of global guideline documents, a list of 72 initial candidate predictor variables was generated. A two-round modified Delphi process involving 26 experts from both resource-rich and resource-limited settings, who were also encouraged to suggest new variables, yielded a final list of 45 predictor variables after evaluating each variable based on three domains: predictive potential, measurement reliability, and level of training and resources required. The final list of predictor variables will be used to collect data and contribute to the derivation of a prediction model.

IntroductionWe estimated unit costs for COVID-19 case management for patients with asymptomatic, mild-to-moderate, severe and critical COVID-19 disease in Kenya.MethodsWe estimated per-day unit costs of COVID-19 case management for patients. We used a bottom-up approach to estimate full economic costs and adopted a health system perspective and patient episode of care as our time horizon. We obtained data on inputs and their quantities from data provided by three public COVID-19 treatment hospitals in Kenya and augmented this with guidelines. We obtained input prices from a recent costing survey of 20 hospitals in Kenya and from market prices for Kenya.ResultsPer-day, per-patient unit costs for asymptomatic patients and patients with mild-to-moderate COVID-19 disease under home-based care are 1993.01 Kenyan shilling (KES) (US$18.89) and 1995.17 KES (US$18.991), respectively. When these patients are managed in an isolation centre or hospital, the same unit costs for asymptomatic patients and patients with mild-to-moderate disease are 6717.74 KES (US$63.68) and 6719.90 KES (US$63.70), respectively. Per-day unit costs for patients with severe COVID-19 disease managed in general hospital wards and those with critical COVID-19 disease admitted in intensive care units are 13 137.07 KES (US$124.53) and 63 243.11 KES (US$599.51).ConclusionCOVID-19 case management costs are substantial, ranging between two and four times the average claims value reported by Kenya’s public health insurer. Kenya will need to mobilise substantial resources and explore service delivery adaptations that will reduce unit costs.