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In low-income and middle-income countries, most patients with febrile illnesses present to peripheral levels of the health system where diagnostic capacity is very limited. In these contexts, accurate risk stratification can be particularly impactful, helping to guide allocation of scarce resources to ensure timely and tailored care. However, reporting of prognostic research is often imprecise and few prognostic tests or algorithms are translated into clinical practice.Here, we review the often-conflated concepts of prognosis and diagnosis, with a focus on patients with febrile illnesses. Drawing on a recent global stakeholder consultation, we apply these concepts to propose three use-cases for prognostic tools in the management of febrile illnesses in resource-limited settings: (1) guiding referrals from the community to higher-level care; (2) informing resource allocation for patients admitted to hospital and (3) identifying patients who may benefit from closer follow-up post-hospital discharge. We explore the practical implications for new technologies and reflect on the challenges and knowledge gaps that must be addressed before this approach could be incorporated into routine care settings.Our intention is that these use-cases, alongside other recent initiatives, will help to promote a harmonised yet contextualised approach for prognostic research in febrile illness. We argue that this is especially important given the heterogeneous settings in which care is often provided for patients with febrile illnesses living in low-income and middle-income countries.

Background 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. Methods 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. Results 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. Conclusion 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.

Background Sepsis is the leading cause of death and disability in children. Every hour of delay in treatment is associated with an escalating risk of morbidity and mortality. The burden of sepsis is greatest in low- and middle-income countries where timely treatment may not occur due to delays in diagnosis and prioritization of critically ill children. To circumvent these challenges, we propose the development and clinical evaluation of a digital triage tool that will identify high risk children and reduce time to treatment. We will also implement and clinically validate a Radio-Frequency Identification system to automate tracking of patients. The mobile platform (mobile device and dashboard) and automated patient tracking system will create a low cost, highly scalable solution for critically ill children, including those with sepsis. Methods This is pre-post intervention study consisting of three phases. Phase I will be a baseline period where data is collected on key predictors and outcomes before implementation of the digital triage tool. In Phase I, there will be no changes to healthcare delivery processes in place at the study hospitals. Phase II will involve model derivation, technology development, and usability testing. Phase III will be the intervention period where data is collected on key predictors and outcomes after implementation of the digital triage tool. The primary outcome, time to treatment initiation, will be compared to assess effectiveness of the digital health intervention. Discussion Smart technology has the potential to overcome the barrier of limited clinical expertise in the identification of the child at risk. This mobile health platform, with sensors and data-driven applications, will provide real-time individualized risk prediction to rapidly triage patients and facilitate timely access to life-saving treatments for children in low- and middle-income countries, where specialists are not regularly available and deaths from sepsis are common. Trial registration Clinical Trials.gov Identifier: NCT04304235, Registered 11 March 2020.

Background: Over two-thirds of the five million annual deaths in children under five occur in infants, mostly in developing countries and many after hospital discharge. However, there is a lack of understanding of which children are at higher risk based on early clinical predictors. Early identification of vulnerable infants at high-risk for death post-discharge is important in order to craft interventional programs. Objectives: To determine potential predictor variables for post-discharge mortality in infants less than one year of age who are likely to die after discharge from health facilities in the developing world. Methods: A two-round modified Delphi process was conducted, wherein a panel of experts evaluated variables selected from a systematic literature review. Variables were evaluated based on (1) predictive value, (2) measurement reliability, (3) availability, and (4) applicability in low-resource settings. Results: In the first round, 18 experts evaluated 37 candidate variables and suggested 26 additional variables. Twenty-seven variables derived from those suggested in the first round were evaluated by 17 experts during the second round. A final total of 55 candidate variables were retained. Conclusion: A systematic approach yielded 55 candidate predictor variables to use in devising predictive models for post-discharge mortality in infants in a low-resource setting. Keywords: Candidate predictor variables, pediatrics, neonatal, infants, prediction, post-discharge mortality, sepsis.

Summary Background Selection of optimal second-line antiretroviral therapy (ART) has important clinical and programmatic implications. To inform the 2016 revision of the WHO ART guidelines, we assessed the comparative effectiveness and safety of available second-line ART regimens for adults and adolescents in whom first-line non-nucleoside reverse transcriptase inhibitor (NNRTI)-based regimens have failed. Methods In this systematic review and network meta-analysis, we searched for randomised controlled trials and prospective and retrospective cohort studies that evaluated outcomes in treatment-experienced adults living with HIV who switched ART regimen after failure of a WHO-recommended first-line NNRTI-based regimen. We searched Embase, MEDLINE, and the Cochrane Central Register of Controlled Trials for reports published from Jan 1, 1996, to Aug 8, 2016, and searched conference abstracts published from Jan 1, 2014, to Aug 8, 2016. Outcomes of interest were viral suppression, mortality, AIDS-defining illnesses or WHO stage 3–4 disease, discontinuations, discontinuations due to adverse events, and serious adverse events. We assessed comparative efficacy and safety in a network meta-analysis, using Bayesian hierarchical models. Findings We identified 12 papers pertaining to eight studies, including 4778 participants. The network was centred on ritonavir-boosted lopinavir plus two nucleoside or nucleotide reverse transcriptase inhibitors. Ritonavir-boosted lopinavir monotherapy was the only regimen inferior to others. With the lower estimate of the 95% credible interval (CrI) not exceeding the predefined threshold of 15%, evidence at 48 weeks supported the non-inferiority of ritonavir-boosted lopinavir plus raltegravir to regimens including ritonavir-boosted protease inhibitor plus two NRTIs with respect to viral suppression (odds ratio 1·09, 95% CrI 0·88–1·35). Estimated efficacy of ritonavir-boosted darunavir (800 mg once daily) was too imprecise to determine non-inferiority. Overall, regimens did not differ significantly with respect to continuations, AIDS-defining illnesses or WHO stage 3–4 disease, or mortality. Interpretation With the exception of ritonavir-boosted lopinavir plus raltegravir, the evidence base is unable to provide strong support to alternative second-line options to ritonavir-boosted protease inhibitor plus two NRTIs, and thus more trials are warranted. Funding WHO.

IntroductionThe burden of childhood mortality continues to be born largely by low-income and middle-income countries. The critical postdischarge period has been largely neglected despite evidence that mortality rates during this period can exceed inpatient mortality rates. However, there is a paucity of data on the paediatric discharge process from the perspective of the healthcare provider. Provider perspectives may be important in the development of an improved understanding of the barriers and facilitators to improving the transition from hospital to home.ObjectivesTo explore healthcare providers’ and facility administrators’ perspectives of the paediatric discharge process with respect to: (1) current procedures, (2) barriers and challenges, (3) ideas for change, (4) facilitators for change and (5) the importance of discharge planning.DesignA qualitative exploratory approach using focus groups (14) and in-depth interviews (7).SettingThis study was conducted at seven hospitals providing paediatric care in Uganda.ResultsCurrent discharge procedures are largely based on hospital-specific protocols or clinician opinion, as opposed to national guidelines. Some key barriers to an improved discharge process included caregiver resources and education, critical communication gaps, traditional practices, and a lack of human and physical resources. Teamwork and motivation to see improved paediatric transitions to home were identified as facilitators to implementing the ideas for change proposed by participants. The need for a standardised national policy guiding paediatric discharges, implemented through education at many levels and coupled with appropriate community referral and follow-up, was broadly perceived as essential to improving outcomes for children.ConclusionsAlthough significant challenges and gaps were identified within the current health system, participants’ ideas and the identified facilitators provide a significant basis from which change may occur. This work can facilitate the development of sustainable and effective interventions to improve postdischarge outcomes in Uganda and other similar settings.

Background: Many hospitalized children in developing countries die from infectious diseases. Early recognition of those who are critically ill coupled with timely treatment can prevent many deaths. A data-driven, electronic triage system to assist frontline health workers in categorizing illness severity is lacking. This study aimed to develop a data-driven parsimonious triage algorithm for children under five years of age. Methods: This was a prospective observational study of children under-five years of age presenting to the outpatient department of Mbagathi Hospital in Nairobi, Kenya between January and June 2018. A study nurse examined participants and recorded history and clinical signs and symptoms using a mobile device with an attached low-cost pulse oximeter sensor. The need for hospital admission was determined independently by the facility clinician and used as the primary outcome in a logistic predictive model. We focused on the selection of variables that could be quickly and easily assessed by low skilled health workers. Results: The admission rate (for more than 24 hours) was 12% (N=138/1,132). We identified an eight-predictor logistic regression model including continuous variables of weight, mid-upper arm circumference, temperature, pulse rate, and transformed oxygen saturation, combined with dichotomous signs of difficulty breathing, lethargy, and inability to drink or breastfeed. This model predicts overnight hospital admission with an area under the receiver operating characteristic curve of 0.88 (95% CI 0.82 to 0.94). Low- and high-risk thresholds of 5% and 25%, respectively were selected to categorize participants into three triage groups for implementation. Conclusion: A logistic regression model comprised of eight easily understood variables may be useful for triage of children under the age of five based on the probability of need for admission. This model could be used by frontline workers with limited skills in assessing children. External validation is needed before adoption in clinical practice.

BackgroundAfrica has the highest rates of child mortality. Little is known about outcomes after hospitalization for children with very severe anemia.ObjectiveTo determine one year mortality and predictors of mortality in Tanzanian children hospitalized with very severe anemia.MethodsWe conducted a prospective cohort study enrolling children 2-12 years hospitalized from August 2014 to November 2014 at two public hospitals in northwestern Tanzania. Children were screened for anemia and followed until 12 months after discharge. The primary outcome measured was mortality. Predictors of mortality were determined using Cox regression analysis.ResultsOf the 505 children, 90 (17.8%) had very severe anemia and 415 (82.1%) did not. Mortality was higher for children with very severe anemia compared to children without over a one year period from admission, 27/90 (30.0%) vs. 59/415 (14.2%) respectively (Hazard Ratio (HR) 2.42, 95% Cl 1.53–3.83). In-hospital mortality was 11/90 (12.2%) and post-hospital mortality was 16/79 (20.2%) for children with very severe anemia. The strongest predictors of mortality were age (HR 1.01, 95% Cl 1.00–1.03) and decreased urine output (HR 4.30, 95% Cl 1.04 – 17.7).ConclusionsChildren up to 12 years of age with very severe anemia have nearly a 30% chance of mortality following admission over a one year period, with over 50% of mortality occurring after discharge. Post-hospital interventions are urgently needed to reduce mortality in children with very severe anemia, and should include older children.

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.

ObjectivesTo update the current evidence base on paediatric postdischarge mortality (PDM) in developing countries. Secondary objectives included an evaluation of risk factors, timing and location of PDM.DesignSystematic literature review without meta-analysis.Data sourcesSearches of Medline and EMBASE were conducted from October 2012 to July 2017.Eligibility criteriaStudies were included if they were conducted in developing countries and examined paediatric PDM. 1238 articles were screened, yielding 11 eligible studies. These were added to 13 studies identified in a previous systematic review including studies prior to October 2012. In total, 24 studies were included for analysis.Data extraction and synthesisTwo independent reviewers extracted and synthesised data using Microsoft Excel.ResultsStudies were conducted mostly within African countries (19 of 24) and looked at all admissions or specific subsets of admissions. The primary subpopulations included malnutrition, respiratory infections, diarrhoeal diseases, malaria and anaemia. The anaemia and malaria subpopulations had the lowest PDM rates (typically 1%–2%), while those with malnutrition and respiratory infections had the highest (typically 3%–20%). Although there was significant heterogeneity between study populations and follow-up periods, studies consistently found rates of PDM to be similar, or to exceed, in-hospital mortality. Furthermore, over two-thirds of deaths after discharge occurred at home. Highly significant risk factors for PDM across all infectious admissions included HIV status, young age, pneumonia, malnutrition, anthropometric variables, hypoxia, anaemia, leaving hospital against medical advice and previous hospitalisations.ConclusionsPostdischarge mortality rates are often as high as in-hospital mortality, yet remain largely unaddressed. Most children who die following discharge do so at home, suggesting that interventions applied prior to discharge are ideal to addressing this neglected cause of mortality. The development, therefore, of evidence-based, risk-guided, interventions must be a focus to achieve the sustainable development goals.

Post-hospital discharge is a vulnerable time for recurrent illness and death among children. An intervention package consisting of (1) referrals for scheduled follow-up visits, (2) discharge counseling, and (3) simple prevention items such as soap and oral rehydration salts resulted in much higher health seeking and hospital readmissions compared with historical controls., Background: Recurrent illness following hospital discharge is a major contributor to childhood mortality in resource-poor countries. Yet post-discharge care is largely ignored by health care workers and policy makers due to a lack of resources to identify children with recurrent illness and a lack of cohesive systems to provide care. The purpose of this proof-of-concept study was to evaluate the effectiveness of a bundle of interventions at discharge to improve health outcomes during the vulnerable post-discharge period. Methods: The study was conducted between December 2014 and April 2015. Eligible children were between ages 6 months and 5 years who were admitted with a suspected or proven infectious disease to one of two hospitals in Mbarara, Uganda. A bundle of interventions was provided at the time of discharge. This bundle included post-discharge referrals for follow-up visits and a discharge kit. The post-discharge referral was to ensure follow-up with a nearby health care provider on days 2, 7, and 14 following discharge. The discharge kit included brief educational counseling along with simple preventive items as incentives (soap, a mosquito net, and oral rehydration salts) to reinforce the education. The primary study outcome was the number of post-discharge referral visits completed. Secondary study outcomes included satisfaction with the intervention, rates of readmission after 60 days, and post-discharge mortality rates. In addition, outcomes were compared with a historical control group, enrolled using the same inclusion criteria and outcome-ascertainment methods. Results: During the study, 216 children were admitted, of whom 14 died during hospitalization. Of the 202 children discharged, 85% completed at least 1 of the 3 follow-up referral visits, with 48% completing all 3 visits. Within 60 days after discharge, 22 children were readmitted at least once and 5 children (2.5%) died. Twelve (43%) readmissions occurred during a scheduled follow-up visit. Compared with prospectively enrolled historical controls, the post-discharge referral for follow-up increased the odds of readmission (odds ratio [OR], 1.92; 95% confidence interval [CI], 1.14 to 3.23) and care sought after discharge (OR, 14.61; 95% CI, 9.41 to 22.67). Overall satisfaction with the bundle of interventions was high, with most caregivers strongly agreeing that the discharge kit and post-discharge referrals improved their ability to care for their child. Conclusions: Interventions initiated at the time of discharge have the potential to profoundly affect the landscape of care during illness recovery and lead to significantly improved outcomes among children under 5 years of age.

Acute infectious diseases are the most common cause of under-5 mortality. However, the hospital burden of nonneonatal pediatric sepsis has not previously been described in the resource poor setting. The objective of this study was to determine the prevalence of sepsis among children 6 months to 5 years old admitted with proven or suspected infection and to evaluate the presence of sepsis as a predictive tool for mortality during admission.In this prospective cohort study, we used the pediatric International Consensus Conference definition of sepsis to determine the prevalence of sepsis among children admitted to the pediatric ward with a proven or suspected infection. The diagnosis of sepsis, as well as each individual component of the sepsis definition, was evaluated for capturing in-hospital mortality.The pediatric ward of two hospitals in Mbarara, Uganda.Admitted children between 6 months and 5 years with a confirmed or suspected infection.None.One thousand three hundred seven (1,307) subjects with a confirmed or suspected infection were enrolled, and 65 children died (5.0%) during their admission. One thousand one hundred twenty-one (85.9%) met the systemic inflammatory response syndrome criteria, and therefore, they were defined as having sepsis. The sepsis criteria captured 61 deaths, demonstrating a sensitivity and a specificity of 95% (95% CI, 90-100%) and 15% (95% CI, 13-17%), respectively. The most discriminatory individual component of the systemic inflammatory response syndrome criteria was the leukocyte count, which alone had a sensitivity of 72% and a specificity of 56% for the identification of mortality in hospital.This study is among the first to quantify the burden of nonneonatal pediatric sepsis in children with suspected infection, using the international consensus sepsis definition, in a typical resource-constrained setting in Africa. This definition was found to be highly sensitive in identifying those who died but had very low specificity as most children who were admitted with infections had sepsis. The systemic inflammatory response syndrome-based sepsis definition offers little value in identification of children at high risk of in-hospital mortality in this setting.

Conducting collaborative and comprehensive epidemiological research on neonatal sepsis in low- and middle-income countries (LMICs) is challenging due to a lack of diagnostic tests. This prospective study protocol aims to obtain epidemiological data on bacterial sepsis in newborns and young infants at Kamuzu Central Hospital in Lilongwe, Malawi. The main goal is to determine if the use of whole blood transcriptome host immune response signatures can help in the identification of infants who have sepsis of bacterial causes. The protocol includes a detailed clinical assessment with vital sign measurements, strict aseptic blood culture protocol with state-of-the-art microbial analyses and RNA-sequencing and metagenomics evaluations of host responses and pathogens, respectively. We also discuss the directions of a brief analysis plan for RNA sequencing data. This study will provide robust epidemiological data for sepsis in neonates and young infants in a setting where sepsis confers an inordinate burden of disease.

BackgroundSepsis is the leading cause of death in children under five in low- and middle-income countries. The rapid identification of the sickest children and timely antibiotic administration may improve outcomes. We developed and implemented a digital triage platform to rapidly identify critically ill children to facilitate timely intravenous antibiotic administration.ObjectiveThis quality improvement initiative sought to reduce the time to antibiotic administration at a dedicated children's hospital outpatient department in Mbarara, Uganda.Intervention and study designThe digital platform consisted of a mobile application that collects clinical signs, symptoms, and vital signs to prioritize children through a combination of emergency triggers and predictive risk algorithms. A computer-based dashboard enabled the prioritization of children by displaying an overview of all children and their triage categories. We evaluated the impact of the digital triage platform over an 11-week pre-implementation phase and an 11-week post-implementation phase. The time from the end of triage to antibiotic administration was compared to evaluate the quality improvement initiative.ResultsThere was a difference of -11 minutes (95% CI, -16.0 to -6.0; p < 0.001; Mann-Whitney U test) in time to antibiotics, from 51 minutes (IQR, 27.0-94.0) pre-implementation to 44 minutes (IQR, 19.0-74.0) post-implementation. Children prioritized as emergency received the greatest time benefit (-34 minutes; 95% CI, -9.0 to -58.0; p < 0.001; Mann-Whitney U test). The proportion of children who waited more than an hour until antibiotics decreased by 21.4% (p = 0.007).ConclusionA data-driven patient prioritization and continuous feedback for healthcare workers enabled by a digital triage platform led to expedited antibiotic therapy for critically ill children with sepsis. This platform may have a more significant impact in facilities without existing triage processes and prioritization of treatments, as is commonly encountered in low resource settings.

Conducting collaborative and comprehensive epidemiological research on neonatal sepsis in low- and middle-income countries (LMICs) is challenging due to a lack of diagnostic tests. This prospective study protocol aims to obtain epidemiological data on bacterial sepsis in newborns and young infants at Kamuzu Central Hospital in Lilongwe, Malawi. The main goal is to determine if the use of whole blood transcriptome host immune response signatures can help in the identification of infants who have sepsis of bacterial causes. The protocol includes a detailed clinical assessment with vital sign measurements, strict aseptic blood culture protocol with state-of-the-art microbial analyses and RNA-sequencing and metagenomics evaluations of host responses and pathogens, respectively. We also discuss the directions of a brief analysis plan for RNA sequencing data. This study will provide robust epidemiological data for sepsis in neonates and young infants in a setting where sepsis confers an inordinate burden of disease.

We evaluated the association between HIV exposed-uninfected (HEU) status, malnutrition and risk of death in Ugandan children hospitalized with pneumonia. Both HIV exposure and infection were associated with lower anthropometric indices on univariate analysis, and mid-upper arm circumference was significantly associated with overall mortality (odds ratio (OR), 0.96) in a multivariable model. HIV infection (OR 5.0) but not HEU status was associated with overall mortality. Malnutrition may contribute to poor pneumonia outcomes among HIV-infected and HEU children requiring hospitalization.

Not much is known about clinical decision-making in rural, low-resource settings regarding fever, a common reason for presentation to care. In this prospective cohort study of patients presenting with febrile illness to a rural Ugandan health center, we examined demographic and clinical factors predictive of an initial disposition of inpatient admission after clinical evaluation, but before laboratory testing. We then assessed the association of laboratory results and system factors with a change between initial and final disposition plans. Four thousand nine hundred twenty-four patients with suspected febrile illness were included in the primary analysis. The strongest predictors for an initial disposition of admission after clinical examination were impaired consciousness (adjusted risk ratio [aRR], 3.21; 95% confidence interval [CI]: 2.44-4.21) and fever on examination (aRR, 2.27; 95% CI: 1.79-2.87). Providers initially planned to discharge patients with significant vital sign abnormalities, including tachypnea (3.6%) and hypotension (1.3%). Anemia strongly predicted a final disposition of admission after an initial disposition of discharge (aRR, 48.34; 95% CI: 24.22-96.49); other laboratory abnormalities, including hypoglycemia and acidosis, did not change disposition planning. In those with an initial disposition of admission, living farther than the two neighboring villages was associated with a final disposition of discharge (aRR, 2.12; 95% CI: 1.10-4.12). A concerning number of patients with abnormal vital signs and laboratory results were not admitted for inpatient care. Geographic factors may influence a patient's final disposition contrary to a provider's initial disposition plan. Future work should assess longer term outcomes after discharge and a broader study population.

Chagas disease is a neglected parasitic illness affecting approximately 8 million people, predominantly in Latin America. Benznidazole is the drug of choice for treatment, although its availability has been limited. A paucity of knowledge of the pharmacokinetic properties of this drug has contributed to its limited availability in several jurisdictions. The objective of this study was to conduct a systematic literature review and a Bayesian meta-analysis of pharmacokinetic studies to improve estimates of the basic pharmacokinetic properties of benznidazole. A systematic search of the Embase, Medline, LILACS, and SciELO (Scientific Electronic Library Online) databases was conducted. Eligible studies reported patient-level data from single-100-mg-dose pharmacokinetic evaluations of benznidazole in adults or otherwise provided data relevant to the estimation of pharmacokinetic parameters which could be derived from such studies. A Bayesian hierarchical model was used for analysis. Secondary data (i.e., data from studies that did not include patient-level, single-100-mg-dose data) were used for the generation of empirical priors for the Bayesian analysis. The systematic search identified nine studies for inclusion. Nine pharmacokinetic parameters were estimated, including the area under the concentration-time curve (AUC), the maximum concentration of drug in plasma ( C max ), the time to C max , the elimination rate constant ( k el ), the absorption rate constant ( K a ), the absorption and elimination half-lives, the apparent oral clearance, and the apparent oral volume of distribution. The results showed consistency across studies. AUC and C max were 51.31 mg · h/liter (95% credible interval [CrI], 45.01, 60.28 mg · h/liter) and 2.19 mg/liter (95% CrI, 2.06, 2.33 mg/liter), respectively. K a and k el were 1.16 h −1 (95% CrI, 0.59, 1.76 h −1 ) and 0.052 h −1 (95% CrI, 0.045, 0.059 h −1 ), respectively, with the corresponding absorption and elimination half-lives being 0.60 h (95% CrI, 0.38, 1.11 h) and 13.27 h (95% CrI, 11.79, 15.42 h), respectively. The oral clearance and volume of distribution were 2.04 liters/h (95% CrI, 1.77, 2.32 liters/h) and 39.19 liters (95% CrI, 36.58, 42.17 liters), respectively. A Bayesian meta-analysis was used to improve the estimates of the standard pharmacokinetic parameters of benznidazole. These data can inform clinicians and policy makers as access to this drug increases.

KEY POINTS The failure to recognize and treat the child with sepsis is devastating to the child and family, as well as for physicians, other health care providers and policy-makers. Several recent high-profile deaths from sepsis in Canadian children1 have highlighted the need for rapid and reliable

Background: Post-discharge mortality is a frequent but poorly recognized contributor to child mortality in resource limited countries. The identification of children at high risk for post-discharge mortality is a critically important first step in addressing this problem. Objectives: The objective of this project was to determine the variables most likely to be associated with post-discharge mortality which are to be included in a prediction modelling study. Methods: A two-round modified Delphi process was completed for the review of a priori selected variables and selection of new variables. Variables were evaluated on relevance according to (1) prediction (2) availability (3) cost and (4) time required for measurement. Participants included experts in a variety of relevant fields. Results: During the first round of the modified Delphi process, 23 experts evaluated 17 variables. Forty further variables were suggested and were reviewed during the second round by 12 experts. During the second round 16 additional variables were evaluated. Thirty unique variables were compiled for use in the prediction modelling study. Conclusion: A systematic approach was utilized to generate an optimal list of candidate predictor variables for the incorporation into a study on prediction of pediatric post-discharge mortality in a resource poor setting. Keywords: Candidate predictor variables, pediatrics, prediction, post-discharge mortality, sepsis

Background: Postdischarge death in children is increasingly being recognized as a major contributor to overall child mortality. The PAediatric Risk Assessment (PARA) app is an mHealth tool developed to aid health care workers in resource-limited settings such as Sub-Saharan Africa to identify pediatric patients at high risk of both in-hospital and postdischarge mortality. The intended users of the PARA app are health care workers (ie, nurses, doctors, and clinical officers) with varying levels of education and technological exposure, making testing of this clinical tool critical to successful implementation. Objective: Our aim was to summarize the usability evaluation of the PARA app among target users, which consists of assessing the ease of use, functionality, and navigation of the interfaces and then iteratively improving the design of this clinical tool. Methods: Health care workers (N=30) were recruited to participate at Mbarara Regional Referral Hospital and Holy Innocents Children’s Hospital in Mbarara, Southwestern Uganda. This usability study was conducted in two phases to allow for iterative improvement and testing of the interfaces. The PARA app was evaluated using quantitative and qualitative measures, which were compared between Phases 1 and 2 of the study. Participants were given two patient scenarios that listed hypothetical information (ie, demographic, social, and clinical data) to be entered into the app and to determine the patient’s risk of in-hospital and postdischarge mortality. Time-to-completion and user errors were recorded for each participant while using the app. A modified computer system usability questionnaire was utilized at the end of each session to elicit user satisfaction with the PARA app and obtain suggestions for future improvements. Results: The average time to complete the PARA app decreased by 30% from Phase 1 to Phase 2, following user feedback and modifications. Participants spent the longest amount of time on the oxygen saturation interface, but modifications following Phase 1 cut this time by half. The average time-to-completion (during Phase 2) for doctors/medical students was 3 minutes 56 seconds. All participants agreed they would use the PARA app if available at their health facility. Given a high PARA risk score, participants suggested several interventions that would be appropriate for the sociocultural context in southwestern Uganda, which involved strengthening discharge and referral procedures within the current health care system. Conclusions: Through feedback and modifications made during this usability study, the PARA app was developed into a user-friendly app, encompassing user expectations and culturally intuitive interfaces for users with a range of technological exposure. Doctors and medical students had shorter task completion times, though all participants reported the usefulness of this tool to improve postdischarge outcomes. [JMIR Mhealth Uhealth 2016;4(1):e16]

OBJECTIVES: Diabetes is increasing in prevalence across Canada. In the continuously evolving primary care landscape, practitioners from varied training paths are claiming rights to care for patients, including those with diabetes. Little is known about patient exposure to complementary and alternative medicine (CAM) providers, or about such providers' use of guideline-based monitoring and treatment recommendations. The purpose of this study was to examine compliance with 4 recommendations (influenza vaccination, eye examination, glycated hemoglobin measurement and foot exam) by patients with diabetes who use CAM providers compared to those who exclusively use primary care physicians. METHODS: We analyzed data on 7209 patients with diabetes using the Canadian Community Health Survey. Patients with exposure to CAM providers were compared with individuals who were exposed to a family physician only. Multivariate logistic regression was conducted adjusted for age, sex, duration of diabetes, insulin/oral antihyperglycemic agent use and education. RESULTS: Approximately 4% of persons had been exposed to CAM providers in the preceding year. The odds ratio for receiving influenza vaccination among those exposed to a CAM provider was 0.94 (95% CI 0.74–1.17). The odds ratios for eye examinations in the preceding 24 months, and for foot examinations and glycated hemoglobin tests in the preceding 12 months were 1.02 (95% CI 0.69–1.48), 1.18 (0.83–1.67) and 1.09 (95% CI 0.71–1.66), respectively. CONCLUSION: Our results did not show statistical significance in any of the 4 outcomes analyzed. This study supports others suggesting that persons using CAM providers do so to complement traditional medical care, rather than as an alternative to such care.

Objective Anaemia affects the majority of children in sub-Saharan Africa (SSA). Previous studies of risk factors for anaemia have been limited by sample size, geography and the association of many risk factors with poverty. In order to measure the relative impact of individual, maternal and household risk factors for anaemia in young children, we analysed data from all SSA countries that performed haemoglobin (Hb) testing in the Demographic and Health Surveys. Design and setting This cross-sectional study pooled household-level data from the most recent Demographic and Health Surveys conducted in 27 SSA between 2008 and 2014. Participants 96 804 children age 6–59 months. Results The prevalence of childhood anaemia (defined as Hb

Background Children discharged from hospitals in developing countries are at high risk of morbidity and mortality. However, few data describe these outcomes among children seen and discharged from rural outpatient centers. Objective The objective of this exploratory study was to identify predictors of immediate and follow-up morbidity and mortality among children visiting a rural health center in Uganda. Methods Subjects 0–12 years of age seeking care with a caregiver were consecutively enrolled from a single rural health center in Southwestern Uganda. Baseline variables were collected by research nurses and outcomes of referral, admission or death were recorded (immediate events). Death, hospital admission and health seeking occurring during the 30 days following the clinic visit were also determined (follow-up events). Univariate logistic regression was performed to identify baseline variables associated with immediate outcome and follow-up outcomes. Results Over the four-month recruitment period 717 subjects were enrolled. There were 85 (11.9%) immediate events (10.1% were admitted, 2.2% were referred, none died). Forty-seven (7.8%) events occurred within 30 days after the visit (7.3% sought care from a health provider, 1.5% were admitted and 0.5% died). Variables associated with immediate events included living more than 30 minutes from the health center, age older than 5 years, having received an antimalarial prior to the visit, having seen a community health worker prior to the visit, elevated respiratory rate or temperature, and depressed weight-for-age z score or decreased oxygen saturation. These variables were not associated with follow-up events. Conclusions Sick-child visits at a rural health center in South Western Uganda were associated with rates of mortality and subsequent admission of less than 2% in the period following the sick child visits. Other types of health seeking behavior occurred in approximately 7% of subjects during this same period. Several variables were associated with immediate events but there were no reliable predictors of follow-up events, possibly due to low statistical power.

Introduction : Expanding and sustaining antiretroviral therapy (ART) coverage may require simplified HIV service delivery strategies that concomitantly reduce the burden of care on the health system and patients while ensuring optimal outcomes. We conducted a systematic review to assess the impact of reduced frequency of clinic visits and drug dispensing on patient outcomes. Methods : As part of the development process of the World Health Organization antiretroviral (ARV) guidelines, we systematically searched medical literature databases for publications up to 30 August 2016. Information was extracted on trial characteristics, patient characteristics and the following outcomes: mortality, morbidity, treatment adherence, retention, patient and provider acceptability, cost and patients exiting the programme. When feasible, conventional pairwise meta-analyses were conducted. Results and discussion : Of 6443 identified citations, 21 papers, pertaining to 16 studies, were included in this review, with 11 studies contributing to analyses. Although analyses were feasible, they were limited by the sparse evidence base, despite the importance of the research area, and relatively low quality. Comparative analyses of eight studies reporting on frequency of clinic visits showed that less frequent clinic visits led to higher odds of being retained in care (odds ratio [OR]: 1.90; 95% CI: 1.21–2.99). No differences were found with respect to viral failure, morbidity or mortality; however, most estimates were favourable to reduced clinic visits. Reduced frequency of ARVs pick-ups showed a trend towards better retention (OR: 1.93; 95% CI: 0.62–6.04). Strategies using community support tended to have better outcomes; however, their implementation varied, particularly by location. External validity may be questionable. Conclusions : Our systematic review suggests that reduction of clinical visits (and likely ARVs pick-ups) may improve clinical outcomes, and that they are a viable option to relieve health systems and reduce burden of care for PLHIV. Strategies aimed at reducing clinic visits or drug refill services should focus on stable patients who are virally suppressed, tolerant to their drug regimen and fully adherent. These strategies may be critical to the current changes taking place in HIV treatment policy; thus, due to the data limitations, further high quality research is needed to inform policy and programmatic interventions. Keywords HIV Services; clinical visit frequency; antiretroviral therapy HIV/AIDS; systematic literature review; meta-analysis To access the supplementary material to this article please see Supplementary Files under Article Tools online. (Published: 21 July 2017) Mutasa-Apollo T et al. Journal of the International AIDS Society 2017, 20 :21647 http://www.jiasociety.org/index.php/jias/article/view/21647 | http://dx.doi.org/10.7448/IAS.20.5.21647

BACKGROUND:Pediatric hospital mortality from infectious diseases in resource constrained countries remains unacceptably high. Improved methods of risk-stratification can assist in referral decision making and resource allocation. The purpose of this study was to create prediction models for in-hospital mortality among children admitted with suspected infectious diseases. METHODS:This two-site prospective observational study enrolled children between 6 months and 5 years admitted with a proven or suspected infection. Baseline clinical and laboratory variables were collected on enrolled children. The primary outcome was death during admission. Stepwise logistic regression minimizing Akaike's information criterion was used to identify the most promising multivariate models. The final model was chosen based on parsimony. RESULTS:1307 children were enrolled consecutively, and 65 (5%) of whom died during their admission. Malaria, pneumonia and gastroenteritis were diagnosed in 50%, 31% and 8% of children, respectively. The primary model included an abnormal Blantyre coma scale, HIV and weight-for-age z-score. This model had an area under the curve (AUC) of 0.85 (95% CI, 0.80-0.89) with a sensitivity and specificity of 83% and 76%, respectively. The positive and negative predictive values were 15% and 99%, respectively. Two alternate models with similar performance characteristics were developed withholding HIV and weight-for-age z-score, for use when these variables are not available. CONCLUSIONS:Risk stratification of children admitted with infectious diseases can be calculated based on several easily measured variables. Risk stratification at admission can be used for allocation of scarce human and physical resources and to guide referral among children admitted to lower level health facilities.

Objectives To derive a model of paediatric postdischarge mortality following acute infectious illness. Design Prospective cohort study. Setting 2 hospitals in South-western Uganda. Participants 1307 children of 6 months to 5 years of age were admitted with a proven or suspected infection. 1242 children were discharged alive and followed up 6 months following discharge. The 6-month follow-up rate was 98.3%. Interventions None. Primary and secondary outcome measures The primary outcome was postdischarge mortality within 6 months following the initial hospital discharge. Results 64 children died during admission (5.0%) and 61 died within 6 months of discharge (4.9%). Of those who died following discharge, 31 (51%) occurred within the first 30 days. The final adjusted model for the prediction of postdischarge mortality included the variables mid-upper arm circumference (OR 0.95, 95% CI 0.94 to 0.97, per 1 mm increase), time since last hospitalisation (OR 0.76, 95% CI 0.61 to 0.93, for each increased period of no hospitalisation), oxygen saturation (OR 0.96, 95% CI 0.93 to 0·99, per 1% increase), abnormal Blantyre Coma Scale score (OR 2.39, 95% CI 1·18 to 4.83), and HIV-positive status (OR 2.98, 95% CI 1.36 to 6.53). This model produced a receiver operating characteristic curve with an area under the curve of 0.82. With sensitivity of 80%, our model had a specificity of 66%. Approximately 35% of children would be identified as high risk (11.1% mortality risk) and the remaining would be classified as low risk (1.4% mortality risk), in a similar cohort. Conclusions Mortality following discharge is a poorly recognised contributor to child mortality. Identification of at-risk children is critical in developing postdischarge interventions. A simple prediction tool that uses 5 easily collected variables can be used to identify children at high risk of death after discharge. Improved discharge planning and care could be provided for high-risk children.