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Abstract Background Sepsis is a life-threatening condition which may arise from infection in any organ system and requires early recognition and management. Healthcare professionals working in any specialty may need to manage patients with sepsis. Educating medical students about this condition may be an effective way to ensure all future doctors have sufficient ability to diagnose and treat septic patients. However, there is currently no consensus on what competencies medical students should achieve regarding sepsis recognition and treatment. This study aims to outline what sepsis-related competencies medical students should achieve by the end of their medical student training in both high or upper-middle incomes countries/regions and in low or lower-middle income countries/regions. Methods Two separate panels from high or upper-middle income and low or lower-middle income countries/regions participated in a Delphi method to suggest and rank sepsis competencies for medical students. Each panel consisted of 13–18 key stakeholders of medical education and doctors in specialties where sepsis is a common problem (both specialists and trainees). Panelists came from all continents, except Antarctica. Results The panels reached consensus on 38 essential sepsis competencies in low or lower-middle income countries/regions and 33 in high or upper-middle incomes countries/regions. These include competencies such as definition of sepsis and septic shock and urgency of antibiotic treatment. In the low or lower-middle income countries/regions group, consensus was also achieved for competencies ranked as very important, and was achieved in 4/5 competencies rated as moderately important. In the high or upper-middle incomes countries/regions group, consensus was achieved in 41/57 competencies rated as very important but only 6/11 competencies rated as moderately important. Conclusion Medical schools should consider developing curricula to address essential competencies, as a minimum, but also consider addressing competencies rated as very or moderately important.

Infectious diseases in neonates account for half of the under-five mortality in low- and middle-income countries. Data-driven algorithms such as clinical prediction models can be used to efficiently detect critically ill children in order to optimize care and reduce mortality. Thus far, only a handful of prediction models have been externally validated and are limited to neonatal in-hospital mortality. The aim of this study is to externally validate a previously derived clinical prediction model (Smart Triage) using a combined prospective baseline cohort from Uganda and Kenya with a composite endpoint of hospital admission, mortality, and readmission. We evaluated model discrimination using area under the receiver-operator curve (AUROC) and visualized calibration plots with age subsets (< 30 days, ≤ 2 months, ≤ 6 months, and < 5 years). Due to reduced performance in neonates (< 1 month), we re-estimated the intercept and coefficients and selected new thresholds to maximize sensitivity and specificity. 11595 participants under the age of five (under-5) were included in the analysis. The proportion with an endpoint ranged from 8.9% in all children under-5 (including neonates) to 26% in the neonatal subset alone. The model achieved good discrimination for children under-5 with AUROC of 0.81 (95% CI: 0.79-0.82) but poor discrimination for neonates with AUROC of 0.62 (95% CI: 0.55-0.70). Sensitivity at the low-risk thresholds (CI) were 85% (83%-87%) and 68% (58%-76%) for children under-5 and neonates, respectively. After model revision for neonates, we achieved an AUROC of 0.83 (95% CI: 0.79-0.87) with 13% and 41% as the low- and high-risk thresholds, respectively. The updated Smart Triage performs well in its predictive ability across different age groups and can be incorporated into current triage guidelines at local healthcare facilities. Additional validation of the model is indicated, especially for the neonatal model.

Models for digital triage of sick children at emergency departments of hospitals in resource poor settings have been developed. However, prior to their adoption, external validation should be performed to ensure their generalizability. We externally validated a previously published nine-predictor paediatric triage model (Smart Triage) developed in Uganda using data from two hospitals in Kenya. Both discrimination and calibration were assessed, and recalibration was performed by optimizing the intercept for classifying patients into emergency, priority, or non-urgent categories based on low-risk and high-risk thresholds. A total of 2539 patients were eligible at Hospital 1 and 2464 at Hospital 2, and 5003 for both hospitals combined; admission rates were 8.9%, 4.5%, and 6.8%, respectively. The model showed good discrimination, with area under the receiver-operator curve (AUC) of 0.826, 0.784 and 0.821, respectively. The pre-calibrated model at a low-risk threshold of 8% achieved a sensitivity of 93% (95% confidence interval, (CI):89%-96%), 81% (CI:74%-88%), and 89% (CI:85%-92%), respectively, and at a high-risk threshold of 40%, the model achieved a specificity of 86% (CI:84%-87%), 96% (CI:95%-97%), and 91% (CI:90%-92%), respectively. Recalibration improved the graphical fit, but new risk thresholds were required to optimize sensitivity and specificity.The Smart Triage model showed good discrimination on external validation but required recalibration to improve the graphical fit of the calibration plot. There was no change in the order of prioritization of patients following recalibration in the respective triage categories. Recalibration required new site-specific risk thresholds that may not be needed if prioritization based on rank is all that is required. The Smart Triage model shows promise for wider application for use in triage for sick children in different settings.

In 2019, 80% of the 7.4 million global child deaths occurred in low- and middle-income countries (LMICs). Global and regional estimates of cause of hospital death and admission in LMIC children are needed to guide global and local priority setting and resource allocation but are currently lacking. The study objective was to estimate global and regional prevalence for common causes of pediatric hospital mortality and admission in LMICs. We performed a systematic review and meta-analysis to identify LMIC observational studies published January 1, 2005-February 26, 2021. Eligible studies included: a general pediatric admission population, a cause of admission or death, and total admissions. We excluded studies with data before 2,000 or without a full text. Two authors independently screened and extracted data. We performed methodological assessment using domains adapted from the Quality in Prognosis Studies tool. Data were pooled using random-effects models where possible. We reported prevalence as a proportion of cause of death or admission per 1,000 admissions with 95% confidence intervals (95% CI). Our search identified 29,637 texts. After duplicate removal and screening, we analyzed 253 studies representing 21.8 million pediatric hospitalizations in 59 LMICs. All-cause pediatric hospital mortality was 4.1% [95% CI 3.4%–4.7%]. The most common causes of mortality (deaths/1,000 admissions) were infectious [12 (95% CI 9–14)]; respiratory [9 (95% CI 5–13)]; and gastrointestinal [9 (95% CI 6–11)]. Common causes of admission (cases/1,000 admissions) were respiratory [255 (95% CI 231–280)]; infectious [214 (95% CI 193–234)]; and gastrointestinal [166 (95% CI 143–190)]. We observed regional variation in estimates. Pediatric hospital mortality remains high in LMICs. Global child health efforts must include measures to reduce hospital mortality including basic emergency and critical care services tailored to the local disease burden. Resources are urgently needed to promote equity in child health research, support researchers, and collect high-quality data in LMICs to further guide priority setting and resource allocation.

Introduction To our knowledge, this study is the first to identify and describe current sepsis policies, clinical practice guidelines, and health professional training standards in Canada to inform evidence-based policy recommendations.Methods and analysis This study will be designed and reported according to the Arksey and O’Malley framework for scoping reviews and the Preferred Reporting Items for Systematic Review and Meta-Analyses Extension for Scoping Reviews. EMBASE, CINAHL, Medline, Turning Research Into Practice and Policy Commons will be searched for policies, clinical practice guidelines and health professional training standards published or updated in 2010 onwards, and related to the identification, management or reporting of sepsis in Canada. Additional sources of evidence will be identified by searching the websites of Canadian organisations responsible for regulating the training of healthcare professionals and reporting health outcomes. All potentially eligible sources of evidence will be reviewed for inclusion, followed by data extraction, independently and in duplicate. The included policies will be collated and summarised to inform future evidence-based sepsis policy recommendations.Ethics and dissemination The proposed study does not require ethics approval. The results of the study will be submitted for publication in a peer-reviewed journal and presented at local, national and international forums.

Sub-Saharan Africa accounts for two-thirds of the global burden of maternal and newborn deaths. Adverse outcomes among postpartum women and newborns occurring in the first six weeks of life are often related, though data co-examining patients are limited. This study is an exploratory analysis describing the epidemiology of postnatal complications among postpartum women and newborns following facility birth and discharge in Mbarara, Uganda. This single-site prospective cohort observational study enrolled postpartum women following facility-based delivery. To capture health information about both the postpartum women and newborns, data was collected and categorized according to domains within the continuum of care including (1) social and demographic, (2) pregnancy history and antenatal care, (3) delivery, (4) maternal discharge, and (5) newborn discharge. The primary outcomes were readmission and mortality within the six-week postnatal period as defined by the WHO. Multivariable logistic regression was used to identify risk factors. Among 2930 discharged dyads, 2.8% and 9.0% of women and newborns received three or more postnatal visits respectively. Readmission and deaths occurred among 108(3.6%) and 25(0.8%) newborns and in 80(2.7%) and 0(0%) women, respectively. Readmissions were related to sepsis/infection in 70(88%) women and 68(63%) newborns. Adjusted analysis found that caesarean delivery (OR:2.91; 95%CI:1.5-6.04), longer travel time to the facility (OR:1.54; 95%CI:1.24-1.91) and higher maternal heart rate at discharge (OR:1.02; 95%CI:1.00-1.01) were significantly associated with maternal readmission. Discharge taken on all patients including maternal haemoglobin (per g/dL) (OR:0.90; 95%CI:0.82-0.99), maternal symptoms (OR:1.76; 95%CI:1.02-2.91), newborn temperature (OR:1.66; 95%CI:1.28-2.13) and newborn heart rate at (OR:1.94; 95%CI:1.19-3.09) were risk factors among newborns. Readmission and death following delivery and discharge from healthcare facilities is still a problem in settings with low rates of postnatal care visits for both women and newborns. Strategies to identify vulnerable dyads and provide better access to follow-up care, are urgently required.

In many low-income countries, over five percent of hospitalized children die following hospital discharge. The lack of available tools to identify those at risk of post-discharge mortality has limited the ability to make progress towards improving outcomes. We aimed to develop algorithms designed to predict post-discharge mortality among children admitted with suspected sepsis. Four prospective cohort studies of children in two age groups (0-6 and 6-60 months) were conducted between 2012-2021 in six Ugandan hospitals. Prediction models were derived for six-months post-discharge mortality, based on candidate predictors collected at admission, each with a maximum of eight variables, and internally validated using 10-fold cross-validation. 8,810 children were enrolled: 470 (5.3%) died in hospital; 257 (7.7%) and 233 (4.8%) post-discharge deaths occurred in the 0-6-month and 6-60-month age groups, respectively. The primary models had an area under the receiver operating characteristic curve (AUROC) of 0.77 (95%CI 0.74-0.80) for 0-6-month-olds and 0.75 (95%CI 0.72-0.79) for 6-60-month-olds; mean AUROCs among the 10 cross-validation folds were 0.75 and 0.73, respectively. Calibration across risk strata was good: Brier scores were 0.07 and 0.04, respectively. The most important variables included anthropometry and oxygen saturation. Additional variables included: illness duration, jaundice-age interaction, and a bulging fontanelle among 0-6-month-olds; and prior admissions, coma score, temperature, age-respiratory rate interaction, and HIV status among 6-60-month-olds. Simple prediction models at admission with suspected sepsis can identify children at risk of post-discharge mortality. Further external validation is recommended for different contexts. Models can be digitally integrated into existing processes to improve peri-discharge care as children transition from the hospital to the community.

Summary: Background: Under-five mortality remains concentrated in resource-poor countries. Post-discharge mortality is becoming increasingly recognized as a significant contributor to overall child mortality. With a substantial recent expansion of research and novel data synthesis methods, this study aims to update the current evidence base by providing a more nuanced understanding of the burden and associated risk factors of pediatric post-discharge mortality after acute illness. Methods: Eligible studies published between January 1, 2017 and January 31, 2023, were retrieved using MEDLINE, Embase, and CINAHL databases. Studies published before 2017 were identified in a previous review and added to the total pool of studies. Only studies from countries with low or low-middle Socio-Demographic Index with a post-discharge observation period greater than seven days were included. Risk of bias was assessed using a modified version of the Joanna Briggs Institute critical appraisal tool for prevalence studies. Studies were grouped by patient population, and 6-month post-discharge mortality rates were quantified by random-effects meta-analysis. Secondary outcomes included post-discharge mortality relative to in-hospital mortality, pooled risk factor estimates, and pooled post-discharge Kaplan–Meier survival curves. PROSPERO study registration: #CRD42022350975. Findings: Of 1963 articles screened, 42 eligible articles were identified and combined with 22 articles identified in the previous review, resulting in 64 total articles. These articles represented 46 unique patient cohorts and included a total of 105,560 children. For children admitted with a general acute illness, the pooled risk of mortality six months post-discharge was 4.4% (95% CI: 3.5%–5.4%, I2 = 94.2%, n = 11 studies, 34,457 children), and the pooled in-hospital mortality rate was 5.9% (95% CI: 4.2%–7.7%, I2 = 98.7%, n = 12 studies, 63,307 children). Among disease subgroups, severe malnutrition (12.2%, 95% CI: 6.2%–19.7%, I2 = 98.2%, n = 10 studies, 7760 children) and severe anemia (6.4%, 95% CI: 4.2%–9.1%, I2 = 93.3%, n = 9 studies, 7806 children) demonstrated the highest 6-month post-discharge mortality estimates. Diarrhea demonstrated the shortest median time to death (3.3 weeks) and anemia the longest (8.9 weeks). Most significant risk factors for post-discharge mortality included unplanned discharges, severe malnutrition, and HIV seropositivity. Interpretation: Pediatric post-discharge mortality rates remain high in resource-poor settings, especially among children admitted with malnutrition or anemia. Global health strategies must prioritize this health issue by dedicating resources to research and policy innovation. Funding: No specific funding was received.

Abstract Background In low- and middle-income countries, approximately two thirds of maternal deaths occur in the postpartum period. Yet, care for women beyond 24 h after discharge is limited. The objective of this systematic review is to summarize current evidence on socio-demographic and clinical risk factors for (1) postpartum mortality and (2) postpartum hospital readmission. Methods A combination of keywords and subject headings (i.e. MeSH terms) for postpartum maternal mortality or readmission were searched. Articles published up to January 9, 2021 were identified in MEDLINE, EMBASE, and CINAHL databases, without language restrictions. Studies reporting socio-demographic or clinical risk factors for postpartum mortality or readmission within six weeks of delivery among women who delivered a livebirth in a low- or middle-income country were included. Data were extracted independently by two reviewers based on study characteristics, population, and outcomes. Included studies were assessed for quality and risk of bias using the Downs and Black checklist for ratings of randomized and non-randomized studies. Results Of 8783 abstracts screened, seven studies were included (total N = 387,786). Risk factors for postpartum mortality included Caesarean mode of delivery, nulliparity, low or very low birthweight, and shock upon admission. Risk factors for postpartum readmission included Caesarean mode of delivery, HIV positive serostatus, and abnormal body temperature. Conclusions Few studies reported individual socio-demographic or clinical risk factors for mortality or readmission after delivery in low- and middle-income countries; only Caesarean delivery was consistently reported. Further research is needed to identify factors that put women at greatest risk of post-discharge complications and mortality. Understanding post-discharge risk would facilitate targeted postpartum care and reduce adverse outcomes in women after delivery. Trial registration PROSPERO registration number: CRD42018103955.

IntroductionIn low-income country settings, the first six weeks after birth remain a critical period of vulnerability for both mother and newborn. Despite recommendations for routine follow-up after delivery and facility discharge, few mothers and newborns receive guideline recommended care during this period. Prediction modelling of post-delivery outcomes has the potential to improve outcomes for both mother and newborn by identifying high-risk dyads, improving risk communication, and informing a patient-centered approach to postnatal care interventions. This study aims to derive post-discharge risk prediction algorithms that identify mother-newborn dyads who are at risk of re-admission or death in the first six weeks after delivery at a health facility.MethodsThis prospective observational study will enroll 7,000 mother-newborn dyads from two regional referral hospitals in southwestern and eastern Uganda. Women and adolescent girls aged 12 and above delivering singletons and twins at the study hospitals will be eligible to participate. Candidate predictor variables will be collected prospectively by research nurses. Outcomes will be captured six weeks following delivery through a follow-up phone call, or an in-person visit if not reachable by phone. Two separate sets of prediction models will be built, one set of models for newborn outcomes and one set for maternal outcomes. Derivation of models will be based on optimization of the area under the receiver operator curve (AUROC) and specificity using an elastic net regression modelling approach. Internal validation will be conducted using 10-fold cross-validation. Our focus will be on the development of parsimonious models (5–10 predictor variables) with high sensitivity (>80%). AUROC, sensitivity, and specificity will be reported for each model, along with positive and negative predictive values.DiscussionThe current recommendations for routine postnatal care are largely absent of benefit to most mothers and newborns due to poor adherence. Data-driven improvements to postnatal care can facilitate a more patient-centered approach to such care. Increasing digitization of facility care across low-income settings can further facilitate the integration of prediction algorithms as decision support tools for routine care, leading to improved quality and efficiency. Such strategies are urgently required to improve newborn and maternal postnatal outcomes. Clinical trial registrationhttps://clinicaltrials.gov/, identifier (NCT05730387).

Abstract Background Effective triage at hospitals can improve outcomes for children globally by helping identify and prioritize care for those most at-risk of death. Paper-based pediatric triage guidelines have been developed to support frontline health workers in low-resource settings, but these guidelines can be challenging to implement. Smart Triage is a digital triaging platform for quality improvement (QI) that aims to address this challenge. Smart Triage represents a major cultural and behavioural shift in terms of managing patients at health facilities in low-and middle-income countries. The purpose of this study is to understand user perspectives on the usability, feasibility, and acceptability of Smart Triage to inform ongoing and future implementation. Methods This was a descriptive qualitative study comprising of face-to-face interviews with health workers (n = 15) at a regional referral hospital in Eastern Uganda, conducted as a sub-study of a larger clinical trial to evaluate Smart Triage (NCT04304235). Thematic analysis was used to assess the usability, feasibility, and acceptability of the platform, focusing on its use in stratifying and prioritizing patients according to their risk and informing QI initiatives implemented by health workers. Results With appropriate training and experience, health workers found most features of Smart Triage usable and feasible to implement, and reported the platform was acceptable due to its positive impact on reducing the time to treatment for emergency pediatric cases and its use in informing QI initiatives within the pediatric ward. Several factors that reduced the feasibility and acceptability were identified, including high staff turnover, a lack of medical supplies at the hospital, and challenges with staff attitudes. Conclusion Health workers can use the Smart Triage digital triaging platform to identify and prioritize care for severely ill children and improve quality of care at health facilities in low-resource settings. Future innovation is needed to address identified feasibility and acceptability challenges; however, this platform could potentially address some of the challenges to implementing current paper-based systems.

Introduction Diarrhoea is one of the leading causes of under-5 childhood mortality and accounts for 8% of 5.4 million global under-5 deaths. In severely malnourished children, diarrhoea progresses to shock, where the risk of mortality is even higher. At icddr,b Dhaka Hospital, the fatality rate is as high as 69% in children with severe malnutrition and fluid refractory septic shock. To date, no study has evaluated systematically the effects of inotrope or vasopressor or blood transfusion in children with dehydrating diarrhoea (eg, in cholera) and severe acute malnutrition (SAM) or severe underweight who are in shock and unresponsive to WHO-recommended fluid therapy. To reduce the mortality of severely malnourished children presenting with diarrhoea and fluid refractory shock, we aim to compare the efficacy of blood transfusion, dopamine and epinephrine in fluid refractory shock in children who do not respond to WHO-recommended fluid resuscitation.Methods and analysis In this randomised, three-arm, controlled, non-masked clinical trial in children 1–59 months old with SAM or severe underweight and fluid refractory shock, we will compare the efficacy of dopamine or epinephrine administration versus blood transfusion in children who failed to respond to WHO-recommended fluid resuscitation. The primary outcome variable is the case fatality rate. The effect of the intervention will be assessed by performing an intention-to-treat analysis. Recruitment and data collection began in July 2021 and are now ongoing. Results are expected by May 2023.Ethics and dissemination This study has been approved by the icddr,b Institutional Review Board. We adhere to the ‘Declaration of Helsinki’ (2000), guidelines for Good Clinical Practice. Before enrolment, we collect signed informed consent from the parents or caregivers of the children. We will publish the results in a peer-reviewed journal and will arrange a dissemination seminar.Trial registration number NCT04750070.

Autoresuscitation, also referred to as Lazarus phenomenon, is a rare occurrence whereby a patient may experience restoration of spontaneous circulation and signs of life after a diagnosis of “death” following unsuccessful cardiopulmonary resuscitation. “Found alive after declared dead” has often appeared as sensational news on print, electronic, and social media, and the medical fraternity falls prey to media trials and court enquiry, but this rare phenomenon remains underreported in the medical literature. In this article, we review the reports of Lazarus phenomenon in the medical literature and discuss possible explanations to throw some light on the medicolegal and social implications of this condition.

Neonatal sepsis is a serious public health problem; however, there is substantial heterogeneity in the outcomes measured and reported in research evaluating the effectiveness of the treatments. Therefore, we aim to develop a Core Outcome Set (COS) for studies evaluating the effectiveness of treatments for neonatal sepsis. Since a systematic review of key outcomes from randomised trials of therapeutic interventions in neonatal sepsis was published recently, we will complement this with a qualitative systematic review of the key outcomes of neonatal sepsis identified by parents, other family members, parent representatives, healthcare providers, policymakers, and researchers. We will interpret the outcomes of both studies using a previously established framework. Stakeholders across three different groups i.e., (1) researchers, (2) healthcare providers, and (3) patients' parents/family members and parent representatives will rate the importance of the outcomes in an online Real-Time Delphi Survey. Afterwards, consensus meetings will be held to agree on the final COS through online discussions with key stakeholders. This COS is expected to minimize outcome heterogeneity in measurements and publications, improve comparability and synthesis, and decrease research waste.

Bacterial sepsis is generally a major concern in ill infants. To help triaging decisions by front-line health workers in these situations, the World Health Organization (WHO) has developed danger signs (DS). The objective of this study was to evaluate the extent to which nine DS predict bacterial sepsis in young infants presenting with suspected sepsis in a low-income country setting. The study pragmatically evaluated nine DS in infants younger than 3 months with suspected sepsis in a regional hospital in Lilongwe, Malawi, between June 2018 and April 2020. Main outcomes were positive blood or cerebrospinal fluid (CSF) cultures for neonatal pathogens, and mortality. Among 401 infants (gestational age [mean ± SD]: 37.1±3.3 weeks, birth weight 2865±785 grams), 41 had positive blood or CSF cultures for a neonatal pathogen. In-hospital mortality occurred in 9.7% of infants overall (N = 39/401), of which 61.5% (24/39) occurred within 48 hours of admission. Mortality was higher in infants with bacterial sepsis compared to other infants (22.0% [9/41] versus 8.3% [30/360]; p = 0.005). All DS were associated with mortality except for temperature instability and tachypnea, whereas none of the DS were significantly associated with bacterial sepsis, except for "unable to feed" (OR 2.25; 95%CI: 1.17-4.44; p = 0.017). The number of DS predicted mortality (OR: 1.75; 95%CI: 1.43-2.17; p

The World Health Organization (WHO) Integrated Management of Childhood Illness (IMCI) guidelines recognize the importance of discharge planning to ensure continuation of care at home and appropriate follow-up. However, insufficient attention has been paid to post discharge planning in many hospitals contributing to poor implementation. To understand the reasons for suboptimal discharge, we evaluated the pediatric discharge process from hospital admission through the transition to care within the community in Ugandan hospitals. This mixed methods prospective study enrolled 92 study participants in three phases: patient journey mapping for 32 admitted children under-5 years of age with suspected or proven infection, discharge process mapping with 24 pediatric healthcare workers, and focus group discussions with 36 primary caregivers and fathers of discharged children. Data were descriptively and thematically analyzed. We found that the typical discharge process is often not centered around the needs of the child and family. Discharge planning often does not begin until immediately prior to discharge and generally does not include caregiver input. Discharge education and counselling are generally limited, rarely involves the father, and does not focus significantly on post-discharge care or follow-up. Delays in the discharge process itself occur at multiple points, including while awaiting a physical discharge order and then following a discharge order, mainly with billing or transportation issues. Poor peri-discharge care is a significant barrier to optimizing health outcomes among children in Uganda. Process improvements including initiation of early discharge planning, improved communication between healthcare workers and caregivers, as well as an increased focus on post-discharge care, are key to ensuring safe transitions from facility-based care to home-based care among children recovering from severe illness.

BackgroundMore than 50 countries, mainly in Sub-Saharan Africa and South Asia, are not on course to meet the neonatal and under-five mortality target set by the Sustainable Development Goals (SDGs) for the year 2030. One important, yet neglected, aspect of child mortality rates is deaths occurring during the post-discharge period. For children living in resource-poor countries, the rate of post-discharge mortality within the first several months after discharge is often as high as the rates observed during the initial admission period. This has generally been observed within the context of acute illness and has been closely linked to underlying conditions such as malnutrition, HIV, and anemia. These post-discharge mortality rates tend to be underreported and present a major oversight in the efforts to reduce overall child mortality. This review will explore recurrent illness following discharge through determination of rates of, and risk factors for, pediatric post-discharge mortality in resource-poor settings.MethodsEligible studies will be retrieved using MEDLINE, EMBASE, and CINAHL databases. Only studies with a post-discharge observation period of more than 7 days following discharge will be eligible for inclusion. Secondary outcomes will include post-discharge mortality relative to in-hospital mortality, overall readmission rates, pooled estimates of risk factors (e.g. admission details vs discharge factors, clinical vs social factors), pooled post-discharge mortality Kaplan-Meier survival curves, and outcomes by disease subgroups (e.g. malnutrition, anemia, general admissions). A narrative description of the included studies will be synthesized to categorize commonly affected patient population categories and a random-effects meta-analysis will be conducted to quantify overall post-discharge mortality rates at the 6-month time point.DiscussionPost-discharge mortality contributes to global child mortality rates with a greater burden of deaths occurring in resource-poor settings. Literature concentrated on child mortality published over the last decade has expanded to focus on the fatal outcomes of children post-discharge and associated risk factors. The results from this systematic review will inform current policy and interventions on the epidemiological burden of post-discharge mortality and morbidity following acute illness among children living in resource-poor settings.Systematic review registrationPROSPERO Registration ID: CRD42022350975.

IntroductionEarly and accurate recognition of children at risk of progressing to critical illness could contribute to improved patient outcomes and resource allocation. In resource limited settings digital triage tools can support decision making and improve healthcare delivery. We developed a model for rapid identification of critically ill children at triage.MethodsThis was a prospective cohort study of acutely ill children presenting at Jinja Regional Referral Hospital in Eastern Uganda. Variables collected in the emergency department informed the development of a logistic model based on hospital admission using bootstrap stepwise regression. Low and high-risk thresholds for 90% minimum sensitivity and specificity, respectively generated three risk level categories. Performance was assessed using receiver operating characteristic curve analysis on a held-out test set generated by an 80:20 split with 10-fold cross validation. A risk stratification table informed clinical interpretation.ResultsThe model derivation cohort included 1,612 participants, with an admission rate of approximately 23%. The majority of admitted patients were under five years old and presenting with sepsis, malaria, or pneumonia. A 9-predictor triage model was derived: logit (p) = −32.888 + (0.252, square root of age) + (0.016, heart rate) + (0.819, temperature) + (−0.022, mid-upper arm circumference) + (0.048 transformed oxygen saturation) + (1.793, parent concern) + (1.012, difficulty breathing) + (1.814, oedema) + (1.506, pallor). The model afforded good discrimination, calibration, and risk stratification at the selected thresholds of 8% and 40%.ConclusionIn a low income, pediatric population, we developed a nine variable triage model with high sensitivity and specificity to predict who should be admitted. The triage model can be integrated into any digital platform and used with minimal training to guide rapid identification of critically ill children at first contact. External validation and clinical implementation are in progress.

Data sharing has enormous potential to accelerate and improve the accuracy of research, strengthen collaborations, and restore trust in the clinical research enterprise. Nevertheless, there remains reluctancy to openly share raw data sets, in part due to concerns regarding research participant confidentiality and privacy. Statistical data de-identification is an approach that can be used to preserve privacy and facilitate open data sharing. We have proposed a standardized framework for the de-identification of data generated from cohort studies in children in a low-and-middle income country. We applied a standardized de-identification framework to a data sets comprised of 241 health related variables collected from a cohort of 1750 children with acute infections from Jinja Regional Referral Hospital in Eastern Uganda. Variables were labeled as direct and quasi-identifiers based on conditions of replicability, distinguishability, and knowability with consensus from two independent evaluators. Direct identifiers were removed from the data sets, while a statistical risk-based de-identification approach using the k-anonymity model was applied to quasi-identifiers. Qualitative assessment of the level of privacy invasion associated with data set disclosure was used to determine an acceptable re-identification risk threshold, and corresponding k-anonymity requirement. A de-identification model using generalization, followed by suppression was applied using a logical stepwise approach to achieve k-anonymity. The utility of the de-identified data was demonstrated using a typical clinical regression example. The de-identified data sets was published on the Pediatric Sepsis Data CoLaboratory Dataverse which provides moderated data access. Researchers are faced with many challenges when providing access to clinical data. We provide a standardized de-identification framework that can be adapted and refined based on specific context and risks. This process will be combined with moderated access to foster coordination and collaboration in the clinical research community.

BackgroundThe majority of childhood deaths occur in low- and middle-income countries (LMICs). Many of these deaths are avoidable with basic critical care interventions. Quantifying the burden of pediatric critical illness in LMICs is essential for targeting interventions to reduce childhood mortality.ObjectiveTo determine the burden of hospitalization and mortality associated with acute pediatric critical illness in LMICs through a systematic review and meta-analysis of the literature.Data Sources and Search StrategyWe will identify eligible studies by searching MEDLINE, EMBASE, CINAHL, and LILACS using MeSH terms and keywords. Results will be limited to infants or children (ages >28 days to 12 years) hospitalized in LMICs and publications in English, Spanish, or French. Publications with non-original data (e.g., comments, editorials, letters, notes, conference materials) will be excluded.Study SelectionWe will include observational studies published since January 1, 2005, that meet all eligibility criteria and for which a full text can be located.Data ExtractionData extraction will include information related to study characteristics, hospital characteristics, underlying population characteristics, patient population characteristics, and outcomes.Data SynthesisWe will extract and report data on study, hospital, and patient characteristics; outcomes; and risk of bias. We will report the causes of admission and mortality by region, country income level, and age. We will report or calculate the case fatality rate (CFR) for each diagnosis when data allow.ConclusionsBy understanding the burden of pediatric critical illness in LMICs, we can advocate for resources and inform resource allocation and investment decisions to improve the management and outcomes of children with acute pediatric critical illness in LMICs.

Abstract 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.

BackgroundThe burden of pediatric critical illness and resource utilization by children with critical illness in resource limited settings (RLS) are largely unknown. Without specific data that captures key aspects of critical illness, disease presentation, and resource utilization for pediatric populations in RLS, development of a contextual framework for appropriate, evidence-based interventions to guide allocation of limited but available resources is challenging. We present this methods paper which describes our efforts to determine the prevalence, etiology, hospital outcomes, and resource utilization associated with pediatric acute, critical illness in RLS globally.MethodsWe will conduct a prospective, observational, multicenter, multinational point prevalence study in sixty-one participating RLS hospitals from North, Central and South America, Africa, Middle East and South Asia with four sampling time points over a 12-month period. Children aged 29 days to 14 years evaluated for acute illness or injury in an emergency department) or directly admitted to an inpatient unit will be enrolled and followed for hospital outcomes and resource utilization for the first seven days of hospitalization. The primary outcome will be prevalence of acute critical illness, which Global PARITY has defined as death within 48 hours of presentation to the hospital, including ED mortality; or admission/transfer to an HDU or ICU; or transfer to another institution for a higher level-of-care; or receiving critical care-level interventions (vasopressor infusion, invasive mechanical ventilation, non-invasive mechanical ventilation) regardless of location in the hospital, among children presenting to the hospital. Secondary outcomes include etiology of critical illness, in-hospital mortality, cause of death, resource utilization, length of hospital stay, and change in neurocognitive status. Data will be managed via REDCap, aggregated, and analyzed across sites.DiscussionThis study is expected to address the current gap in understanding of the burden, etiology, resource utilization and outcomes associated with pediatric acute and critical illness in RLS. These data are crucial to inform future research and clinical management decisions and to improve global pediatric hospital outcomes.

OBJECTIVES:. To identify the epidemiology and outcome of adults and children with and without sepsis in a rural sub-Sahara African setting. DESIGN:. A priori planned substudy of a prospective, before-and-after trial. SETTING:. Rural, sub-Sahara African hospital. PATIENTS:. One-thousand four-hundred twelve patients (adults, n = 491; children, n = 921) who were admitted to hospital because of an acute infection. INTERVENTIONS:. None. MEASUREMENTS AND MAIN RESULTS:. Demographic, clinical, laboratory data, danger signs, and the presence of sepsis (defined as a quick Sequential Organ Failure Assessment score count ≥ 2) at admission were extracted. Sepsis was observed in 69 adults (14.1%) and 248 children (26.9%). Sepsis patients differed from subjects without sepsis in several demographic and clinical aspects. Malaria was the most frequent type of infection in adults (66.7%) and children (63.7%) with sepsis, followed by suspected bacterial and parasitic infections other than malaria. Adults with sepsis more frequently developed respiratory failure (8.7% vs 2.1%; p = 0.01), had a higher in-hospital mortality (17.4% vs 8.3%; p < 0.001), were less often discharged home (81.2% vs 92.2%; p = 0.007), and had higher median (interquartile range) costs of care (30,300 [19,400–49,900] vs 42,500 Rwandan Francs [27,000–64,400 Rwandan Francs]; p = 0.004) than adults without sepsis. Children with sepsis were less frequently discharged home than children without sepsis (93.1% vs 96.4%; p = 0.046). Malaria and respiratory tract infections claimed the highest absolute numbers of lives. The duration of symptoms before hospital admission did not differ between survivors and nonsurvivors in adults (72 [24–168] vs 96 hr [72–168 hr]; p = 0.27) or children (48 [24–72] vs 36 [24–108 hr]; p = 0.8). Respiratory failure and coma were the most common causes of in-hospital death. CONCLUSIONS:. In addition to suspected bacterial, viral, and fungal infections, malaria and other parasitic infections are common and important causes of sepsis in adults and children admitted to a rural hospital in sub-Sahara Africa. The in-hospital mortality associated with sepsis is substantial, primarily in adults.

This White Paper has been formally accepted for support by the International Federation for Emergency Medicine (IFEM) and by the World Federation of Intensive and Critical Care (WFICC), put forth by a multi-specialty group of intensivists and emergency medicine providers from low- and low-middle-income countries (LMICs) and high-income countries (HiCs) with the aim of 1) defining the current state of caring for the critically ill in low-resource settings (LRS) within LMICs and 2) highlighting policy options and recommendations for improving the system-level delivery of early critical care services in LRS. LMICs have a high burden of critical illness and worse patient outcomes than HICs, hence, the focus of this White Paper is on the care of critically ill patients in the early stages of presentation in LMIC settings. In such settings, the provision of early critical care is challenged by a fragmented health system, costs, a health care workforce with limited training, and competing healthcare priorities. Early critical care services are defined as the early interventions that support vital organ function during the initial care provided to the critically ill patient—these interventions can be performed at any point of patient contact and can be delivered across diverse settings in the healthcare system and do not necessitate specialty personnel. Currently, a single “best” care delivery model likely does not exist in LMICs given the heterogeneity in local context; therefore, objective comparisons of quality, efficiency, and cost-effectiveness between varying models are difficult to establish. While limited, there is data to suggest that caring for the critically ill may be cost effective in LMICs, contrary to a widely held belief. Drawing from locally available resources and context, strengthening early critical care services in LRS will require a multi-faceted approach, including three core pillars: education, research, and policy. Education initiatives for physicians, nurses, and allied health staff that focus on protocolized emergency response training can bridge the workforce gap in the short-term; however, each country’s current human resources must be evaluated to decide on the duration of training, who should be trained, and using what curriculum. Understanding the burden of critical Illness, best practices for resuscitation, and appropriate quality metrics for different early critical care services implementation models in LMICs are reliant upon strengthening the regional research capacity, therefore, standard documentation systems should be implemented to allow for registry use and quality improvement. Policy efforts at a local, national and international level to strengthen early critical care services should focus on funding the building blocks of early critical care services systems and promoting the right to access early critical care regardless of the patient’s geographic or financial barriers. Additionally, national and local policies describing ethical dilemmas involving the withdrawal of life-sustaining care should be developed with broad stakeholder representation based on local cultural beliefs as well as the optimization of limited resources.

Background Globally, critical illness results in millions of deaths every year. Although many of these deaths are potentially preventable, the basic, life-saving care of critically ill patients are often overlooked in health systems. Essential Emergency and Critical Care (EECC) has been devised as the care that should be provided to all critically ill patients in all hospitals in the world. EECC includes the effective care of low cost and low complexity for the identification and treatment of critically ill patients across all medical specialties. This study aimed to specify the content of EECC and additionally, given the surge of critical illness in the ongoing pandemic, the essential diagnosis-specific care for critically ill patients with COVID-19.Methods In a Delphi process, consensus (>90% agreement) was sought from a diverse panel of global clinical experts. The panel iteratively rated proposed treatments and actions based on previous guidelines and the WHO/ICRC’s Basic Emergency Care. The output from the Delphi was adapted iteratively with specialist reviewers into a coherent and feasible package of clinical processes plus a list of hospital readiness requirements.Results The 269 experts in the Delphi panel had clinical experience in different acute medical specialties from 59 countries and from all resource settings. The agreed EECC package contains 40 clinical processes and 67 requirements, plus additions specific for COVID-19.Conclusion The study has specified the content of care that should be provided to all critically ill patients. Implementing EECC could be an effective strategy for policy makers to reduce preventable deaths worldwide.

Abstract Background The identification of sepsis in children varies depending on the definition used. Our purpose was to compare clinical data and outcome of atypical sepsis, manifested as having sepsis but not fulfilling the criteria of systemic inflammatory response syndrome (SIRS-negative sepsis, SNS), in children based on the modified Angus criteria with those of sepsis (S) and severe sepsis (SS) based on the international consensus criteria. Methods Pediatric departments in 11 regional city and county referral hospitals with emergency and intensive care settings in Huai’an serving for 843,000 children participated in a parallel multicenter prospective survey. Clinical data registry was used to recruit those who fulfilled the diagnostic criteria for pediatric sepsis from all admissions (n = 27,836) from 28 days to 15 years old, from September 1, 2010 to August 31, 2011. Results A total of 1606 children met the criteria for pediatric sepsis and were divided into three groups: S, (n = 1377), SS (n = 153, including 32 septic shock), based on the consensus definition criteria, and SNS (n = 76) based on the modified Angus criteria. Most deaths (38/54, 70.3%) occurred within three days of admission. The SNS mainly occurred in infants and was associated with cardiopulmonary and neurologic dysfunction without satisfying the SIRS criteria. Conclusions SNS differed from SS in that it predominantly affected infants and manifested with cardiopulmonary and neurologic dysfunction. There were no laboratory variables which were useful in identification of SNS, or predicting response to therapy or outcome.

Objective: The ongoing coronavirus 2019 (COVID-19) pandemic is disproportionally impacting the adult population. This study describes the experiences after repurposing a PICU and its staff for adult critical care within a state mandated COVID-19 hospital and compares the outcomes to adult patients admitted to the institution's MICU during the same period.Design: A retrospective chart review was performed to analyze outcomes for the adults admitted to the PICU and MICU during the 27-day period the PICU was incorporated into the institution's adult critical care surge plan.Setting: Tertiary care state University hospital.Patients: Critically ill adult patients with proven or suspected COVID-19.Interventions: To select the most ideal adult patients for PICU admission a tiered approach that incorporated older patients with more comorbidities at each stage was implemented.Measurements and Main Results: There were 140 patients admitted to the MICU and 9 patients admitted to the PICU during this period. The mean age of the adult patients admitted to the PICU was lower (49.1 vs. 63.2 p = 0.017). There was no statistically significant difference in the number of comorbidities, intubation rates, days of ventilation, dialysis or LOS. Patients selected for PICU care did not have coronary artery disease, CHF, cerebrovascular disease or COPD. Mean admission Sequential Organ Failure Assessment (SOFA) score was lower in patients admitted to the PICU (4 vs. 6.4, p = 0.017) with similar rates of survival to discharge (66.7 vs. 44.4%, p = 0.64).Conclusion: Outcomes for the adult patients who received care in the PICU did not appear to be worse than those who were admitted to the MICU during this time. While limited by a small sample size, this single center cohort study revealed that careful assessment of critical illness considering age and type of co-morbidities may be a safe and effective approach in determining which critically ill adult patients with known or suspected COVID-19 are the most appropriate for PICU admission in general hospitals with primary management by its physicians and nurses.

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.

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 a clinical syndrome characterized by organ dysfunction due to presumed or proven infection. Severe cases can have case fatality ratio 25% or higher in low-middle income countries, but early diagnosis and timely treatment have a proven benefit. The Smart Triage program in Jinja Regional Referral Hospital in Uganda will provide expedited sepsis treatment in children through a data-driven electronic patient triage system. To complement the ongoing Smart Triage interventional trial, we propose methods for a concurrent cost-effectiveness analysis of the Smart Triage platform. Methods We will use a decision-analytic model taking a societal perspective, combining government and out-of-pocket costs, as patients bear a sizeable portion of healthcare costs in Uganda due to the lack of universal health coverage. Previously published secondary data will be used to link healthcare utilization with costs and intermediate outcomes with mortality. We will model uncertainty via probabilistic sensitivity analysis and present findings at various willingness-to-pay thresholds using a cost-effectiveness acceptability curve. Discussion Our proposed analysis represents a first step in evaluating the cost-effectiveness of an innovative digital triage platform designed to improve clinical outcomes in pediatric sepsis through expediting care in low-resource settings. Our use of a decision analytic model to link secondary costing data, incorporate post-discharge healthcare utilization, and model clinical endpoints is also novel in the pediatric sepsis triage literature for low-middle income countries. Our analysis, together with subsequent analyses modelling budget impact and scale up, will inform future modifications to the Smart Triage platform, as well as motivate scale-up to the district and national levels. Trial registration Trial registration of parent clinical trial: NCT04304235, https://clinicaltrials.gov/ct2/show/NCT04304235. Registered 11 March 2020.

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.

Summary: Background: Oral rehydration solution (ORS) is a form of oral rehydration therapy (ORT) for diarrhoea that has the potential to drastically reduce child mortality; yet, according to UNICEF estimates, less than half of children younger than 5 years with diarrhoea in low-income and middle-income countries (LMICs) received ORS in 2016. A variety of recommended home fluids (RHF) exist as alternative forms of ORT; however, it is unclear whether RHF prevent child mortality. Previous studies have shown considerable variation between countries in ORS and RHF use, but subnational variation is unknown. This study aims to produce high-resolution geospatial estimates of relative and absolute coverage of ORS, RHF, and ORT (use of either ORS or RHF) in LMICs. Methods: We used a Bayesian geostatistical model including 15 spatial covariates and data from 385 household surveys across 94 LMICs to estimate annual proportions of children younger than 5 years of age with diarrhoea who received ORS or RHF (or both) on continuous continent-wide surfaces in 2000–17, and aggregated results to policy-relevant administrative units. Additionally, we analysed geographical inequality in coverage across administrative units and estimated the number of diarrhoeal deaths averted by increased coverage over the study period. Uncertainty in the mean coverage estimates was calculated by taking 250 draws from the posterior joint distribution of the model and creating uncertainty intervals (UIs) with the 2·5th and 97·5th percentiles of those 250 draws. Findings: While ORS use among children with diarrhoea increased in some countries from 2000 to 2017, coverage remained below 50% in the majority (62·6%; 12 417 of 19 823) of second administrative-level units and an estimated 6 519 000 children (95% UI 5 254 000–7 733 000) with diarrhoea were not treated with any form of ORT in 2017. Increases in ORS use corresponded with declines in RHF in many locations, resulting in relatively constant overall ORT coverage from 2000 to 2017. Although ORS was uniformly distributed subnationally in some countries, within-country geographical inequalities persisted in others; 11 countries had at least a 50% difference in one of their units compared with the country mean. Increases in ORS use over time were correlated with declines in RHF use and in diarrhoeal mortality in many locations, and an estimated 52 230 diarrhoeal deaths (36 910–68 860) were averted by scaling up of ORS coverage between 2000 and 2017. Finally, we identified key subnational areas in Colombia, Nigeria, and Sudan as examples of where diarrhoeal mortality remains higher than average, while ORS coverage remains lower than average. Interpretation: To our knowledge, this study is the first to produce and map subnational estimates of ORS, RHF, and ORT coverage and attributable child diarrhoeal deaths across LMICs from 2000 to 2017, allowing for tracking progress over time. Our novel results, combined with detailed subnational estimates of diarrhoeal morbidity and mortality, can support subnational needs assessments aimed at furthering policy makers' understanding of within-country disparities. Over 50 years after the discovery that led to this simple, cheap, and life-saving therapy, large gains in reducing mortality could still be made by reducing geographical inequalities in ORS coverage. Funding: Bill & Melinda Gates Foundation.

Objectives:. Sepsis is responsible for a substantial proportion of global childhood morbidity and mortality. However, evidence demonstrates major inaccuracies in the use of the term “sepsis” in clinical practice, coding, and research. Current and previous definitions of sepsis have been developed using expert consensus but the specific criteria used to identify children with sepsis have not been rigorously evaluated. Therefore, as part of the Society of Critical Care Medicine’s Pediatric Sepsis Definition Taskforce, we will conduct a systematic review to synthesize evidence on individual factors, clinical criteria, or illness severity scores that may be used to identify children with infection who have or are at high risk of developing sepsis-associated organ dysfunction and separately those factors, criteria, and scores that may be used to identify children with sepsis who are at high risk of progressing to multiple organ dysfunction or death. Data Sources:. We will identify eligible studies by searching the following databases: MEDLINE, Embase, and the Cochrane Central Register of Controlled Trials. Study Selection:. We will include all randomized trials and cohort studies published between January 1, 2004, and March 16, 2020. Data Extraction:. Data extraction will include information related to study characteristics, population characteristics, clinical criteria, and outcomes. Data Synthesis:. We will calculate sensitivity and specificity of each criterion for predicting sepsis and conduct a meta-analysis if the data allow. We will also provide pooled estimates of overall hospital mortality. Conclusions:. The potential risk factors, clinical criteria, and illness severity scores from this review which identify patients with infection who are at high risk of developing sepsis-associated organ dysfunction and/or progressing to multiple organ dysfunction or death will be used to inform the next steps of the Pediatric Sepsis Definition Taskforce.

Sickle cell disease (SCD) results in chronic hemolytic anemia, recurrent vascular occlusion, insidious vital organ deterioration, early mortality, and diminished quality of life. Life-threatening acute physiologic crises may occur on a background of progressive diminishing vital organ function. Sickle hemoglobin polymerizes in the deoxygenated state, resulting in erythrocyte membrane deformation, vascular occlusion, and hemolysis. Vascular occlusion and increased blood viscosity results in functional asplenia and immune deficiency in early childhood, resulting in life-long increased susceptibility to serious bacterial infections. Infection remains a main cause of overall mortality in patients with SCD in low- and middle-income countries due to increased exposure to pathogens, increased co-morbidities such as malnutrition, lower vaccination rates, and diminished access to definitive care, including antibiotics and blood. Thus, the greatest gains in preventing infection-associated mortality can be achieved by addressing these factors for SCD patients in austere environments. In contrast, in high-income countries, perinatal diagnosis of SCD, antimicrobial prophylaxis, vaccination, aggressive use of antibiotics for febrile episodes, and the availability of contemporary critical care resources have resulted in a significant reduction in deaths from infection; however, chronic organ injury is problematic. All clinicians, regardless of their discipline, who assume the care of SCD patients must understand the importance of infectious disease as a contributor to death and disability. In this concise narrative review, we summarize the data that describes the importance of infectious diseases as a contributor to death and disability in SCD and discuss pathophysiology, prevalent organisms, prevention, management of acute episodes of critical illness, and ongoing care.

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.

Abstract Sepsis is a major contributor to the global burden of disease. The majority of sepsis cases and deaths are estimated to occur in low and middle-income countries. Barriers to reducing the global burden of sepsis include difficulty quantifying attributable morbidity and mortality, low awareness, poverty and health inequity, and under-resourced and low-resilience public health and acute health care delivery systems. Important differences in the populations at risk, infecting pathogens, and clinical capacity to manage sepsis in high and low-resource settings necessitate context-specific approaches to this significant problem. We review these challenges and propose strategies to overcome them. These strategies include strengthening health systems, accurately identifying and quantifying sepsis cases, conducting inclusive research, establishing data-driven and context-specific management guidelines, promoting creative clinical interventions, and advocacy.

Background: Infections leading to sepsis are major contributors to mortality and morbidity in children world-wide. Determining the capacity of pediatric hospitals in Nigeria to manage sepsis establishes an important baseline for quality-improvement interventions and resource allocations.Objectives: To assess the availability and functionality of resources and manpower for early detection and prompt management of sepsis in children at tertiary pediatric centers in Nigeria.Methods: This was an online survey of tertiary pediatric hospitals in Nigeria using a modified survey tool designed by the World Federation of Pediatric Intensive and Critical Care Societies (WFPICCS). The survey addressed all aspects of pediatric sepsis identification, management, barriers and readiness.Results: While majority of the hospitals 97% (28/29) reported having adequate triage systems, only 60% (16/27) follow some form of guideline for sepsis management. There was no consensus national guideline for management of pediatric sepsis. Over 50% of the respondents identified deficit in parental education, poor access to healthcare services, failure to diagnose sepsis at referring institutions, lack of medical equipment and lack of a definitive protocol for managing pediatric sepsis, as significant barriers.Conclusions: Certain sepsis-related interventions were reportedly widespread, however, there is no standardized sepsis protocol, and majority of the hospitals do not have pediatric intensive care units (PICU). These findings could guide quality improvement measures at institutional level, and healthcare policy/spending at the national level.

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.

Background: Neonates and infants comprise the majority of the 6 million annual deaths under 5 years of age around the world. Most of these deaths occur in low/middle income countries (LMICs) and are preventable. However, the clinical identification of neonates and infants at imminent risk of death is challenging in developing countries.Objective: To systematically review the literature on clinical risk factors for mortality in infants under 12 months of age hospitalized for sepsis or serious infections in LMICs.Methods: MEDLINE and EMBASE were systematically searched using MeSH terms through April 2017. Abstracts were independently screened by two reviewers. Subsequently, full-text articles were selected by two independent reviewers based on PICOS criteria for inclusion in the final analysis. Study data were qualitatively synthesized without quantitative pooling of data due to heterogeneity in study populations and methodology.Results: A total of 1,139 abstracts were screened, and 169 full-text articles were selected for text review. Of these, 45 articles were included in the analysis, with 21 articles featuring neonatal populations (under 28 days of age) exclusively. Most studies were from Sub-Saharan Africa and South Asia. Risk factors for mortality varied significantly according to study populations. For neonatal deaths, prematurity, low birth-weight and young age at presentation were most frequently associated with mortality. For infant deaths, malnutrition, lack of breastfeeding and low oxygen saturation were associated with mortality in the highest number of studies.Conclusions: Risk factors for mortality differ between the neonatal and young infant age groups and were also dependant on the study population. These data can serve as a starting point for the development of individualized predictive models for in-hospital and post-discharge mortality and for the development of interventions to improve outcomes among these high-risk groups.

A geographic information system (GIS)-based transport network within an emergency referral system can be the key to reducing health system delays and increasing the chances of survival, especially during an emergency. We employed a GIS to design an emergency transport system for the rapid transfer of pregnant or early post-partum women, newborns, and children under 5 years of age with suspected sepsis under the Interrupting Pathways to Sepsis Initiative (IPSI) project.A GIS database was developed by mapping the villages, roads, and relevant physical features of the study area. A travel-time algorithm was developed to incorporate the time taken by different modes of local transport to reach the health complexes. These were used in a network analysis to identify the shortest routes to the hospitals from the villages, which were categorized into green, yellow, and red zones based on their proximity to the nearest hospitals to provide transport facilities. An emergency call-in centre established for the project managed the transport system, and its data was used to assess the uptake of this transport system amongst distant communities.Fifteen pre-existing and two new routes were identified as the shortest routes to the health complexes. The call-in centre personnel used this route information to direct both patients and transport drivers to the nearest transport hubs or pick-up points. Adherence with referral advice was high in areas where the IPSI transport operated. Over the study period, the utilisation of the project's transport doubled and referral compliance from distant zones similarly increased.The GIS system created for this study facilitated rapid referral of patients in emergency from distant zones, using locally available transport and resources. The methodology described in this study to develop and implement an emergency transport system can be applied in similar, rural, low-income country settings.

IntroductionThere is need for more data on critical care outcomes and interventions from low- and middle-income countries (LMIC). Global research collaborations could help improve health-care delivery for critically ill children in LMIC where child mortality rates remain high.Materials and methodsTo inform the role of collaborative research in health-care delivery for critically ill children in LMIC, an anonymous online survey of pediatric critical care (PCC) physicians from LMIC was conducted to assess priorities, major challenges, and potential solutions to PCC research. A convenience sample of 56 clinician-researchers taking care of critically ill children in LMIC was targeted. In addition, the survey was made available on a Latin American PCC website. Descriptive statistics were used for data analysis.ResultsThe majority of the 47 survey respondents worked at urban, public teaching hospitals in LMIC. Respondents stated their primary PCC research motivations were to improve clinical care and establish guidelines to standardize care. Top challenges to conducting research were lack of funding, high clinical workload, and limited research support staff. Respondent-proposed solutions to these challenges included increasing research funding options for LMIC, better access to mentors from high-income countries, research training and networks, and higher quality medical record documentation.ConclusionLMIC clinician-researchers must be better empowered and resourced to lead and influence the local and global health research agenda for critically ill children. Increased funding options, access to training and mentorship in research methodology, and improved data collection systems for LMIC PCC researchers were recognized as key needs for success.

Sepsis is dysregulated systemic inflammatory response which can lead to tissue damage, organ failure, and death. With an estimated 30 million cases per year, it is a global public health concern. Severe infections leading to sepsis account for more than half of all under five deaths and around one quarter of all neonatal deaths annually. Most of these deaths occur in low and middle income countries and could be averted by rapid assessment and appropriate treatment. Evidence suggests that service provision and quality of care pertaining to sepsis management in resource poor settings can be improved significantly with minimum resource allocation and investments. Cognizant of the stark realities, a project titled 'Interrupting Pathways to Sepsis Initiative' (IPSI) introduced a package of interventions for improving quality of care pertaining to sepsis management at 2 sub-district level public hospitals in rural Bangladesh. We present here the quality improvement process and achievements regarding some fundamental steps of sepsis management which include rapid identification and admission, followed by assessment for hypoxemia, hypoglycaemia and hypothermia, immediate resuscitation when required and early administration of parenteral broad spectrum antibiotics.Key components of the intervention package include identification of structural and functional gaps through a baseline environmental scan, capacity development on protocolized management through training and supportive supervision by onsite 'Program Coaches', facilitating triage and rapid transfer of patients through 'Welcoming Persons' and enabling rapid treatment through 'Task Shifting' from on-call physicians to on-duty paramedics in the emergency department and on-call physicians to on-duty nurses in the inpatient department.From August, 2013 to March, 2015, 1,262 under-5 children were identified as syndromic sepsis in the emergency departments; of which 82% were admitted. More neonates (30%) were referred to higher level facilities than post-neonates (6%) (p

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.