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The aim of this "Technical Note" is to inform the pediatric critical care data research community about the "2024 Pediatric Sepsis Data Challenge." This competition aims to facilitate the development of open-source algorithms to predict in-hospital mortality in Ugandan children with sepsis. The challenge is to first develop an algorithm using a synthetic training dataset, which will then be scored according to standard diagnostic testing criteria, and then be evaluated against a nonsynthetic test dataset. The datasets originate from admissions to six hospitals in Uganda (2017-2020) and include 3837 children, 6 to 60 months old, who were confirmed or suspected to have a diagnosis of sepsis. The synthetic dataset was created from a random subset of the original data. The test validation dataset closely resembles the synthetic dataset. The challenge should generate an optimal model for predicting in-hospital mortality. Following external validation, this model could be used to improve the outcomes for children with proven or suspected sepsis in low- and middle-income settings., Competing Interests: Ms. Huxford’s institution received funding from Grand Challenges Canada, Thrasher Research Fund, BC Children’s Hospital Foundation, and Mining4Life. Dr. Businge received funding from the Pediatric Sepsis Data CoLaboratory, the World Federation of Pediatric Intensive and Critical Care Societies, the University of British Columbia, and the BC Children’s Hospital Foundation. Dr. Komugisha received support for article research from Grand Challenges Canada. Dr. Tayebwa received funding from the Mbarara University of Science and Technology. Dr. Kamaleswaran received support for article research from the National Institutes of Health. The remaining authors have disclosed that they do not have any potential conflicts of interest., (Copyright © 2024 by the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies.)

Background: Reducing child mortality in low-income countries is constrained by a lack of vital statistics. In the absence of such data, verbal autopsies provide an acceptable method to determining attributable causes of death. The objective was to assess potential causes of pediatric postdischarge mortality in children younger than age 5 years (under-5) originally admitted for suspected sepsis using verbal autopsies., Methods: Secondary analysis of verbal autopsy data from children admitted to 6 hospitals across Uganda from July 2017 to March 2020. Structured verbal autopsy interviews were conducted for all deaths within 6 months after discharge. Two physicians independently classified a primary cause of death, up to 4 alternative causes, and up to 5 contributing conditions using the Start-Up Mortality List, with discordance resolved by consensus., Results: Verbal autopsies were completed for 361 (98.6%) of the 366 (5.9%) children who died among 6191 discharges (median admission age: 5.4 months [interquartile range, 1.8-16.7]; median time to mortality: 28 days [interquartile range, 9-74]). Most deaths (62.3%) occurred in the community. Leading primary causes of death, assigned in 356 (98.6%) of cases, were pneumonia (26.2%), sepsis (22.1%), malaria (8.5%), and diarrhea (7.9%). Common contributors to death were malnutrition (50.5%) and anemia (25.7%). Reviewers were less confident in their causes of death for neonates than older children (P < .05)., Conclusions: Postdischarge mortality frequently occurred in the community in children admitted for suspected sepsis in Uganda. Analyses of the probable causes for these deaths using verbal autopsies suggest potential areas for interventions, focused on early detection of infections, as well as prevention and treatment of underlying contributors such as malnutrition and anemia., (Copyright © 2023 by the American Academy of Pediatrics.)

Background: Sepsis, characterized by organ dysfunction due to presumed or proven infection, has a case-fatality over 20% in severe cases in low-and-middle income countries. Early diagnosis and treatment have proven benefits, prompting our implementation of Smart Triage at Jinja Regional Referral Hospital in Uganda, a program that expedites treatment through a data-driven triage platform. We conducted a cost-effectiveness analysis of Smart Triage to explore its impact on patients and inform multicenter scale up., Methods: The parent clinical trial for Smart Triage was pre-post in design, using the proportion of children receiving sepsis treatment within one hour as the primary outcome, a measure linked to mortality benefit in existing literature. We used a decision-analytic model with Monte Carlo simulation to calculate the cost per year-of-life-lost (YLL) averted of Smart Triage from societal, government, and patient perspectives. Healthcare utilization and lost work for seven days post-discharge were translated into costs and productivity losses via secondary linkage data., Results: In 2021 United States dollars, Smart Triage requires an annuitized program cost of only $0.05 per child, but results in $15.32 saved per YLL averted. At a willingness-to-pay threshold of only $3 per YLL averted, well below published cost-effectiveness threshold estimates for Uganda, Smart Triage approaches 100% probability of cost-effectiveness over the baseline manual triage system. This cost-effectiveness was observed from societal, government, and patient perspectives. The cost-effectiveness observed was driven by a reduction in admission that, while explainable by an improved triage mechanism, may also be partially attributable to changes in healthcare utilization influenced by the coronavirus pandemic. However, Smart Triage remains cost-effective in sensitivity analyses introducing a penalty factor of up to 50% in the reduction in admission., Conclusion: Smart Triage's ability to both save costs and avert YLLs indicates that patients benefit both economically and clinically, while its high probability of cost-effectiveness strongly supports multicenter scale up. Areas for further research include the incorporation of years lived with disability when sepsis disability weights in low-resource settings become available and analyzing budget impact during multicenter scale up., Trial Registration: NCT04304235 (registered on 11/03/2020, clinicaltrials.gov)., (© 2023. BioMed Central Ltd., part of Springer Nature.)

Background: Substantial mortality occurs after hospital discharge in children younger than 5 years with suspected sepsis, especially in low-income countries. A better understanding of its epidemiology is needed for effective interventions to reduce child mortality in these countries. We evaluated risk factors for death after discharge in children admitted to hospital for suspected sepsis in Uganda, and assessed how these differed by age, time of death, and location of death., Methods: In this prospective, multisite, observational cohort study, we recruited and consecutively enrolled children aged 0-60 months admitted with suspected sepsis from the community to the paediatric wards of six Ugandan hospitals. Suspected sepsis was defined as the need for admission due to a suspected or proven infectious illness. At admission, trained study nurses systematically collected data on clinical variables, sociodemographic variables, and baseline characteristics with encrypted study tablets. Participants were followed up for 6 months after discharge by field officers who contacted caregivers at 2 months and 4 months after discharge by telephone and at 6 months after discharge in person to measure vital status, health-care seeking after discharge, and readmission details. We assessed 6-month mortality after hospital discharge among those discharged alive, with verbal autopsies conducted for children who had died after hospital discharge., Findings: Between July 13, 2017, and March 30, 2020, 16 991 children were screened for eligibility. 6545 children (2927 [44·72%] female children and 3618 [55·28%] male children) were enrolled and 6191 were discharged from hospital alive. 6073 children (2687 [44·2%] female children and 3386 [55·8%] male children) completed follow-up. 366 children died in the 6-month period after discharge (weighted mortality rate 5·5%). Median time from discharge to death was 28 days (IQR 9-74). For the 360 children for whom location of death was documented, deaths occurred at home (162 [45·0%]), in transit to care (66 [18·3%]), or in hospital (132 [36·7%]) during a subsequent readmission. Death after hospital discharge was strongly associated with weight-for-age Z scores less than -3 (adjusted risk ratio [aRR] 4·7, 95% CI 3·7-5·8 vs a Z score of >-2), discharge or referral to a higher level of care (7·3, 5·6-9·5), and unplanned discharge (3·2, 2·5-4·0). Hazard ratios (HRs) for severe anaemia (<7g/dL) increased with time since discharge, from 1·7 (95% CI 0·9-3·0) for death occurring in the first time tertile to 5·2 (3·1-8·5) in the third time tertile. HRs for some discharge vulnerabilities decreased significantly with increasing time since discharge, including unplanned discharge (from 4.5 [2·9-6·9] in the first tertile to 2·0 [1·3-3·2] in the third tertile) and poor feeding status (from 7·7 [5·4-11·0] to 1·84 [1·0-3·3]). Age interacted with several variables, including reduced weight-for-age Z score, severe anaemia, and reduced admission temperature., Interpretation: Paediatric mortality following hospital discharge after suspected sepsis is common, with diminishing, although persistent, risk during the first 6 months after discharge. Efforts to improve outcomes after hospital discharge are crucial to achieving Sustainable Development Goal 3.2 (ending preventable childhood deaths under age 5 years)., Funding: Grand Challenges Canada, Thrasher Research Fund, BC Children's Hospital Foundation, and Mining4Life., Competing Interests: Declaration of interests We declare no competing interests., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Introduction: While there have been several literature reviews on the performance of digital sepsis prediction technologies and clinical decision-support algorithms for adults, there remains a knowledge gap in examining the development of automated technologies for sepsis prediction in children. This scoping review will critically analyse the current evidence on the design and performance of automated digital technologies to predict paediatric sepsis, to advance their development and integration within clinical settings., Methods and Analysis: This scoping review will follow Arksey and O'Malley's framework, conducted between February and December 2022. We will further develop the protocol using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews. We plan to search the following databases: Association of Computing Machinery (ACM) Digital Library, Cumulative Index to Nursing and Allied Health Literature (CINAHL), Embase, Google Scholar, Institute of Electric and Electronic Engineers (IEEE), PubMed, Scopus and Web of Science. Studies will be included on children >90 days postnatal to <21 years old, predicted to have or be at risk of developing sepsis by a digitalised model or algorithm designed for a clinical setting. Two independent reviewers will complete the abstract and full-text screening and the data extraction. Thematic analysis will be used to develop overarching concepts and present the narrative findings with quantitative results and descriptive statistics displayed in data tables., Ethics and Dissemination: Ethics approval for this scoping review study of the available literature is not required. We anticipate that the scoping review will identify the current evidence and design characteristics of digital prediction technologies for the timely and accurate prediction of paediatric sepsis and factors influencing clinical integration. We plan to disseminate the preliminary findings from this review at national and international research conferences in global and digital health, gathering critical feedback from multidisciplinary stakeholders. SCOPING REVIEW REGISTRATION: https://osf.io/veqha/?view&#95;only=f560d4892d7c459ea4cff6dcdfacb086., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Sepsis disproportionately affects children from socioeconomically disadvantaged families in low-resource settings, where care seeking may consume scarce family resources and lead to financial hardships. Those financial hardships may, in turn, contribute to late presentation or failure to seek care and result in high mortality during hospitalization and during the post discharge period, a period of increasingly recognized vulnerability. The purpose of this study is to explore the out-of-pocket costs related to sepsis hospitalizations and post-discharge care among children admitted with sepsis in Uganda., Methods: This mixed-methods study was comprised of focus group discussions (FGD) with caregivers of children admitted for sepsis, which then informed a quantitative cross-sectional household survey to measure out-of-pocket costs of sepsis care both during initial admission and during the post-discharge period. All participants were families of children enrolled in a concurrent sepsis study., Results: Three FGD with mothers (n = 20) and one FGD with fathers (n = 7) were conducted. Three primary themes that emerged included (1) financial losses, (2) time and productivity losses and (3) coping with costs. A subsequently developed cross-sectional survey was completed for 153 households of children discharged following admission for sepsis. The survey revealed a high cost of care for families attending both private and public facilities, although out-of-pocket cost were higher at private facilities. Half of those surveyed reported loss of income during hospitalization and a third sold household assets, most often livestock, to cover costs. Total mean out-of-pocket costs of hospital care and post-discharge care were 124.50 USD and 44.60 USD respectively for those seeking initial care at private facilities and 62.10 USD and 14.60 USD at public facilities, a high sum in a country with widespread poverty., Conclusions: This study reveals that families incur a substantial economic burden in accessing care for children with sepsis., (© 2021. The Author(s).)

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., Competing Interests: The authors have declared that no competing interests exist.

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.

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., Competing Interests: The authors have declared that no competing interests exist.

Competing Interests: Competing interests: J. Mark Ansermino is the founder of LGT Medical, which developed a prediction tool for preeclampsia, and has an equity stake in the company (less than 5%). Niranjan Kissoon is Vice-Chair of the Global Alliance for Sepsis. No other competing interests were declared.

Objectives: 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., Design: 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., Setting: The pediatric ward of two hospitals in Mbarara, Uganda., Patients: Admitted children between 6 months and 5 years with a confirmed or suspected infection., Interventions: None., Measurements and Main Results: 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., Conclusions: 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., Competing Interests: The authors have no conflicts of interest to declare

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.