Assessment of Facility Readiness for Pediatric Emergency and Critical Care Utilizing a 2-Phase Survey Conducted in Six Hospitals in Uganda and Cameroon: A Quality Improvement Study.

Objectives: Each year, 5.3 million children under 5 years of age die in low-resource settings, often due to delayed recognition of disease severity, inadequate treatment, or a lack of supplies. We describe the use of a comprehensive digital facility-readiness survey tool, recently developed by the Pediatric Sepsis Data CoLaboratory, which aims to identify target areas for quality improvement related to pediatric emergency and critical care.

Hierarchical deep compartment modeling: A workflow to leverage machine learning and Bayesian inference for hierarchical pharmacometric modeling.

Population pharmacokinetic (PK) modeling serves as the cornerstone for understanding drug behavior within a specific population. It integrates subject covariates to elucidate the variability in PK parameters, thus enhancing predictive accuracy. However, covariate modeling within this framework can be intricate and time-consuming due to the often obscure structural relationship between covariates and PK parameters.

Pharmacometrics-Enhanced Bayesian Borrowing for Pediatric Extrapolation - A Case Study of the DINAMO Trial.

Bayesian borrowing analyses have an important role in the design and analysis of pediatric trials. This paper describes use of a prespecified Pharmacometrics Enhanced Bayesian Borrowing (PEBB) analysis that was conducted to overcome an expectation for reduced statistical power in the pediatric DINAMO trial due to a greater than expected variability in the primary endpoint. The DINAMO trial assessed the efficacy and safety of an empagliflozin dosing regimen versus placebo and linagliptin versus placebo on glycemic control (change in HbA1c over 26 weeks) in young people with type 2 diabetes (T2D).

Caregivers' and nurses' perceptions of the Smart Discharges Program for children with sepsis in Uganda: A qualitative study.

Sepsis arises when the body's response to an infection injures its own tissues and organs. Among children hospitalized with suspected sepsis in low-income country settings, mortality rates following discharge are high, similar to mortality rates in hospital. The Smart Discharges Program uses a mobile health (mHealth) platform to identify children at high risk of post-discharge mortality to receive enhanced post-discharge care.

Benchmarking bulk and single-cell variant-calling approaches on Chromium scRNA-seq and scATAC-seq libraries.

Single-cell sequencing methodologies such as scRNA-seq and scATAC-seq have become widespread and effective tools to interrogate tissue composition. Increasingly, variant callers are being applied to these methodologies to resolve the genetic heterogeneity of a sample, especially in the case of detecting the clonal architecture of a tumor. Typically, traditional bulk DNA variant callers are applied to the pooled reads of a single-cell library to detect candidate mutations.

Digital solutions in paediatric sepsis: current state, challenges, and opportunities to improve care around the world.

The digitisation of health care is offering the promise of transforming the management of paediatric sepsis, which is a major source of morbidity and mortality in children worldwide. Digital technology is already making an impact in paediatric sepsis, but is almost exclusively benefiting patients in high-resource health-care settings. However, digital tools can be highly scalable and cost-effective, and-with the right planning-have the potential to reduce global health disparities.

The epidemiology and risk factors for postnatal complications among postpartum women and newborns in southwestern Uganda: A prospective cohort study.

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.

Geographical validation of the Smart Triage Model by age group.

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.

AI-based histopathology image analysis reveals a distinct subset of endometrial cancers.

Endometrial cancer (EC) has four molecular subtypes with strong prognostic value and therapeutic implications. The most common subtype (NSMP; No Specific Molecular Profile) is assigned after exclusion of the defining features of the other three molecular subtypes and includes patients with heterogeneous clinical outcomes. In this study, we employ artificial intelligence (AI)-powered histopathology image analysis to differentiate between p53abn and NSMP EC subtypes and consequently identify a sub-group of NSMP EC patients that has markedly inferior progression-free and disease-specific survival (termed 'p53abn-like NSMP'), in a discovery cohort of 368 patients and two independent validation cohorts of 290 and 614 from other centers.

Etiology of hospital mortality in children living in low- and middle-income countries: a systematic review and meta-analysis.

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 2024 Pediatric Sepsis Challenge: Predicting In-Hospital Mortality in Children With Suspected Sepsis in Uganda.

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.

Prediction models for post-discharge mortality among under-five children with suspected sepsis in Uganda: A multicohort analysis.

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.

Prognostic algorithms for post-discharge readmission and mortality among mother-infant dyads: an observational study protocol.

Introduction: In 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.

Facilitators and constraints to family integrated care in low-resource settings informed the adaptation in Uganda.

Aim: Family Integrated Care (FICare) was developed in high-income countries and has not been tested in resource-poor settings. We aimed to identify the facilitators and constraints that informed the adaptation of FICare to a neonatal hospital unit in Uganda.

Methods: Maternal focus groups and healthcare provider interviews were conducted at Uganda's Jinja Regional Referral Hospital in 2020.

Renal tubule-specific Atgl deletion links kidney lipid metabolism to glucagon-like peptide 1 and insulin secretion independent of renal inflammation or lipotoxicity.

Objective: Lipotoxic injury from renal lipid accumulation in obesity and type 2 diabetes (T2D) is implicated in associated kidney damage. However, models examining effects of renal ectopic lipid accumulation independent of obesity or T2D are lacking. We generated renal tubule-specific adipose triglyceride lipase knockout (RT-SAKO) mice to determine if this targeted triacylglycerol (TAG) over-storage affects glycemic control and kidney health.

Efficacy of Palivizumab Immunoprophylaxis for Reducing Severe RSV Outcomes in Children with Immunodeficiencies: A Systematic Review.

Background: Palivizumab is recommended for prevention of severe respiratory syncytial virus (RSV) disease in immunocompromised children, despite a lack of strong supporting evidence. The recent approval of substitute RSV-neutralizing monoclonal antibodies against RSV, offers an opportunity to synthesize the most current evidence supporting the palivizumab standard of care.

Objective: To evaluate the efficacy of palivizumab in preventing acute respiratory tract infection- or RSV-related hospitalization, or mortality in immunocompromised children.

International Consensus Criteria for Pediatric Sepsis and Septic Shock.

Importance: Sepsis is a leading cause of death among children worldwide. Current pediatric-specific criteria for sepsis were published in 2005 based on expert opinion. In 2016, the Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3) defined sepsis as life-threatening organ dysfunction caused by a dysregulated host response to infection, but it excluded children.

Pediatric post-discharge mortality in resource-poor countries: a systematic review and meta-analysis.

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.

Bayesian estimation in NONMEM.

Bayesian estimation is a powerful but underutilized tool for answering drug development questions. In this tutorial, the principles of Bayesian model development, assessment, and prior selection will be outlined. An example pharmacokinetic (PK) model will be used to demonstrate the implementation of Bayesian modeling using the nonlinear mixed-effects modeling software NONMEM.

World Health Organization Danger Signs to predict bacterial sepsis in young infants: A pragmatic cohort study.

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.

Planning for Hospital Discharge for Older Adults in Uganda: A Qualitative Study Among Healthcare Providers Using the COM-B Framework.

Background: Proper discharge planning enhances continuity of patient care, reduces readmissions, and ensures safe and timely transition from health facility to home-based care. The current study aimed at exploring the healthcare providers' perspectives of discharge planning among older adults, with respect to barriers and facilitators within the Ugandan health system.

Methods: We conducted a qualitative exploratory study that used one-on-one interviews (Additional file 1) to describe individual perspectives of healthcare providers in their routine clinical care setting.

Clinical decision support tools for paediatric sepsis in resource-poor settings: an international qualitative study.

Objective: New paediatric sepsis criteria are being developed by an international task force. However, it remains unknown what type of clinical decision support (CDS) tools will be most useful for dissemination of those criteria in resource-poor settings. We sought to design effective CDS tools by identifying the paediatric sepsis-related decisional needs of multidisciplinary clinicians and health system administrators in resource-poor settings.

Verbal Autopsy to Assess Postdischarge Mortality in Children With Suspected Sepsis in Uganda.

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.