The burden of critical illness in hospitalized children in low- and middle-income countries: Protocol for a systematic review and meta-analysis

BACKGROUND: The 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. OBJECTIVE: To 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 STRATEGY: We 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 \u3e28 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 SELECTION: We will include observational studies published since January 1, 2005, that meet all eligibility criteria and for which a full text can be located. DATA EXTRACTION: Data extraction will include information related to study characteristics, hospital characteristics, underlying population characteristics, patient population characteristics, and outcomes. DATA SYNTHESIS: We 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. CONCLUSIONS: By 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

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 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

Surviving paediatric sepsis in Tanzania: a prospective cohort study to identify risk factors

Background: In 2015, there were 5·9 million deaths in children aged under 5 years worldwide: mortality is highest in sub-Saharan Africa (81 per 1000 livebirths) and sepsis is an important cause of these deaths. Paediatric sepsis is preventable and treatable, yet remains a serious and life-threatening condition. Prompt recognition and early treatment can improve survival; however, the understanding of how to identify and manage paediatric sepsis in sub-Saharan Africa is poor because of a lack of regional data. These data are crucial for the identification of high-risk patients, development of triage systems, and the reduction of barriers to care. In this study, we aim to identify mortality risk factors for paediatric sepsis patients at a national referral hospital in Tanzania. Methods: We conducted an exploratory analysis of prospective cohort pilot data. We included children aged between 28 days and 14 years in the emergency medicine department at Muhimbili National Hospital in Dar es Salaam with sepsis (defined as ≥2 clinical criteria for systemic inflammatory response syndrome). The primary outcome was in-hospital mortality and secondary outcomes included mortality in the emergency department and length of stay. We used t-tests and Wilcoxon rank-sum, Kruskal Wallis, χ2, and Fisher's exact tests for data analysis. Findings: Of the 2232 children screened between July 1 and September 30, 2017, 433 were eligible, 405 were enrolled, and 402 were followed to discharge or death. Median age was 25·2 months (IQR 11·4–63·5) and prevalence of malaria and HIV was 9·1% (28/307) and 1·7% (n=7), respectively. 247 (61·0%) patients were referred from outside health facilities and 116/244 (47·5%) had received antibiotics before arrival. Mortality was 14·2% (n=57): 89·5% (n=51) died on a hospital ward and 10·5% (n=6) died in the emergency department. Non-survivors were younger than survivors (median age 16 and 27 months, respectively, p=0·002), and more likely to have respiratory insufficiency (54 (94·7%) vs 293 (84·9%), p=0·046) or altered mental status (43 (75·4%) vs 171 (49·6%), p<0·001). 52 non-survivors (91·2%) were referred from another facility compared with 193 survivors (55·9%; p<0·001). Interpretation: We identified several risk factors for mortality, but only that of referral status can be modified. Most children—and a disproportionately high number of non-survivors—were assessed at other health facilities before coming to Muhimbili, suggesting that there could be an opportunity for improved sepsis identification and earlier intervention. Next steps include development of a clinical illness severity score to allow risk stratification of patients and also investigation of barriers to care. Data collection is ongoing. Funding: University of California, San Francisco, Department of Pediatrics Clinical-Translational Pilot

'Not all fevers are malaria': a mixed methods study of non-malarial fever management in rural southern Malawi.

IntroductionWith the ability to diagnose malaria with rapid diagnostic tests (mRDT), interest in improving diagnostics for non-malarial fevers has increased. Understanding how health providers diagnose and treat fevers is important for identifying additional tools to improve outcomes and reduce unnecessary antibiotic prescribing, particularly in areas where access to laboratory diagnostics is limited. This study aimed to understand rural health providers' practice patterns, both quantitatively and qualitatively, and influences on diagnostic and treatment decision-making.MethodsA mixed-methods study was conducted in Mulanje and Phalombe districts in southern Malawi. Retrospective data on diagnoses and treatments of febrile illness from seven mobile clinic logbooks were collected for a 2-month period in both the dry and wet seasons. Mobile health clinics visited remote villages in southern Malawi once every 7 days. Records from all patients with a recorded axillary temperature of 37.5ºC or higher or reported history of fever within 48 hours, and a negative mRDT, were included in the analysis. Key informant interviews were conducted with 31 mobile clinic health workers who triage, diagnose, and treat patients as well as dispense medication.ResultsIn total, 30 672 febrile patients were seen during the study period. Of those, 9924 (32%) tested negative for malaria by mRDT. Acute respiratory infection was the most common diagnosis for mRDT-negative patients (44.6%), and this number increased in the rainy season as compared to the dry season (odds ratio=2.18, 95% confidence interval=2.01-2.36). Over half (60%) of mRDT-negative patients received antibiotics as a treatment. Almost all the health providers in this study reported limited training in non-malarial fever management, despite the fact that roughly 30% of all patients with fever seen at the mobile clinics tested negative by mRDT. Without diagnostic tools beyond mRDTs, providers relied heavily on patient history to guide treatment decisions.ConclusionAdditional simple-to-use diagnostic tests as well as additional training in patient examination and clinical assessment are needed in rural settings where health providers risk over-prescribing antibiotics or missing a potentially dangerous infection in febrile patients who test negative for malaria

Diagnosis and Acute Management of COVID-19 and Multisystem Inflammatory Syndrome in Children

AbstractMost children with coronavirus disease 2019 (COVID-19) infection are asymptomatic or have mild disease. About 5% of infected children will develop severe or critical disease. Rapid identification and treatment are essential for children who are critically ill with signs and symptoms of respiratory failure, septic shock, and multisystem inflammatory syndrome in children. This article is intended for pediatricians, pediatric emergency physicians, and individuals involved in the emergency care of children. It reviews the current epidemiology of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in children, summarizes key aspects of clinical assessment including identification of high-risk patients and manifestations of severe disease, and provides an overview of COVID-19 management in the emergency department based on clinical severity

Distinct Biomarker Profiles Distinguish Malawian Children with Malarial and Non-malarial Sepsis.

Presently, it is difficult to accurately diagnose sepsis, a common cause of childhood death in sub-Saharan Africa, in malaria-endemic areas, given the clinical and pathophysiological overlap between malarial and non-malarial sepsis. Host biomarkers can distinguish sepsis from uncomplicated fever, but are often abnormal in malaria in the absence of sepsis. To identify biomarkers that predict sepsis in a malaria-endemic setting, we retrospectively analyzed data and sera from a case-control study of febrile Malawian children (aged 6-60 months) with and without malaria who presented to a community health center in Blantyre (January-August 2016). We characterized biomarkers for 29 children with uncomplicated malaria without sepsis, 25 without malaria or sepsis, 17 with malaria and sepsis, and 16 without malaria but with sepsis. Sepsis was defined using systemic inflammatory response criteria; biomarkers (interleukin-6 [IL-6], tumor necrosis factor receptor-1, interleukin-1 β [IL-1β], interleukin-10 [IL-10], von Willebrand factor antigen-2, intercellular adhesion molecule-1, and angiopoietin-2 [Ang-2]) were measured with multiplex magnetic bead assays. IL-6, IL-1β, and IL-10 were elevated, and Ang-2 was decreased in children with malaria compared with non-malarial fever. Children with non-malarial sepsis had greatly increased IL-1β compared with the other subgroups. IL-1β best predicted sepsis, with an area under the receiver operating characteristic (AUROC) of 0.71 (95% CI: 0.57-0.85); a combined biomarker-clinical characteristics model improved prediction (AUROC of 0.77, 95% CI: 0.67-0.85). We identified a distinct biomarker profile for non-malarial sepsis and developed a sepsis prediction model. Additional clinical and biological data are necessary to further explore sepsis pathophysiology in malaria-endemic regions

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 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

The Burden of Critical Illness in Hospitalized Children in Low- and Middle-Income Countries: Protocol for a Systematic Review and Meta-Analysis.

Background The 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. Objective To 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 Strategy We 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 Selection We will include observational studies published since January 1, 2005, that meet all eligibility criteria and for which a full text can be located. Data Extraction Data extraction will include information related to study characteristics, hospital characteristics, underlying population characteristics, patient population characteristics, and outcomes. Data Synthesis We 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. Conclusions By 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

The Burden of Critical Illness in Hospitalized Children in Low- and Middle-Income Countries: Protocol for a Systematic Review and Meta-Analysis

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 &gt;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