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

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

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

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

Global PARITY: Study Design for a Multi-Centered, International Point Prevalence Study to Estimate the Burden of Pediatric Acute Critical Illness in Resource-Limited Settings

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

BioTIME:a database of biodiversity time series for the Anthropocene

Abstract Motivation: The BioTIME database contains raw data on species identities and abundances in ecological assemblages through time. These data enable users to calculate temporal trends in biodiversity within and amongst assemblages using a broad range of metrics. BioTIME is being developed as a community‐led open‐source database of biodiversity time series. Our goal is to accelerate and facilitate quantitative analysis of temporal patterns of biodiversity in the Anthropocene. Main types of variables included: The database contains 8,777,413 species abundance records, from assemblages consistently sampled for a minimum of 2 years, which need not necessarily be consecutive. In addition, the database contains metadata relating to sampling methodology and contextual information about each record. Spatial location and grain: BioTIME is a global database of 547,161 unique sampling locations spanning the marine, freshwater and terrestrial realms. Grain size varies across datasets from 0.0000000158 km² (158 cm²) to 100 km² (1,000,000,000,000 cm²). Time period and grain: BioTIME records span from 1874 to 2016. The minimal temporal grain across all datasets in BioTIME is a year. Major taxa and level of measurement: BioTIME includes data from 44,440 species across the plant and animal kingdoms, ranging from plants, plankton and terrestrial invertebrates to small and large vertebrates. Software format: .csv and .SQL

Comparative Studies on the Effects of Various Combined-Chemotherapy in the Experimental Tuberculosis

この論文は国立情報学研究所の学術雑誌公開支援事業により電子化されました。海の実験的前眼部結核症を対象として, 30週間にわたつてSM-PAS, INH-SI, INH-PZA, INH-PASの2者併用療法を施行し順序を交替して投与したのと, 終始一貫, SM-INH週2日-PAS毎日の3者併用療法を施行し, その効果を比較検討したことに就いては既に報告したが, 本篇においては各臓器の定量培養により検出された結核菌に就いて, SM, PAS及びINHに対する耐性検査を行なつた。其の結果2者併用療法を交替させた群では耐性の発現は軽度であつた。しかしSM-PAS&xrarr;INH-PASと言う風にPASを終始使用した例では, 主剤を交替しても比較的耐性の発現は高度であつた。3者併用(S_2I_2P毎)を行なつた群ではその中間の成績であつた。併しINHに対する耐性獲得はすべての治療群に殆んど認める事が出来なかつた