Community referral in home management of malaria in western Uganda: A case series study

BACKGROUND: Home Based Management of fever (HBM) was introduced as a national policy in Uganda to increase access to prompt presumptive treatment of malaria. Pre-packed Chloroquine/Fansidar combination is distributed free of charge to febrile children <5 years. Persisting fever or danger signs are referred to the health centre. We assessed overall referral rate, causes of referral, referral completion and reasons for non-completion under the HBM strategy. METHODS: A case-series study was performed during 20 weeks in a West-Ugandan sub-county with an under-five population of 3,600. Community drug distributors (DDs) were visited fortnightly and recording forms collected. Referred children were located and primary caretaker interviewed in the household. Referral health facility records were studied for those stating having completed referral. RESULTS: Overall referral rate was 8% (117/1454). Fever was the main reason for mothers to seek DD care and for DDs to refer. Twenty-six of the 28 (93%) "urgent referrals" accessed referral care but 8 (31%) delayed >24 hours. Waiting for antimalarial drugs to finish caused most delays. Of 32 possible pneumonias only 16 (50%) were urgently referred; most delayed ≥ 2 days before accessing referral care. CONCLUSION: The HBM has high referral compliance and extends primary health care to the communities by maintaining linkages with formal health services. Referral non-completion was not a major issue but failure to recognise pneumonia symptoms and delays in referral care access for respiratory illnesses may pose hazards for children with acute respiratory infections. Extending HBM to also include pneumonia may increase prompt and effective care of the sick child in sub-Saharan Africa

Measurement of B(/\c->pKpi)

The /\c->pKpi yield has been measured in a sample of two-jet continuum events containing a both an anticharm tag (Dbar) as well as an antiproton (e+e- -> Dbar pbar X), with the antiproton in the hemisphere opposite the Dbar. Under the hypothesis that such selection criteria tag e+e- -> Dbar pbar (/\c) X events, the /\c->pkpi branching fraction can be determined by measuring the pkpi yield in the same hemisphere as the antiprotons in our Dbar pbar X sample. Combining our results from three independent types of anticharm tags, we obtain B(/\c->pKpi)=(5.0+/-0.5+/-1.2)

Effects of circadian disruption on physiology and pathology: from bench to clinic (and back)

Nested within the hypothalamus, the suprachiasmatic nuclei (SCN) represent a central biological clock that regulates daily and circadian (i.e., close to 24 h) rhythms in mammals. Besides the SCN, a number of peripheral oscillators throughout the body control local rhythms and are usually kept in pace by the central clock. In order to represent an adaptive value, circadian rhythms must be entrained by environmental signals or zeitgebers, the main one being the daily light?dark (LD) cycle. The SCN adopt a stable phase relationship with the LD cycle that, when challenged, results in abrupt or chronic changes in overt rhythms and, in turn, in physiological, behavioral, and metabolic variables. Changes in entrainment, both acute and chronic, may have severe consequences in human performance and pathological outcome. Indeed, animal models of desynchronization have become a useful tool to understand such changes and to evaluate potential treatments in human subjects. Here we review a number of alterations in circadian entrainment, including jet lag, social jet lag (i.e., desynchronization between body rhythms and normal time schedules), shift work, and exposure to nocturnal light, both in human subjects and in laboratory animals. Finally, we focus on the health consequences related to circadian/entrainment disorders and propose a number of approaches for the management of circadian desynchronization.Fil: Chiesa, Juan José. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Duhart, José Manuel. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Casiraghi, Leandro Pablo. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Paladino, Natalia. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Bussi, Ivana Leda. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Golombek, Diego Andrés. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin

Mapping inequalities in exclusive breastfeeding in low- and middle-income countries, 2000–2018

Exclusive breastfeeding (EBF)-giving infants only breast-milk for the first 6 months of life-is a component of optimal breastfeeding practices effective in preventing child morbidity and mortality. EBF practices are known to vary by population and comparable subnational estimates of prevalence and progress across low- and middle-income countries (LMICs) are required for planning policy and interventions. Here we present a geospatial analysis of EBF prevalence estimates from 2000 to 2018 across 94 LMICs mapped to policy-relevant administrative units (for example, districts), quantify subnational inequalities and their changes over time, and estimate probabilities of meeting the World Health Organization's Global Nutrition Target (WHO GNT) of ≥70% EBF prevalence by 2030. While six LMICs are projected to meet the WHO GNT of ≥70% EBF prevalence at a national scale, only three are predicted to meet the target in all their district-level units by 2030.This work was primarily supported by grant no. OPP1132415 from the Bill & Melinda Gates Foundation. Co-authors used by the Bill & Melinda Gates Foundation (E.G.P. and R.R.3) provided feedback on initial maps and drafts of this manuscript. L.G.A. has received support from Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Brasil (CAPES), Código de Financiamento 001 and Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) (grant nos. 404710/2018-2 and 310797/2019-5). O.O.Adetokunboh acknowledges the National Research Foundation, Department of Science and Innovation and South African Centre for Epidemiological Modelling and Analysis. M.Ausloos, A.Pana and C.H. are partially supported by a grant from the Romanian National Authority for Scientific Research and Innovation, CNDS-UEFISCDI, project no. PN-III-P4-ID-PCCF-2016-0084. P.C.B. would like to acknowledge the support of F. Alam and A. Hussain. T.W.B. was supported by the Alexander von Humboldt Foundation through the Alexander von Humboldt Professor award, funded by the German Federal Ministry of Education and Research. K.Deribe is supported by the Wellcome Trust (grant no. 201900/Z/16/Z) as part of his international intermediate fellowship. C.H. and A.Pana are partially supported by a grant of the Romanian National Authority for Scientific Research and Innovation, CNDS-UEFISCDI, project no. PN-III-P2-2.1-SOL-2020-2-0351. B.Hwang is partially supported by China Medical University (CMU109-MF-63), Taichung, Taiwan. M.Khan acknowledges Jatiya Kabi Kazi Nazrul Islam University for their support. A.M.K. acknowledges the other collaborators and the corresponding author. Y.K. was supported by the Research Management Centre, Xiamen University Malaysia (grant no. XMUMRF/2020-C6/ITM/0004). K.Krishan is supported by a DST PURSE grant and UGC Centre of Advanced Study (CAS II) awarded to the Department of Anthropology, Panjab University, Chandigarh, India. M.Kumar would like to acknowledge FIC/NIH K43 TW010716-03. I.L. is a member of the Sistema Nacional de Investigación (SNI), which is supported by the Secretaría Nacional de Ciencia, Tecnología e Innovación (SENACYT), Panamá. M.L. was supported by China Medical University, Taiwan (CMU109-N-22 and CMU109-MF-118). W.M. is currently a programme analyst in Population and Development at the United Nations Population Fund (UNFPA) Country Office in Peru, which does not necessarily endorses this study. D.E.N. acknowledges Cochrane South Africa, South African Medical Research Council. G.C.P. is supported by an NHMRC research fellowship. P.Rathi acknowledges support from Kasturba Medical College, Mangalore, Manipal Academy of Higher Education, Manipal, India. Ramu Rawat acknowledges the support of the GBD Secretariat for supporting the reviewing and collaboration of this paper. B.R. acknowledges support from Manipal College of Health Professions, Manipal Academy of Higher Education, Manipal. A.Ribeiro was supported by National Funds through FCT, under the programme of ‘Stimulus of Scientific Employment—Individual Support’ within the contract no. info:eu-repo/grantAgreement/FCT/CEEC IND 2018/CEECIND/02386/2018/CP1538/CT0001/PT. S.Sajadi acknowledges colleagues at Global Burden of Diseases and Local Burden of Disease. A.M.S. acknowledges the support from the Egyptian Fulbright Mission Program. F.S. was supported by the Shenzhen Science and Technology Program (grant no. KQTD20190929172835662). A.Sheikh is supported by Health Data Research UK. B.K.S. acknowledges Kasturba Medical College, Mangalore, Manipal Academy of Higher Education, Manipal for all the academic support. B.U. acknowledges support from Manipal Academy of Higher Education, Manipal. C.S.W. is supported by the South African Medical Research Council. Y.Z. was supported by Science and Technology Research Project of Hubei Provincial Department of Education (grant no. Q20201104) and Outstanding Young and Middle-aged Technology Innovation Team Project of Hubei Provincial Department of Education (grant no. T2020003). The funders of the study had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. The corresponding author had full access to all the data in the study and had final responsibility for the decision to submit for publication. All maps presented in this study are generated by the authors and no permissions are required to publish them

Spontaneous Breathing in Early Acute Respiratory Distress Syndrome: Insights From the Large Observational Study to UNderstand the Global Impact of Severe Acute Respiratory FailurE Study

OBJECTIVES: To describe the characteristics and outcomes of patients with acute respiratory distress syndrome with or without spontaneous breathing and to investigate whether the effects of spontaneous breathing on outcome depend on acute respiratory distress syndrome severity. DESIGN: Planned secondary analysis of a prospective, observational, multicentre cohort study. SETTING: International sample of 459 ICUs from 50 countries. PATIENTS: Patients with acute respiratory distress syndrome and at least 2 days of invasive mechanical ventilation and available data for the mode of mechanical ventilation and respiratory rate for the 2 first days. INTERVENTIONS: Analysis of patients with and without spontaneous breathing, defined by the mode of mechanical ventilation and by actual respiratory rate compared with set respiratory rate during the first 48 hours of mechanical ventilation. MEASUREMENTS AND MAIN RESULTS: Spontaneous breathing was present in 67% of patients with mild acute respiratory distress syndrome, 58% of patients with moderate acute respiratory distress syndrome, and 46% of patients with severe acute respiratory distress syndrome. Patients with spontaneous breathing were older and had lower acute respiratory distress syndrome severity, Sequential Organ Failure Assessment scores, ICU and hospital mortality, and were less likely to be diagnosed with acute respiratory distress syndrome by clinicians. In adjusted analysis, spontaneous breathing during the first 2 days was not associated with an effect on ICU or hospital mortality (33% vs 37%; odds ratio, 1.18 [0.92-1.51]; p = 0.19 and 37% vs 41%; odds ratio, 1.18 [0.93-1.50]; p = 0.196, respectively ). Spontaneous breathing was associated with increased ventilator-free days (13 [0-22] vs 8 [0-20]; p = 0.014) and shorter duration of ICU stay (11 [6-20] vs 12 [7-22]; p = 0.04). CONCLUSIONS: Spontaneous breathing is common in patients with acute respiratory distress syndrome during the first 48 hours of mechanical ventilation. Spontaneous breathing is not associated with worse outcomes and may hasten liberation from the ventilator and from ICU. Although these results support the use of spontaneous breathing in patients with acute respiratory distress syndrome independent of acute respiratory distress syndrome severity, the use of controlled ventilation indicates a bias toward use in patients with higher disease severity. In addition, because the lack of reliable data on inspiratory effort in our study, prospective studies incorporating the magnitude of inspiratory effort and adjusting for all potential severity confounders are required

Identifying associations between diabetes and acute respiratory distress syndrome in patients with acute hypoxemic respiratory failure: an analysis of the LUNG SAFE database

Background: Diabetes mellitus is a common co-existing disease in the critically ill. Diabetes mellitus may reduce the risk of acute respiratory distress syndrome (ARDS), but data from previous studies are conflicting. The objective of this study was to evaluate associations between pre-existing diabetes mellitus and ARDS in critically ill patients with acute hypoxemic respiratory failure (AHRF). Methods: An ancillary analysis of a global, multi-centre prospective observational study (LUNG SAFE) was undertaken. LUNG SAFE evaluated all patients admitted to an intensive care unit (ICU) over a 4-week period, that required mechanical ventilation and met AHRF criteria. Patients who had their AHRF fully explained by cardiac failure were excluded. Important clinical characteristics were included in a stepwise selection approach (forward and backward selection combined with a significance level of 0.05) to identify a set of independent variables associated with having ARDS at any time, developing ARDS (defined as ARDS occurring after day 2 from meeting AHRF criteria) and with hospital mortality. Furthermore, propensity score analysis was undertaken to account for the differences in baseline characteristics between patients with and without diabetes mellitus, and the association between diabetes mellitus and outcomes of interest was assessed on matched samples. Results: Of the 4107 patients with AHRF included in this study, 3022 (73.6%) patients fulfilled ARDS criteria at admission or developed ARDS during their ICU stay. Diabetes mellitus was a pre-existing co-morbidity in 913 patients (22.2% of patients with AHRF). In multivariable analysis, there was no association between diabetes mellitus and having ARDS (OR 0.93 (0.78-1.11); p = 0.39), developing ARDS late (OR 0.79 (0.54-1.15); p = 0.22), or hospital mortality in patients with ARDS (1.15 (0.93-1.42); p = 0.19). In a matched sample of patients, there was no association between diabetes mellitus and outcomes of interest. Conclusions: In a large, global observational study of patients with AHRF, no association was found between diabetes mellitus and having ARDS, developing ARDS, or outcomes from ARDS. Trial registration: NCT02010073. Registered on 12 December 2013

Epidemiology and patterns of tracheostomy practice in patients with acute respiratory distress syndrome in ICUs across 50 countries

Background: To better understand the epidemiology and patterns of tracheostomy practice for patients with acute respiratory distress syndrome (ARDS), we investigated the current usage of tracheostomy in patients with ARDS recruited into the Large Observational Study to Understand the Global Impact of Severe Acute Respiratory Failure (LUNG-SAFE) study. Methods: This is a secondary analysis of LUNG-SAFE, an international, multicenter, prospective cohort study of patients receiving invasive or noninvasive ventilation in 50 countries spanning 5 continents. The study was carried out over 4 weeks consecutively in the winter of 2014, and 459 ICUs participated. We evaluated the clinical characteristics, management and outcomes of patients that received tracheostomy, in the cohort of patients that developed ARDS on day 1-2 of acute hypoxemic respiratory failure, and in a subsequent propensity-matched cohort. Results: Of the 2377 patients with ARDS that fulfilled the inclusion criteria, 309 (13.0%) underwent tracheostomy during their ICU stay. Patients from high-income European countries (n = 198/1263) more frequently underwent tracheostomy compared to patients from non-European high-income countries (n = 63/649) or patients from middle-income countries (n = 48/465). Only 86/309 (27.8%) underwent tracheostomy on or before day 7, while the median timing of tracheostomy was 14 (Q1-Q3, 7-21) days after onset of ARDS. In the subsample matched by propensity score, ICU and hospital stay were longer in patients with tracheostomy. While patients with tracheostomy had the highest survival probability, there was no difference in 60-day or 90-day mortality in either the patient subgroup that survived for at least 5 days in ICU, or in the propensity-matched subsample. Conclusions: Most patients that receive tracheostomy do so after the first week of critical illness. Tracheostomy may prolong patient survival but does not reduce 60-day or 90-day mortality. Trial registration: ClinicalTrials.gov, NCT02010073. Registered on 12 December 2013

Global variation in diabetes diagnosis and prevalence based on fasting glucose and hemoglobin A1c

Fasting plasma glucose (FPG) and hemoglobin A1c (HbA1c) are both used to diagnose diabetes, but these measurements can identify different people as having diabetes. We used data from 117 population-based studies and quantified, in different world regions, the prevalence of diagnosed diabetes, and whether those who were previously undiagnosed and detected as having diabetes in survey screening, had elevated FPG, HbA1c or both. We developed prediction equations for estimating the probability that a person without previously diagnosed diabetes, and at a specific level of FPG, had elevated HbA1c, and vice versa. The age-standardized proportion of diabetes that was previously undiagnosed and detected in survey screening ranged from 30% in the high-income western region to 66% in south Asia. Among those with screen-detected diabetes with either test, the age-standardized proportion who had elevated levels of both FPG and HbA1c was 29–39% across regions; the remainder had discordant elevation of FPG or HbA1c. In most low- and middle-income regions, isolated elevated HbA1c was more common than isolated elevated FPG. In these regions, the use of FPG alone may delay diabetes diagnosis and underestimate diabetes prevalence. Our prediction equations help allocate finite resources for measuring HbA1c to reduce the global shortfall in diabetes diagnosis and surveillance