Iron deficiency in chronic heart failure: case-based practical guidance

In patients with chronic heart failure, iron deficiency, even in the absence of anaemia, can aggravate the underlying disease and have a negative impact on clinical outcomes and quality of life. The 2016 European Society of Cardiology guidelines for the diagnosis and treatment of acute and chronic heart failure recognize iron deficiency as a co-morbidity in chronic heart failure and recommend iron status screening in all newly diagnosed patients with chronic heart failure. Furthermore, the guidelines specifically recommend considerations of intravenous iron therapy, ferric carboxymaltose, for the treatment of iron deficiency. However, in spite of these recommendations, iron deficiency remains often overlooked and undertreated. This may be due, in part, to the lack of clinical context and practical guidance accompanying the guidelines for the treating physician. Here, we provide practical guidance complemented by a case study to assist and improve the timely diagnosis, treatment, and routine management of iron deficiency in patients with chronic heart failure

Global late Quaternary megafauna extinctions linked to humans, not climate change

The late Quaternary megafauna extinction was a severe global-scale event. Two factors, climate change and modern humans, have received broad support as the primary drivers, but their absolute and relative importance remains controversial. To date, focus has been on the extinction chronology of individual or small groups of species, specific geographical regions or macroscale studies at very coarse geographical and taxonomic resolution, limiting the possibility of adequately testing the proposed hypotheses. We present, to our knowledge, the first global analysis of this extinction based on comprehensive country-level data on the geographical distribution of all large mammal species (more than or equal to 10 kg) that have gone globally or continentally extinct between the beginning of the Last Interglacial at 132 000 years BP and the late Holocene 1000 years BP, testing the relative roles played by glacial–interglacial climate change and humans. We show that the severity of extinction is strongly tied to hominin palaeobiogeography, with at most a weak, Eurasia-specific link to climate change. This first species-level macroscale analysis at relatively high geographical resolution provides strong support for modern humans as the primary driver of the worldwide megafauna losses during the late Quaternary

Improving coverage measurement for reproductive, maternal, neonatal and child health: gaps and opportunities.

BACKGROUND: Regular monitoring of coverage for reproductive, maternal, neonatal, and child health (RMNCH) is central to assessing progress toward health goals. The objectives of this review were to describe the current state of coverage measurement for RMNCH, assess the extent to which current approaches to coverage measurement cover the spectrum of RMNCH interventions, and prioritize interventions for a novel approach to coverage measurement linking household surveys with provider assessments. METHODS: We included 58 interventions along the RMNCH continuum of care for which there is evidence of effectiveness against cause-specific mortality and stillbirth. We reviewed household surveys and provider assessments used in low- and middle-income countries (LMICs) to determine whether these tools generate measures of intervention coverage, readiness, or quality. For facility-based interventions, we assessed the feasibility of linking provider assessments to household surveys to provide estimates of intervention coverage. RESULTS: Fewer than half (24 of 58) of included RMNCH interventions are measured in standard household surveys. The periconceptional, antenatal, and intrapartum periods were poorly represented. All but one of the interventions not measured in household surveys are facility-based, and 13 of these would be highly feasible to measure by linking provider assessments to household surveys. CONCLUSIONS: We found important gaps in coverage measurement for proven RMNCH interventions, particularly around the time of birth. Based on our findings, we propose three sets of actions to improve coverage measurement for RMNCH, focused on validation of coverage measures and development of new measurement approaches feasible for use at scale in LMICs

Quality of health worker and caregiver interaction during child vaccination sessions: A qualitative study from Benishangul-Gumuz region of Ethiopia

Introduction: Benishangul-Gumuz is one of nine regions in Ethiopia, located in the north-west of the country. The region has low immunization coverage, and a corresponding high risk to children from vaccine-preventable diseases. Adequate and clear communication during immunization sessions is a key factor that influences caregivers to adhere to the vaccination schedule and continue to bring children for vaccination. This study aims to explore the quality of interaction between health workers and caregivers during vaccination sessions, and to identify communication gaps that impact on the continued use of the vaccination service. Methods: This cross-sectional qualitative study was carried out using in-depth interviews with health workers who provide vaccination at health facilities, observation of the interactions between vaccinators and caregivers during vaccination sessions, and exit interviews of caregivers. Health workers who provided vaccinations in 12 health facilities based in central and remote parts of the region were interviewed. A total of 79 vaccination sessions in the 12 health facilities were observed and caregivers were interviewed on exit. Results: Health workers at the health facilities expressed that they enjoy the work they do to get children vaccinated, while caregivers who brought their children for vaccination described the vaccinators as friendly and supportive. Not all health workers explain the purpose of the immunization card to caregivers, hence caregivers do not give due attention to the importance of the card. Some caregivers forget to bring the immunization card with them to vaccination session. In some institutions, those who did not bring the immunization card were refused the service. Health workers write the date of the next vaccination on immunization cards. The majority of caregivers, however, cannot read, so do not understand the return date, type of vaccine, or the purpose of the vaccine given. Caregivers agree that their children should get all vaccines recommended by health workers. Vaccination is scheduled twice weekly at health centers and once weekly at health posts. The BCG and measles vaccination is scheduled monthly. However, when there are uncertainties regarding the availability and/or transportation of vaccines for the scheduled day, health workers do not tell caregivers when the next vaccination date will be. Health workers work with community volunteers to pass on immunization messages house to house. Conclusions: Health workers do not communicate all key immunization messages to caregivers during vaccination sessions. Training health workers in health facilities on the essentials of immunization and interpersonal communication is important to ensure the continued use of the vaccination service by caregivers. [Ethiop. J. Health Dev. 2020; 34(2):122-128] Key words: Immunization, vaccine, communication, health workers, caregivers, Ethiopi

Harmonisation of variables names prior to conducting statistical analyses with multiple datasets: an automated approach

ABSTRACT: BACKGROUND: Data requirements by governments, donors and the international community to measure health and development achievements have increased in the last decade. Datasets produced in surveys conducted in several countries and years are often combined to analyse time trends and geographical patterns of demographic and health related indicators. However, since not all datasets have the same structure, variables definitions and codes, they have to be harmonised prior to submitting them to the statistical analyses. Manually searching, renaming and recoding variables are extremely tedious and prone to errors tasks, overall when the number of datasets and variables are large. This article presents an automated approach to harmonise variables names across several datasets, which optimises the search of variables, minimises manual inputs and reduces the risk of error. RESULTS: Three consecutive algorithms are applied iteratively to search for each variable of interest for the analyses in all datasets. The first search (A) captures particular cases that could not be solved in an automated way in the search iterations; the second search (B) is run if search A produced no hits and identifies variables the labels of which contain certain key terms defined by the user. If this search produces no hits, a third one (C) is run to retrieve variables which have been identified in other surveys, as an illustration. For each variable of interest, the outputs of these engines can be (O1) a single best matching variable is found, (O2) more than one matching variable is found or (O3) not matching variables are found. Output O2 is solved by user judgement. Examples using four variables are presented showing that the searches have a 100% sensitivity and specificity after a second iteration. CONCLUSION: Efficient and tested automated algorithms should be used to support the harmonisation process needed to analyse multiple datasets. This is especially relevant when the numbers of datasets or variables to be included are larg

Precarious Work Experiences of Racialized Immigrant Woman in Toronto: A Community- Based Study

Despite their high levels of education, racialized immigrant women in Canada are over-represented in low-paid, low-skill jobs characterized by high risk and precarity. Our project documents the experiences with precarious employment of racialized immigrant women in Toronto. We conducted 30 semi-structured interviews with racialized immigrant women. Participants were recruited through posted flyers, partner agencies, peer researcher networks and snowball sampling. Interviews were transcribed and analyzed using NVivo software. The project followed a community-based participatory action research model. Participants faced powerful structural barriers to decent employment and additionally faced barriers associated with household gender relations. Their labour market experiences negatively impacted their physical and mental health as well as that of their families. These problems further constrained women’s ability to secure decent employment. Our study makes important contributions in filling the gap on the gendered barriers racialized immigrant women face in the labour market and the gendered impacts of deskilling and precarity on women and their families. We propose labour market reforms and changes in immigration and social policies to enable racialized immigrant women to overcome barriers to decent work

GPU Concurrency: Weak Behaviours and Programming Assumptions

Concurrency is pervasive and perplexing, particularly on graphics processing units (GPUs). Current specifications of languages and hardware are inconclusive; thus programmers often rely on folklore assumptions when writing software. To remedy this state of affairs, we conducted a large empirical study of the concurrent behaviour of deployed GPUs. Armed with litmus tests (i.e. short concurrent programs), we questioned the assumptions in programming guides and vendor documentation about the guarantees provided by hardware. We developed a tool to generate thousands of litmus tests and run them under stressful workloads. We observed a litany of previously elusive weak behaviours, and exposed folklore beliefs about GPU programming---often supported by official tutorials---as false. As a way forward, we propose a model of Nvidia GPU hardware, which correctly models every behaviour witnessed in our experiments. The model is a variant of SPARC Relaxed Memory Order (RMO), structured following the GPU concurrency hierarchy

Iron deficiency in chronic heart failure: case-based practical guidance

In patients with chronic heart failure, iron deficiency, even in the absence of anaemia, can aggravate the underlying disease and have a negative impact on clinical outcomes and quality of life. The 2016 European Society of Cardiology guidelines for the diagnosis and treatment of acute and chronic heart failure recognize iron deficiency as a co-morbidity in chronic heart failure and recommend iron status screening in all newly diagnosed patients with chronic heart failure. Furthermore, the guidelines specifically recommend considerations of intravenous iron therapy, ferric carboxymaltose, for the treatment of iron deficiency. However, in spite of these recommendations, iron deficiency remains often overlooked and undertreated. This may be due, in part, to the lack of clinical context and practical guidance accompanying the guidelines for the treating physician. Here, we provide practical guidance complemented by a case study to assist and improve the timely diagnosis, treatment, and routine management of iron deficiency in patients with chronic heart failure

Powerful rare variant association testing in a copula-based joint analysis of multiple phenotypes

In genetic association studies of rare variants, the low power of association tests is one of the main challenges. In this study, we propose a new single‐marker association test called C‐JAMP (Copula-based Joint Analysis of Multiple Phenotypes), which is based on a joint model of multiple phenotypes given genetic markers and other covariates. We evaluated its performance and compared its empirical type I error and power with existing univariate and multivariate single-marker and multi-marker rare-variant tests in extensive simulation studies. C-JAMP yielded unbiased genetic effect estimates and valid type I errors with an adjusted test statistic. When strongly dependent traits were jointly analyzed, C-JAMP had the highest power in all scenarios except when a high percentage of variants were causal with moderate/small effect sizes. When traits with weak or moderate dependence were analyzed, whether C-JAMP or competing approaches had higher power depended on the effect size. When C‐JAMP was applied with a misspecified copula function, it still achieved high power in some of the scenarios considered. In a real-data application, we analyzed sequencing data using C‐JAMP and performed the first genome-wide association studies of high-molecular-weight and medium-molecular-weight adiponectin plasma concentrations. C-JAMP identified 20 rare variants with p-values smaller than 10(−5), while all other tests resulted in the identification of fewer variants with higher p-values. In summary, the results indicate that C-JAMP is a powerful, flexible, and robust method for association studies, and we identified novel candidate markers for adiponectin. C‐JAMP is implemented as an R package and freely available from https://cran.r-project.org/package=CJAMP