8 research outputs found

    Prognostic value of biochemical parameters among severe COVID-19 patients admitted to an intensive care unit of a tertiary hospital in South Africa

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    Background: Data on biochemical markers and their association with mortality rates in patients with severe coronavirus disease 2019 (COVID-19) admitted to intensive care units (ICUs) in sub-Saharan Africa are scarce. An evaluation of baseline routine biochemical parameters was performed in COVID-19 patients admitted to the ICU, in order to identify prognostic biomarkers. Methods: Demographic, clinical, and laboratory data were collected prospectively from patients with PCR-confirmed COVID-19 admitted to the adult ICU of a tertiary hospital in Cape Town, South Africa, between October 2020 and February 2021. Robust Poisson regression methods and the receiver operating characteristic (ROC) curve were used to explore the association of biochemical parameters with severity and mortality. Results: A total of 82 patients (median age 53.8 years, interquartile range 46.4–59.7 years) were enrolled, of whom 55 (67%) were female and 27 (33%) were male. The median duration of ICU stay was 10 days (interquartile range 5–14 days); 54/82 patients died (66% case fatality rate). Baseline lactate dehydrogenase (LDH) (adjusted relative risk 1.002, 95% confidence interval 1.0004–1.004; P = 0.016) and N-terminal pro B-type natriuretic peptide (NT-proBNP) (adjusted relative risk 1.0004, 95% confidence interval 1.0001–1.0007; P = 0.014) were both found to be independent risk factors of a poor prognosis, with optimal cut-off values of 449.5 U/l (sensitivity 100%, specificity 43%) and 551 pg/ml (sensitivity 49%, specificity 86%), respectively. Conclusions: LDH and NT-proBNP appear to be promising predictors of a poor prognosis in COVID-19 patients in the ICU. Studies with a larger sample size are required to confirm the validity of this combination of biomarkers

    Haematological predictors of poor outcome among COVID-19 patients admitted to an intensive care unit of a tertiary hospital in South Africa

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    BACKGROUND: Studies from Asia, Europe and the USA indicate that widely available haematological parameters could be used to determine the clinical severity of Coronavirus disease 2019 (COVID-19) and predict management outcome. There is limited data from Africa on their usefulness in patients admitted to Intensive Care Units (ICUs). We performed an evaluation of baseline haematological parameters as prognostic biomarkers in ICU COVID-19 patients. METHODS: Demographic, clinical and laboratory data were collected prospectively on patients with confirmed COVID-19, admitted to the adult ICU in a tertiary hospital in Cape Town, South Africa, between March 2020 and February 2021. Robust Poisson regression methods and receiver operating characteristic (ROC) curves were used to explore the association of haematological parameters with COVID-19 severity and mortality. RESULTS: A total of 490 patients (median age 54.1 years) were included, of whom 237 (48%) were female. The median duration of ICU stay was 6 days and 309/490 (63%) patients died. Raised neutrophil count and neutrophil/lymphocyte ratio (NLR) were associated with worse outcome. Independent risk factors associated with mortality were age (ARR 1.01, 95%CI 1.0–1.02; p = 0.002); female sex (ARR 1.23, 95%CI 1.05–1.42; p = 0.008) and D-dimer levels (ARR 1.01, 95%CI 1.002–1.03; p = 0.016). CONCLUSIONS: Our study showed that raised neutrophil count, NLR and D-dimer at the time of ICU admission were associated with higher mortality. Contrary to what has previously been reported, our study revealed females admitted to the ICU had a higher risk of mortality

    Is evidence-informed urban health planning a myth or reality? Lessons from a qualitative assessment in three Asian cities

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    City governments are well-positioned to effectively address urban health challenges in the context of rapid urbanization in Asia. They require good quality and timely evidence to inform their planning decisions. In this article, we report our analyses of degree of data-informed urban health planning from three Asian cities: Dhaka, Hanoi and Pokhara. Our theoretical framework stems from conceptualizations of evidence-informed policymaking, health planning and policy analysis, and includes: (1) key actors, (2) approaches to developing and implementing urban health plans, (3) characteristics of the data itself. We collected qualitative data between August 2017 and October 2018 using: in-depth interviews with key actors, document review and observations of planning events. Framework approach guided the data analysis. Health is one of competing priorities with multiple plans being produced within each city, using combinations of top-down, bottom-up and fragmented planning approaches. Mostly data from government information systems are used, which were perceived as good quality though often omits the urban poor and migrants. Key common influences on data use include constrained resources and limitations of current planning approaches, alongside data duplication and limited co-ordination within Dhaka’s pluralistic system, limited opportunities for data use in Hanoi and inadequate and incomplete data in Pokhara. City governments have the potential to act as a hub for multi-sectoral planning. Our results highlight the tensions this brings, with health receiving less attention than other sector priorities. A key emerging issue is that data on the most marginalized urban poor and migrants are largely unavailable. Feasible improvements to evidence-informed urban health planning include increasing availability and quality of data particularly on the urban poor, aligning different planning processes, introducing clearer mechanisms for data use, working within the current systemic opportunities and enhancing participation of local communities in urban health planning

    May measurement month 2018: a pragmatic global screening campaign to raise awareness of blood pressure by the International Society of Hypertension (vol 40, pg 2006, 2019)

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