Access to and use of bank services in Nigeria: Micro-econometric evidence

This study examined the access to, and use of bank services in Nigeria using data from the World Bank Household Survey (2011) on financial inclusion. A framework was developed to situate the decision of individuals towards financial services in Nigeria. We examined three dependent variables – use of bank services, use of the account to save and frequency of bank withdrawals. Our results show that the attributes, income level, age and ICT inclination of individuals have an effect on the access to and use of bank services in Nigeria

Sustainable Fiscal Policies and Institutional Framework in West African Countries

A number of African countries have relied on external debt financing from multilateral institutions and 'generous' developed countries (e.g. through bilateral arrangements, etc.), with the intention of meeting their numerous financial needs. However, fiscal balances in West African countries have gradually declined in the last few years, following expansive infrastructural investment, coupled with weak institutions and poor revenue performance. This study examines the extent to which institutions affect fiscal sustainability in 15 West African countries (1996-20 12). With the aid of the Feasible Generalized Least Squares (FGLS) estimator, and using institutional indicators of government effectiveness, political stability, rule of law, regulatory quality and control of corruption, the results, among others, suggest that regulatory quality plays the most significant role in attaining sustainable fiscal policies in West Africa

Extracellular microRNAs in blood differentiate between ischaemic and haemorrhagic stroke subtypes.

Rapid identification of patients suffering from cerebral ischaemia, while excluding intracerebral haemorrhage, can assist with patient triage and expand patient access to chemical and mechanical revascularization. We sought to identify blood-based, extracellular microRNAs 15 (ex-miRNAs) derived from extracellular vesicles associated with major stroke subtypes using clinical samples from subjects with spontaneous intraparenchymal haemorrhage (IPH), aneurysmal subarachnoid haemorrhage (SAH) and ischaemic stroke due to cerebral vessel occlusion. We collected blood from patients presenting with IPH (n = 19), SAH (n = 17) and ischaemic stroke (n = 21). We isolated extracellular vesicles from plasma, extracted RNA cargo, 20 sequenced the small RNAs and performed bioinformatic analyses to identify ex-miRNA biomarkers predictive of the stroke subtypes. Sixty-seven miRNAs were significantly variant across the stroke subtypes. A subset of exmiRNAs differed between haemorrhagic and ischaemic strokes, and LASSO analysis could distinguish SAH from the other subtypes with an accuracy of 0.972 ± 0.002. Further analyses predicted 25 miRNA classifiers that stratify IPH from ischaemic stroke with an accuracy of 0.811 ± 0.004 and distinguish haemorrhagic from ischaemic stroke with an accuracy of 0.813 ± 0.003. Blood-based, ex-miRNAs have predictive value, and could be capable of distinguishing between major stroke subtypes with refinement and validation. Such a biomarker could one day aid in the triage of patients to expand the pool eligible for effective treatment

Extracellular microRNAs in blood differentiate between ischaemic and haemorrhagic stroke subtypes

Rapid identification of patients suffering from cerebral ischaemia, while excluding intracerebral haemorrhage, can assist with patient triage and expand patient access to chemical and mechanical revascularization. We sought to identify blood-based, extracellular microRNAs 15 (ex-miRNAs) derived from extracellular vesicles associated with major stroke subtypes using clinical samples from subjects with spontaneous intraparenchymal haemorrhage (IPH), aneurysmal subarachnoid haemorrhage (SAH) and ischaemic stroke due to cerebral vessel occlusion. We collected blood from patients presenting with IPH (n = 19), SAH (n = 17) and ischaemic stroke (n = 21). We isolated extracellular vesicles from plasma, extracted RNA cargo, 20 sequenced the small RNAs and performed bioinformatic analyses to identify ex-miRNA biomarkers predictive of the stroke subtypes. Sixty-seven miRNAs were significantly variant across the stroke subtypes. A subset of exmiRNAs differed between haemorrhagic and ischaemic strokes, and LASSO analysis could distinguish SAH from the other subtypes with an accuracy of 0.972 +/- 0.002. Further analyses predicted 25 miRNA classifiers that stratify IPH from ischaemic stroke with an accuracy of 0.811 +/- 0.004 and distinguish haemorrhagic from ischaemic stroke with an accuracy of 0.813 +/- 0.003. Blood-based, ex-miRNAs have predictive value, and could be capable of distinguishing between major stroke subtypes with refinement and validation. Such a biomarker could one day aid in the triage of patients to expand the pool eligible for effective treatment.Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Adaptively monitoring streamflow using a stereo computer vision system

The gauging of free surface flows in waterways provides the foundation for monitoring and managing the water resources of built and natural environments. A significant body of literature exists around the techniques and benefits of optical surface velocimetry methods to estimate flows in waterways without intrusive instruments or structures. However, to date, the operational application of these surface velocimetry methods has been limited by site configuration and inherent challenging optical variability across different natural and constructed waterway environments. This work demonstrates a significant advancement in the operationalisation of non-contact stream discharge gauging applied in the computer vision stream gauging (CVSG) system through the use of methods for remotely estimating water levels and adaptively learning discharge ratings over time. A cost-effective stereo camera-based stream gauging device (CVSG device) has been developed for streamlined site deployments and automated data collection. Evaluations between reference state-of-the-art discharge measurement technologies using DischargeLab (using surface structure image velocimetry), Hydro-STIV (using space–time image velocimetry), acoustic Doppler current profilers (ADCPs), and gauging station discharge ratings demonstrated that the optical surface velocimetry methods were capable of estimating discharge within a 5 %–15 % range between these best available measurement approaches. Furthermore, results indicated model machine learning approaches leveraging data to improve performance over a period of months at the study sites produced a marked 5 %–10 % improvement in discharge estimates, despite underlying noise in stereophotogrammetry water level or optical flow measurements. The operationalisation of optical surface velocimetry technology, such as CVSG, offers substantial advantages towards not only improving the overall density and availability of data used in stream gauging, but also providing a safe and non-contact approach for effectively measuring high-flow rates while providing an adaptive solution for gauging streams with non-stationary characteristics.</p

Management of primary hepatic malignancies during the COVID-19 pandemic: recommendations for risk mitigation from a multidisciplinary perspective

Around the world, recommendations for cancer treatment are being adapted in real time in response to the pandemic of COVID-19. We, as a multidisciplinary team, reviewed the standard management options, according to the Barcelona Clinic Liver Cancer classification system, for hepatocellular carcinoma. We propose treatment recommendations related to COVID-19 for the different stages of hepatocellular carcinoma (ie, 0, A, B, and C), specifically in relation to surgery, locoregional therapies, and systemic therapy. We suggest potential strategies to modify risk during the pandemic and aid multidisciplinary treatment decision making. We also review the multidisciplinary management of intrahepatic cholangiocarcinoma as a potentially curable and incurable diagnosis in the setting of COVID-19

SCAMP:standardised, concentrated, additional macronutrients, parenteral nutrition in very preterm infants: a phase IV randomised, controlled exploratory study of macronutrient intake, growth and other aspects of neonatal care

<p>Abstract</p> <p>Background</p> <p>Infants born <29 weeks gestation are at high risk of neurocognitive disability. Early postnatal growth failure, particularly head growth, is an important and potentially reversible risk factor for impaired neurodevelopmental outcome. Inadequate nutrition is a major factor in this postnatal growth failure, optimal protein and calorie (macronutrient) intakes are rarely achieved, especially in the first week. Infants <29 weeks are dependent on parenteral nutrition for the bulk of their nutrient needs for the first 2-3 weeks of life to allow gut adaptation to milk digestion. The prescription, formulation and administration of neonatal parenteral nutrition is critical to achieving optimal protein and calorie intake but has received little scientific evaluation. Current neonatal parenteral nutrition regimens often rely on individualised prescription to manage the labile, unpredictable biochemical and metabolic control characteristic of the early neonatal period. Individualised prescription frequently fails to translate into optimal macronutrient delivery. We have previously shown that a standardised, concentrated neonatal parenteral nutrition regimen can optimise macronutrient intake.</p> <p>Methods</p> <p>We propose a single centre, randomised controlled exploratory trial of two standardised, concentrated neonatal parenteral nutrition regimens comparing a standard macronutrient content (maximum protein 2.8 g/kg/day; lipid 2.8 g/kg/day, dextrose 10%) with a higher macronutrient content (maximum protein 3.8 g/kg/day; lipid 3.8 g/kg/day, dextrose 12%) over the first 28 days of life. 150 infants 24-28 completed weeks gestation and birthweight <1200 g will be recruited. The primary outcome will be head growth velocity in the first 28 days of life. Secondary outcomes will include a) auxological data between birth and 36 weeks corrected gestational age b) actual macronutrient intake in first 28 days c) biomarkers of biochemical and metabolic tolerance d) infection biomarkers and other intravascular line complications e) incidence of major complications of prematurity including mortality f) neurodevelopmental outcome at 2 years corrected gestational age</p> <p>Trial registration</p> <p>Current controlled trials: <a href="http://www.controlled-trials.com/ISRCTN76597892">ISRCTN76597892</a>; EudraCT Number: 2008-008899-14</p

Risk Predictors and Symptom Features of Long COVID Within a Broad Primary Care Patient Population Including Both Tested and Untested Patients

Introduction: Symptoms may persist after the initial phases of COVID-19 infection, a phenomenon termed long COVID. Current knowledge on long COVID has been mostly derived from test-confirmed and hospitalized COVID-19 patients. Data are required on the burden and predictors of long COVID in a broader patient group, which includes both tested and untested COVID-19 patients in primary care. Methods: This is an observational study using data from Platform C19, a quality improvement program-derived research database linking primary care electronic health record data (EHR) with patient-reported questionnaire information. Participating general practices invited consenting patients aged 18– 85 to complete an online questionnaire since 7th August 2020. COVID-19 self-diagnosis, clinician-diagnosis, testing, and the presence and duration of symptoms were assessed via the questionnaire. Patients were considered present with long COVID if they reported symptoms lasting ≥ 4 weeks. EHR and questionnaire data up till 22nd January 2021 were extracted for analysis. Multivariable regression analyses were conducted comparing demographics, clinical characteristics, and presence of symptoms between patients with long COVID and patients with shorter symptom duration. Results: Long COVID was present in 310/3151 (9.8%) patients with self-diagnosed, clinician-diagnosed, or test-confirmed COVID-19. Only 106/310 (34.2%) long COVID patients had test-confirmed COVID-19. Risk predictors of long COVID were age ≥ 40 years (adjusted Odds Ratio [AdjOR]=1.49 [1.05– 2.17]), female sex (adjOR=1.37 [1.02– 1.85]), frailty (adjOR=2.39 [1.29– 4.27]), visit to A&E (adjOR=4.28 [2.31– 7.78]), and hospital admission for COVID-19 symptoms (adjOR=3.22 [1.77– 5.79]). Aches and pain (adjOR=1.70 [1.21– 2.39]), appetite loss (adjOR=3.15 [1.78– 5.92]), confusion and disorientation (adjOR=2.17 [1.57– 2.99]), diarrhea (adjOR=1.4 [1.03– 1.89]), and persistent dry cough (adjOR=2.77 [1.94– 3.98]) were symptom features statistically more common in long COVID. Conclusion: This study reports the factors and symptom features predicting long COVID in a broad primary care population, including both test-confirmed and the previously missed group of COVID-19 patients