Pre-and-In-Class Practical Lesson Habits of Selected University Physical Education Students in Ghana: Implications for Health and Physical Education

Habits formed during schooling are probably the strongest that influence individuals throughout life. It is always the intention of curriculum planners that, habits formed by students as a result of schooling be positive to promote healthy lifestyle in the future. However, nothing is documented on the pre-practical physical activity habits of physical education (PE) students in universities in Ghana. The paper focused on common physical activity behaviours exhibited and the food products consumed by the students prior to and during PE practical lessons. We conveniently sampled 112 level 100-300 University of Cape Coast PE students during the 2012/2013 academic year. We developed a questionnaire to gather data for this study. We found that only 24% (n=27) of the students practice three times and over, the techniques taught in class before the next class. Also, 36% (n=40) of the students reported not using appropriate protective gears during practical classes. Beside, 35% (n=39) of the students would not do post-activity stretching without lecturers’ supervision. Of the products consumed, 9% (n=10) and 6% (n=7) take energy drinks prior to and during PE classes, respectively. Other 2% (n=2) take in alcoholic beverages before classes. However, 30% (33) consume nothing prior to morning practical lessons. Many university PE students in Ghana engage in many unhealthy habits that need attention. This paper discusses how this new knowledge can assist professionals in Health and PE to moderate the habits acquired and practiced by students while at school. Key Words: Pre-practical activity, pre-practical food consumption, physical education, physical activity habits

Cost-effectiveness of cenobamate for focal seizures in people with drug-resistant epilepsy

OBJECTIVES: To estimate the cost-effectiveness of add-on cenobamate in the UK when used to treat drug-resistant focal seizures in adults who are not adequately controlled with at least two prior antiseizure medication, including at least one used adjunctively. METHODS: We estimated the cost per quality-adjusted life-year (QALY) for cenobamate compared to brivaracetam, eslicarbazepine, lacosamide and perampanel in the UK National Health Service over a lifetime time horizon. We used a Markov cohort structure to determine response to treatment, using pooled data from three long-term studies of cenobamate. A network meta-analysis informed the likelihood of response to therapy with brivaracetam, eslicarbazepine, lacosamide and perampanel relative to cenobamate. Once individuals discontinued treatment, they transitioned to subsequent treatment health states, including other antiseizure medicines, surgery, and vagus nerve stimulation. Costs included treatment, administration, routine monitoring, event management and adverse events. Published evidence and expert opinion informed the likelihood of response to subsequent treatments, associated adverse events, and costs. Utility data was based on short-form, six dimensions utility. Discounting was applied at 3.5% per annum as per National Institute for Health and Care Excellence guidance. Uncertainty was explored through deterministic and probabilistic sensitivity analyses. RESULTS: In the base case, cenobamate led to cost savings of £51,967 (compared to brivaracetam), £21,080 (compared to eslicarbazepine), £33,619 (compared to lacosamide), and £28,296 (compared to perampanel) and increased QALYs of 1.047 (compared to brivaracetam), 0.598 (compared to eslicarbazepine), 0.776 (compared to lacosamide), and 0.703 (compared to perampanel) per individual over a lifetime time horizon. Cenobamate also dominated the four drugs across most sensitivity analyses. Differences were due to reduced seizure frequency with cenobamate relative to comparators. SIGNIFICANCE: Cenobamate improved QALYs and was less costly than brivaracetam, eslicarbazepine, lacosamide and perampanel. Therefore, cenobamate may be considered as a cost-effective adjunctive antiseizure medication for people with drug-resistant focal seizures

Comparison of genomic signatures of selection on Plasmodium falciparum between different regions of a country with high malaria endemicity.

BACKGROUND: Genome wide sequence analyses of malaria parasites from widely separated areas of the world have identified contrasting population structures and signatures of selection. To compare relatively closely situated but ecologically contrasting regions within an endemic African country, population samples of Plasmodium falciparum clinical isolates were collected in Ghana from Kintampo in the central forest-savannah area, and Navrongo in a drier savannah area ~350 km to the north with more seasonally-restricted transmission. Parasite DNA was sequenced and paired-end reads mapped to the P. falciparum reference genome. RESULTS: High coverage genome wide sequence data for 85 different clinical isolates enabled analysis of 121,712 single nucleotide polymorphisms (SNPs). The local populations had similar proportions of mixed genotype infections, similar SNP allele frequency distributions, and eleven chromosomal regions had elevated integrated haplotype scores (|iHS|) in both. A between-population Rsb metric comparing extended haplotype homozygosity indicated a stronger signal within Kintampo for one of these regions (on chromosome 14) and in Navrongo for two of these regions (on chromosomes 10 and 13). At least one gene in each of these identified regions is a potential target of locally varying selection. The candidates include genes involved in parasite development in mosquitoes, members of variant-expressed multigene families, and a leading vaccine-candidate target of immunity. CONCLUSIONS: Against a background of very similar population structure and selection signatures in the P. falciparum populations of Ghana, three narrow genomic regions showed evidence indicating local differences in historical timing or intensity of selection. Sampling of closely situated populations across heterogeneous environments has potential to refine the mapping of important loci under temporally or spatially varying selection

Detectability of Plasmodium falciparum clones

BACKGROUND: In areas of high transmission people often harbour multiple clones of Plasmodium falciparum, but even PCR-based diagnostic methods can only detect a fraction (the detectability, q) of all clones present in a host. Accurate measurements of detectability are desirable since it affects estimates of multiplicity of infection, prevalence, and frequency of breakthrough infections in clinical drug trials. Detectability can be estimated by typing repeated samples from the same host but it has been unclear what should be the time interval between the samples and how the data should be analysed. METHODS: A longitudinal molecular study was conducted in the Kassena-Nankana district in northern Ghana. From each of the 80 participants, four finger prick samples were collected over a period of 8 days, and tested for presence of different Merozoite Surface Protein (msp) 2 genotypes. Implications for estimating q were derived from these data by comparing the fit of statistical models of serial dependence and over-dispersion. RESULTS: The distribution of the frequencies of detection for msp2 genotypes was close to binomial if the time span between consecutive blood samples was at least 7 days. For shorter intervals the probabilities of detection were positively correlated, i.e. the shorter the interval between two blood collections, the more likely the diagnostic results matched for a particular genotype. Estimates of q were rather insensitive to the statistical model fitted. CONCLUSIONS: A simple algorithm based on analysing blood samples collected 7 days apart is justified for generating robust estimates of detectability. The finding of positive correlation of detection probabilities for short time intervals argues against imperfect detection being directly linked to the 48-hour periodicity of P. falciparum. The results suggest that the detectability of a given parasite clone changes over time, at an unknown rate, but fast enough to regard blood samples taken one week apart as statistically independent

Design of a phase III multicenter trial to evaluate the efficacy of the RTS,S/AS01 malaria vaccine in children across diverse transmission settings in Africa

BACKGROUND\ud \ud GlaxoSmithKline Biologicals and the PATH Malaria Vaccine Initiative are working in partnership to develop a malaria vaccine to protect infants and children living in malaria endemic regions of sub-Saharan Africa, which can be delivered through the Expanded Programme on Immunization. The RTS,S/AS candidate vaccine has been evaluated in multiple phase I/II studies and shown to have a favourable safety profile and to be well-tolerated in both adults and children. This paper details the design of the phase III multicentre efficacy trial of the RTS,S/AS01 malaria vaccine candidate, which is pivotal for licensure and policy decision-making.\ud \ud METHODS\ud \ud The phase III trial is a randomized, controlled, multicentre, participant- and observer-blind study on-going in 11 centres associated with different malaria transmission settings in seven countries in sub-Saharan Africa. A minimum of 6,000 children in each of two age categories (6-12 weeks, 5-17 months) have been enrolled. Children were randomized 1:1:1 to one of three study groups: (1) primary vaccination with RTS,S/AS01 and booster dose of RTS,S/AS01; (2) primary vaccination with RTS,S/AS01 and a control vaccine at time of booster; (3) primary vaccination with control vaccine and a control vaccine at time of booster. Primary vaccination comprises three doses at monthly intervals; the booster dose is administered at 18 months post-primary course. Subjects will be followed to study month 32. The co-primary objectives are the evaluation of efficacy over one year post-dose 3 against clinical malaria when primary immunization is delivered at: (1) 6-12 weeks of age, with co-administration of DTPwHepB/Hib antigens and OPV; (2) 5-17 months of age. Secondary objectives include evaluation of vaccine efficacy against severe malaria, anaemia, malaria hospitalization, fatal malaria, all-cause mortality and other serious illnesses including sepsis and pneumonia. Efficacy of the vaccine against clinical malaria under different transmission settings, the evolution of efficacy over time and the potential benefit of a booster will be evaluated. In addition, the effect of RTS,S/AS01 vaccination on growth, and the safety and immunogenicity in HIV-infected and malnourished children will be assessed. Safety of the primary course of immunization and the booster dose will be documented in both age categories.\ud \ud CONCLUSIONS\ud \ud This pivotal phase III study of the RTS,S/AS01 candidate malaria vaccine in African children was designed and implemented by the Clinical Trials Partnership Committee. The study will provide efficacy and safety data to fulfil regulatory requirements, together with data on a broad range of endpoints that will facilitate the evaluation of the public health impact of the vaccine and will aid policy and implementation decisions.\ud \ud TRIAL REGISTRATION\ud \ud Clinicaltrials.gov NCT00866619

PHYSICO-MECHANICAL PROPERTIES OF BAUXITE RESIDUE-CLAY BRICKS

ABSTRACT This study is focused on consolidating knowledge on the application of Bauxite residue in the building industry. X-Ray fluorescence (XRF) reports of the bauxite and bauxite residue are given. Physico-mechanical properties of red mud (RM)-Clay (AC) bricks are also presented. The RM-AC bricks have compositions; 90%-10%, 80%-20%, 70%-30%, 60%-40%, 50%-50%, 40%-60% prepared and fired at sintering temperatures 800 o C, 900 o C and 1100 o C. The experimental results obtained showed that at each of the three stated sintering temperatures, bulk density increases as apparent porosity and water of absorption reduces. Bulk densities computed were within the range (1.3-1.8)g/cm 3 at 1100 o C sintering temperature. Maximum flexural strength was found to be associated with 50%-50% (Red mud-clay) composition at 1100 o C. And the compressive strength (3.2-12.5) MPa range found for all batches at 1100 o C sintering temperature. Generally, flexural and compressive strengths were increased with higher sintering temperature. The results obtained for various characterization analysis compares well with literature and hold potential in bauxite residue eco-friendly application as fired brick

Development and validation of a diagnostic aid for convulsive epilepsy in sub-Saharan Africa: a retrospective case-control study

Background Identification of convulsive epilepsy in sub-Saharan Africa relies on access to resources that are often unavailable. Infrastructure and resource requirements can further complicate case verification. Using machine-learning techniques, we have developed and tested a region-specific questionnaire panel and predictive model to identify people who have had a convulsive seizure. These findings have been implemented into a free app for health-care workers in Kenya, Uganda, Ghana, Tanzania, and South Africa. Methods In this retrospective case-control study, we used data from the Studies of the Epidemiology of Epilepsy in Demographic Sites in Kenya, Uganda, Ghana, Tanzania, and South Africa. We randomly split these individuals using a 7:3 ratio into a training dataset and a validation dataset. We used information gain and correlation-based feature selection to identify eight binary features to predict convulsive seizures. We then assessed several machine-learning algorithms to create a multivariate prediction model. We validated the best-performing model with the internal dataset and a prospectively collected external-validation dataset. We additionally evaluated a leave-one-site-out model (LOSO), in which the model was trained on data from all sites except one that, in turn, formed the validation dataset. We used these features to develop a questionnaire-based predictive panel that we implemented into a multilingual app (the Epilepsy Diagnostic Companion) for health-care workers in each geographical region. Findings We analysed epilepsy-specific data from 4097 people, of whom 1985 (48·5%) had convulsive epilepsy, and 2112 were controls. From 170 clinical variables, we initially identified 20 candidate predictor features. Eight features were removed, six because of negligible information gain and two following review by a panel of qualified neurologists. Correlation-based feature selection identified eight variables that demonstrated predictive value; all were associated with an increased risk of an epileptic convulsion except one. The logistic regression, support vector, and naive Bayes models performed similarly, outperforming the decision-tree model. We chose the logistic regression model for its interpretability and implementability. The area under the receiver operator curve (AUC) was 0·92 (95% CI 0·91–0·94, sensitivity 85·0%, specificity 93·7%) in the internal-validation dataset and 0·95 (0·92–0·98, sensitivity 97·5%, specificity 82·4%) in the external-validation dataset. Similar results were observed for the LOSO model (AUC 0·94, 0·93–0·96, sensitivity 88·2%, specificity 95·3%). Interpretation On the basis of these findings, we developed the Epilepsy Diagnostic Companion as a predictive model and app offering a validated culture-specific and region-specific solution to confirm the diagnosis of a convulsive epileptic seizure in people with suspected epilepsy. The questionnaire panel is simple and accessible for health-care workers without specialist knowledge to administer. This tool can be iteratively updated and could lead to earlier, more accurate diagnosis of seizures and improve care for people with epilepsy. Funding The Wellcome Trust, the UK National Institute of Health Research, and the Oxford NIHR Biomedical Research Centre

Current respiratory symptoms and risk factors in pregnant women cooking with biomass fuels in rural Ghana.

BACKGROUND: More than 75% of the population in Ghana relies on biomass fuels for cooking and heating. Household air pollution (HAP) emitted from the incomplete combustion of these fuels has been associated with adverse health effects including respiratory effects in women that can lead to chronic obstructive pulmonary disease (COPD), a major contributor to global HAP-related mortality. HAP is a modifiable risk factor in the global burden of disease, exposure to which can be reduced. OBJECTIVE: This study assessed the prevalence of respiratory symptoms, as well as associations between respiratory symptoms and HAP exposure, as measured using continuous personal carbon monoxide (CO), in nonsmoking pregnant women in rural Ghana. METHODS: We analyzed current respiratory health symptoms and CO exposures upon enrollment in a subset (n = 840) of the population of pregnant women cooking with biomass fuels and enrolled in the GRAPHS randomized clinical control trial. Personal CO was measured using Lascar continuous monitors. Associations between CO concentrations as well as other sources of pollution exposures and respiratory health symptoms were estimated using logistic regression models. CONCLUSION: There was a positive association between CO exposure per 1 ppm increase and a composite respiratory symptom score of current cough (lasting >5 days), wheeze and/or dyspnea (OR: 1.2, p = 0.03). CO was also positively associated with wheeze (OR: 1.3, p = 0.05), phlegm (OR: 1.2, p = 0.08) and reported clinic visit for respiratory infection in past 4 weeks (OR: 1.2, p = 0.09). Multivariate models showed significant associations between second-hand tobacco smoke and a composite outcome (OR: 2.1, p 5 days (OR: 3.1, p = 0.01), wheeze (OR: 2.7, p < 0.01) and dyspnea (OR: 2.2, p = 0.01). Other covariates found to be significantly associated with respiratory outcomes include involvement in charcoal production business and dyspnea, and involvement in burning grass/field and wheeze. Results suggest that exposure to HAP increases the risk of adverse respiratory symptoms among pregnant women using biomass fuels for cooking in rural Ghana

Needs assessment to strengthen capacity in water and sanitation research in Africa:experiences of the African SNOWS consortium

Despite its contribution to global disease burden, diarrhoeal disease is still a relatively neglected area for research funding, especially in low-income country settings. The SNOWS consortium (Scientists Networked for Outcomes from Water and Sanitation) is funded by the Wellcome Trust under an initiative to build the necessary research skills in Africa. This paper focuses on the research training needs of the consortium as identified during the first three years of the project

Development and validation of a diagnostic aid for convulsive epilepsy in sub-Saharan Africa: a retrospective case-control study

BACKGROUND: Identification of convulsive epilepsy in sub-Saharan Africa relies on access to resources that are often unavailable. Infrastructure and resource requirements can further complicate case verification. Using machine-learning techniques, we have developed and tested a region-specific questionnaire panel and predictive model to identify people who have had a convulsive seizure. These findings have been implemented into a free app for health-care workers in Kenya, Uganda, Ghana, Tanzania, and South Africa. METHODS: In this retrospective case-control study, we used data from the Studies of the Epidemiology of Epilepsy in Demographic Sites in Kenya, Uganda, Ghana, Tanzania, and South Africa. We randomly split these individuals using a 7:3 ratio into a training dataset and a validation dataset. We used information gain and correlation-based feature selection to identify eight binary features to predict convulsive seizures. We then assessed several machine-learning algorithms to create a multivariate prediction model. We validated the best-performing model with the internal dataset and a prospectively collected external-validation dataset. We additionally evaluated a leave-one-site-out model (LOSO), in which the model was trained on data from all sites except one that, in turn, formed the validation dataset. We used these features to develop a questionnaire-based predictive panel that we implemented into a multilingual app (the Epilepsy Diagnostic Companion) for health-care workers in each geographical region. FINDINGS: We analysed epilepsy-specific data from 4097 people, of whom 1985 (48·5%) had convulsive epilepsy, and 2112 were controls. From 170 clinical variables, we initially identified 20 candidate predictor features. Eight features were removed, six because of negligible information gain and two following review by a panel of qualified neurologists. Correlation-based feature selection identified eight variables that demonstrated predictive value; all were associated with an increased risk of an epileptic convulsion except one. The logistic regression, support vector, and naive Bayes models performed similarly, outperforming the decision-tree model. We chose the logistic regression model for its interpretability and implementability. The area under the receiver operator curve (AUC) was 0·92 (95% CI 0·91-0·94, sensitivity 85·0%, specificity 93·7%) in the internal-validation dataset and 0·95 (0·92-0·98, sensitivity 97·5%, specificity 82·4%) in the external-validation dataset. Similar results were observed for the LOSO model (AUC 0·94, 0·93-0·96, sensitivity 88·2%, specificity 95·3%). INTERPRETATION: On the basis of these findings, we developed the Epilepsy Diagnostic Companion as a predictive model and app offering a validated culture-specific and region-specific solution to confirm the diagnosis of a convulsive epileptic seizure in people with suspected epilepsy. The questionnaire panel is simple and accessible for health-care workers without specialist knowledge to administer. This tool can be iteratively updated and could lead to earlier, more accurate diagnosis of seizures and improve care for people with epilepsy. FUNDING: The Wellcome Trust, the UK National Institute of Health Research, and the Oxford NIHR Biomedical Research Centre