939 research outputs found
Prevalence and risk factors for Active Convulsive Epilepsy in Kintampo, Ghana
Introduction: epilepsy is common in sub-Saharan Africa, but there is little data in West Africa, to develop public health measures for epilepsy in this region.
Methods: we conducted a three-stage cross-sectional survey to determine the prevalence and risk factors for active convulsive epilepsy (ACE), and estimated the treatment gap in Kintampo situated in the middle of Ghana.
Results: 249 people with ACE were identified in a study population of 113,796 individuals. After adjusting for attrition and the sensitivity of the screening method, the prevalence of ACE was 10.1/1000 (95% Confidence Interval (95%CI) 9.5-10.7). In children aged \u3c18 years, risk factors for ACE were: family history of seizures (OR=3.31; 95%CI: 1.83-5.96), abnormal delivery (OR=2.99; 95%CI: 1.07-8.34), problems after birth (OR=3.51; 95%CI: 1.02-12.06), and exposure to Onchocerca volvulus (OR=2.32; 95%CI: 1.12-4.78). In adults, a family history of seizures (OR=1.83; 95%CI: 1.05-3.20), never attended school (OR=11.68; 95%CI: 4.80-28.40), cassava consumption (OR=3.92; 95%CI: 1.14-13.54), pork consumption (OR=1.68; 95%CI: 1.09-2.58), history of snoring at least 3 nights per week (OR=3.40: 95%CI: 1.56-7.41), exposure to Toxoplasma gondii (OR=1.99; 95%CI: 1.15-3.45) and Onchocerca volvulus (OR=2.09: 95%CI: 1.29-3.40) were significant risk factors for the development of ACE. The self-reported treatment gap was 86.9% (95%CI: 83.5%-90.3%).
Conclusion: ACE is common within the middle belt of Ghana and could be reduced with improved obstetric care and prevention of parasite infestations such as Onchocerca volvulus and Toxoplasma gondii
Exposure to parasitic infections determines features and phenotypes of active convulsive epilepsy in Africa
Background: Epilepsy affects 70 million people worldwide, 80% of whom are in low-and-middle income countries (LMICs). Infections of the central nervous system (CNS) contribute considerably to the burden of epilepsy in LMICs, but the nature and presentation of epilepsy following these infections is not fully understood. We examined if epilepsy foutcomes are associated with the exposure to parasitic infections. Methods: This was a case-comparison study nested in a cross-sectional survey of people with active convulsive epilepsy, with cases as those exposed to parasitic infections, and comparison as those unexposed. Associations of exposure to parasites with clinical and electroencephalographic features of epilepsy were done using a modified mixed effects Poisson regression model across five sites in Africa. Multiplicative and additive scale (RERI) interactions were explored to determine the effect of co-infections on epilepsy features. Population attributable fractions (PAF) were calculated to determine the proportion of severe clinical and electroencephalographic features of epilepsy attributable to CNS infections. Results: A total of 997 participants with active convulsive epilepsy from the five African sites were analyzed, 51% of whom were males. Exposure to parasitic infections was associated with more frequent seizures in adult epilepsy (relative risk (RR)=2.58, 95% confidence interval (95%CI):1.71-3.89). In children, exposure to any parasite was associated with convulsive status epilepticus (RR=4.68, (95%CI: 3.79-5.78), intellectual disabilities (RR=2.13, 95%CI: 1.35-3.34) and neurological deficits (RR=1.92, 95%CI: 1.42-2.61). Toxoplasma gondii and Onchocerca volvulus interacted synergistically to increase the risk of status epilepticus (RERI=0.91, 95%CI=0.48-1.35) in the data pooled across the sites. Exposure to parasitic infections contributed to 30% of severe features of epilepsy as shown by PAF. Conclusions: Parasitic infections may determine features and phenotypes of epilepsy through synergistic or antagonistic interactions, which can be different in children and adults. Interventions to control or manage infections may reduce complications and improve prognosis in epilepsy
Differential expression analysis with global network adjustment
<p>Background: Large-scale chromosomal deletions or other non-specific perturbations of the transcriptome can alter the expression of hundreds or thousands of genes, and it is of biological interest to understand which genes are most profoundly affected. We present a method for predicting a gene’s expression as a function of other genes thereby accounting for the effect of transcriptional regulation that confounds the identification of genes differentially expressed relative to a regulatory network. The challenge in constructing such models is that the number of possible regulator transcripts within a global network is on the order of thousands, and the number of biological samples is typically on the order of 10. Nevertheless, there are large gene expression databases that can be used to construct networks that could be helpful in modeling transcriptional regulation in smaller experiments.</p>
<p>Results: We demonstrate a type of penalized regression model that can be estimated from large gene expression databases, and then applied to smaller experiments. The ridge parameter is selected by minimizing the cross-validation error of the predictions in the independent out-sample. This tends to increase the model stability and leads to a much greater degree of parameter shrinkage, but the resulting biased estimation is mitigated by a second round of regression. Nevertheless, the proposed computationally efficient “over-shrinkage” method outperforms previously used LASSO-based techniques. In two independent datasets, we find that the median proportion of explained variability in expression is approximately 25%, and this results in a substantial increase in the signal-to-noise ratio allowing more powerful inferences on differential gene expression leading to biologically intuitive findings. We also show that a large proportion of gene dependencies are conditional on the biological state, which would be impossible with standard differential expression methods.</p>
<p>Conclusions: By adjusting for the effects of the global network on individual genes, both the sensitivity and reliability of differential expression measures are greatly improved.</p>
Electroencephalographic features of convulsive epilepsy in Africa: A multicentre study of prevalence, pattern and associated factors
Objective: We investigated the prevalence and pattern of electroencephalographic (EEG) features of epilepsy and the associated factors in Africans with active convulsive epilepsy (ACE).
Methods: We characterized electroencephalographic features and determined associated factors in a sample of people with ACE in five African sites. Mixed-effects modified Poisson regression model was used to determine factors associated with abnormal EEGs.
Results: Recordings were performed on 1426 people of whom 751 (53%) had abnormal EEGs, being an adjusted prevalence of 2.7 (95% confidence interval (95% CI), 2.5–2.9) per 1000. 52% of the abnormal EEG had focal features (75% with temporal lobe involvement). The frequency and pattern of changes differed with site. Abnormal EEGs were associated with adverse perinatal events (risk ratio (RR) = 1.19 (95% CI, 1.07–1.33)), cognitive impairments (RR = 1.50 (95% CI, 1.30–1.73)), use of anti-epileptic drugs (RR = 1.25 (95% CI, 1.05–1.49)), focal seizures (RR = 1.09 (95% CI, 1.00–1.19)) and seizure frequency (RR = 1.18 (95% CI, 1.10–1.26) for daily seizures; RR = 1.22 (95% CI, 1.10–1.35) for weekly seizures and RR = 1.15 (95% CI, 1.03–1.28) for monthly seizures)).
Conclusions: EEG abnormalities are common in Africans with epilepsy and are associated with preventable risk factors.
Significance: EEG is helpful in identifying focal epilepsy in Africa, where timing of focal aetiologies is problematic and there is a lack of neuroimaging services
Effect of preoperative thoracic duct drainage on canine kidney transplantation
Chronic drainage of the thoracic duct to the esophagus was developed in dogs, and its efficacy in immunomodulation was tested using kidney transplantation. Compared to 9.7 days in the control, the mean animal survival was prolonged to 9.9 days, 17.8 days, and 18.5 days when TDD was applied preoperatively for 3 weeks, 6 weeks, and 9 weeks, respectively. Prolongation was significant after 6 weeks. Patency of the fistula was 93.5, 80.4, and 76.1% at respective weeks. Number of peripheral T-lymphocytes determined by a new monoclonal antibody diminished after 3 weeks. All animals were in normal health, requiring no special care for fluid, electrolyte, or protein replacement
Environmental Suitability of Vibrio Infections in a Warming Climate: An Early Warning System
Background: Some Vibrio spp. are pathogenic and ubiquitous in marine waters with low to moderate salinity and thrive with elevated sea surface temperature (SST). Objectives: Our objective was to monitor and project the suitability of marine conditions for Vibrio infections under climate change scenarios. Methods: The European Centre for Disease Prevention and Control (ECDC) developed a platform (the ECDC Vibrio Map Viewer) to monitor the environmental suitability of coastal waters for Vibrio spp. using remotely sensed SST and salinity. A case-crossover study of Swedish cases was conducted to ascertain the relationship between SST and Vibrio infection through a conditional logistic regression. Climate change projections for Vibrio infections were developed for Representative Concentration Pathway (RCP) 4.5 and RCP 8.5. Results: The ECDC Vibrio Map Viewer detected environmentally suitable areas for Vibrio spp. in the Baltic Sea in July 2014 that were accompanied by a spike in cases and one death in Sweden. The estimated exposure–response relationship for Vibrio infections at a threshold of 16°C revealed a relative risk (RR)=1.14 (95% CI: 1.02, 1.27; p=0.024) for a lag of 2 wk; the estimated risk increased successively beyond this SST threshold. Climate change projections for SST under the RCP 4.5 and RCP 8.5 scenarios indicate a marked upward trend during the summer months and an increase in the relative risk of these infections in the coming decades. Conclusions: This platform can serve as an early warning system as the risk of further Vibrio infections increases in the 21st century due to climate change. https://doi.org/10.1289/EHP219
Which symptoms are linked to a delayed presentation among melanoma patients? A retrospective study
Background: The incidence of melanoma is rising. Early detection is associated with a more favourable outcome. The factors that influence the timing of a patient’s presentation for medical assessment are not fully understood. The aims of the study were to measure the nature and duration of melanoma symptoms in a group of patients diagnosed with melanoma within the preceding 18 months and to identify the symptoms and barriers associated with a delay in presentation. Methods: A questionnaire was distributed to a random sample of 200 of the 963 melanoma patients who had participated in the Cancer Patient Experience Survey 2010 and were known to be alive 1 year later. Data were collected on symptoms, duration of symptoms prior to presentation and the reasons for not attending a doctor sooner. Results: A total of 159 patients responded to the questionnaire; 74 (47%) were men; mean age was 62 (range 24–90) years. Of the 149 patients who reported a symptom, 40 (27%) had a delayed presentation (i.e. >3 months). A mole growing bigger was the most common symptom and reporting this symptom was significantly associated with a delayed presentation (odds ratio (OR) 2.04, 95% confidence interval (95% CI) 1.14–5.08). Patients aged ≥65 years were less likely to report a barrier to presentation and were less likely to delay than those under 40, although this was of borderline statistical significance (OR 0.28, 95% CI 0.08–1.00). Conclusions: This study highlights that an enlarging mole is a significant symptom influencing the timing of presentation. Increasing public awareness of the signs of melanoma and of the importance of early presentation is desirable. Health professionals should take advantage of the opportunity to educate patients on such symptoms and signs where feasible. Further exploration of the barriers to presentation in younger people should be considered
The role of art education in adult prisons: The Western Australian experience
Incarceration costs are high; in Australia, for example, each prisoner costs an average of AUD 115,000 per year. Other countries are also feeling the fiscal pinch of high incarceration costs, and a number of jurisdictions are now closing some of their prisons. Most prison costs are non-discretionary (accommodation, meals, etc.). But some of the costs relate to discretionary activities, services and facilities (including schooling). In terms of correctional education, many prison managers try to invest any meagre correctional education resources available to them in those classes and courses which have proven to have the best results, such as improved labour market outcomes and reduced recidivism, minimising subsequent re-imprisonment. Course offers for prisoner-students include vocational training, adult basic education (ABE) and art studies. The two-tiered question this paper asks is: do art classes and courses produce these measurable outcomes and, if not, are there other reasons why they should continue to be funded? Addressing these issues, the authors argue that (1) these measurable outcomes are too narrow and do not reflect the complex but less quantifiable benefits to the individual and the community of studying art in prison, and (2) better measures of all impacts of art studies in prisons are needed, including qualitative and humanitarian aspects
Development and external validation study of a melanoma risk prediction model incorporating clinically assessed naevi and solar lentigines
Background:
Melanoma risk prediction models could be useful for matching preventive interventions to patients’ risk.
Objectives:
To develop and validate a model for incident first‐primary cutaneous melanoma using clinically assessed risk factors.
Methods:
We used unconditional logistic regression with backward selection from the Australian Melanoma Family Study (461 cases and 329 controls) in which age, sex and city of recruitment were kept in each step, and we externally validated it using the Leeds Melanoma Case–Control Study (960 cases and 513 controls). Candidate predictors included clinically assessed whole‐body naevi and solar lentigines, and self‐assessed pigmentation phenotype, sun exposure, family history and history of keratinocyte cancer. We evaluated the predictive strength and discrimination of the model risk factors using odds per age‐ and sex‐adjusted SD (OPERA) and the area under curve (AUC), and calibration using the Hosmer–Lemeshow test.
Results:
The final model included the number of naevi ≥ 2 mm in diameter on the whole body, solar lentigines on the upper back (a six‐level scale), hair colour at age 18 years and personal history of keratinocyte cancer. Naevi was the strongest risk factor; the OPERA was 3·51 [95% confidence interval (CI) 2·71–4·54] in the Australian study and 2·56 (95% CI 2·23–2·95) in the Leeds study. The AUC was 0·79 (95% CI 0·76–0·83) in the Australian study and 0·73 (95% CI 0·70–0·75) in the Leeds study. The Hosmer–Lemeshow test P‐value was 0·30 in the Australian study and < 0·001 in the Leeds study.
Conclusions:
This model had good discrimination and could be used by clinicians to stratify patients by melanoma risk for the targeting of preventive interventions.
What's already known about this topic?
Melanoma risk prediction models may be useful in prevention by tailoring interventions to personalized risk levels.
For reasons of feasibility, time and cost many melanoma prediction models use self‐assessed risk factors. However, individuals tend to underestimate their naevus numbers.
What does this study add?
We present a melanoma risk prediction model, which includes clinically‐assessed whole‐body naevi and solar lentigines, and self‐assessed risk factors including pigmentation phenotype and history of keratinocyte cancer.
This model performs well on discrimination, the model's ability to distinguish between individuals with and without melanoma, and may assist clinicians to stratify patients by melanoma risk for targeted preventive interventions
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