Investigation of the Experimental Pharmacokinetics of the Bis-Chlorinated Bis-pyridinium Mono-aldoxime Cholinesterase Reactivator K-868 in Rats

Background: The widespread use of organophosphorus compounds in agriculture and their existence in some military arsenals present continuous threats. Quaternary bis-pyridinium aldoximes are potent, highly polar cholinesterase reactivators and the most intensively studied candidate antidotes against poisoning with organophosphorus compounds. Objective: The in vivo experimental pharmacokinetic properties of K-868, a novel bis-chlorinated, bis-pyridinium mono-aldoxime are detailed and put in context with regard to similar compounds described earlier. Methods: Rats received 30 µmol K-868 i.m. and were sacrificed at various time points following treatment. Blood, cerebrospinal fluid and tear were collected, while the brains, eyes, kidneys, livers, lungs and testes were removed, dissected and homogenized. K-868 concentrations were determined using high performance liquid chromatography with ultraviolet absorption detection. Results: K-868 was detected in the eyes, kidneys, lungs and tear within 5 minutes in maximal serum concentrations attained 15 minutes following administration. Elimination was slow for K-868 which remained detectable at 120 minutes in the blood and the kidneys, and at 60 minutes in the eyes, lungs and tear following its administration. Nevertheless, its distribution was overall poor with areas under the 120-minute concentration curves (AUC120) showing close similarity in the blood and the kidneys, while reaching just approximately 5% of serum AUC120 in the eyes and lungs. Conclusion: K-868 is a potent candidate antidote against organophosphate poisoining with a prolonged presence in the circulation.

Assessing equity and the determinants of socio-economic impacts of COVID-19: Results from a cross-sectional survey in three counties in Kenya

Background: COVID-19 mitigation measures have major ramifications on all aspects of people’s livelihoods. Based on data collected in February 2021, we present an analysis of the socio-economic impacts of COVID-19 mitigation measures in three counties in Kenya. Methods: We conducted a cross-sectional phone-based survey in three counties in Kenya to assess the level of disruption across seven domains: income, food insecurity, schooling, domestic tension/violence, communal violence, mental health, and decision-making. An overall disruption index was computed from the seven domains using principal component analysis. We used a linear regression model to examine the determinants of vulnerability to disruptions as measured by the index. We used concentration curves and indices to assess inequality in the disruption domains and the overall disruption index. Results: The level of disruption in income was the highest (74%), while the level of disruption for domestic tension/violence was the lowest (30%). Factors associated with increased vulnerability to the overall disruption index included: older age, being married, belonging in the lowest socio-economic tertile and receiving COVID-19 related assistance. The concentration curves showed that all the seven domains of disruption were disproportionately concentrated among households in the lowest socio-economic tertile, a finding that was supported by the concentration index of the overall disruption index (CI = - 0.022; p = 0.074). Conclusion: The COVID-19 mitigation measures resulted in unintended socio-economic effects that unfairly affected certain vulnerable groups such as those in the lowest socio-economic group and the elderly. Measures to protect households against the adverse socio-economic effects of the pandemic should be scaled up and targeted to the most vulnerable, with attention to the constantly evolving nature of the pandemic.

Inequalities in Knowledge About COVID-19 in the Kingdom of Saudi Arabia

Background: As the world is still being ravaged by the coronavirus disease 2019 (COVID-19) pandemic, the first line of prevention lies in understanding the causative and preventive factors of the disease. However, given varied socioeconomic circumstances, there may be some inequality in the level of proper knowledge of COVID-19. Despite a proliferation of studies on COVID-19, the extent and prevalence of inequalities in knowledge about COVID-19 in Saudi Arabia are not known. Most related studies have only focused on understanding the determinants of COVID-19 knowledge. Therefore, the aim of this study was to assess the socioeconomic inequalities in knowledge regarding COVID-19 in Saudi Arabia.Methods: Data were extracted from an online cross-sectional self-reported questionnaire conducted on the knowledge about COVID-19 from 3,388 participants. Frequencies and graphs were used to identify the level and distribution of inequality in knowledge about COVID-19. Concentration curves and concentration indices were further used to assess and quantify the income- and education-related inequality in knowledge about COVID-19.Results: The level of COVID-19 knowledge was high among the surveyed sample, although the extent of knowledge varied. The findings further suggest the existence of socioeconomic inequality in obtaining proper knowledge about COVID-19, indicating that inequality in comprehensive knowledge is disproportionately concentrated among the wealthy (concentration index = 0.016; P < 0.001) and highly educated individuals (concentration index = 0.003; P = 0.029) in Saudi Arabia.Conclusions: There is inequality in the level of knowledge about COVID-19 among the more socioeconomically privileged population of Saudi Arabia. Given that COVID-19 cases ebb and flow in different waves, it is important that proper policies be put in place that will help in improving knowledge among the lower income and less educated individuals, leading to behavior that can help reduce transmission.

Kinetic Modeling and Algorithm of Three-Component Reaction Network

The definite solutions of the differential equations from a three-component triangle reaction network have been obtained by utilizing the concept of virtual component concentration and some mathematical techniques. The kinetic model forming from the above definite solutions reveals that the overall reaction rate will be affected by the distribution entropy of the rate coefficients. The improved eigenvector method including a basic equation, algorithm, and criterion has been proposed for calculating the rate coefficients from experimental concentration curves.

Assessing equity and the determinants of socio-economic impacts of COVID-19: results from a cross-sectional survey in three counties in Kenya

Background: COVID-19 mitigation measures have major ramifications on all aspects of people’s livelihoods. Based on data collected in February 2021, we present an analysis of the socio-economic impacts of COVID-19 mitigation measures in three counties in Kenya.Methods: We conducted a cross-sectional phone-based survey in three counties in Kenya to assess the level of disruption across seven domains: income, food insecurity, schooling, domestic tension/violence, communal violence, mental health, and decision-making. An overall disruption index was computed from the seven domains using principal component analysis. We used a linear regression model to examine the determinants of vulnerability to disruptions as measured by the index. We used concentration curves and indices to assess inequality in the disruption domains and the overall disruption index.Results: The level of disruption in income was the highest (74%), while the level of disruption for domestic tension/violence was the lowest (30%). Factors associated with increased vulnerability to the overall disruption index included: older age, being married, belonging in the lowest socio-economic tertile and receiving COVID-19 related assistance. The concentration curves showed that all the seven domains of disruption were disproportionately concentrated among households in the lowest socio-economic tertile, a finding that was supported by the concentration index of the overall disruption index (CI = - 0.022; p = 0.074).Conclusion: The COVID-19 mitigation measures resulted in unintended socio-economic effects that unfairly affected certain vulnerable groups, including those in the lowest socio-economic group and the elderly. Measures to protect households against the adverse socio-economic effects of the pandemic should be scaled up and targeted to the most vulnerable, with attention to the constantly evolving nature of the pandemic.

Inequality and Inequity in the Use of Oral Health Services in Australian Adults

Objective: Social determinants drive disparities in dental visiting. This study aimed to measure inequality and inequity in dental visiting among Australian adults. Methods: Data were obtained from the National Study of Adult Oral Health (2017 to 2018). Participants were Australian adults aged ≥30 y. The outcome of interest was dental visiting in the last 12 mo. Disparity indicators included education and income. Other sociodemographic characteristics included age, gender, Indigenous status, main language, place of birth, residential location, health card and dental insurance status, and individual’s self-rated and impaired oral health. To characterize inequality in dental service use, we examined bivariate relationships using indices of inequality: the absolute and relative concentration indexes and the slope and relative indexes of inequality. Inequalities were depicted through concentration curves. Indirect standardization with a nonlinear model was used to measure inequity. Results: A total of 9,919 Australian adults were included. Bivariate analysis showed a gradient by education and income on dental visiting, with 48% of those with lowest educational attainment/income having not visited a dentist in the last 12 mo. The concentration curves showed pro–low education and pro–poor income inequalities. All measures of absolute and relative indices were negative, indicating that from the bottom to the top of the socioeconomic ladder (education and income), the prevalence of no dental visiting decreased: absolute and relative concentration index estimates were approximately 2.5% and 5.0%, while the slope and relative indexes of inequality estimates were 14% to 18% and 0.4%, respectively. After need standardization, the group with the highest education or income had almost 1.5-times less probability of not having a dental visit in the previous year than those with the lowest education or income. Conclusion: The use of oral health services exhibited socioeconomic inequalities and inequities, disproportionately burdening disadvantaged Australian adults. Knowledge Transfer Statement: The results of this study can be used by policy makers when planning a dental labor force in relation to the capacity of supply dental services to 1) reduce the inequality and inequity in the use of oral health services and 2) meet identified oral health needs across the Australian population, which is important for preventive dental care.

Use of oral health care services in the United States: unequal, inequitable—a cross-sectional study

Background Social determinants drive disparities in dental visiting. Disparities can be measured simply by comparing outcomes between groups (inequality) but can also consider concepts of social justice or fairness (inequity). This study aimed to assess differences in dental visiting in the United States in terms of both social inequality and inequity. Methods Data were obtained from a cross-sectional study—the National Health and Nutrition Examination Survey (NHANES) 2015–2016, and participants were US adults aged 30+ years. The outcome of interest, use of oral health care services, was measured in terms of dental visiting in the past 12 months. Disparity was operationalized through education and income. Other characteristics included age, gender, race/ethnicity, main language, country of birth, citizenship and oral health status. To characterize existing inequality in dental service use, we examined bivariate relationships using indices of inequality: the absolute and relative concentration index (ACI and RCI), the slope index of inequality (SII) and relative index of inequality (RII) and through concentration curves (CC). Indirect standardization with a non-linear model was used to measure inequity. Results A total of 4745 US adults were included. Bivariate analysis showed a gradient by both education and income in dental visiting, with a higher proportion (> 60%) of those with lower educational attainment /lower income having not visited a dentist. The concentration curves showed pro-higher education and income inequality. All measures of absolute and relative indices were negative, indicating that from lower to higher socioeconomic position (education and income), the prevalence of no dental visiting decreased: ACI and RCI estimates were approximately 8% and 20%, while SII and RII estimates were 50% and 30%. After need-standardization, the group with the highest educational level had nearly 2.5 times- and the highest income had near three times less probability of not having a dental visit in the past 12 months than those with the lowest education and income, respectively. Conclusion The findings indicate that use of oral health care is threatened by existing social inequalities and inequities, disproportionately burdening disadvantaged populations. Efforts to reduce both oral health inequalities and inequities must start with action in the social, economic and policy spheres.

Towards an Algorithm-Based Tailored Treatment of Acute Neonatal Hyperammonemia

Acute neonatal hyperammonemia is associated with poor neurological outcomes and high mortality. We developed, based on kinetic modeling, a user-friendly and widely applicable algorithm to tailor the treatment of acute neonatal hyperammonemia. A single compartmental model was calibrated assuming a distribution volume equal to the patient’s total body water (V), as calculated using Wells’ formula, and dialyzer clearance as derived from the measured ammonia time–concentration curves during 11 dialysis sessions in four patients (3.2 ± 0.4 kg). Based on these kinetic simulations, dialysis protocols could be derived for clinical use with different body weights, start concentrations, dialysis machines/dialyzers and dialysis settings (e.g., blood flow QB). By a single measurement of ammonia concentration at the dialyzer inlet and outlet, dialyzer clearance (K) can be calculated as K = QB∙[(Cinlet − Coutlet)/Cinlet]. The time (T) needed to decrease the ammonia concentration from a predialysis start concentration Cstart to a desired target concentration Ctarget is then equal to T = (−V/K)∙LN(Ctarget/Cstart). By implementing these formulae in a simple spreadsheet, medical staff can draw an institution-specific flowchart for patient-tailored treatment of hyperammonemia.

Trends in equity of inpatient health service utilization for the middle-aged and elderly in China: based on longitudinal data from 2011 to 2018

Background The aim of this study was to assess the trends in equity of receiving inpatient health service utilization (IHSU) in China over the period 2011–2018. Methods Longitudinal data obtained from China Health and Retirement Longitudinal Studies were used to determine trends in receiving IHSU. Concentration curves, concentration indices, and horizontal inequity indices were applied to evaluate the trends in equity of IHSU. Results This study showed that the annual rate of IHSU gradually increased from 7.99% in 2011 to 18.63% in 2018. Logistic regression shows that the rates of annual IHSU in 2018 were nearly 3 times (OR = 2.86, 95%CL: 2.57, 3.19) higher for rural respondents and 2.5 times (OR = 2.49, 95%CL: 1.99, 3.11) higher for urban respondents than the rates in 2011 after adjusting for other variables. Concentration curves both in urban and rural respondents lay above the line of equality from 2011 to 2018. The concentration index remained negative and increased significantly from − 0.0147 (95% CL: − 0.0506, 0.0211) to − 0.0676 (95% CL: − 0.0894, − 0.458), the adjusted concentration index kept the same tendency. The horizontal inequity index was positive in 2011 but became negative from 2013 to 2018, evidencing a pro-low-economic inequity trend. Conclusions We find that the inequity of IHSU for the middle-aged and elderly increased over the past 10 years, becoming more focused on the lower-economic population. Economic status, lifestyle factors were the main contributors to the pro-low-economic inequity. Health policies to allocate resources and services are needed to satisfy the needs of the middle-aged and elderly.