Inform Decisions Research Articles

Comparing Pharmacotherapies for ADHD in Adults: Evidence From Outcome-Focused Analysis of Food and Drug Administration Drug Label Registration Trials

Objective: We appraised whether FDA registration trials for ADHD pharmacotherapy in adults provides comparable information to inform treatment expectations. Method: Comparison of ADHD outcome measure patterns in ADHD pharmacotherapy FDA drug label source studies. Results: Among stimulants, from fixed-dose titration data, amphetamine agents had numerically higher placebo-corrected symptom improvement and symptom effect sizes than methylphenidate agents. Symptom effect sizes were lower in the flexible dosing registration studies of atomoxetine and viloxazine. Varying responder definitions were analyzable, based on ≥30% symptom improvement and/or CGI-I improvement of “much” or “very much improved.” Number of exposures needed to create these responses were lower for stimulants than for viloxazine. Conclusion: Heterogeneity in the design and analysis of FDA drug label source trials restricts implications for clinical practice. Research conducted using replicated designs, direct comparison of available treatments, and outcome analyses that generalize to clinical care could better inform clinical decision making.

Mapping of health technology assessment in China: a comparative study between 2016 and 2021

BackgroundHealth Technology Assessment (HTA) in China has recently expanded from purely academic research to include policy or decision-oriented practice, especially after HTA evidence was used to update the National Reimbursement Drug List for the first time in 2017. This study aims to identify the progress and challenges of HTA development from 2016 to 2021 and inform policies and decisions to promote further HTA development in China.MethodsWe conducted a cross-sectional web-based survey with policy makers, researchers and industry-providers in China in 2016 and 2021 respectively. The ‘Mapping of HTA Instrument’, was utilized to assess the HTA development across eight domains: Institutionalization, Identification, Priority setting, Assessment, Appraisal, Reporting, Dissemination of findings and conclusions, and Implementation in policy and practice. To reduce the influence of confounders and compare the mapping outcomes between the 2016 and 2021 groups, we conducted 1:1 Propensity Score Matching (PSM). Univariate analysis was conducted to compare the differences between the two groups. The overall results were further compared with those of a mapping study that included ten countries.ResultsIn total, 212 and 255 respondents completed the survey in 2016 and 2021, respectively. The total score of the HTA development level in China in 2021 was higher than that in 2016 before PSM (89.38 versus 83.96). Following PSM, 183 respondents from the 2016 and 2021 groups were matched. Overall, the mean scores for most indicators in the Institutionalization domain and Dissemination domain in 2021 were higher than those in 2016 (P < 0.05). The Appraisal domain in 2021 was more explicit, transparent and replicable than that in 2016 (t = −3.279, P < 0.05). However, the mean scores of most indicators in the Assessment domain were higher in 2016 than those in 2021 (P < 0.05).ConclusionsOur study suggest that the level of HTA development in China progressed significantly from 2016 to 2021. However, before engaging in HTA activities, further efforts are required to enhance the assessment process. For instance, it is important to establish a clear goal and scope for HTA; adapt standardized methodologies for evaluating the performance of systematic reviews or meta-analyses; and provide comprehensive descriptions of the safety, clinical effectiveness, cost, and cost-effectiveness of the assessed technologies, thus improving the development of HTA in China.

Adapting COVID-19 research infrastructure to capture influenza and respiratory syncytial virus alongside SARS-CoV-2 in UK healthcare workers winter 2022/23 and beyond: protocol for a pragmatic sub-study

Introduction During the COVID-19 pandemic, extensive research was conducted on SARS-CoV-2; however, important questions about other respiratory pathogens remain unanswered. A severe influenza season in 2022–2023 with simultaneous circulation of SARS-CoV2 and respiratory syncytial virus is anticipated. This sub-study aims to determine the incidence and impact of these respiratory viruses on healthcare workers, the symptoms they experienced, the effectiveness of both COVID-19 and influenza vaccination and the burden of these infections on the National Health Service (NHS) workforce. Methods and analysis This is a longitudinal prospective cohort sub-study, utilising the population and infrastructure of the SARS-CoV-2 Immunity &amp; Reinfection Evaluation (SIREN) study, which focuses on hospital staff in the UK. Participants undergo fortnightly nucleic acid amplification testing on a multiplex assay including SARS-CoV-2, influenza A and B and RSV, regardless of symptoms. Questionnaires are completed every two weeks, capturing symptoms, sick days, exposures, and vaccination records. Serum samples are collected monthly or quarterly from participants associated with a SIREN site. This sub-study commenced on 28/11/22 to align with the predicted influenza season and participants’ influenza vaccine status. The SIREN Participant Involvement Panel shaped the aims and methods for the study, highlighting its acceptability. UK devolved administrations were supported to develop local protocols. Analysis plans include incidence of asymptomatic and symptomatic infection, comparisons of vaccination coverage, assessment of sick day burden, and effectiveness of seasonal influenza against infection and time off work. Data are also integrated into UKHSA nosocomial modelling. Ethics and dissemination The protocol was approved by the Berkshire Research Ethics Committee (IRAS ID 284460, REC Reference 20SC0230) on 14/11/2022. Participants were informed in advance. As the frequency and method of sampling remained the same, implied consent processes were approved by the committee. Participants returning to the study give informed consent. Regular reports to advisory groups and peer-reviewed publications are planned to disseminate findings and inform decision making. Clinical trial registration number: ISRCTN11041050; registration date: 12 January 2021. Sub study included in protocol version: v8.0, and amended in v9.0

Time use and dimensions of healthy sleep: A cross-sectional study of Australian children and adults

BackgroundSleep is increasingly recognized as a multidimensional construct that occurs within the 24-hour day. Despite advances in our understanding, studies continue to consider the relationship between sleep, sedentary time and physical activity separately, and not as part of the 24-hour day. AimsTo determine the association between the 24-hour activity composition and dimensions of healthy sleep. MethodsThis study examined data on 1168 children (mean age 12years; 49% female) and 1360 adults (mean age 44years; 87% female) collected as part of the Child Health CheckPoint study. Participants were asked to wear a GENEActiv monitor (Activinsights, Cambs, UK) on their nondominant wrist for eight consecutive days to measure 24-hour time-use. Compositional data analysis was used to examine the association between time use (actigraphy-derived sleep duration, sedentary time, light physical activity and moderate-vigorous physical activity) and dimensions of healthy sleep. Healthy sleep was conceptualized in terms of continuity/efficiency, timing, alertness/sleepiness, satisfaction/quality, and regularity. Time allocations were also examined. ResultsThe 24-hour activity composition was significantly associated with all objectively measured and self-report dimensions of healthy sleep in both children and adults. Allocating more time to sleep was associated with earlier sleep onsets, later sleep offsets, less efficient and more consistent sleep patterns for both children and adults. ConclusionThis study highlights the integral relationship between daily activities and dimensions of sleep. Considering sleep within the 24-hour day activity composition framework may help inform lifestyle decisions to improve sleep health.

Risk from future climate change to Pakistan's protected area network: A composite analysis for hotspot identification

As climate change becomes a primary driver of global ecosystem deterioration and biodiversity loss, protected areas (PAs) are posed to play a crucial conservation role. At a global scale, 17 % of land is currently covered by PAs; a figure expected to reach 30 % by 2030 under the UN post-2020 global biodiversity framework. However, focusing only on the percent coverage of PAs without assessing their efficacy may not accomplish the intended conservation goals. Here, we present the first assessment of the risk from climate change to existing PAs and non-protected lands across Pakistan by combining data on the local exposure and vulnerability of 409 species of birds, mammals, reptiles and amphibians to multidimensional changes in climate by mid (2040–2060) and late (2061–2080) century under two climate emission scenarios (RCP4.5 and RCP8.5). We find that between 7 % (2050 RCP4.5) and 19 % (2080 RCP8.5) of the current network of PAs, mostly located in the eastern and southeastern parts of the country, are projected to be under future extreme risk (i.e., highly exposed areas containing highly vulnerable communities). Importantly, hotspots of risk within these PAs are projected to significantly expand over time and with increasing severity of the scenario. In contrast, PAs in the northern part of the country are projected to remain under moderate to low risk. Results are subject to variability across the country reflecting interesting differences in climate change exposure and species vulnerability between protected and non-protected lands. Importantly, significantly lower level of risks from future climate change are projected for PAs than non-protected lands across emission scenarios and periods suggesting potential candidate areas for the future expansion of the country's PA network. Our analysis provides novel insights that can help inform conservation decisions and management at a time when the country is investing in ambitious efforts to expand its network of protected areas.

Hernia Support Garments for Parastomal Hernia Following Ostomy Procedure

What Is the Issue?&#x0D; &#x0D; Parastomal hernia is a common complication that can occur following ostomy surgery. They can have a negative impact on a person’s quality of life, affecting them both physically and psychologically. One intervention that may be used to help prevent or manage parastomal hernias are hernia support garments.&#x0D; To help inform decisions about the most appropriate use for hernia support garments, it is important to understand the current best practices as well as potential benefits and harms of using these garments.&#x0D; &#x0D; What Did We Do?&#x0D; &#x0D; We searched for clinical and cost-effectiveness literature comparing hernia support garments to alternative hernia prevention or management strategies or no intervention. We also searched for evidence-based guidelines that provide recommendations about the use of hernia support garments for the prevention or management of parastomal hernias.&#x0D; An information specialist searched for peer-reviewed and grey literature sources published between January 1, 2013, and November 1, 2023.&#x0D; We engaged with an individual who has lived experience of an ostomy and parastomal hernia and who wears a hernia belt regularly. He shared his thoughts on the physical and psychological benefits, impact on quality of life, and challenges of using a hernia belt. This gave CADTH a more nuanced understanding of the literature.&#x0D; &#x0D; What Did We Find?&#x0D; &#x0D; We did not find any studies directly evaluating the clinical or cost-effectiveness of hernia support garments versus alternative hernia prevention or management interventions or no treatment that met the inclusion criteria for this review.&#x0D; Three evidence-based guidelines made recommendations related to using hernia support garments to prevent and manage parastomal hernia. One guideline recommends that individuals with an ostomy should be assessed to determine the type and level of support required to prevent or manage hernia. Another guideline recommends that health providers provide postoperative education on using support garments. The third guideline recommends that stoma care nurses provide lifestyle advice about support garments to individuals with a stoma. This guideline also recommends that these nurses should be available to advise on non-operative management options for parastomal hernias more generally.&#x0D; &#x0D; What Does This Mean?&#x0D; &#x0D; Decision-makers might wish to consider ways to ensure that individuals who have had or are scheduled to have an ostomy surgery have timely access to parastomal hernia risk assessment, education, and advice on the use of hernia support garments from nurses specialized in wound, ostomy, and continence care. They may also want to consider out-of-pocket costs that may be a barrier to this care.&#x0D;

IMPLICATIONS OF NEURAL NETWORK AS A DECISION-MAKING TOOL IN MANAGING KAZAKHSTAN’S AGRICULTURAL ECONOMY

This study investigates the application of Artificial Neural Networks (ANN) in forecasting agricultural yields in Kazakhstan, highlighting its implications for economic management and policy-making. Utilizing data from the Bureau of National Statistics of the Republic of Kazakhstan (2000-2023), the research develops two ANN models using the Neural Net Fitting library in MATLAB. The first model predicts the total gross yield of main agricultural crops, while the second forecasts the share of individual crops, including cereals, oilseeds, potatoes, vegetables, melons, and sugar beets. The models demonstrate high accuracy, with the total gross yield model achieving an R-squared value of 0.98 and the individual crop model showing an R value of 0.99375. These results indicate a strong predictive capability, essential for practical agricultural and economic planning. The study extends previous research by incorporating a comprehensive range of climatic and agrochemical data, enhancing the precision of yield predictions. The findings have significant implications for Kazakhstan's economy. Accurate yield predictions can optimize agricultural planning, contribute to food security, and inform policy decisions. The successful application of ANN models showcases the potential of AI and machine learning in agriculture, suggesting a pathway towards more efficient, sustainable farming practices and improved quality management systems.

Interpreting and integrating genomic tests results in clinical cancer care: Overview and practical guidance.

The last decade has seen rapid progress in the use of genomic tests, including gene panels, whole-exome sequencing, and whole-genome sequencing, in research and clinical cancer care. These advances have created expansive opportunities to characterize the molecular attributes of cancer, revealing a subset of cancer-associated aberrations called driver mutations. The identification of these driver mutations can unearth vulnerabilities of cancer cells to targeted therapeutics, which has led to the development and approval of novel diagnostics and personalized interventions in various malignancies. The applications of this modern approach, often referred to as precision oncology or precision cancer medicine, are already becoming a staple in cancer care and will expand exponentially over the coming years. Although genomic tests can lead to better outcomes by informing cancer risk, prognosis, and therapeutic selection, they remain underutilized in routine cancer care. A contributing factor is a lack of understanding of their clinical utility and the difficulty of results interpretation by the broad oncology community. Practical guidelines on how to interpret and integrate genomic information in the clinical setting, addressed to clinicians without expertise in cancer genomics, are currently limited. Building upon the genomic foundations of cancer and the concept of precision oncology, the authors have developed practical guidance to aid the interpretation of genomic test results that help inform clinical decision making for patients with cancer. They also discuss the challenges that prevent the wider implementation of precision oncology.

Public perception of coastal eco-engineering interventions in Singapore

The successful implementation of coastal eco-engineering strategies, such as retrofitting biodiversity enhancement units onto seawalls, requires scientific, economic, and social inputs. It is important to involve various agencies and local communities to gauge the level of public support, especially when local coastal areas function as public amenities. Social surveys are an essential tool in collecting empirical data that can help inform decisions regarding location, visibility, and potential interactivity with eco-engineered solutions. To assess public perceptions of coastal eco-engineering interventions on publicly accessible shorelines in Singapore, we disseminated questionnaires both online and face-to-face in various residential and coastal areas. The majority of the 536 respondents supported eco-engineering efforts and were keen to see local seawall enhancement designs installed at visible and accessible areas of the coastline. Respondents also showed interest in interacting with these enhancements if appropriate management protocols are established. We found no evidence that having prior knowledge of the environment or interest in nature-based activities affected their opinions. Collectively, our findings indicate strong public support for coastal habitat enhancements in Singapore. We present an overview of the general public’s perception on local marine ecosystem function and services, and when informed, how their opinions can provide a supportive space for local eco-engineering projects. This paper also provides useful data, such as movement of the public to accessible shorelines and understanding what the public want from usable nature spaces, to support future coastal management decisions. We hope to highlight from this study the importance of including the local public in management decisions so that these projects can have the greatest chance for success.

Long-term surveillance of invasive pneumococcal disease: The impact of 10-valent pneumococcal conjugate vaccine in the metropolitan region of Salvador, Brazil

BackgroundIn 2010, Brazil introduced the ten-valent pneumococcal conjugate vaccine (PCV10) in the national infant immunization program. Limited data on the long-term impact of PCV10 are available from lower-middle-income settings. We examined invasive pneumococcal disease (IPD) in Salvador, Bahia, over 11 years. MethodsProspective laboratory-based surveillance for IPD was carried out in 9 hospitals in the metropolitan region of Salvador from 2008 to 2018. IPD was defined as Streptococcus pneumoniae cultured from a normally sterile site. Serotype was determined by multiplex polymerase chain reaction and/or Quellung reaction. Incidence rates per 100,000 inhabitants were calculated for overall, vaccine-type, and non-vaccine-type IPD using census data as the denominator. Incidence rate ratios (IRRs) were calculated to compare rates during the early (2010–2012), intermediate (2013–2015), and late (2016–2018) post-PCV10 periods in comparison to the pre-PCV10 period (2008–2009). ResultsPre-PCV10, overall IPD incidence among all ages was 2.48/100,000. After PCV10 introduction, incidence initially increased (early post-PCV10 IRR 3.80, 95% CI 1.18–1.99) and then declined to 0.38/100,000 late post-PCV10 (IRR 0.15; 95% CI 0.09–0.26). The greatest reductions in the late post-PCV10 period were observed in children aged ≤2 years, with no cases (IRR not calculated) and those ≥60 years (IRR 0.11, 95% CI 0.03–0.48). Late post-PCV10, significant reductions were observed for both PCV10 serotypes (IRR 0.02; 95% CI 0.0–0.15) and non-PCV10 serotypes (IRR 0.27; 95%CI 0.14–0.53). Non-PCV10 serotypes 15B, 12F, 3, 17F, and 19A became predominant late post-PCV10 without a significant increase in serotype-specific IPD incidence compared to pre-PCV10. ConclusionSignificant declines in IPD, including among adults not eligible for vaccination, suggest direct and indirect protection up to nine years after PCV10 introduction, without evidence of significant replacement disease. Continued surveillance is needed to monitor changes in non-vaccine serotypes and inform decisions about introducing higher valent PCVs.

Anti-S Antibodies Against SARS-CoV-2 Infection Among Four Types of Vaccines in Malaysia.

Monitoring SARS-CoV-2 antibody levels can provide insights into a person's immunity to COVID-19 and inform decisions about vaccination and public health measures. Anti-S may be useful as an indicator of an effective immune response. Thus, we conducted this study that aimed to determine the immune response of anti-S antibodies against SARS-CoV-2 for all the vaccine types over time among adult recipients in Malaysia and to determine the associated factors. This study was a cohort that recruited 2513 respondents aged 18 years and above from June to December 2021. Each participant was followed-up for 1-year period from the initial vaccine dose (baseline). We found that the anti-S antibody generally increased for all vaccine types and peaked at two weeks after the second dose vaccination, with Pfizer recipients having the highest median of 100 (100.00-100.00). During the third-month follow-up, the seropositivity of anti-S antibody and the median level decreased for all vaccines. We found that type of vaccines, comorbid status, infection, and booster status were significantly associated with the anti-S antibody level after one year.

Empirical Analysis of the Automation-Augmented Solow Growth Model and Income Differences in the South Korean Economy

The integration of automation into production processes is emerging as a transformative force, impacting economic growth, labor market structures, and broader economic landscapes. Prettner's automation-augmented Solow Growth Model provides a novel theoretical framework for analyzing the role of automation capital in economic production, offering insights into its effects on both economic growth and income disparities between workers and business owners. This study investigates the impact of automation on economic growth and income inequality in South Korea, applying Prettner’s automation-augmented Solow Growth Model. By incorporating automation capital into the production function, this model helps elucidate the broader economic implications of automation. South Korea, with its advanced manufacturing sector and rapid technological adoption, serves as an ideal case for examining these dynamics. Using time series data from 2011 to 2019 and the Ordinary Least Squares (OLS) method, our analysis reveals a positive correlation between automation capital and economic growth, highlighting automation's role in driving South Korea’s economic progress. While the link between automation and income inequality is less clear, the study suggests that automation has the potential to significantly influence economic structures in South Korea. This emphasizes the need for further research to fully understand these relationships and inform policy decisions.

Adult refugees' perspectives on the impact of trauma and post-migration hardships on learning.

Background: Research shows that adult refugees' well-being and future in the reception country heavily depend on successfully learning the host language. However, we know little about how adult learners from refugee backgrounds experience the impact of trauma and adversity on their learning.Objective: The current study aims to investigate the perspectives of adult refugee learners on whether and how trauma and other adversity affect their learning.Methods: We conducted in-depth interviews with 22 adult refugees (10 women) attending the Norwegian Introduction Programme (NIP). The participants came from six Middle Eastern, Central Asian, and African countries. Two questionnaires were included, one about past stressful life events (SLESQ-Revised), and one about mental health symptoms and current psychological distress following potentially traumatic experiences (PCL-5).Results: Participants held varying beliefs about trauma's impact on learning: that it had a constant impact, that it was situational, or that it had no impact. Other aspects they brought up as having an essential effect on learning and school attendance include psychological burdens from past and present school experiences, and post-migration hardships such as loneliness, depression, ongoing violence, and negative social control. Post-migration trauma and hardships exacerbated the burden of previous trauma and were frequently associated with a greater negative influence on learning.Conclusion: This study adds new insights from adult refugee learners themselves into how post-migration hardships as well as trauma can impact their learning, and the importance of recognising their struggles. A safe space is required for refugees to open up about their difficulties in life and with learning. This knowledge can be used to enhance teaching practices, foster better teacher-student relationships, and inform policy-making decisions, ultimately benefiting both individuals and society.

Prevalence of Avian Influenza Virus in Atypical Wild Birds Host Groups during an Outbreak of Highly Pathogenic Strain EA/AM H5N1

The global outbreak of highly pathogenic avian influenza (HPAI) H5N1 Eurasian lineage goose/Guangdong clade 2.3.4.4b virus that was detected in North America in 2021 is the largest in history and has significantly impacted wild bird populations and domestic poultry across the continent. Synanthropic birds may play an important role in transmitting the virus laterally to other wild bird species and domestic poultry. Understanding the dynamics of HPAI in atypical, or nonreservoir, wild bird hosts may help inform management decisions and potential risk factors to both wild and domestic bird populations. Following the confirmation of infections of HPAI H5N1 in domestic poultry at two commercial premises in Indiana, United States, we sampled and tested 266 Columbiformes and Passeriformes birds and found no detections of the virus at either location. We further queried laboratories within the National Animal Health Laboratory Network for avian influenza (AI) virus diagnostic test results for wild birds submitted from morbidity/mortality events, for a total of 9,368 birds tested across eight orders and 1,543 avian influenza virus detections between February 2022 and March 2023. Query results were assessed for viral prevalence by taxonomic group and suggested that the virus most often was observed in predatory and scavenging birds. The highest prevalence was observed in raptors (0.2514), with prevalence rates in exclusively scavenging Cathartidae reaching up to 0.5333. There is evidence that the consumption of infected tissues is a key pathway for transmission of AI viruses in predatory and scavenging birds. Although detections were found in nonpredatory synanthropic birds, including orders Columbiformes and Passeriformes, the risk of transmission from and between these groups appears comparatively low. Understanding the dynamics of AI viruses in synanthropic bird orders during the global HPAI H5N1 outbreak in wild bird populations can provide pertinent information on viral transmission, disease ecology, and risk to humans and agriculture.

Relationships among return and liquidity of cryptocurrencies

The cryptocurrency market is a complex and rapidly evolving financial landscape in which understanding the inter- and intra-asset dependencies among key financial variables, such as return and liquidity, is crucial. In this study, we analyze daily return and liquidity data for six major cryptocurrencies, namely Bitcoin, Ethereum, Ripple, Binance Coin, Litecoin, and Dogecoin, spanning the period from June 3, 2020, to November 30, 2022. Liquidity is estimated using three low-frequency proxies: the Amihud ratio and the Abdi and Ranaldo (AR) and Corwin and Schultz (CS) estimators. To account for autoregressive and persistent effects, we apply the autoregressive integrated moving average-generalized autoregressive conditional heteroscedasticity (ARIMA-GARCH) model and subsequently utilize the copula method to examine the interdependent relationships between the return on and liquidity of the six cryptocurrencies. Our analysis reveals strong cross-asset lower-tail dependence in return and significant cross-asset upper-tail dependence in illiquidity measures, with more pronounced dependence observed in specific cryptocurrency pairs, primarily involving Bitcoin, Ethereum, and Litecoin. We also observe that returns tend to be higher when liquidity is lower in the cryptocurrency market. Our findings have significant implications for portfolio diversification, asset allocation, risk management, and trading strategy development for investors and traders, as well as regulatory policy-making for regulators. This study contributes to a deeper understanding of the cryptocurrency marketplace and can help inform investment decision making and regulatory policies in this emerging financial domain.

An Application of the First-Order Linear Ordinary Differential Equation to Regression Modeling of Unemployment Rates

The unemployment rate investigates the relationship between labor market outcomes and poverty, evaluates the effect of labor market policies and programs, and provides ways to improve their performance. This study analyzes data-driven regression modeling for the economy, specifically the first-order linear ordinary differential equation (ODE). Consider a collection of actual data for the Ilocos Region's unemployment rate and calculate the numerical derivative. Then, a general equation for the first-order linear ODE is presented, with two parameters that will be determined using regression modeling. Following that, a loss function is defined as the sum of squared errors to reduce the difference between estimated and real data in the presence of fluctuations. After this, a loss function is defined as the sum of squared errors to minimize the differences between estimated and actual data. A set of necessary conditions is derived, and the regression parameters are analytically determined. Based on these optimal parameter estimates, the solution of the first-order linear ODE, which matches the actual data trend, shall be obtained. The observations show that the relationship between the actual data and the adjusted predicted regression dynamics closely matches. Results also indicate that the new insight includes the analysis of fluctuations in the unemployment rate for regression modeling dynamics. This research helps Filipino economists provide insights and inform policy decisions aimed at the labor market, and they can focus their efforts on improving these indicators to stimulate job creation and reduce unemployment.

Podocyte number and glomerulosclerosis indices are associated with the response to therapy for primary focal segmental glomerulosclerosis.

Corticosteroid therapy, often in combination with inhibition of the renin-angiotensin system, is first-line therapy for primary focal and segmental glomerulosclerosis (FSGS) with nephrotic-range proteinuria. However, the response to treatment is variable, and therefore new approaches to indicate the response to therapy are required. Podocyte depletion is a hallmark of early FSGS, and here we investigated whether podocyte number, density and/or size in diagnostic biopsies and/or the degree of glomerulosclerosis could indicate the clinical response to first-line therapy. In this retrospective single center cohort study, 19 participants (13 responders, 6 non-responders) were included. Biopsies obtained at diagnosis were prepared for analysis of podocyte number, density and size using design-based stereology. Renal function and proteinuria were assessed 6 months after therapy commenced. Responders and non-responders had similar levels of proteinuria at the time of biopsy and similar kidney function. Patients who did not respond to treatment at 6 months had a significantly higher percentage of glomeruli with global sclerosis than responders (p < 0.05) and glomerulosclerotic index (p < 0.05). Podocyte number per glomerulus in responders was 279 (203-507; median, IQR), 50% greater than that of non-responders (186, 118-310; p < 0.05). These findings suggest that primary FSGS patients with higher podocyte number per glomerulus and less advanced glomerulosclerosis are more likely to respond to first-line therapy at 6 months. A podocyte number less than approximately 216 per glomerulus, a GSI greater than 1 and percentage global sclerosis greater than approximately 20% are associated with a lack of response to therapy. Larger, prospective studies are warranted to confirm whether these parameters may help inform therapeutic decision making at the time of diagnosis of primary FSGS.

Genetic kidney disease has a higher likelihood and cost of inpatient admissions compared to other aetiologies

PurposeThere is increasing recognition of monogenic aetiologies for kidney disease. We sought to identify whether genetic kidney disease (GKD) has distinct hospitalization patterns compared to other forms of chronic kidney disease (CKD). MethodsHealth service utilization analysis was undertaken in a CKD cohort study across public hospital services in Queensland, Australia. CKD due to clinically coded potential monogenic causes was compared to all other causes in terms of annual frequency, cost, and type of hospital admission. ResultsWe analyzed 7 years of hospital admissions data (809,188 admissions) among 29,046 patients. Compared to non-genetic CKD, GKD was associated with a higher likelihood and cost of admissions. GKD had consistently more admissions (mean excess annual number of admissions increasing from 5.2 in year 1 to 13.4 in year 7) and more costly admissions (mean excess annual cost increasing from $5,265 in year 1 to $12,993 in year 7). This gap in hospitalization likelihood and cost increased over time for both surgical and medical admission episodes, but not for all (immunological, cancer) causes of admissions. ConclusionUnderstanding the nature and extent of differences in healthcare needs between GKD and other CKD will enable better secondary prevention and inform resource allocation decisions to reduce healthcare system pressures attributable to knowable causes.

A refined measurement method of highway truck carbon emissions in the context of carbon peaking and carbon neutrality --Take G30 Yandun Toll Station as an Example

This study uses two different carbon emission factor methods to analyze the differences in carbon emissions from trucks under different types and times. The analysis is based on the Xinjiang Expressway Database and other data, with the G30 Yandun Toll Station as an example. The study aims to provide insight into the environmental impact of trucking and inform future policy decisions. The study indicates that heavy-duty trucks are responsible for 90% and 97% of the total carbon emissions from all trucks, respectively. The number of vehicles and the type of trucks are the main factors contributing to these emissions. Additionally, the second quarter shows the highest carbon emissions, while the first quarter exhibits the most considerable difference between the results of the two methods. In March, carbon emissions were at their highest. Additionally, the fuel consumption of trucks with GVW ⩾ 31000kg was the highest, with a significant difference between the results of the two methods. It is worth noting that the fuel consumption of trucks with GVW ⩾ 31000kg was also measured. This study provides data to support the implementation of policies related to transportation carbon emissions in Xinjiang. The paper is significant for promoting green travel.

Good Governance and Economic Growth in Nepal: A Critical Appraisal

The paper seeks to examine the connections between good governance and economic growth in the context of Nepal. In doing so, it attempts to examine Nepal’s existing level of good governance and how it affects economic growth, identify the dificulties Nepal has in promoting good governance, and make recommendations for enhancing good governance and fostering economic growth in Nepal. This paper concludes that Nepal has long grappled with challenges of corruption and weak institutions, which have hampered its ability to thrive economically. One of the biggest challenges to good governance in Nepal is corruption. Corruption can take many forms, including bribery, nepotism, and embezzlement. It can distort the market and discourage investment, leading to slower economic growth. Another challenge to good governance in Nepal is political instability. Despite these obstacles, the paper further concludes that Nepal has improved recently in terms of lowering poverty and increasing access to services, as well as by taking steps to promote the expansion of the private sector. In addition, the paper suggests some measures to cope with corruption and take initiatives for the good governance. By investigating the interplay between good governance and economic growth in the context of Nepal, this study aims to contribute to the existing knowledge base and inform evidence-based policy decisions.