Global, regional, and national burden of blindness and vision loss attributable to high fasting plasma glucose from 1990 to 2019, and forecasts to 2030: A systematic analysis for the Global Burden of Disease Study 2019.

AIMS: To systematically clarify the spatiotemporal trends, and age-sex-specific blindness and vision loss (BVL) burden due to high fasting plasma glucose (HFPG) from 1990 to 2019, and project this burden over the next decade. MATERIALS AND METHODS: We obtained the number and rate of years lived with disability (YLDs) for the BVL burden attributable to HFPG by age, sex, socio-demographic index (SDI), and location between 1990 and 2019 from the Global Burden of Disease (GBD) 2019 database. The average annual percentage changes (AAPCs) were calculated to assess the temporal trends of HFPG-attributable BVL burden. The Bayesian age-period-cohort model was used to predict the HFPG-attributable BVL burden. RESULTS: In 2019, the global number and age-standardized rate (ASR) for YLDs of BVL attributable to HFPG were 673.13 (95% UI: 159.52 to 1565.34) thousand and 8.44 (95% UI: 2.00 to 19.63) per 100,000 people, respectively. The highest burdens were found in Oceania, South Asia, and Southeast Asia, and the BVL burden due to HFPG was higher in the elderly and lower SDI regions. From 1990 to 2019, the global ASR of HFPG-attributable BVL gradually increased with AAPC (95% CI) being 0.80 (0.74 to 0.86). In addition, the HFPG-attributable BVL burden will slightly increase in the future decade. CONCLUSIONS: The HFPG remains the important cause of BVL worldwide, placing a substantial disease burden. From 1990 to 2019, the age-standardized burden of BVL due to HFPG increased, and will consistently increase in the future decade, particularly in the elderly and in regions with middle SDI or below.

Error Compensation Method for Pedestrian Navigation System Based on Low-Cost Inertial Sensor Array.

In the pedestrian navigation system, researchers have reduced measurement errors and improved system navigation performance by fusing measurements from multiple low-cost inertial measurement unit (IMU) arrays. Unfortunately, the current data fusion methods for inertial sensor arrays ignore the system error compensation of individual IMUs and the correction of position information in the zero-velocity interval. Therefore, these methods cannot effectively reduce errors and improve accuracy. An error compensation method for pedestrian navigation systems based on a low-cost array of IMUs is proposed in this paper. The calibration method for multiple location-free IMUs is improved by using a sliding variance detector to segment the angular velocity magnitude into stationary and motion intervals, and each IMU is calibrated independently. Compensation is then applied to the velocity residuals in the zero-velocity interval after zero-velocity update (ZUPT). The experimental results show a significant improvement in the average noise performance of the calibrated IMU array, with a 3.01-fold increase in static noise performance. In the closed-loop walking experiment, the average horizontal position error of a single calibrated IMU is reduced by 27.52% compared to the uncalibrated IMU, while the calibrated IMU array shows a 2.98-fold reduction in average horizontal position error compared to a single calibrated IMU. After compensating for residual velocity, the average horizontal position error of a single IMU is reduced by 0.73 m, while that of the IMU array is reduced by 64.52%.

Global burden of all cause-specific injuries among children and adolescents from 1990 to 2019: a prospective cohort study.

BACKGROUND: To assess the burden and change in incidence, death, and disability-adjusted life years (DALYs) for all-cause-specific injuries among children and adolescents in 204 countries and territories between 1990 and 2019. MATERIALS AND METHODS: Data were extracted from the Global Burden of Disease, Injury, and Risk Factor Study 2019 (GBD 2019). Global, regional, and country-level age-standardized rate (per 100 000) of incidence (ASRI), mortality (ASRM), and DALYs (ASRD) with 95% uncertainty interval (95% UI) of injuries were estimated by age, sex, socio-demographic index (SDI), and all-cause-specific injuries from 1990 to 2019. RESULTS: Overall, the ASRI, ASRM, and ASRD of injury were 9006.18 (95% UI: 7459.74-10 918.04), 23.04 (20.00-26.50), and 2020.19 (1759.47-2318.64) among children and adolescents worldwide in 2019, respectively. All the above indicators showed a downward trend from 1990 to 2019. In level 2 cause of injury, both the global transport injury and unintentional injury declined during the study years, while self-harm and interpersonal violence-related injury showed an increasing trend. High SDI regions had higher ASRI of injuries, but low SDI regions had higher ASRM and ASRD of injuries globally in 2019. Males had a higher burden of injuries than those in females. The ASRI of injuries is higher in adolescents aged 15-19 years, whereas the mortality and DALYs rate are higher among children under 5 years old. Moreover, adolescents aged 15-19 years and individuals living in Central Asia, Middle East, and Africa had higher ASRI, ASRM, and ASRD of injuries owing to self-harm and interpersonal violence. Generally, falls and road traffic injuries are the leading cause of injury among the population aged 0-19 years worldwide, but self-harm, interpersonal violence, and conflict and terrorism are also leading types of injuries in some regions, particularly in Low-Income Countries and Middle-Income Countries. CONCLUSIONS: Injury remains a major global public health problem among children and adolescents, although its burden at the worldwide level showed a decreasing trend from 1990 to 2019. Of concern, the burden of injuries caused by transport injuries, and unintentional injuries has shown a downward trend in most countries, while the burden caused by self-harm and interpersonal violence has shown an upward trend in most countries. These findings suggest that more targeted and specific strategies to prevent the burden of injuries should be reoriented, and our study provides important findings for decision-makers and healthcare providers to reduce injury burden among children and adolescents.

Global, regional and national burden of retinopathy of prematurity among childhood and adolescent: a spatiotemporal analysis based on the Global Burden of Disease Study 2019.

BACKGROUND: This study aimed to provide a comprehensive assessment of burden estimates and the secular trend of vision loss due to retinopathy of prematurity (ROP) among people younger than 20 years, at the global, regional and national levels. METHODS: Data were obtained from the Global Burden of Disease Study 2019 database. The average annual percentage change (AAPC) was calculated to quantify the temporal trends in the measures of vision loss. RESULTS: In 2019, the global age-standardised rates (ASRs) of prevalence per 100 000 population was 86.4 for vision loss, specifically, 35 for moderate vision loss, 19.9 for severe vision loss, 31.6 for blindness due to ROP among people younger than 20 years. Moreover, the ASR of years lived with disability per 100 000 was 10.6 for vision loss, specifically, 1.1 for moderate vision loss, 3.6 for severe vision loss, 5.9 for blindness, respectively. From 1990 to 2019, the ASR of prevalence of blindness and vision loss due to ROP significantly increased, while its burden slightly decreased. Males showed higher ASR of prevalence than females in 2019, whereas females have larger increasing trend than males from 1990 to 2019. The global highest ASR of disease burden was observed in South Asia and Southern sub-Saharan Africa, as well as low sociodemographic index (SDI) regions in 2019. CONCLUSIONS: Globally, although the burden decreased, the prevalence of childhood and adulthood vision loss due to ROP continues to increase. Reasonable resource allocation and advanced intervention are recommended to prevent and control the vision loss due to ROP.

Mapping the global, regional, and national burden of diarrheal diseases attributable to unsafe water.

Background: Diarrheal diseases are major contributors to deaths. Data on global and country-specific levels and trends of diarrheal diseases resulting from unsafe water are essential for policymakers to allocate resources. Aims: This study aimed to describe the global, regional, and national spatiotemporal burden of diarrheal diseases resulting from unsafe water exposure. Methods: According to the Global Burden of Disease (GBD) 2019 dataset, deaths, disability-adjusted life years (DALYs) of diarrheal diseases, and their age-standardized rates (ASRs) were analyzed by age and sex in 204 countries and territories. Moreover, the average annual percentage change (AAPC) was estimated by a log-linear regression model to reflect the time trend. The association between ASR of diarrheal diseases due to unsafe water and socio-demographic index (SDI) levels was also analyzed. Results: From 1990 to 2019, the number of deaths and DALYs of diarrheal diseases resulting from unsafe water decreased by 50 and 59%, respectively. Moreover, the ASR of deaths and DALYs also decreased during the study period, with AAPCs of -3.69 (95% CI [95% confidence interval]: -3.91 to -3.47) and - 3.66 (95% CI: -3.8 to -3.52), respectively. High diarrheal diseases resulting from unsafe water occurred mainly in low SDI regions and Africa. Males exhibited greater diarrheal deaths attributable to unsafe water than females, which was contrary to the condition in terms of DALYs. The age-specific burden of diarrheal deaths attributable to unsafe water is concentrated in children younger than 5 years. The AAPCs of the ASR of both deaths and DALYs showed a strong negative correlation with the SDI levels. Conclusion: The current study indicated that the global burden of unsafe water exposure-related diarrheal diseases decreased from 1990 to 2019 and varied significantly according to age, sex, and geographical location. Effective health promotion and health communication strategies and policies should be adopted to prevent and control diarrheal diseases resulting from unsafe water exposure.

Review of the Perspectives and Study of Thermo-Responsive Polymer Gels and Applications in Oil-Based Drilling Fluids.

Thermoresponsive polymer gels are a type of intelligent material that can react to changes in temperature. These materials possess excellent innovative properties and find use in various fields. This paper systematically analyzes the methods for testing and regulating phase transition temperatures of thermo-responsive polymer gels based on their response mechanism. The report thoroughly introduces the latest research on thermo-responsive polymer gels in oil and gas extraction, discussing their advantages and challenges across various environments. Additionally, it elucidates how the application limitations of high-temperature and high-salt conditions can be resolved through process optimization and material innovation, ultimately broadening the scope of application of thermo-responsive polymer gels in oil and gas extraction. The article discusses the technological development and potential applications of thermo-responsive polymer gels in oil-based drilling fluids. This analysis aims to offer researchers in the oil and gas industry detailed insights into future possibilities for thermo-responsive polymer gels and to provide helpful guidance for their practical use in oil-based drilling fluids.

An enhanced decision-making framework for predicting future trends of sharing economy.

This work aims to provide a reliable and intelligent prediction model for future trends in sharing economy. Moreover, it presents valuable insights for decision-making and policy development by relevant governmental bodies. Furthermore, the study introduces a predictive system that incorporates an enhanced Harris Hawk Optimization (HHO) algorithm and a K-Nearest Neighbor (KNN) forecasting framework. The method utilizes an improved simulated annealing mechanism and a Gaussian bare bone structure to improve the original HHO, termed SGHHO. To achieve optimal prediction performance and identify essential features, a refined simulated annealing mechanism is employed to mitigate the susceptibility of the original HHO algorithm to local optima. The algorithm employs a mechanism that boosts its global search ability by generating fresh solution sets at a specific likelihood. This mechanism dynamically adjusts the equilibrium between the exploration and exploitation phases, incorporating the Gaussian bare bone strategy. The best classification model (SGHHO-KNN) is developed to mine the key features with the improvement of both strategies. To assess the exceptional efficacy of the SGHHO algorithm, this investigation conducted a series of comparative trials employing the function set of IEEE CEC 2014. The outcomes of these experiments unequivocally demonstrate that the SGHHO algorithm outperforms the original HHO algorithm on 96.7% of the functions, substantiating its remarkable superiority. The algorithm can achieve the optimal value of the function on 67% of the tested functions and significantly outperforms other competing algorithms. In addition, the key features selected by the SGHHO-KNN model in the prediction experiment, including " Form of sharing economy in your region " and " Attitudes to the sharing economy ", are important for predicting the future trends of the sharing economy in this study. The results of the prediction demonstrate that the proposed model achieves an accuracy rate of 99.70% and a specificity rate of 99.38%. Consequently, the SGHHO-KNN model holds great potential as a reliable tool for forecasting the forthcoming trajectory of the sharing economy.

Multi-scenario optimization of land use structure and prediction of ecosystem service value in Guanzhong Plain urban agglomeration.

Rapid economic development has led to significant changes in land use in the Guanzhong Plain urban agglomeration, which alters regional ecosystem service value (ESV). Based on the land use and driver data of the Guanzhong Plain urban agglomeration, we used the system dynamics (SD) model coupled with the mixed-cell cellular automata (MCCA) model to predict the subtle spatial and temporal changes of ESV within the land use unit in 2040 under the scenarios of natural development, economic development, ecological protection, and arable land conservation, to reveal the responses of ESV to the socio-economic evolution. We examined the impacts of land use change on ESV by using the sensitivity index. The results showed that land use transformation between 2000 and 2020 in the study area was mainly the conversion between arable land, forest, grassland, and the conversion of arable land to construction land. Due to increased forest and water, ESV increased slightly during this period. In 2040, compared with the ecological protection scenario, the proportion of forest in the economic development scenario decreased by 1.8%, and the construction land increased by 1.3%. During 2020-2040, under the economic development scenario, ESV showed a downward trend in the central and eastern regions but an upward trend under the arable land conservation scenario, with hydrological and climatic regulation contributing the most to ESV. Total ESV showed a decreasing trend except for the ecological conservation scenario. In the ecological protection scenario, land use change positively impacted ESV. In contrast, ESV had a negative response to land use change in other scenarios, with the greatest reduction in the economic development scenario. The research could provide new methods for multi-scenario land use simulation and ESV prediction and have scientific and practical significance for optimizing land space layout, land resource planning management, and sustainable development path strategy of urban agglomerations.

Analysis of the Impact of Public Services on Residents' Health: A Spatial Econometric Analysis of Chinese Provinces.

Objectives: The aim of this study was to explore the mechanism between public services and residents' health, focusing on the role of spatial geographical factors. Methods: Leveraging a comprehensive panel dataset encompassing 30 mainland Chinese provinces from 2007 to 2019, this study engineered a spatial Durbin model furnished with dual fixed effects through the application of the Lagrange multiplier, Hausman, and likelihood ratio tests. The primary objective was to delve into the repercussions of varying public service levels on residents' health outcomes. Results: The empirical findings reveal a palpable spatial autocorrelation between residents' health outcomes and the public services levels dispensed across Chinese provinces. Intriguingly, an elevation in the public service level in a given province not only ameliorates its residents' health outcomes but also triggers a spatial spillover effect, thereby positively influencing residents' health in neighboring provinces. The rigorous endogeneity and robustness checks affirm the reliability of the principal outcomes. Conclusion: Due to the increase in social uncertainty, all regions should break free of the administrative monopoly, enhance regional integration and development, and improve residents' health status by clustering public service supply.

An overview of optimal designs under a given budget in cluster randomized trials with a binary outcome.

Cluster randomized trial design may raise financial concerns because the cost to recruit an additional cluster is much higher than to enroll an additional subject in subject-level randomized trials. Therefore, it is desirable to develop an optimal design. For local optimal designs, optimization means the minimum variance of the estimated treatment effect under the total budget. The local optimal design derived from the variance needs the input of an association parameter ρ in terms of a "working" correlation structure R(ρ) in the generalized estimating equation models. When the range of ρ instead of an exact value is available, the parameter space is defined as the range of ρ and the design space is defined as enrollment feasibility, for example, the number of clusters or cluster size. For any value ρ within the range, the optimal design and relative efficiency for each design in the design space is obtained. Then, for each design in the design space, the minimum relative efficiency within the parameter space is calculated. MaxiMin design is the optimal design that maximizes the minimum relative efficiency among all designs in the design space. Our contributions are threefold. First, for three common measures (risk difference, risk ratio, and odds ratio), we summarize all available local optimal designs and MaxiMin designs utilizing generalized estimating equation models when the group allocation proportion is predetermined for two-level and three-level parallel cluster randomized trials. We then propose the local optimal designs and MaxiMin designs using the same models when the group allocation proportion is undecided. Second, for partially nested designs, we develop the optimal designs for three common measures under the setting of equal number of subjects per cluster and exchangeable working correlation structure in the intervention group. Third, we create three new Statistical Analysis System (SAS) macros and update two existing SAS macros for all the optimal designs. We provide two examples to illustrate our methods.

[Assessment of Critical Loads of Nitrogen Deposition in Natural Ecosystems of China].

Excessive nitrogen (N) deposition causes a series of environmental problems, including biodiversity loss. Therefore, assessing current N deposition thresholds of natural ecosystems is critical for regional N management and pollution control. In this study, the critical loads of N deposition in mainland China were estimated using the steady-state mass balance method, and the spatial distribution of ecosystems that exceeded the critical load was evaluated. The results showed that areas with critical loads of N deposition higher than 56, in the range of 14-56, and lower than 14 kg·(hm2·a)-1 accounted for 6%, 67%, and 27% of that in China, respectively. The areas with higher critical loads of N deposition were mainly distributed in the eastern Tibetan Plateau, northeastern Inner Mongolia, and parts of south China. Lower critical loads of N deposition were mainly distributed in the western Tibetan Plateau, northwest China, and parts of southeast China. Moreover, the areas where N deposition exceeded the critical loads accounted for 21% of that in mainland China, being mainly distributed in southeast and northeast China. The exceedances of critical loads of N deposition in northeast China, northwest China, and the Qinghai-Tibet Plateau were generally lower than 14 kg·(hm2·a)-1. Therefore, the management and control of N in these areas that exceeded the critical load of deposition is more worthy of future attention.

Prevalence, incidence, deaths, and disability-adjusted life-years of drug use disorders for 204 countries and territories during the past 30 years.

Drug use disorders are increasingly recognized as the main cause of public health issues worldwide. The current analysis aims to provide the most comprehensive, updated estimates of the burden from drug use disorders at global, regional, and national levels during the past three decades. Prevalence, incidence, deaths, and disability-adjusted life-years (DALYs) were estimated from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 by age and sex for drug use disorder as well as its four main categories (opioid use disorders, cocaine use disorders, amphetamine use disorders, and cannabis use disorders) in 204 countries and territories between 1990 and 2019. DisMod-MR 2.1, and Bayesian meta-regression were used to analyze prevalence and incidence, while the Cause of Death Ensemble model (CODEm) was used to estimate death of diseases. Globally, the burden of drug use disorders, as measured by the average annual percentage change (AAPC) of deaths and DALYs, continues to increase. The patterns by regions of DALYs due to drug use disorders varied significantly, and it is mainly in developed countries and concentrated among young people and males. Programs for drug use disorders management should be improved, particularly in opioid use disorders. Governments will face increasing demand for treatment and support services, and effective prevention as well as control strategies are required to reduce the burden from these causes.

Life cycle environmental impact assessment for battery-powered electric vehicles at the global and regional levels.

As an important part of electric vehicles, lithium-ion battery packs will have a certain environmental impact in the use stage. To analyze the comprehensive environmental impact, 11 lithium-ion battery packs composed of different materials were selected as the research object. By introducing the life cycle assessment method and entropy weight method to quantify environmental load, a multilevel index evaluation system was established based on environmental battery characteristics. The results show that the Li-S battery is the cleanest battery in the use stage. In addition, in terms of power structure, when battery packs are used in China, the carbon footprint, ecological footprint, acidification potential, eutrophication potential, human toxicity cancer and human toxicity noncancer are much higher than those in the other four regions. Although the current power structure in China is not conducive to the sustainable development of electric vehicles, the optimization of the power structure is expected to make electric vehicles achieve clean driving in China.

Treatment cost assessment for COVID-19 inpatients in Shenzhen, China 2020-2021: facts and suggestions.

Background: Knowledge regarding the treatment cost of coronavirus disease 2019 (COVID-19) in the real world is vital for disease burden forecasts and health resources planning. However, it is greatly hindered by obtaining reliable cost data from actual patients. To address this knowledge gap, this study aims to estimate the treatment cost and specific cost components for COVID-19 inpatients in Shenzhen city, China in 2020-2021. Methods: It is a 2 years' cross-sectional study. The de-identified discharge claims were collected from the hospital information system (HIS) of COVID-19 designated hospital in Shenzhen, China. One thousand three hundred ninety-eight inpatients with a discharge diagnosis for COVID-19 from January 10, 2020 (the first COVID-19 case admitted in the hospital in Shenzhen) to December 31, 2021. A comparison was made of treatment cost and cost components of COVID-19 inpatients among seven COVID-19 clinical classifications (asymptomatic, mild, moderate, severe, critical, convalescent and re-positive cases) and three admission stages (divided by the implementation of different treatment guidelines). The multi-variable linear regression models were used to conduct the analysis. Results: The treatment cost for included COVID-19 inpatients was USD 3,328.8. The number of convalescent cases accounted for the largest proportion of all COVID-19 inpatients (42.7%). The severe and critical cases incurred more than 40% of treatment cost on western medicine, while the other five COVID-19 clinical classifications spent the largest proportion (32%-51%) on lab testing. Compared with asymptomatic cases, significant increases of treatment cost were observed in mild cases (by 30.0%), moderate cases (by 49.2%), severe cases (by 228.7%) and critical cases (by 680.7%), while reductions were shown in re-positive cases (by 43.1%) and convalescent cases (by 38.6%). The decreasing trend of treatment cost was observed during the latter two stages by 7.6 and 17.9%, respectively. Conclusions: Our findings identified the difference of inpatient treatment cost across seven COVID-19 clinical classifications and the changes at three admission stages. It is highly suggestive to inform the financial burden experienced by the health insurance fund and the Government, to emphasize the rational use of lab tests and western medicine in the COVID-19 treatment guideline, and to design suitable treatment and control policy for convalescent cases.

A hybrid machine learning model for landslide-oriented risk assessment of long-distance pipelines.

Preparation of pipeline risk zoning is essential for pipeline construction and safe operation. Landslides are one of the main sources of risk to the safe operations of oil and gas pipelines in mountainous areas. This work aims to propose a quantitative assessment model of landslide-induced long-distance pipeline risk by analyzing historical landslide hazard data along oil and gas pipelines. Using the Changshou-Fuling-Wulong-Nanchuan (CN) gas pipeline dataset, two independent assessments were carried out: landslide susceptibility assessment and pipeline vulnerability assessment. Firstly, the study combined the recursive feature elimination and particle swarm optimization-AdaBoost method (RFE-PSO-AdaBoost) to develop a landslide susceptibility mapping model. The RFE method was used to select the conditioning factors, while PSO was used to tune the hyper-parameters. Secondly, considering the angular relationship between the pipelines and landslides, and the segmentation of the pipelines using the fuzzy clustering (FC), the CRITIC method (FC-CRITIC) was combined to develop a pipeline vulnerability assessment model. Accordingly, a pipeline risk map was obtained based on pipeline vulnerability and landslide susceptibility assessment. The study results show that almost 35.3% of the slope units were in extremely high susceptibility zones, 6.68% of the pipelines were in extremely high vulnerability areas, the southern and eastern pipelines segmented in the study area were located in high risk areas and coincided well with the distribution of landslides. The proposed hybrid machine learning model for landslide-oriented risk assessment of long-distance pipelines can provide a scientific and reasonable risk classification for new planning or in service pipelines to avoid landslide-oriented risk and ensure their safe operation in mountainous areas.

Dissipation and dietary exposure risk assessment of spinosad, thiocyclam, and its metabolite nereistoxin in cucumber and groundwater for different population groups.

A QuEChERS (quick, easy, cheap, effective, rugged, and safe) technique using ultrahigh-performance liquid chromatography with tandem mass spectrometry for the analysis of spinosad (spinosyn A + spinosyn D), thiocyclam, and nereistoxin in cucumber was developed with mean recoveries of 93-104%, relative standard deviations of ≤9%, and limits of quantification of 0.01 mg/kg. Field trials of spinosad and thiocyclam were performed in 12 representative cultivating areas in China. Field trial results indicate that spinosyn A and spinosyn D easily dissipated in cucumber with half-lives of 2.48-6.24 and <3 days, respectively. Nereistoxin was produced after thiocyclam application and was more persistent than its parent. The terminal residues of spinosad were all below the maximum residue limits (0.2 mg/kg) in China, whereas the terminal concentration of nereistoxin (calculated as the stoichiometric equivalent of thiocyclam), which was much higher than that of thiocyclam, was far beyond the maximum residue limits of thiocyclam in cucumber (0.01 mg/kg) established by the European Union. The predicted no-effect concentrations of spinosyn A, spinosyn D, thiocyclam, and nereistoxin leaching into groundwater were estimated using China-PEARL (Pesticide Emission Assessment at Regional and Local scales) models after application. However, the dietary (food and water) exposure risk quotient for different populations was below 1 with a preharvest interval set at 5 days after the last application, indicating that the application of spinosad and thiocyclam in cucumber was unlikely to pose unacceptable risk for human health. This study provides data for the safe use of spinosad and thiocyclam in cucumber ecosystem.

Exploring differences in symptomatic adverse events assessment between nurses and physicians in the clinical trial setting.

A cross-sectional study was performed at Hebei Medical University Fourth Affiliated Hospital from April to July 2020 to explore the difference and consistency between nurses and physicians in terms of symptomatic adverse event (AE) assessment. The Common Terminology Criteria for Adverse Events (CTCAE) was utilized by nurses and physicians to assess patients' symptomatic AEs. Patients self-reported their AEs utilizing the Patient-Reported Outcomes Version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE). Four nurses and three physicians were enrolled to assess patients' symptomatic AEs. Given the same AEs, nurses tended to detect more AEs than physicians, and the differences were statistically significant (P < 0.001). The toxicity grade reported by nurses and physicians showed no difference for all AEs, except for fatigue (χ2 = 5.083, P = 0.024). The agreement between nurses and patients was highest compared to the agreement between nurses versus physicians and physicians versus patients. The differences in symptomatic AE assessment can lead to different symptom management. Thus, it is important to establish a collaborative approach between nurses and physicians to ensure continuity in care delivery.

Global, Regional, and National Burdens of Blindness and Vision Loss in Children and Adolescents from 1990 to 2019: A Trend Analysis.

PURPOSE: To provide estimates for regional and national burdens of blindness and vision loss among children and adolescents between 1990 and 2019 by disease, age, and sociodemographic index (SDI). DESIGN: This was a retrospective demographic analysis based on aggregated data. METHODS: This was a population-based study using 1990-2019 data on the burden of vision loss and blindness from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019. The burden of vision loss and blindness was evaluated in terms of case numbers, rates per 100 000 population, and average annual percentage changes (AAPCs) in prevalence rates and years lived with disability (YLDs). RESULTS: Globally, the rates of blindness and vision loss per 100 000 population decreased in all age groups between 1990 and 2019, with prevalence rates decreasing from 1091.4 (95% uncertainty interval [UI], 895.2-1326.1) to 1036.9 (95% UI, 847.8-1265.9, AAPC, -0.2) and YLDs decreasing from 44.5 (95% UI, 28.1-66.5) to 40.2 (95% UI, 25.1-60.7, AAPC, -0.4). Most of these reductions in prevalence rates (AAPC, -0.2, 95% confidence interval [CI], -0.2 to -0.1) and YLDs (AAPC, -0.2, 95% CI, -0.3 to -0.2) were due to decreases in refractive disorder. Notably, near-vision loss prevalence (AAPC, 0.3, 95% CI, 0.2-0.4) and YLDs (AAPC, 0.3, 95% CI, 0.2-0.4) substantially increased in all age groups. Children and adolescents in low- and low-middle SDI countries exhibited substantial decreases in the prevalence rates and YLDs of blindness and vision loss, but their counterparts in high- and middle-high SDI countries experienced a substantial increase in prevalence. CONCLUSIONS: Globally, efforts in the past 3 decades have substantially decreased the burdens of blindness and vision loss among children and adolescents. However, there is extensive variation according to the kind of impairment, age group, and country SDI. FINANCIAL DISCLOSURE(S): The author(s) have no proprietary or commercial interest in any materials discussed in this article.

Social Determinants, Cardiovascular Disease, and Health Care Cost: A Nationwide Study in the United States Using Machine Learning.

Background Existing studies on cardiovascular diseases (CVDs) often focus on individual-level behavioral risk factors, but research examining social determinants is limited. This study applies a novel machine learning approach to identify the key predictors of county-level care costs and prevalence of CVDs (including atrial fibrillation, acute myocardial infarction, congestive heart failure, and ischemic heart disease). Methods and Results We applied the extreme gradient boosting machine learning approach to a total of 3137 counties. Data are from the Interactive Atlas of Heart Disease and Stroke and a variety of national data sets. We found that although demographic composition (eg, percentages of Black people and older adults) and risk factors (eg, smoking and physical inactivity) are among the most important predictors for inpatient care costs and CVD prevalence, contextual factors such as social vulnerability and racial and ethnic segregation are particularly important for the total and outpatient care costs. Poverty and income inequality are the major contributors to the total care costs for counties that are in nonmetro areas or have high segregation or social vulnerability levels. Racial and ethnic segregation is particularly important in shaping the total care costs for counties with low poverty rates or social vulnerability level. Demographic composition, education, and social vulnerability are consistently important across different scenarios. Conclusions The findings highlight the differences in predictors for different types of CVD cost outcomes and the importance of social determinants. Interventions directed toward areas that have been economically and socially marginalized may aid in reducing the impact of CVDs.

Long-Term Cost-Effectiveness of Subcutaneous Once-Weekly Semaglutide Versus Polyethylene Glycol Loxenatide for Treatment of Type 2 Diabetes Mellitus in China.

OBJECTIVE: This study aimed to evaluate the long-term cost-effectiveness of once-weekly subcutaneous semaglutide versus polyethylene glycol loxenatide (PEG-loxenatide) in patients with type 2 diabetes uncontrolled on metformin, from a Chinese healthcare systems perspective. METHODS: The study applied the Swedish Institute of Health Economics Diabetes Cohort Model to evaluate the long-term clinical and economic outcomes of once-weekly treatment of semaglutide at 0.5 mg and 1.0 mg, respectively, versus PEG-loxenatide 0.2 mg, over a 40-year time horizon. Baseline cohort characteristics were collected from the SUSTAIN China trial. A network meta-analysis was conducted to obtain comparative treatment effects of once-weekly semaglutide and PEG-loxenatide based on two phase 3a clinical trials. Drug costs were sourced from the national bidding price of China. Outcomes were discounted at 5.0% per annum. One-way sensitivity analysis and probabilistic sensitivity analysis were conducted to assess the uncertainty of the base-case results. RESULTS: When compared with PEG-loxenatide 0.2 mg, the projections of outcomes over the 40-year time horizon in patients with type 2 diabetes uncontrolled on metformin showed that treatment with once-weekly semaglutide 0.5 mg and 1.0 mg were associated with improved discounted life expectancy by 0.08 and 0.12 years, and improved discounted quality-adjusted life expectancy by 0.16 and 0.22 quality-adjusted life-years, respectively. Once-weekly semaglutide 0.5 mg and 1.0 mg were achieved at lifetime cost savings of 19,309 China Yuan (CNY) and 10,179 CNY, respectively. Sensitivity analyses verified the robustness of the results. CONCLUSION: From the perspective of Chinese healthcare systems, treatment with once-weekly subcutaneous semaglutide represents a dominant option versus PEG-loxenatide for patients with type 2 diabetes uncontrolled on metformin.