Evaluating the Cost-Utility of Continuous Glucose Monitoring in Individuals with Type 1 Diabetes: A Systematic Review of the Methods and Quality of Studies Using Decision Models or Empirical Data.

INTRODUCTION: This review presents a critical appraisal of differences in the methodologies and quality of model-based and empirical data-based cost-utility studies on continuous glucose monitoring (CGM) in type 1 diabetes (T1D) populations. It identifies key limitations and challenges in health economic evaluations on CGM and opportunities for their improvement. METHODS: The review and its documentation adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines for systematic reviews. Searches for articles published between January 2000 and January 2023 were conducted using the MEDLINE, Embase, Web of Science, Cochrane Library, and Econlit databases. Published studies using models and empirical data to evaluate the cost utility of all CGM devices used by T1D patients were included in the search. Two authors independently extracted data on interventions, populations, model settings (e.g., perspectives and time horizons), model types and structures, clinical outcomes used to populate the model, validation, and uncertainty analyses. They subsequently met to confirm consensus. Quality was assessed using the Philips checklist for model-based studies and the Consensus Health Economic Criteria (CHEC) checklist for empirical studies. Model validation was assessed using the Assessment of the Validation Status of Health-Economic decision models (AdViSHE) checklist. The extracted data were used to generate summary tables and figures. The study protocol is registered with PROSPERO (CRD42023391284). RESULTS: In total, 34 studies satisfied the selection criteria, two of which only used empirical data. The remaining 32 studies applied 10 different models, with a substantial majority adopting the CORE Diabetes Model. Model-based studies often lacked transparency, as their assumptions regarding the extrapolation of treatment effects beyond available evidence from clinical studies and the selection and processing of the input data were not explicitly stated. Initial scores for disagreements concerning checklists were relatively high, especially for the Philips checklist. Following their resolution, overall quality scores were moderate at 56%, whereas model validation scores were mixed. Strikingly, costing approaches differed widely across studies, resulting in little consistency in the elements included in intervention costs. DISCUSSION AND CONCLUSION: The overall quality of studies evaluating CGM was moderate. Potential areas of improvement include developing systematic approaches for data selection, improving uncertainty analyses, clearer reporting, and explaining choices for particular modeling approaches. Few studies provided the assurance that all relevant and feasible options had been compared, which is required by decision makers, especially for rapidly evolving technologies such as CGM and insulin administration. High scores for disagreements indicated that several checklists contained questions that were difficult to interpret consistently for quality assessment. Therefore, simpler but comprehensive quality checklists may be needed for model-based health economic evaluation studies.

A Blueprint for Multi-use Disease Modeling in Health Economics: Results from Two Expert-Panel Consultations.

BACKGROUND: The current use of health economic decision models in HTA is mostly confined to single use cases, which may be inefficient and result in little consistency over different treatment comparisons, and consequently inconsistent health policy decisions, for the same disorder. Multi-use disease models (MUDMs) (other terms: generic models, whole disease models, disease models) may offer a solution. However, much is uncertain about their definition and application. The current research aimed to develop a blueprint for the application of MUDMs. METHODS: We elicited expert opinion using a two-round modified Delphi process. The panel consisted of experts and stakeholders in health economic modelling from various professional backgrounds. The first questionnaire concerned definition, terminology, potential applications, issues and recommendations for MUDMs and was based on an exploratory scoping review. In the second round, the panel members were asked to reconsider their input, based on feedback regarding first-round results, and to score issues and recommendations for priority. Finally, adding input from external advisors and policy makers in a structured way, an overview of issues and challenges was developed during two team consensus meetings. RESULTS: In total, 54 respondents contributed to the panel results. The term 'multi-use disease models' was proposed and agreed upon, and a definition was provided. The panel prioritized 10 potential applications (with comparing alternative policies and supporting resource allocation decisions as the top 2), while 20 issues (with model transparency and stakeholders' roles as the top 2) were identified as challenges. Opinions on potential features concerning operationalization of multi-use models were given, with 11 of these subsequently receiving high priority scores (regular updates and revalidation after updates were the top 2). CONCLUSIONS: MUDMs would improve on current decision support regarding cost-effectiveness information. Given feasibility challenges, this would be most relevant for diseases with multiple treatments, large burden of disease and requiring more complex models. The current overview offers policy makers a starting point to organize the development, use, and maintenance of MUDMs and to support choices concerning which diseases and policy decisions they will be helpful for.

Global, regional and national epidemiology of allergic disorders in children from 1990 to 2019: findings from the Global Burden of Disease study 2019.

OBJECTIVE: This modelling study aimed to estimate the burden for allergic diseases in children during a period of 30 years. DESIGN: Population-based observational study. MAIN OUTCOMES AND MEASURES: The data on the incidence, mortality and disability-adjusted life years (DALYs) for childhood allergic diseases, such as atopic dermatitis (AD) and asthma, were retrieved from the Global Burden of Disease study 2019 online database. This data set spans various groups, including different regions, ages, genders and Socio-Demographic Indices (SDI), covering the period from 1990 to 2019. RESULTS: In 2019, there were approximately 81 million children with asthma and 5.6 million children with AD worldwide. The global incidence of asthma in children was 20 million. Age-standardised incidence rates showed a decrease of 4.17% for asthma, from 1075.14 (95% uncertainty intervals (UI), 724.63 to 1504.93) per 100 000 population in 1990 to 1030.33 (95% UI, 683.66 to 1449.53) in 2019. Similarly, the rates for AD decreased by 5.46%, from 594.05 (95% UI, 547.98 to 642.88) per 100 000 population in 1990 to 561.61 (95% UI, 519.03 to 608.29) in 2019. The incidence of both asthma and AD was highest in children under 5 years of age, gradually decreasing with age. Interestingly, an increase in SDI was associated with a rise in the incidence of both conditions. However, the mortality rate and DALYs for asthma showed a contrasting trend. CONCLUSIONS: Over the past three decades, there has been a worldwide increase in new asthma and AD cases, even though mortality rates have significantly declined. However, the prevalence of these allergic diseases among children varies considerably across regions, countries and age groups. This variation highlights the need for precise prevalence assessments. These assessments are vital in formulating effective strategies for prevention and treatment.

Burden of depression in adolescents in the Western Pacific Region from 1990 to 2019: An age-period-cohort analysis of the Global Burden of Disease study.

BACKGROUND: Depression is a highly prevalent and disabling mental health condition among adolescents. The epidemiology of depression in adolescents has been changing over time, reflecting changes in risk factors as well as disease concepts and diagnosis. However, few studies have characterized the longitudinal epidemiology of depression in adolescents. Understanding trends of disease burden provides key insights to improve resource allocation and design targeted interventions for this vulnerable population. The Western Pacific Region (WPR) is home to over 1.3 billion people with tremendous diversity in culture and socioeconomic development. The epidemiology of adolescent depression in WPR remains largely unknown. In this study, we aimed to estimate trends of disease burden attributable to depressive disorders among adolescents aged 10-24 years in WPR countries between 1990 and 2019, and to investigate period and cohort effects using the Global Burden of Disease (GBD) study database. METHODS: The study utilized data from the Global Burden of Disease, Injuries, and Risk Factors Study 2019, concentrating on adolescents aged 10 to 24 years with depression. We conducted an in-depth analysis of depression, including its age-standardized prevalence, incidence, and Disability-Adjusted Life Years (DALYs), across diverse demographics such as regions, ages, genders, and socio-demographic indexes, spanning from 1990 to 2019. RESULTS: The analysis found decreasing trends in the prevalence, incidence, and DALYs of adolescent depression in the WPR between 1990-2019, although some countries like Australia and Malaysia showed increases. Specifically, the prevalence of adolescent depression in the region decreased from 9,347,861.6 cases in 1990 to 5,551,341.1 cases in 2019. The incidence rate declined from 2,508.6 per 100,000 adolescents in 1990 to 1,947.9 per 100,000 in 2019. DALYs decreased from 371.9 per 100,000 in 1990 to ASR 299.7 per 100,000 in 2019. CONCLUSION: This study found an overall decreasing trend in adolescent depression burden in the Western Pacific Region between 1990 and 2019, with heterogeneity across countries. For 30 years, the 20-24 age group accounted for the majority of depression among adolescents Widening inequality in depression burden requires policy attention. Further analysis of risk factors contributing to epidemiological trends is warranted to inform prevention strategies targeting adolescent mental health in the region.

Temporal Trends of Asthma Among Children in the Western Pacific Region From 1990 to 2045: Longitudinal Observational Study.

BACKGROUND: Asthma has become one of the most common chronic conditions worldwide, especially among children. Recent findings show that the prevalence of childhood asthma has increased by 12.6% over the past 30 years, with >262 million people currently affected globally. The reasons for the growing asthma epidemic remain complex and multifactorial. OBJECTIVE: This study aims to provide an up-to-date analysis of the changing global and regional asthma prevalence, mortality, disability, and risk factors among children aged <20 years by leveraging the latest data from the Global Burden of Disease Study 2019. Findings from this study can help inform priority areas for intervention to alleviate the rising burden of childhood asthma globally. METHODS: The study used data from the Global Burden of Disease Study 2019, concentrating on children aged 0 to 14 years with asthma. We conducted an in-depth analysis of asthma, including its age-standardized prevalence, incidence, mortality, and disability-adjusted life years (DALYs), across diverse demographics, such as region, age, sex, and sociodemographic index, spanning 1990 to 2019. We also projected the future burden of the disease. RESULTS: Overall, in the Western Pacific Region, the age-standardized prevalence rate of asthma among children increased slightly, from 3898.4 cases per 100,000 people in 1990 to 3924 per 100,000 in 2019. The age-standardized incidence rate of asthma also increased slightly, from 979.2 to 994.9 per 100,000. In contrast, the age-standardized death rate of asthma decreased from 0.9 to 0.4 per 100,000 and the age-standardized DALY rate decreased from 234.9 to 189.7 per 100,000. At the country level, Japan experienced a considerable decrease in the age-standardized prevalence rate of asthma among children, from 6669.1 per 100,000 in 1990 to 5071.5 per 100,000 in 2019. Regarding DALYs, Japan exhibited a notable reduction, from 300.6 to 207.6 per 100,000. Malaysia also experienced a DALY rate reduction, from 188.4 to 163.3 per 100,000 between 1990 and 2019. We project that the burden of disease in countries other than Japan and the Philippines will remain relatively stable up to 2045. CONCLUSIONS: The study indicates an increase in the prevalence and incidence of pediatric asthma, coupled with a decrease in mortality and DALYs in the Western Pacific Region between 1990 and 2019. These intricate phenomena appear to result from a combination of lifestyle shifts, environmental influences, and barriers to health care access. The findings highlight that nations such as Japan have achieved notable success in managing asthma. Overall, the study identified areas of improvement in view of persistent disease burden, underscoring the need for comprehensive collaborative efforts to mitigate the impact of pediatric asthma throughout the region.

A literature review of quality assessment and applicability to HTA of risk prediction models of coronary heart disease in patients with diabetes.

This literature review had two objectives: to identify models for predicting the risk of coronary heart diseases in patients with diabetes (DM); and to assess model quality in terms of risk of bias (RoB) and applicability for the purpose of health technology assessment (HTA). We undertook a targeted review of journal articles published in English, Dutch, Chinese, or Spanish in 5 databases from 1st January 2016 to 18th December 2022, and searched three systematic reviews for the models published after 2012. We used PROBAST (Prediction model Risk Of Bias Assessment Tool) to assess RoB, and used findings from Betts et al. 2019, which summarized recommendations and criticisms of HTA agencies on cardiovascular risk prediction models, to assess model applicability for the purpose of HTA. As a result, 71 % and 67 % models reporting C-index showed good discrimination abilities (C-index >= 0.7). Of the 26 model studies and 30 models identified, only one model study showed low RoB in all domains, and no model was fully applicable for HTA. Since the major cause of high RoB is inappropriate use of analysis method, we advise clinicians to carefully examine the model performance declared by model developers, and to trust a model if all PROBAST domains except analysis show low RoB and at least one validation study conducted in the same setting (e.g. country) is available. Moreover, since general model applicability is not informative for HTA, novel adapted tools may need to be developed.

The congenital birth defects burden in children younger than 14 years of age, 1990 - 2019: An age-period-cohort analysis of the global burden of disease study.

Background: This study aims to delineate the burden of congenital birth defects (CBDs) in children under 14 years of age from 1990 to 2019, using an age-period-cohort framework to analyse data from the Global Burden of Disease Study (GBD). Methods: Data on prevalence cases, age-standardised prevalence rates (ASPRs), death cases, and age-standardised death rates (ASDRs) of congenital birth defects (CBDs) from 1990 to 2019 were obtained from GBD 2019. Using this data set, we conducted an age-period-cohort (APC) analysis to examine patterns and trends in mortality, prevalence, and disability-adjusted life years (DALYs) associated with CBDs, while exploring correlations with age, time periods, and generational birth cohorts. Furthermore, to quantify the temporal trends, we calculated the estimated annual percentage changes (EAPCs) for these parameters. Results: The global prevalence of CBDs decreased from 1404.22 to 1301.66 per 100 000 with an EAPC of -0.18% from 1990 to 2019. CBD mortality decreased by 42.52% between 1990 and 2019, with the global age-standardised death rate declining from 49.72 to 25.58 per 100 000. The age-standardised DALY rate decreased from 4529.16 to 2393.61 per 100 000. Prevalence declined most notably among older children. The risk of CBDs reached its lowest during adolescence (10-14 years) across all regions. The most recent period (2015-2019) showed a reduced risk of prevalence compared to 2000-2004. Earlier birth cohorts displayed declining tendencies followed by slight increases in risk. Conclusions: This study demonstrates encouraging global reductions in the burden of CBDs among children over the past three decades. Prevalence, mortality, and DALYs attributable to CBDs have exhibited downward trajectories, although regional disparities remain. APC analysis provides valuable insights to inform prevention and management strategies for pediatric CBDs.

Environmental impact assessment of battery boxes based on lightweight material substitution.

Power battery is one of the core components of electric vehicles (EVs) and a major contributor to the environmental impact of EVs, and reducing their environmental emissions can help enhance the sustainability of electric vehicles. Based on the principle of stiffness equivalence, the steel case of the power cell is replaced with lightweight materials, a life cycle model is established with the help of GaBi software, and its environmental impact is evaluated using the CML2001 method. The results can be summarized as follows: (1) Based on the four environmental impact categories of GWP, AP, ADP (f), and HTP, which are the global warming potential (GWP), acidification potential (AP), abiotic depletion potential (ADP (f)) and human toxicity potential (HTP), the environmental impact of lightweight materials is lower than that of the steel box. Among them, the aluminum alloy box has the largest reduction, and the Carbon Fiber Sheet Molding Compound (CF-SMC) box is the second. (2) In the sensitivity analysis of electric structure, an aluminum alloy box is still the most preferable choice for environmental impact. (3) In the sensitivity analysis of driving mileage, the aluminum alloy box body is also the best choice for vehicle life. (4) Quantitative assessment using substitution factors measures the decrease in greenhouse gas emissions following the substitution of steel battery box with lightweight materials. The adoption of aluminum alloy battery box can lead to a reduction of 1.55 tons of greenhouse gas emissions, with a substitution factor of 1.55 tC sb-1. In the case that composite materials have not been recycled commercially on a large scale, aluminum alloy is still one of the best materials for the integrated environmental impact of the whole life cycle of the battery boxes.

Pollution Status and Associated Risk Assessment of Heavy Metals in Sewage Sludge in the Yangtze River Delta, China.

The risk assessment of heavy metals (HMs) in sewage sludge (SS) is essential before land application. Six HMs in nineteen SS collected in the Yangtze River Delta were analyzed to assess risks to environment, ecosystem, and human health. HMs concentrations were ranked in the order of Zn > Cu > Cr > Ni > Pb > Cd, with Cu, Zn, and Ni in a total of 16% of samples exceeding the legal standard. Zn showed greatest extractability according to EDTA-extractable concentrations. HMs in 16% of SS samples posed heavy contamination to the environment with Zn as the major pollutant. HMs in 26% of samples posed ecological risk to the ecosystem and Cd was the highest risky HM. The probabilistic health risk assessment revealed that HMs posed carcinogenic risks to all populations, but non-carcinogenic risks only to children. This work will provide fundamental information for land application of SS in this area.

Exploring the impacts of ecosystem services on human well-being in Qinghai Province under the framework of the sustainable development goals.

Ecosystem services (ESs) play vital roles in meeting the needs of human well-being and supporting sustainable development. However, there is limited research on how the types, amounts, interactions, and changes of the ESs collectively impact human well-being under the context of sustainable development goals (SDGs) of the United Nations. This study selected Qinghai Province of China as the study area and intended to make such an attempt to fill this gap in terms of the following aspects: (1) analyzing the spatial patterns and changing trends of ten ESs (food supply, water supply, carbon sink, soil retention, sand fixation, hydrological regulation, flood mitigation，cultural service，net primary productivity, and habitat quality) in Qinghai Province from 2000 to 2018; (2)constructing a multi-level index system of human well-being under the framework of the SDGs, and setting the criteria to assess the level of local human well-being; and (3) building a structural equation model to explore the direct and indirect impacts of the types, amounts, interactions and changes of the ESs on actual human well-being and the gaps between actual and targeted human well-being. The findings revealed that: (1) most of the ecosystem services fluctuated with significant downward or upward trends during 2000-2018, except for four ESs (i.e., carbon sink, soil retention, flood mitigation, and habitat quality); (2) only a few indicators of local residents' well-being such as meat production, milk production, the numbers of medical technical personnel in hospitals and health centers, and the numbers of scientific and technical personnel met the SDG criteria in most time, while other indicators remained at low levels and there were large gaps between them and the SDG criteria; (3) actual human well-being and the gaps between actual and targeted human well-being were affected by the types, amounts, interactions and changes of the ESs with different degrees directly or indirectly. The approaches and results in this study are instructive for other regions of the world to make certain the roles of ESs in promoting human well-being and substantiating the SDGs.

Global, regional, and national epidemiology of migraine and tension-type headache in youths and young adults aged 15-39 years from 1990 to 2019: findings from the global burden of disease study 2019.

BACKGROUND: In recent years, headache disorders have garnered significant attention as a pressing global health issue. This concern is especially pronounced in low- to middle-income countries and exhibits a notable increase in prevalence among adolescents and young adults. Such a surge in these disorders has invariably diminished the quality of life for affected individuals. Despite its global impact, comprehensive studies exploring the ramifications of headache disorders in the younger population remain scant. Our study endeavored to quantify the global prevalence of headache disorders in individuals between the ages of 15 and 39, over a three-decade span from 1990 to 2019. METHODS: Our study, conducted from 1990 to 2019, evaluated the impact of headache disorders, specifically migraines and tension-type headaches (TTH), in 204 different countries and territories. This comprehensive assessment included a detailed analysis of incidence rates, prevalence, and disability-adjusted life-years (DALYs) across various demographics such as age, gender, year, geographical location, and Socio-demographic Index (SDI). RESULTS: In 2019, there were an estimated 581,761,847.2 migraine cases globally (95% UI: 488,309,998.1 to 696,291,713.7), marking a 16% increase from 1990. Concurrently, TTH cases numbered at 964,808,567.1 (95% UI: 809,582,531.8 to 1,155,235,337.2), reflecting a 37% rise since 1990. South Asia reported the highest migraine prevalence with 154,490,169.8 cases (95% UI: 130,296,054.6 to 182,464,065.6). High SDI regions exhibited the most substantial migraine prevalence rates both in 1990 (22,429 per 100,000 population) and 2019 (22,606 per 100,000 population). Among the five SDI classifications, the middle SDI region recorded the highest tally of TTH cases in both 1990 (210,136,691.6 cases) and 2019 (287,577,250 cases). Over the past 30 years, East Asia experienced the most pronounced surge in the number of migraine cases. On the whole, there was a discernible positive correlation between the disease burden of migraine and TTH and the SDI. CONCLUSION: Migraine and TTH represent formidable challenges in global health. The intensity of their impact exhibits marked disparities across nations and is distinctly elevated among women, individuals within the 30-39 age bracket, and populations characterized by a high SDI. The results of our research emphasize the imperative of assimilating migraine and TTH management into contemporary healthcare paradigms. Such strategic integration holds the potential to amplify public cognizance regarding pertinent risk factors and the spectrum of therapeutic interventions at hand.

NN-Based Reinforcement Learning Optimal Control for Inequality-Constrained Nonlinear Discrete-Time Systems With Disturbances.

Based on actor-critic neural networks (NNs), an optimal controller is proposed for solving the constrained control problem of an affine nonlinear discrete-time system with disturbances. The actor NNs provide the control signals and the critic NNs work as the performance indicators of the controller. By converting the original state constraints into new input constraints and state constraints, the penalty functions are introduced into the cost function, and then the constrained optimal control problem is transformed into an unconstrained one. Further, the relationship between the optimal control input and worst-case disturbance is obtained using the Game theory. With Lyapunov stability theory, the control signals are ensured to be uniformly ultimately bounded (UUB). Finally, the effectiveness of the control algorithms is tested through a numeral simulation using a third-order dynamic system.

Cost-Effectiveness of SGLT2 Inhibitors in a Real-World Population: A MICADO Model-Based Analysis Using Routine Data from a GP Registry.

OBJECTIVE: Sodium-glucose cotransporter 2 inhibitors (SGLT2i) have been shown to reduce the risk of cardiovascular complications, which largely drive diabetes' health and economic burdens. Trial results indicated that SGLT2i are cost effective. However, these findings may not be generalizable to the real-world target population. This study aims to evaluate the cost effectiveness of SGLT2i in a routine care type 2 diabetes population that meets Dutch reimbursement criteria using the MICADO model. METHODS: Individuals from the Hoorn Diabetes Care System cohort (N = 15,392) were filtered to satisfy trial inclusion criteria (including EMPA-REG, CANVAS, and DECLARE-TIMI58) or satisfy the current Dutch reimbursement criteria for SGLT2i. We validated a health economic model (MICADO) by comparing simulated and observed outcomes regarding the relative risks of events in the intervention and comparator arm from three trials, and used the validated model to evaluate the long-term health outcomes using the filtered cohorts' baseline characteristics and treatment effects from trials and a review of observational studies. The incremental cost-effectiveness ratio (ICER) of SGLT2i, compared with care-as-usual, was assessed from a third-party payer perspective, measured in euros (2021 price level), using a discount rate of 4% for costs and 1.5% for effects. RESULTS: From Dutch individuals with diabetes in routine care, 15.8% qualify for the current Dutch reimbursement criteria for SGLT2i. Their characteristics were significantly different (lower HbA1c, higher age, and generally more preexisting complications) than trial populations. After validating the MICADO model, we found that lifetime ICERs of SGLT2i, when compared with usual care, were favorable (< €20,000/QALY) for all filtered cohorts, resulting in an ICER of €5440/QALY using trial-based treatment effect estimates in reimbursed population. Several pragmatic scenarios were tested, the ICERs remained favorable. CONCLUSIONS: Although the Dutch reimbursement indications led to a target group that deviates from trial populations, SGLT2i are likely to be cost effective when compared with usual care.

Potential Value of Identifying Type 2 Diabetes Subgroups for Guiding Intensive Treatment: A Comparison of Novel Data-Driven Clustering With Risk-Driven Subgroups.

OBJECTIVE: To estimate the impact on lifetime health and economic outcomes of different methods of stratifying individuals with type 2 diabetes, followed by guideline-based treatment intensification targeting BMI and LDL in addition to HbA1c. RESEARCH DESIGN AND METHODS: We divided 2,935 newly diagnosed individuals from the Hoorn Diabetes Care System (DCS) cohort into five Risk Assessment and Progression of Diabetes (RHAPSODY) data-driven clustering subgroups (based on age, BMI, HbA1c, C-peptide, and HDL) and four risk-driven subgroups by using fixed cutoffs for HbA1c and risk of cardiovascular disease based on guidelines. The UK Prospective Diabetes Study Outcomes Model 2 estimated discounted expected lifetime complication costs and quality-adjusted life-years (QALYs) for each subgroup and across all individuals. Gains from treatment intensification were compared with care as usual as observed in DCS. A sensitivity analysis was conducted based on Ahlqvist subgroups. RESULTS: Under care as usual, prognosis in the RHAPSODY data-driven subgroups ranged from 7.9 to 12.6 QALYs. Prognosis in the risk-driven subgroups ranged from 6.8 to 12.0 QALYs. Compared with homogenous type 2 diabetes, treatment for individuals in the high-risk subgroups could cost 22.0% and 25.3% more and still be cost effective for data-driven and risk-driven subgroups, respectively. Targeting BMI and LDL in addition to HbA1c might deliver up to 10-fold increases in QALYs gained. CONCLUSIONS: Risk-driven subgroups better discriminated prognosis. Both stratification methods supported stratified treatment intensification, with the risk-driven subgroups being somewhat better in identifying individuals with the most potential to benefit from intensive treatment. Irrespective of stratification approach, better cholesterol and weight control showed substantial potential for health gains.

Development and investigation of metabolism-associated risk assessment models for patients with viral hepatitis.

Dysregulation of metabolism plays an important role in the onset and progression of multiple pathogenic diseases, including viral hepatitis. However, a model to predict viral hepatitis risk by metabolic pathways is still lacking. Thus, we developed two risk assessment models for viral hepatitis based on metabolic pathways identified through univariate and least absolute shrinkage and selection operator (LASSO) Cox regression analysis. The first model is designed to assess the progression of the disease by evaluating changes in the Child-Pugh class, hepatic decompensation, and the development of hepatocellular carcinoma. The second model is focused on determining the prognosis of the illness, taking into account the patient's cancer status. Our models were further validated by Kaplan-Meier plots of survival curves. In addition, we investigated the contribution of immune cells in metabolic processes and identified three distinct subsets of immune cells-CD8+ T cells, macrophages, and NK cells-that have significantly affected metabolic pathways. Specifically, our findings suggest that resting or inactive macrophages and NK cells contribute to maintaining metabolic homeostasis, particularly with regard to lipid and α-amino acid metabolism, thereby potentially reducing the risk of viral hepatitis progression. Moreover, maintaining metabolic homeostasis ensures a balance between killer-proliferative and exhausted CD8+ T cells, which helps in mitigating CD8+ T cell-mediated liver damage while preserving energy reserves. In conclusion, our study offers a useful tool for early disease detection in viral hepatitis patients through metabolic pathway analysis and sheds light on the immunological understanding of the disease through the examination of immune cell metabolic disorders.

Prediction of complications in health economic models of type 2 diabetes: a review of methods used.

AIM: Diabetes health economic (HE) models play important roles in decision making. For most HE models of diabetes 2 diabetes (T2D), the core model concerns the prediction of complications. However, reviews of HE models pay little attention to the incorporation of prediction models. The objective of the current review is to investigate how prediction models have been incorporated into HE models of T2D and to identify challenges and possible solutions. METHODS: PubMed, Web of Science, Embase, and Cochrane were searched from January 1, 1997, to November 15, 2022, to identify published HE models for T2D. All models that participated in The Mount Hood Diabetes Simulation Modeling Database or previous challenges were manually searched. Data extraction was performed by two independent authors. Characteristics of HE models, their underlying prediction models, and methods of incorporating prediction models were investigated. RESULTS: The scoping review identified 34 HE models, including a continuous-time object-oriented model (n = 1), discrete-time state transition models (n = 18), and discrete-time discrete event simulation models (n = 15). Published prediction models were often applied to simulate complication risks, such as the UKPDS (n = 20), Framingham (n = 7), BRAVO (n = 2), NDR (n = 2), and RECODe (n = 2). Four methods were identified to combine interdependent prediction models for different complications, including random order evaluation (n = 12), simultaneous evaluation (n = 4), the 'sunflower method' (n = 3), and pre-defined order (n = 1). The remaining studies did not consider interdependency or reported unclearly. CONCLUSIONS: The methodology of integrating prediction models in HE models requires further attention, especially regarding how prediction models are selected, adjusted, and ordered.

A Promising Approach to Optimizing Sequential Treatment Decisions for Depression: Markov Decision Process.

The most appropriate next step in depression treatment after the initial treatment fails is unclear. This study explores the suitability of the Markov decision process for optimizing sequential treatment decisions for depression. We conducted a formal comparison of a Markov decision process approach and mainstream state-transition models as used in health economic decision analysis to clarify differences in the model structure. We performed two reviews: the first to identify existing applications of the Markov decision process in the field of healthcare and the second to identify existing health economic models for depression. We then illustrated the application of a Markov decision process by reformulating an existing health economic model. This provided input for discussing the suitability of a Markov decision process for solving sequential treatment decisions in depression. The Markov decision process and state-transition models differed in terms of flexibility in modeling actions and rewards. In all, 23 applications of a Markov decision process within the context of somatic disease were included, 16 of which concerned sequential treatment decisions. Most existing health economic models relating to depression have a state-transition structure. The example application replicated the health economic model and enabled additional capacity to make dynamic comparisons of more interventions over time than was possible with traditional state-transition models. Markov decision processes have been successfully applied to address sequential treatment-decision problems, although the results have been published mostly in economics journals that are not related to healthcare. One advantage of a Markov decision process compared with state-transition models is that it allows extended action space: the possibility of making dynamic comparisons of different treatments over time. Within the context of depression, although existing state-transition models are too basic to evaluate sequential treatment decisions, the assumptions of a Markov decision process could be satisfied. The Markov decision process could therefore serve as a powerful model for optimizing sequential treatment in depression. This would require a sufficiently elaborate state-transition model at the cohort or patient level.

Non-negative matrix factorization model-based construction for molecular clustering and prognostic assessment of head and neck squamous carcinoma.

Purpose: We aimed at exploring the efficacy of non-negative matrix factorization (NMF) model-based clustering for prognostic assessment of head and neck squamous carcinoma (HNSCC). Methods: The transcriptome microarray data of HNSCC samples were downloaded from The Cancer Genome Atlas (TCGA) and the Shanghai Ninth People's Hospital. R software packages were used to establish NMF clustering, from which relevant prognostic models were developed. Results: Based on NMF, samples were allocated into 2 subgroups. Predictive models were constructed using differentially expressed genes between the two subgroups. The high-risk group was associated with poor prognostic outcomes. Moreover, multi-factor Cox regression analysis revealed that the predictive model was an independent prognostic predictor. Conclusion: The NMF-based prognostic model has the potential for prognostic assessment of HNSCC.

Exploration of Spatio-Temporal Characteristics of Carbon Emissions from Energy Consumption and Their Driving Factors: A Case Analysis of the Yangtze River Delta, China.

For the Yangtze River Delta (YRD) region of China, exploring the spatio-temporal characteristics of carbon emissions from energy consumption (CEECs) and their influencing factors is crucial to achieving carbon peaking and carbon neutrality as soon as possible. In this study, an improved LMDI decomposition model based on the Tapio model and Kaya's equation was proposed. Combined with the improved LMDI and k-means cluster analysis methods, the energy structure, energy intensity, unit industrial output value and population size were selected as the driving factors, and the contribution of each driving factor to the CEECs of prefecture-level cities was quantitatively analyzed. Our study found that: (1) By 2020, the total amount of CEECs in the 26 prefecture-level cities in the YRD will stabilize, while their intensity has shown a downward trend in recent years. (2) The decoupling relationship between CEECs and economic development generally showed a trend from negative decoupling to decoupling. The dominant factor in decoupling was generally the shift of DEL values towards urbanization rate and energy intensity and the open utilization of energy technologies. (3) From 2000 to 2010, the dominant factors affecting CEECs in 26 cities were energy intensity and energy structure, followed by industrial output value and urbanization rate. In general, the promotion effect of economic development on carbon emissions in the YRD region was greater than the inhibitory effect. After 2010, the restrictive effect of various factors on CEECs increased significantly, among which the role of gross industrial output was crucial. The research results can provide a scientific policy basis for the subsequent spatial management and control of carbon emission reduction and carbon neutrality in the YRD region at a finer scale.

Low-Cost and Rapid Method of DNA Extraction from Scaled Fish Blood and Skin Mucus.

PCR-based DNA amplification has been one of the major methods in aquaculture research for decades, although its use outside the modern laboratory environment is limited due to the relatively complex methods and high costs. To this end, we investigated a swabbing and disc protocol for the collection of DNA samples from fish which could extract DNA from fish skin mucus by a non-invasion technique costing only $0.02 (USD) and requiring less than 30 seconds. The disc method that we chose could use the cheap filter paper to extract DNA from above 104 crucian carp blood cells, which is comparable to the commercial kit. By using skin mucus swabbing and the disc method, we can obtain amplification-ready DNA from mucus to distinguish different species from our smallest fish (medaka, ~2.5 cm and crucian carp, ~7 cm) to our biggest fish (tilapia, ~15 cm). Furthermore, the viral pathogen Carassius auratus herpesvirus (CaHV) of crucian carp was detected using our method, which would make performing molecular diagnostic assays achievable in limited-resource settings including aquafarms and aqua stores outside the laboratory environment.