Projected Health and Economic Burden of Comorbid Gout and Chronic Kidney Disease in a Virtual US Population: A Microsimulation Study.

INTRODUCTION: Gout, a common comorbidity of chronic kidney disease (CKD), is associated with high morbidity and healthcare utilization. However, a large proportion of gout remains undermanaged or untreated which may lead to worse patient outcomes and greater healthcare costs. This study estimates the present and future health and economic burden of controlled and uncontrolled gout in a virtual United States (US) CKD population. METHODS: A validated microsimulation model was used to project the burden of gout in patients with CKD in the USA through 2035. Databases were utilized to build a virtual CKD population of "individuals" with controlled or uncontrolled gout. Modelling assumptions were made on the basis of the literature, which was sparse in some cases. Health and economic outcomes with the current care (baseline) scenario were evaluated, along with potential benefits of urate-lowering intervention scenarios. RESULTS: The prevalence of comorbid gout and CKD in the USA was projected to increase by 29%, from 7.9 million in 2023 to 9.6 million in 2035 in the baseline scenario. Gout flares, tophi, and comorbidity development were also projected to increase markedly through 2035, with the economic burden of gout in the CKD population subsequently increasing from $38.9 billion in 2023 to $47.3 billion in 2035. An increased use of oral urate-lowering therapies in undermanaged patients, and pegloticase use in patients refractory to oral urate-lowering therapies were also project to result in 744,000 and 353,000 fewer uncontrolled gout cases, respectively, by 2035. Marked reductions in complications and costs ensued. CONCLUSIONS: This study projected a substantial increase in comorbid gout and CKD. However, improved use of urate-lowering interventions could mitigate this growth and reduce the health and economic burdens of gout.

A Novel Low-Cost Simulation Model for Point-of-Care Ultrasound Intussusception Practice.

Pediatric intussusception is a relatively common yet serious condition where prompt diagnosis is crucial. Point-of-care ultrasound (POCUS) has proven accurate for diagnosing this disease and can expedite both diagnosis and treatment. Previous research has shown that emergency physicians can diagnose intussusception with acceptable sensitivity and specificity but require prior training in recognizing the pathology. Despite the disease's relative frequency, any individual physician rarely encounters it, making a simulation model vital for learning this ultrasound modality. We created a model using low-cost, easily available components that can be used to train emergency physicians to diagnose intussusception on POCUS.

Analysis of the Accuracy of CAM-type Deformity Resection on a Low-cost Arthroscopic Simulator in a Training Scenario.

Objective To evaluate surgeons' performance in resecting CAM-type deformities using a realistic arthroscopic surgery simulator. Methods An arthroscopic simulator was created using low-cost materials with the help of a GTMax Core A1 3D printer and the programs Invesalius and Meshmixer 2017, which were used to develop femoral head parts in ABS material, with the presence of a CAM-type deformity, to mimic a femoroacetabular impact situation. After the operations were performed by 16 surgeons, the femurs were compared to a previous model with deformity and another without, using Cloudcompare, and parameters such as the volumetric difference between the operated femurs, with and without deformity, the minimum and maximum distance between them, the percentage of the deformity resected, the estimated time for total resection of the deformity, as well as a qualitative analysis based on the images and graphs provided by the program representing the areas of the parts resected, were evaluated at the end. Results The average resection speed was 34.66 mm 3 /min (SD = 46 mm 3 /min, max = 147.33; min = -2.66). The average resection rate was 26.2% (SD = 34.7%, max = 111; min = -2). Qualitative analysis showed hyporesection of deformities and sometimes hyperresection of nondeformed areas. The simulator was highly rated by the surgeons, with a tactile sensation very similar to real surgery, according to them. Conclusion Arthroscopic simulators have proved very useful in training less experienced surgeons.

The Production, Assessment, and Utility of 3D-Printed Video Laryngoscopes in Eastern India: A Low-Cost Alternative to Conventional Video Laryngoscopes.

Introduction Recognizing the limitations of traditional direct laryngoscopes, particularly in difficult airway situations, video laryngoscopy has emerged as a potentially safer and more effective alternative. This study evaluated the utility of two 3D-printed video laryngoscopes: a standard geometry video laryngoscope (SGVL), resembling the traditional Macintosh blade, and a hyper-angulated video laryngoscope (HAVL) with a more curved design. Their performance was compared to a standard Macintosh direct laryngoscope across various intubation parameters. By leveraging the cost-effectiveness of 3D printing with polylactic acid, the study aimed to assess the potential of this technology to improve airway management across diverse clinical settings and varying levels of physician expertise. Methods This prospective randomized crossover study compared the effectiveness of 3D-printed video laryngoscopes (VL) and a standard direct laryngoscope in intubation. After obtaining IRB approval, physicians from various specialties across multiple centers participated. Participants received training on SGVL, HAVL, and DL intubation using an instructional video and hands-on practice. The training was standardized for all participants. The primary outcome measures were time to successful intubation, number of attempts, and time to visualize vocal cords. Participants were randomized to use all three laryngoscopes on a manikin, with a maximum of two attempts per scope. A 30-minute break separated each laryngoscope evaluation. Successful intubation was defined as the single insertion of each laryngoscope and bougie, followed by endotracheal tube placement and confirmation of lung inflation. Results Ninety-eight doctors, mostly from the EM team (73.5%) and ICU team (23.4%). Teams consist of consultants, residents, and medical officers of the concerned departments. Forty-eight of the participants (49%) were novice operators (<25 intubations). Successful first-attempt intubation in those with <1 year of experience with intubation (n=33) was highest for SGVL (97%) compared to DL (82%) and HAVL (67%). Participants who learned intubation through self-directed learning exhibited a higher acceptance of VL and achieved 100% success on their first attempt. Among those who followed modules or workshops, 97% had successful first-attempt intubation with VL. The average time taken to visualize the vocal cords was lower in SGVL compared to DL (5.6 vs. 7.5 seconds) (p<0.001). The HAVL also had a lower average time compared to the DL (7.1 vs. 7.5 secs) (p<0.001). However, the time taken to intubate using DL (24.2 ±8.7 sec) was similar to SGVL (28.1 ±13 sec). Lastly, the intubation time using HAVL was the longest (49.6 ±35.5 sec). The time to intubate with DL and SGVL had Spearman's rho of 0.64 (p<0.001), and DL and HAVL had 0.59 (p<0.001). Conclusions The ease of use and its cost-effective nature make 3D-printed VLs beneficial in situations where traditional VLs may not be available, especially in simulation and training.

Development of peer assessment rubrics in simulation-based learning for advanced cardiac life support skills among medical students.

INTRODUCTION: Peer assessment can enhance understanding of the simulation-based learning (SBL) process and promote feedback, though research on its rubrics remains limited. This study assesses the validity and reliability of a peer assessment rubric and determines the appropriate number of items and raters needed for a reliable assessment in the advanced cardiac life support (ACLS) context. METHODS: Ninety-five third-year medical students participated in the ACLS course and were assessed by two teachers (190 ratings) and three peers (285 ratings). Students rotated roles and were assessed once as a team leader on a ten-item rubric in three domains: electrocardiogram and ACLS skills, management and mechanisms, and affective domains. Messick's validity framework guided the collection of validity evidence. RESULTS: Five sources of validity evidence were collected: (1) content: expert reviews and alpha, beta, and pilot tests for iterative content validation; (2) response process: achieved acceptable peer interrater reliability (intraclass correlation = 0.78, p = 0.001) and a Cronbach's alpha of 0.83; (3) internal structure: demonstrated reliability through generalizability theory, where one peer rater with ten items achieved sufficient reliability (Phi-coefficient = 0.76), and two raters enhanced reliability (Phi-coefficient = 0.85); construct validity was supported by confirmatory factor analysis. (4) Relations to other variables: Peer and teacher ratings were similar. However, peers rated higher in scenario management; further generalizability theory analysis indicated comparable reliability with the same number of teachers. (5) Consequences: Over 80% of students positively perceived peer assessment on a 5-point Likert scale survey. CONCLUSION: This study confirms the validity and reliability of ACLS SBL rubrics while utilizing peers as raters. Rubrics can exhibit clear performance criteria, ensure uniform grading, provide targeted feedback, and promote peer assessment skills.

Virtual Screening, Molecular Dynamics Simulation, and Bioactivity Assessment Validate T13074 as a Dual-Target EGFR/c-Met Inhibitor.

OBJECTIVES: The objective of this study is to identify dual-target inhibitors against EGFR/c-Met through virtual screening, dynamic simulation, and biological activity evaluation. This endeavor is aimed at overcoming the challenge of drug resistance induced by L858R/T790M mutants. METHODS: Active structures were gathered to construct sets of drug molecules. Next, property filtering was applied to the drug structures within the compound library. Active compounds were then identified through virtual screening and cluster analysis. Subsequently, we conducted MTT antitumor activity evaluation and kinase inhibition assays for the active compounds to identify the most promising candidates. Furthermore, AO staining and JC-1 assays were performed on the selected compounds. Ultimately, the preferred compounds underwent molecular docking and molecular dynamics simulation with the EGFR and c-Met proteins, respectively. RESULT: The IC50 of T13074 was determined as 2.446 µM for EGFRL858R/T790M kinase and 7.401 nM for c-Met kinase, underscoring its potential in overcoming EGFRL858R/T790M resistance. Additionally, T13074 exhibited an IC50 of 1.93 µM on the H1975 cell. Results from AO staining and JC-1 assays indicated that T13074 induced tumor cell apoptosis in a concentration-dependent manner. Notably, the binding energy between T13074 and EGFR protein was found to be -90.329 ± 16.680 kJ/mol, while the binding energy with c-Met protein was -139.935 ± 17.414 kJ/mol. CONCLUSION: T13074 exhibited outstanding antitumor activity both in vivo and in vitro, indicating its potential utility as a dual-target EGFR/c-Met inhibitor. This suggests its promising role in overcoming EGFR resistance induced by the L858R/T790M mutation.

Regional policy options for carbon peaking in the Yangtze River Delta under uncertainty.

The Yangtze River Delta (YRD) region plays a crucial role in achieving China's carbon peaking goal. However, due to uncertainties surrounding future economic growth, energy consumption, energy structure, and population, the attainment of carbon peaking in this region remains uncertain. To address this issue, this study utilized the generalized Divisia index method to analyze the driving factors of carbon emissions, including economy, energy, investment, and population. Subsequently, Monte Carlo simulations were combined with scenario analysis to dynamically explore the peak path of regional heterogeneity in the YRD from 2022 to 2035 under uncertain conditions. The findings highlighted that economic uncertainty has the most significant impact on carbon emissions. Furthermore, reducing energy intensity and promoting the transformation of the energy consumption structure contribute to carbon reduction. The study also revealed that the carbon peak in the YRD exhibits regional heterogeneity. According to the baseline scenario, carbon emissions in the YRD will not peak before 2035. However, under the low-carbon development scenario, the carbon emissions of Zhejiang and Shanghai will peak before 2030. Moreover, under the enhanced emission reduction (EE) scenario, carbon emissions in Jiangsu, Zhejiang, and Shanghai will peak before 2025, while Anhui will reach its peak before 2030. Collectively, the entire YRD region is forecasted to attain a carbon emissions peak of 2.29 billion tons by 2025 under the EE scenario. This study provides valuable insights into the carbon emission trajectories of the YRD region under uncertain conditions. The findings can be instrumental in formulating carbon peaking policies that account for regional heterogeneity.

Assessment of longitudinal dispersion and flow resistance near floodplains through riparian woodlands.

Riparian woodlands prevent bank erosions, recycle minerals, sustain biodiversity, act as flow resistance on floodplains, and filter pollutants. The emergent trees characterize woodlands with different spacing arrangements that dictate flow resistance and longitudinal dispersion of the pollutants in compound channel flow. The single- and multistage compound channels exist in urban and natural watercourses with riparian and transplanted trees on different stages of the floodplain. This study numerically validates the planting of vegetation in lines on single- and multistage floodplains using a wall-modeled large-eddy simulation model. Post-validation, the focus of the study was to assess the hydrodynamic behavior and mixing around the floodplain and main channel section of different tested configurations. The approximation of flow structures for the various configurations of tree plantations shows stronger vortices with significant characteristic length scales for floodplains closer to the main channel. The intensity of the secondary current is higher for denser planted trees at junctions of floodplains. For higher flow events, drag force contributions for staged floodplains with trees on both stages are 45-41%, and trees on the top stage contribute 27-22% to the total frictional force budget. The subsequent investigation shows that the in-line trees geometrical configuration and spacing arrangement on the floodplain dictates flow resistance and longitudinal dispersion of the pollutants and contamination in channel flow. The results show that the overall reduction in discharge for floodplains with tree planting is 19.8-36.2% for single-stage and 10.4-23.6% for multistage compound channels. The longitudinal dispersion coefficients for each multi-zone model predict a 61% and 41% dispersion reduction, respectively, in single- and multistage floodplains with planted trees. Floodplains with denser tree spacing have a maximum zonal discharge reduction of 45% for a single-stage and 27.2% and 28.0% for multistage channels. These findings strongly suggest that the planting parameters of spacing-to-diameter ratio and floodplain geometry play a pivotal role in floodplain management from the perspective of contaminant dispersion and flood risk reduction during high-flow events.

Drinking water QMRA and decision-making: Sensitivity of risk to common independence assumptions about model inputs.

When assessing risk posed by waterborne pathogens in drinking water, it is common to use Monte Carlo simulations in Quantitative Microbial Risk Assessment (QMRA). This method accounts for the variables that affect risk and their different values in a given system. A common underlying assumption in such analyses is that all random variables are independent (i.e., one is not associated in any way with another). Although the independence assumption simplifies the analysis, it is not always correct. For example, treatment efficiency can depend on microbial concentrations if changes in microbial concentrations either affect treatment themselves or are associated with water quality changes that affect treatment (e.g., during/after climate shocks like extreme precipitation events or wildfires). Notably, the effects of erroneous assumptions of independence in QMRA have not been widely discussed. Due to the implications of drinking water safety decisions on public health protection, it is critical that risk models accurately reflect the context being studied to meaningfully support decision-making. This work illustrates how dependence between pathogen concentration and either treatment efficiency or water consumption can impact risk estimates using hypothetical scenarios of relevance to drinking water QMRA. It is shown that the mean and variance of risk estimates can change substantially with different degrees of correlation. Data from a water supply system in Calgary, Canada are also used to illustrate the effect of dependence on risk. Recognizing the difficulty of obtaining data to empirically assess dependence, a framework to guide evaluation of the effect of dependence is presented to enhance support for decision making. This work emphasizes the importance of acknowledging and discussing assumptions implicit to models.

Optimizing health risk assessment for soil trace metals under low-precision sampling conditions: A case study of agricultural soil.

Cost limitations often lead to the adoption of lower precision grids for soil sampling in large-scale areas, potentially causing deviations in the observed trace metal (TM) concentrations from their true values. Therefore, in this study, an enhanced Health Risk Assessment (HRA) model was developed by combining Monte Carlo simulation (MCS) and Empirical Bayesian kriging (EBK), aiming to improve the accuracy of health risk assessment under low-precision sampling conditions. The results showed that the increased sampling scale led to an overestimation of the non-carcinogenic risk for children, resulting in potential risks (the maximum Hazard index value was 1.08 and 1.64 at the 500 and 1000 m sampling scales, respectively). EBK model was suitable for predicting soil TM concentrations at large sampling scale, and the predicted concentrations were closer to the actual value. Furthermore, we found that the improved HRA model by combining EBK and MCS effectively reduced the possibility of over- or under-estimation of risk levels due to the increasing sampling size, and enhanced the accuracy and robustness of risk assessment. This study provides an important methodology support for health risk assessment of soil TMs under data limitation.

Developing a dynamic life cycle assessment framework for buildings through integrating building information modeling and building energy modeling program.

The construction and building sector is one of the largest contributors to the global carbon emissions. Therefore, it is imperative to accurately assess the carbon emissions of buildings throughout the life cycle. Many studies conducted life cycle assessment (LCA) of buildings to evaluate carbon emissions. However, due to the lack of dynamic data, most studies adopted the static LCA methodology, which neglected the dynamic variations during life cycle stages of a building. Unlike previous studies that collected static data from questionnaires and documents, the present study aims to establish a novel dynamic life cycle assessment (D-LCA) framework for buildings by incorporating the building information modeling (BIM) and the building energy modeling program (BEMP) into the static LCA. First, a static LCA is established as the baseline scenario that covers the "cradle-to-grave" life cycle stages. A BIM model is established using Revit to obtain the inventory of building materials. The Designer Simulation Toolkit (DeST) is used as a BEMP to simulate the operating energy consumption of the studied building, taking into account changes in energy mix, climate change, and occupant behavior. At the same time, the DeST results are further used as a data input for dynamic scenarios. The D-LCA framework is applied to a high-rise commercial building in China. This study found that the difference between static and dynamic scenarios was up to 66.7 %, mainly reflected in the dynamic energy consumption during the operation phase, indicating the inaccuracy of traditional static LCA. Therefore, a D-LCA by integrating BIM and BEMP can facilitate dynamic modeling and improve the accuracy and reliability of LCA for buildings.

Bioplastic derived from corn stover: Life cycle assessment and artificial intelligence-based analysis of uncertainty and variability.

Exploring feasible and renewable alternatives to reduce dependency on traditional fossil-based plastics is critical for sustainable development. These alternatives can be produced from biomass, which may have large uncertainties and variabilities in the feedstock composition and system parameters. This study develops a modeling framework that integrates cradle-to-grave life cycle assessment (LCA) with a rigorous process model and artificial intelligence (AI) models to conduct uncertainty and variability analyses, which are highly time-consuming to conduct using only the process model. This modeling framework examines polylactic acid (PLA) produced from corn stover in the U.S. An analysis of uncertainty and variability was conducted by performing a Monte Carlo simulation to show the detailed result distributions. Our Monte Carlo simulation results show that the mean life-cycle Global Warming Potential (GWP) of 1 kg PLA is 4.3 kgCO2eq (P5-P95 4.1-4.4) for composting PLA with natural gas combusted for the biorefinery, 3.7 kgCO2eq (P5-P95 3.4-3.9) for incinerating PLA for electricity with natural gas combusted for the biorefinery, and 1.9 kgCO2eq (P5-P95 1.6-2.1) for incinerating PLA for electricity with wood pellets combusted for the biorefinery. Tradeoffs for different environmental impact categories were identified. Based on feedstock composition variations, two AI models were trained: random forest and artificial neural networks. Both AI models demonstrated high prediction accuracy; however, the random forest performed slightly better.

Pyrolytic urban mining of waste printed circuit boards: an enviro-economic analysis.

E-waste, a global environmental concern resulting from supply chain inefficiency, also offers the opportunity to recover valuable materials, including general and rare earth metals. Waste printed circuit boards (WPCBs) are integral components of e-waste that contains substantial amounts of precious metals, making them a valuable waste category. Pyrolysis has emerged as a promising method for material recovery from WPCBs. Hence, pyrolytic urban mining of WPCBs offers an excellent avenue for resource recovery, redirecting valuable materials back into the supply chain. Under the current study, experimental investigation has been conducted to explore the recovery of materials from WPCBs through pyrolysis followed by process simulation, economic analysis, and life cycle assessment (LCA). An Aspen Plus simulation was conducted to model the pyrolysis of WPCBs and subsequent product recovery using a non-equilibrium kinetic model, which represents a unique approach in this study. Another distinct aspect is the comprehensive assessment of environmental and economic sustainability. The economic analysis has been carried out using Aspen economic analyzer whereas the LCA of WPCB pyrolysis has been conducted using the SimaPro software. The experimental investigation reveals yield of solid residues are about 75-84 wt.%, liquid yields of 6-13 wt.%, and gas yields of 4-21 wt.%, which is in well agreement with the Aspen Plus simulation results. The economic analysis for an e-waste pyrolysis plant with an annual feed rate of 2000 t reveals that the total capital cost of a pyrolysis plant is nearly $51.3 million, whereas the total equipment cost is nearly $2.7 million and the total operating cost is nearly $25.6 million. The desired rate of return is 20% per year and the payback period is 6 years with a profitability index of 1.25. From the LCA, the major impact categories are global warming, fossil resource scarcity, ozone formation in human health, ozone formation in terrestrial ecosystems, fine particulate matter formation, and water consumption. The findings of this study can serve as a guideline for e-waste recyclers, researchers, and decision-makers in establishing circular economy.

Multiple scenario land use simulation based on a coupled MOGA-PLUS model: a case of the Yellow River Basin.

Land use changes have profoundly influenced global environmental dynamics. The Yellow River (YR), as the world's fifth-longest river, significantly contributes to regional social and economic growth due to its extensive drainage area, making it a key global player. To ensure ecological stability and coordinate land use demand, modeling the future land allocation patterns of the Yellow River Basin (YRB) will assist in striking a balance between land use functions and the optimization of its spatial design, particularly in water and sand management. In this research, we used a multi-objective genetic algorithm (MOGA) with the PLUS model to simulate several different futures for the YRB's land use between 1990 and 2020 and predict its spatial pattern in 2030. An analysis of the spatiotemporal evolution of land use changes in the YRB indicated that construction land expansion is the primary driver of landscape pattern and structure changes and ecological degradation, with climate change also contributing to the expansion of the watershed area. On the other hand, the multi-scenario simulation, constrained by specific targets, revealed that economic development was mainly reflected in land expansion for construction. At the same time, grassland and woodland were essential pillars to support the region's ecological health, and increasing the development of unused land emerged as a potential pathway towards sustainable development in the region. This study could be used as a template for the long-term growth of other large river basins by elucidating the impacts of human activities on land use and rationalizing land resource allocation under various policy constraints.

In vitro and in silico assessment of antidiabetic and antioxidant potencies of secondary metabolites from Gymnema sylvestre.

This study investigated the chemical constituents, antioxidant potential, and in vitro and in silico antidiabetic activity of Gymnema sylvestre. Column chromatography and spectroscopic techniques identified twelve compounds from the methanol extract, including 4 sterols (1-4), 5 triterpenoids (5-9), and 3 flavonoids (10-12). The chemophenetic significance of all compounds was also investigated. The antioxidant capacity of the extract and compounds (1-4) was evaluated using FRAP and DPPH assays. The extract exhibited strong free radical scavenging activity (IC50 = 48.34 µg/mL), while compounds (1-4) displayed varying degrees of efficacy (IC50 = 98.30-286.13 µg/mL). The FRAP assay indicated significant reducing power for both extract and compounds (58.54, 47.61, 56.61, and 49.11 mg Eq.VitC/g for extract and compounds 1 & 2, 3, and 4, respectively). The antidiabetic potential was assessed through α-amylase and α-glucosidase enzyme inhibition assays. The crude extract demonstrated the most potent inhibition (IC50 = 218.46 and 57.42 µg/mL for α-glucosidase and α-amylase respectively) suggesting its potential for managing postprandial hyperglycaemia. In silico studies employed molecular docking and dynamics simulations to elucidate the interactions between identified compounds and α-amylase/α-glucosidase enzymes. The results revealed promising binding affinities between the compounds and target enzymes, with compound 6 demonstrating the highest predicted inhibitory activity with -10 kcal/mol and -9.1 kcal/mol for α-amylase and α-glucosidase, respectively. This study highlights the presence of diverse bioactive compounds in Gymnema sylvestre. The extract exhibits antioxidant properties and inhibits carbohydrate-digesting enzymes, suggesting its potential as a complementary therapeutic approach for managing hyperglycaemia associated with type 2 diabetes.

A comprehensive assessment of a prototype high ratio antiscatter grid in interventional cardiology using experimental measurements and Monte Carlo simulations.

Objective. To assess the performance of a new antiscatter grid design in interventional cardiology for image quality improvement and dose reduction using experimental measurements and Monte Carlo (MC) simulation.Approach.Experimental measurements were performed on an angiography system, using a multi-layered tissue simulating composite phantom made from of poly(methyl methacrylate), aluminium and expanded polystyrene (2/0.2/0.7 cm). The total phantom thickness ranged from 20.3 cm to 40.6 cm. Four conditions were compared; (A) 105 cm source-image receptor distance (SID) without grid, (Bi) 105 cm SID with grid ratio (r) and strip density (N) (r15N80), (Bii) 120 cm SID without grid, and (Biii) 120 cm SID with high ratio grid (r29N80). The system efficiency (η), defined by the signal-to-noise ratio, was compared from theBconditions against caseA. These conditions were also simulated with MC techniques, allowing additional phantom compositions to be explored. Weighted image quality improvement factor (ηw(u)) was studied experimentally at a specific spatial frequency due to the SID change. Images were simulated with an anthropomorphic chest phantom for the different conditions, and the system efficiency was compared for the different anatomical regions.Main results.Good agreement was found between theηandηw(u) methods using both measured and simulated data, with average relative differences between 2%-11%. CaseBiiiprovided higherηvalues compared toA, andBifor thicknesses larger than 20.3 cm. In addition, caseBiiialso provided higherηvalues for high attenuating areas in the anthropomorphic phantom, such as behind the spine.Significance.The new antiscatter grid design provided higher system efficiency compared to the standard grid for the parameters explored in this work.

The Cost-Effectiveness of Omalizumab for Treatment of Food Allergy.

BACKGROUND: Omalizumab is an anti-IgE therapy newly approved by the Food and Drug Administration for allergen agnostic treatment of single or multiple food allergies in patients aged 1 year or older. OBJECTIVE: Evaluate the cost-effectiveness of omalizumab as a food allergy treatment. METHODS: We evaluated health and economic outcomes in Markov cohorts of simulated food allergic infants randomized to receive omalizumab using a 15-year horizon. Monte Carlo simulation was used (n = 40,000 subjects) to evaluate cost-effectiveness from a societal perspective, incorporating both a family-level and individual-level analysis. We included family-level analysis to incorporate a broad perspective for health utility change, given treatment effects likely benefit all parties at home (eg, caregivers, siblings), not just the patient, representing the sum of changes in all such persons. Supplemental analyses explored lower omalizumab cost and home initiation. We performed deterministic and probabilistic sensitivity analyses. RESULTS: In the family-level cohort analysis, omalizumab exceeded cost-effectiveness thresholds ($185,183/quality-adjusted life-years [QALY]). In a comparison of the omalizumab strategy (OMA) with the non-omalizumab strategy, the cost of OMA exceeded the non-omalizumab strategy ($315,020 vs $136,609) with greater incremental effectiveness (12.668 vs 11.699 QALY). In the individual-level analysis, the cost-effectiveness of OMA was $573,698/QALY. In base-case assessments, OMA was cost-effective (willingness to pay, $100,000/QALY) at a health state utility (HSU) improvement of 0.265. The value-based cost of OMA ranged from $14,166 to $23,791 when it was considered at the individual and family-unit levels. Requiring OMA administration in the clinic was not cost-effective (incremental cost-effectiveness ratio, $260,239). CONCLUSIONS: In the base case and at current pricing, omalizumab is not cost-effective, but it could be at a lower retail price or when use creates large health utility shifts in the family and patient.

Continuous glucose monitoring vs. self-monitoring in pregnant individuals with type 1 diabetes: an economic analysis.

BACKGROUND: In the United States, approximately 1% of pregnancies are complicated by pregestational diabetes. Individuals with type 1 diabetes have an increased risk of adverse maternal and neonatal outcomes. While continuous glucose monitoring has demonstrated benefits for patients with type 1 diabetes, its cost is higher than traditional intermittent fingerstick monitoring, particularly if used only during pregnancy. OBJECTIVE: To develop an economic analysis model to compare in silico the cost of continuous glucose monitoring and self-monitoring of blood glucose in a cohort of pregnant individuals with type 1 diabetes mellitus. STUDY DESIGN: We developed an economic analysis model to compare two glucose monitoring strategies in pregnant individuals with type 1 diabetes: continuous glucose monitoring and self-monitoring. The model considered hypertensive disorders of pregnancy, large for gestational age, cesarean delivery, neonatal intensive care unit (NICU) admission, and neonatal hypoglycemia. The primary outcome was the total cost per strategy in 2022 USD from a health system perspective, with self-monitoring as the reference group. Probabilities, relative risks, and costs were extracted from the literature, and the costs were adjusted to 2022 US dollars. Sensitivity analyses were conducted by varying parameters based on the probability, relative risk, and cost distributions. The robustness of the results was tested through 1000 Monte Carlo simulations. RESULTS: In the base-case analysis, the cost of pregnancy using continuous glucose monitoring was $26,837 compared to $29,039 for self-monitoring, resulting in a cost reduction of $2,202 per individual. The parameters with the greatest effect on the incremental cost included the relative risk of NICU admission, cost of NICU admission, continuous glucose monitoring costs, and usual care costs. Monte Carlo simulations indicated that continuous glucose monitoring was the optimal strategy 98.7% of the time. One-way sensitivity analysis showed that continuous glucose monitoring was more economical if the relative risk of NICU admission with continuous glucose monitoring vs. self-monitoring was below 1.15. CONCLUSION: Compared to self-monitoring, continuous glucose monitoring is an economical strategy for pregnant individuals with type 1 diabetes mellitus.

Cost-effectiveness Analysis of Colorectal Cancer Screening Strategies Using Active Learning and Monte Carlo Simulation.

INTRODUCTION: Detection of colorectal cancer (CRC) in the early stages through available screening tests increases the patient's survival chances. Multimodal screening policies can benefit patients by providing more diverse screening options and balancing the risks and benefits of screening tests. We investigate the cost-effectiveness of a wide variety of multimodal CRC screening policies. METHODS: We developed a Monte Carlo simulation framework to model CRC dynamics. We proposed an innovative calibration process using machine learning models to estimate age- and size-specific adenomatous polyps' progression and regression rates. The proposed approach significantly expedites the model parameter space search. RESULTS: Two multimodal proposed policies (i.e., 1] colonoscopy at 50 y and fecal occult blood test annually between 60 and 75 y and 2] colonoscopy at 50 and 60 y and fecal immunochemical test annually between 70 and 75 y) are identified as efficient frontier policies. Both policies are cost-effective at a willingness to pay of $50,000. Sensitivity analyses were performed to assess the sensitivity of results to a change in screening test costs as well as adherence behavior. The sensitivity analysis results suggest that the proposed policies are mostly robust to the considered changes in screening test costs, as there is a significant overlap between the efficient frontier policies of the baseline and the sensitivity analysis cases. However, the efficient frontier policies were more sensitive to changes in adherence behavior. CONCLUSION: Generally, combining stool-based tests with visual tests will benefit patients with higher life expectancy and a lower expected cost compared with unimodal screening policies. Colonoscopy at younger ages (when the colonoscopy complication risk is lower) and stool-based tests at older ages are shown to be more effective. HIGHLIGHTS: We propose a detailed Markov model to capture the colorectal cancer (CRC) dynamics. The proposed Markov model presents the detailed dynamics of adenomas progression to CRC.We use more than 44,000 colonoscopy reports and available data in the literature to calibrate the proposed Markov model using an innovative approach that leverages machine learning models to expedite the calibration process.We investigate the cost-effectiveness of a wide variety of multimodal CRC screening policies and compare their performances with the current in-practice policies.

A systematic review of the modelling and economic evaluation studies assessing regulatory options for e-cigarette use.

BACKGROUND: Governments around the world are considering regulating access to nicotine e-cigarettes to prevent uptake among youth however people that smoke tobacco may use them to assist with smoking cessation. The health and cost implications of regulating e-cigarette use among populations are unknown but have been explored in modelling studies. We reviewed health economic evaluation and simulation modelling studies that assessed long-term consequences and interpret their potential usefulness for decision-makers. METHODS: A systematic review with a narrative synthesis was undertaken. Six databases were searched for modelling studies evaluating population-level e-cigarette control policies or interventions restricting e-cigarette use versus more liberalized use. Studies were required to report the outcomes of life years, quality-adjusted life years (QALYs) and/or healthcare costs. The quality of the studies was assessed using two quality assessment tools. RESULTS: In total, 15 studies were included with nine for the United States and one each for the United Kingdom, Italy, Australia, Singapore, Canada, and New Zealand. Three studies included cost-utility analyses. Most studies involved health state transition (or Markov) closed cohort models. Many studies had limitations with their model structures, data input quality and transparency, and insufficient analyses handling model uncertainty. Findings were mixed with 11 studies concluding that policies permitting e-cigarette use lead to net benefits and 4 studies concluding net losses in life-years or QALYs and/or healthcare costs.Five studies had industry conflicts of interest. CONCLUSIONS: While authors did conclude net benefit than net harm in more of the studies so far conducted, the significant limitations that we identified with many of the studies in this review, make it uncertain whether or not countries can expect net population harms or benefits of restrictive versus unrestrictive e-cigarette policies. The generalizability of the findings is limited for decision-makers. In light of the deep uncertainty around the health and economic outcomes of e-cigarettes, simulation modelling methods and uncertainty analyses should be strengthened.