Measure Model Research Articles

Intermittent documentation of blood pressure values does not provide comprehensive evaluation of the hemodynamic response during continuous intravenous medication administration

Blood pressure (BP) is a dynamic measure that is frequently discussed in static terms. There exist many limitations in current documentation systems whereby documented BP values may not be reflective of the dynamic variability of BP. This study used an observational, prospective, non-randomized study design to examine the variability in BP response during intravenous vasoactive medication administration in an intensive care unit setting. Subjects admitted to a neuroscience intensive care unit were monitored continuously during a 12-hour period. The BP values include systolic BP, diastolic BP, and mean arterial pressure. Intermittent values from an intra-arterial figurecatheter (a-line) and continuously sampled values from an a-line obtained using continuous data acquisition (CDA) software, were compared to intermittently sampling of cuff-based BP measurements documented in the medical record. The 30 patients provided 1,220,511 BP observations from CDA, 944 from a-line documentation, and 416 from cuff-based BP documentation. The systolic BP was used as a goal parameter for 23 (77%) of the patients. Repeated measures models demonstrated that on average cuff-based differed from intermittent a-line and from CDA (p < .005) for all BP values. No differences between a-line and CDA were observed. Concordance correlation coefficients ranged from 0.56 to 0.72 for a-line, cuff-based BP, and CDA, indicating moderate agreement. Using intermittently documented BP values does not fully represent the dynamic nature of BP over time.

Psychopathology trajectories and relapse in first episode schizophrenia with assured long-acting injectable adherence over 24 months.

Relapse following a first episode of schizophrenia (FES) is common and often results in serious adverse psychosocial consequences. Treatment non-adherence is a key risk factor for relapse, but why relapse occurs despite antipsychotic treatment adherence remains unclear. This study examined the differences in FES psychopathology trajectories over 24-months with assured long-acting injectable antipsychotic (LAIA) treatment, to control for treatment adherence between those who relapsed and those who did not and what moderates these group differences. We collected clinical and socio-demographic data from 107 participants with FES treated with LAIA medication over a 24-month period. Relapse was defined using the modified Csernansky criteria. Substance use was assessed through participant and family interviews and urine toxicology. Linear mixed model repeated measures models were constructed to (1) compare psychopathology trajectories over 24months between relapse versus non-relapse groups (2) to examine factors moderating differential trajectories between the groups. Positive symptom trajectories were significantly worse in the relapse compared to non-relapse group over 24months (F(8, 649=3.29), p=0.001). More severe childhood trauma (CT), in particular physical abuse (PA) (F(39, 298=1.78), p=0.004), was associated with worse positive symptom trajectories over 24months in those who experienced a relapse event. Our findings suggest that the examination of a history of CT and, in particular childhood PA measures for relapse in individuals with FES, is important.

Effectiveness Trade-Off Between Green Spaces and Built-Up Land: Evaluating Trade-Off Efficiency and Its Drivers in an Expanding City

Urban expansion encroaches on green spaces and weakens ecosystem services, potentially leading to a trade-off between ecological conditions and socio-economic growth. Effectively coordinating the two elements is essential for achieving sustainable development goals at the urban scale. However, few studies have measured urban–ecological linkage in terms of trade-off. In this study, we propose a framework by linking the degraded ecological conditions and urban land use efficiency from a return on investment perspective. Taking a rapidly expanding city as a case study, we comprehensively quantified urban–ecological conditions in four aspects: urban heat island, flood regulating service, habitat quality, and carbon sequestration. These conditions were assessed on 1 km2 grids, along with urban land use efficiency at the same spatial scale. We employed the slack-based measure model to evaluate trade-off efficiency and applied the geo-detector method to identify its driving factors. Our findings reveal that while urban–ecological conditions in Zhengzhou’s periphery degraded over the past two decades, the inner city showed improvement in urban heat island and carbon sequestration. Trade-off efficiency exhibited an overall upward trend during 2000–2020, despite initial declines in some inner city areas. Interaction detection demonstrates significant synergistic effects between pairs of drivers, such as the Normalized Difference Vegetation Index and building height, and the number of patches of green spaces and the patch cohesion index of built-up land, with q-values of 0.298 and 0.137, respectively. In light of the spatiotemporal trend of trade-off efficiency and its drivers, we propose adaptive management strategies. The framework could serve as guidance to assist decision-makers and urban planners in monitoring urban–ecological conditions in the context of urban expansion.

Spatio-temporal Evolution of Carbon Emissions and Emission Reduction Paths in the Northern Farming-pastoral Ecotone

The farming-pastoral ecotone has an important strategic place in the energy supply and ecological layout of China. Thus, exploring the spatial and temporal variation characteristics of carbon emissions in this region will help to deeply understand the information on the historical carbon emissions in China's energy production bases and provide data references for the formulation of differentiated emission reduction policies and the promotion of regional energy-saving and carbon-reducing measures, which is of great significance for the realization of low-carbon economic development. This study constructed a spatialization model of carbon emissions based on land use, night lighting, and provincial energy consumption data； explored the spatiotemporal changes and aggregation characteristics of carbon emissions in the farming-pastoral ecotone from 1995 to 2020 using the global Moran's index and hotspot analysis； and then combined it with the slack-based measure model to calculate the carbon emission efficiency and emission reduction potential of each city from 2010 to 2020 and classify cities to propose a differentiated emission reduction path. The results showed that, firstly, the estimated results at the prefectural city level of the carbon emission spatialization model constructed in this study with multi-source data could reach an R2 of 0.92 for a linear fit. Secondly, the total carbon emissions in the farming-pastoral ecotone increased from 176.29 million tons in 1995 to 1 014.51 million tons in 2020. However, the carbon emission intensity and growth rate both decreased, which was related to adjusting the energy structure and improving energy efficiency. Regarding spatial distribution, the cities with high carbon emissions over time were Datong, Baotou, and Yulin in order. Thirdly, the carbon emissions in the study area showed a significant global spatial positive correlation at the county level, with the hot spots mainly located at the junction of Shanxi, Shaanxi, and Inner Mongolia, while the cold spots were extended from Yanan City to Qingyang and Guyuan City after 2010. Finally, based on the differences in carbon emission efficiency and reduction potential, cities could be classified into four types： "high-efficiency and high potential," "low-efficiency and high potential," "high-efficiency and low potential," and "low-efficiency and low potential" to implement targeted emission reduction strategies.

Analysis of the impact of salt reduction interventions on primary school students' parents based on the home-school interaction model

To analyze the impact of salt reduction interventions on the knowledge, attitude and behavior regarding the salt reduction of students' parents based on the home-school interaction model. In April 2021, parents of students in grades 3-5 from three primary schools in Yichang City were selected as the target population using a cluster sampling method, and the parent population was divided into an intervention group and a control group. In the intervention group, a comprehensive home-school interaction salt reduction intervention was implemented, and in the control group, no intervention measures were taken for students' parents. Baseline and final surveys were conducted before and after the intervention period, which included general information, previous salt reduction interventions received, and salt reduction knowledge, attitude and behavior. Difference-in-difference (DID) method was used to compare the knowledge, attitude and behavior status of two groups before and after the intervention, and stratified analysis of parents with different literacy levels was conducted to assess the net effect of intervention implementation. The results showed that 740 parents completed the baseline and final surveys, with 231 in the intervention group and 509 in the control group. After propensity score matching, there were 231 (33.33%) in the intervention group and 462 (66.67%) in the control group. After the intervention, the proportion of the intervention group who obtained salt control spoons and pots, as well as salt reduction knowledge and advice through school, was 87.45%, 86.58% and 75.45%, respectively, which was significantly higher than that in the control group (P<0.05). After the intervention, the proportion of parents with a high school and lower education who obtained salt control pots was higher in the intervention group (89.23%) than in the control group (74.49%), with significant differences (P<0.05). The proportion of parents with a college degree or above who obtained salt control spoons and pots, as well as salt reduction knowledge and advice through school, was higher than that of the control group (P<0.05). The results of DID method showed that after controlling for monthly income and other factors, the scores of parents' salt reduction-related knowledge and low-salt behavior in the intervention group increased significantly higher than those in the control group, with DID values (95%CI) of 1.18 (0.15-2.21) and 0.62 (0.16-1.09), respectively, indicating a significant net effect of intervention implication. After stratification according to the education level of parents, this difference still existed in the college degree or above group, with DID values (95%CI) of 1.39 (0.13-2.66) and 0.76 (0.16-1.36), respectively. The home-school interaction model for salt reduction measures can improve the salt-related knowledge and low-salt behavioral choices of students' parents.

A study on the correlation between green economy development and foreign investment based on regression analysis

ABSTRACT This study examined the association between foreign direct investment (FDI) and green economic development using data from 30 Chinese provinces and cities between 2011 and 2020. The green economy development efficiency (GEDE) was measured using the super-slacks-based measure (SBM) model, and a regression model was established. The regression analysis revealed that FDI significantly positively affected GEDE, with statistical significance at the 1% level. Among the control variables, gross domestic product (GDP), IS, and UR had positive effects, but informatisation level (INF) had a negative effect. Even after considering the moderating effect, FDI still demonstrated a significant positive impact on GEDE. The coefficient of the interaction term HCFDI was −0.3356, significant at the 10% level, and the coefficient of GOVFDI was 0.0187, significant at the 5% level.

The Mega-MUSCLES Treasury Survey: X-Ray to Infrared Spectral Energy Distributions of a Representative Sample of M Dwarfs

We present 5–1 × 107 Å spectral energy distributions (SEDs) for 12 M dwarf stars covering spectral types M0–M8. Our SEDs are provided for community use as a sequel to the Measurements of the Ultraviolet Spectral Characteristics of Low-mass Exoplanetary Systems (MUSCLES) survey. The 12 stars include eight known exoplanet hosts and four stars chosen to fill out key parameter space in spectral type and rotation period. The SEDs are constructed from Hubble Space Telescope ultraviolet spectroscopy and XMM Newton, Chandra, and/or Swift X-ray observations, and completed with various model data, including Lyα reconstructions, PHOENIX optical models, APEC coronal models, and differential emission measure models in the currently-unobservable extreme ultraviolet. We provide a complete overview of the Mega-MUSCLES program, including a description of the observations, models, and SED construction. The SEDs are available as MAST high-level science products and we describe the various data products here. We also present ensemble measurements from our sample that are of particular relevance to exoplanet science, including the high-energy fluxes in the habitable zone and the far-ultraviolet to near-ultraviolet ratio. Combined with MUSCLES, Mega-MUSCLES provides SEDs covering a wide range of M dwarf spectral types and ages such that suitable proxies for any M dwarf planet host of interest may be found in our sample. However, we find that ultraviolet and X-ray fluxes can vary even between stars with similar parameters, such that observations of each exoplanet host star will remain the gold standard for interpreting exoplanet atmosphere observations.

Metropolitan Construction Carbon Emission Efficiency: An Integrative Static-Dynamic Analytical Framework

Abstract Taking urgent action to combat climate change and promote sustainable cities are part of the 17 Sustainable Development Goals, which demand immediate action from all countries. Enhancing the carbon emission efficiency of the construction industry (CICEE) from the "static-dynamic" perspective is crucial in addressing climate change. This study utilized the super slack-based measure model to analyze static efficiency. The Malmquist-Luenberger index model, multiple non-linear regression model, and principal component analysis were used to research the driving factors dynamically. Factors included technical change (TC), pure technical efficiency change (PEC), and scale efficiency change (SEC), which were subdivided into 21 variables. The panel data was from 11 cities in Zhejiang from 2007 to 2019. The results indicated that the static efficiency values were generally effective, but in 2019, more than half of the cities experienced an average decrease of 52%. Efficiency levels were higher in northern Zhejiang and lower in the southeastern region. CICEE values over one were primarily attributed to high TC levels and stable PEC and SEC conditions. Additionally, a generalized framework for improving CICEE was constructed, assisting policymakers in identifying reasons for low CICEE and providing targeted strategies to reduce emissions and increase efficiency.&amp;#xD;

Benchmarking performance in Targhee sheep in development of a genetic reference flock

Abstract The Targhee breed is important to range sheep production in the Western U.S. The objective of this research was to integrate industry sires participating in national genetic evaluation through the National Sheep Improvement Program (NSIP) into the U.S. Sheep Experiment Station (USSES) flock, where the breed originated, to benchmark sire performance. Estimated breeding values (EBV) of industry sires (n = 16) and USSES sires (n = 12) from the 2023 NSIP Targhee genetic evaluation differed (P &amp;lt; 0.05) only for the NSIP Number Born EBV. This difference, and small (nonsignificant) differences favoring industry sires for maternal weaning weight, yearling fiber diameter, and yearling staple length EBV also resulted in greater (P &amp;lt; 0.05) Western Range Index scores for industry sires. The performance of sires’ direct progeny born 2016 to 2018 was compared for 17 traits. After data cleaning, there were 664 progeny (417 from industry sires and 247 from USSES sires) with 146 to 664 records per trait. Least squares means differed (P &amp;lt; 0.05) for grease fleece weight, side fiber diameter, and britch fiber diameter in favor of the industry sires. Production traits were measured from the progeny and other retained descendants of both sire genetic groups from 2016 through 2022. After data cleaning, there was a range of 1,138 to 1,493 records per trait. A three-generation pedigree was constructed and the proportional assignment of each lamb to each genetic group (e.g., 0.5 industry, 0.5 USSES) was included in an augmented relationship matrix. A univariate animal model was fitted for each lamb trait and a repeated measures model for each of the three ewe traits was fitted to estimate variance components and predict breeding values. Genetic group solutions did not differ (P &amp;gt; 0.05) for any of these traits but provided a means by which to compare the two groups. Establishment of a Targhee genetic reference flock at USSES has been initiated, which can be used to address issues of importance to the industry.

Environmental efficiency assessment of coastal ports in China: Implications for sustainable port management.

By employing Data Envelopment Analysis (DEA) with Slacks-Based Measure (SBM) and DEA-Undesirable Output models, this study aims to investigate the operational and environmental efficiency of 26 major ports across China's Special Economic Zones (SEZs). Focusing on the interplay between operation performance and environmental sustainability, this research evaluates how well these ports manage their operational activities while minimizing their environmental impact. The results indicate that the ports in the Yangtze River Delta, Pearl River Delta, and Southwest Coast significantly outperform others. These ports benefit from advanced infrastructural setups and operational capabilities that enhance throughput while adhering to environmental standards. This study underscores the importance of integrating sustainable practices and green technologies into port operations, suggesting that such integration not only reduces ecological footprints but also bolsters efficiency. It highlights areas where ports lag in efficiency and proposes targeted interventions to enhance environmental and operational outcomes. By identifying the correlation between high efficiency scores and low CO2 emissions, this paper presents a compelling argument for adopting more stringent environmental measures in port management practices, thereby aligning port operations with global sustainability goals.

Validating the Q1.6 Inguinal Hernia application using prospective data from a randomised clinical trial.

The Q1.6 Inguinal Hernia application remotely and continuously collects patient-reported outcomes from inguinal hernia patients. Previous research has explored its technical, legal, and ethical aspects, along with face, content, and construct validity assessments. This study aims to examine its concurrent validity by comparing prospective data with that from the ENTREPPMENT trial, a randomised study. A small cohort of patients participating in the ENTREPPMENT trial were asked to use the Q1.6 application in addition to their standard care. Corresponding prospective data points, in terms of content and timing relative to the operation date, were identified. Correlation coefficients were calculated for matching variables, and a repeated measures model was created to analyse pain and limitation measures during the first two postoperative weeks. Twenty-eight patients were analysed. Preoperative variables, such as hernia side and painkiller use, demonstrated a predominantly high level of agreement between the two measurement methods, ranging from 'substantial' (0.61-0.8) to 'perfect' (1.0) agreement. Evaluating immediate postoperative outcomes, including pain and limitation scores, revealed a prevalent 'substantial' (0.61-0.8) to 'almost perfect' (0.81-1.0) agreement. In a repeated measures model, the overall within-subjects correlation demonstrated levels of agreement ranging from 'moderate' (0.41-0.6) to 'almost perfect' (0.81-1.0). This study demonstrates strong agreement between data from the Q1.6 Inguinal Hernia application and the ENTREPPMENT trial, supporting its concurrent validity. This makes the application a reliable tool for collecting PROs before and immediately after inguinal hernia repair, offering a promising alternative to traditional follow-up methods. Future research will focus on enhancing compliance and refining functionality.

An Empirical Study on the Impact of Local Financial Capacity on the Supply Efficiency of Ecological Public Goods

Improving the quality and level of ecological public goods supply is crucial for enhancing the public happiness index and ensuring ecological welfare. A high-quality ecological environment generates significant positive externalities, making the provision of such goods a key focus of government expenditure. The ability of local governments to adequately fund the supply of ecological public goods depends on the strength of their financial capacity. Based on the panel data of 30 provincial-level regions in China from 2007 to 2019, this paper uses the super-efficiency Slack-Based Measure (SBM) model and the dynamic Malmquist index to measure the supply efficiency of provincial-level regional ecological public goods including undesirable outputs. Furthermore, the panel Tobit model and the system Generalized Method of Moments (GMM) model are used to empirically test the impact of local fiscal capacity on the supply efficiency of ecological public goods. The results show that fiscal absorption capacity can significantly improve the supply efficiency of ecological public goods, and the economic growth preference of fiscal allocation capacity can also significantly improve the supply efficiency of ecological public goods, indicating that under the influence of the current economic structure transformation and ecological civilization construction, the distortion of local governments in the supply of public goods has been improved, while the administrative consumption preference of fiscal allocation capacity hinders the improvement of the supply efficiency of ecological public goods, and the fiscal self-sufficiency has a lag in improving the supply efficiency of ecological public goods. Fiscal transfer payments have significantly improved the efficiency of the supply of ecological public goods.

Analysis of Carbon Emission Driving Factors and Decoupling Effects in the Textile Industry of the Demonstration Zone of Green and Integrated Ecological Development of the Yangtze River Delta

The textile industry is one of the pillar industries in the Yangtze River Delta Region and its green and low-carbon transformation is important for supporting the high-quality development of the Yangtze River Delta. Considering the demonstration zone of green and integrated ecological development of the Yangtze River Delta as an example, this integrated study was conducted on the carbon emission inventory of the textile industry, the driving factors of carbon emissions in the industry, and decoupling effects. Based on the emission factor method, the carbon emissions of Scope 1 and 2 of the textile industry in the demonstration zone were estimated. The carbon emission efficiency of the industry was analyzed using the super efficiency slack-based measure （SBM） model with unexpected outputs. Combining the LMDI factor decomposition method and Tapio decoupling analysis, the driving factors of carbon emissions in the textile industry in the demonstration zone and the decoupling situation between emissions and economic development were identified. The results indicated： ① Between 2014 and 2021, the carbon emissions of the textile industry in the demonstration zone showed a fluctuating trend, reaching the highest value in 2019 at 9.19 million tons of CO2 equivalent. Wujiang District was the primary emission area, with electricity, heat, and coal consumption emissions being the top three emission sources. ② The overall carbon emission efficiency of the textile industry in the demonstration zone showed an upward trend； however, significant differences were present in carbon emission efficiency between regions, with Jiashan County having considerable room for improvement in carbon emission efficiency. ③ Between 2014 and 2021, the driving factors of carbon emissions in the textile industry in various regions of the demonstration zone showed significant changes, with the level of economic development being a positive driving factor affecting carbon emissions. ④ In terms of the decoupling status between carbon emissions and economic development, the overall textile industry in the demonstration zone showed a transition from negative decoupling to decoupling status between 2014 and 2016. The research results provide a scientific basis for the future balanced development of the green and low-carbon transformation of the textile industry and the high-quality development of the economy in the demonstration zone.

Spatial Correlation Network Characteristics and Influencing Factors of Industrial Carbon Emission Efficiency of Cities in Pearl River Basin

China has experienced rapid development of urbanization and industrialization, and urban industrial carbon reduction has become the key to green and sustainable development. Exploring urban industrial carbon emissions and its spatial correlation characteristics is of great importance for promoting collaborative cooperation between cities and achieving the "dual carbon" goal. Considering 49 cities in the Pearl River Basin as research objects, the super slacks-based measure model was used to measure the urban industrial carbon emission efficiency from 2010 to 2020, and exploratory spatiotemporal data analysis was used to explore its spatial pattern. On this basis, we used social network analysis and quadratic assignment procedure （QAP） methods to explore the spatial correlation network characteristics and influencing factors of urban industrial carbon emission efficiency. The results indicated that the industrial carbon emission efficiency of the Pearl River Basin showed a downward trend. Additionally, a strong spatial imbalance and heterogeneity was observed. The Pearl River Delta Region always dominated the spatial correlation network of carbon emission efficiency, forming a multi-level composite network system with the core network as the primary component and the conventional network as the auxiliary component. Economically developed cities, such as Guangzhou, Shenzhen, and Dongguan have long been in the center of the network and have extensive connections with other cities, while playing an intermediary role. The level of urbanization, science and technology, and industrialization have an increasingly significant positive impact on the strength of the connection between urban industrial carbon emission networks. The Pearl River Basin industrial carbon emission efficiency network has significant individual differences and hierarchical characteristics. According to the individual centrality, network role, and clustering characteristics, combined with the corresponding influencing factors, the Pearl River Basin urban collaborative carbon emission reduction strategy was formulated. This study can provide reference for the formulation and implementation of regional low-carbon collaborative development strategies.

Does green finance promote the improvement of regional eco-efficiency? Direct and spillover effects

IntroductionGreen finance plays a pivotal role in advancing China’s ecological civilization construction and achieving sustainable economic and social development.MethodsUsing panel data from 30 provinces in China from 2009 to 2021, this study applies the entropy weighting method and the super-efficiency slack-based measure (Super-SBM) model to assess the levels of green finance and eco-efficiency in each province. Employing spatial statistical methods such as the spatial standard deviation ellipse (SSDE) and the spatial Markov chain, the study reveals the spatiotemporal evolution characteristics of green finance and eco-efficiency. Additionally, the spatial Durbin model is used to analyze the direct effects, spatial spillover effects, and spatial heterogeneity features of green finance on regional eco-efficiency.ResultsThe results show that (1) From 2009 to 2021, green finance and regional eco-efficiency levels exhibited an overall upward trend, though with notable spatiotemporal differences. (2) The direct and spatial spillover effects of green finance on regional eco-efficiency followed a notable inverted U–shaped relationship. However, in most provinces, green finance levels had not yet reached the turning point during the study period, and the impact of green finance on regional eco-efficiency remained largely positive. (3) The effects of green finance on regional eco-efficiency showed considerable structural differences due to regional heterogeneity, with the strongest effects observed in the Eastern regions.DiscussionThis study provides policymakers with strategies to enhance regional eco-efficiency through the development of green finance, offering valuable insights for promoting ecological civilization construction and achieving sustainable development.

Measuring the Ecoefficiency of Tourism in Typical Tourist Cities and Analyzing the Influencing Factors—Anhui Huangshan City as an Example

To protect the environment, promote sustainable tourism, and enhance the quality and efficiency of the tourism industry, accounting for and identifying the ecological efficiency of tourism is crucial. In this study, we constructed a scientific measurement system for assessing the ecological efficiency of tourism in Huangshan City from 2011 to 2022 using a Super-SBM (slack-based measure) model and a Tobit regression model. Our findings revealed the following: (1) The overall trend in the total efficiency in Huangshan City fluctuated considerably during the period under study but demonstrated an overall positive trend of development. Scale efficiency mostly showed consistent annual improvement, while pure technical efficiency remained relatively stable. (2) Economic, social, environmental, and human-resource- and transportation-related factors all exerted significant positive influences on the ecological efficiency of tourism in Huangshan City. Based on these results, in aiming to enhance the ecological efficiency of tourism in Huangshan City, comprehensively considering multiple factors, such as the economy, society, the environment, human resources, and transportation, is recommended. Attention should be paid to balancing industrial expansion with technological innovation while simultaneously investing in the development of education and human resources. Emphasis should also be placed on protecting and improving the environment alongside efforts to improve capabilities in technological innovation and the level of management. The research findings presented in this article offer a valuable theoretical underpinning, as well as practical guidance for Huangshan City and other representative tourist destinations on how they can enhance the efficiency of their tourism ecosystems, thereby facilitating high-quality and sustainable development within the tourism industry.

Navigating Asia's sustainable growth trajectory: a cross-regional comparative analysis.

This study examined the green total factor productivity (GTFP), technical progress change (GTC), and technical efficiency change (GEC) trajectories across 39 Asian countries from 2006 to 2021. GTFP was assessed across five Asian regions using the global Malmquist-Luenberger (GML) index with a slacks-based measure model and directional distance function. The results of the study show that West Asia, with a mean GTFP value of 1.0011, is ahead of Southeast Asia and South Asia, while Central and East Asia show room for improvement. Gini index analysis further shows that GTFP varies significantly within and outside the region, with large fluctuations especially in Southeast Asia and South Asia. GTC stagnated significantly in 2009 and 2015, indicating a bottleneck in technological progress, while GEC showed a positive upward trend, reflecting the improvement in resource efficiency. The 'decoupling' of GTC and GEC highlights the inconsistency between efficiency growth and the pace of technological progress, particularly in East and Central Asia. In 2021, Asia's average GTFP reaches 1.0048, signaling the region's progress towards sustainable productivity. This study provides important theoretical and practical implications by quantifying the regional differences in GTFP, GTC, and GEC, which provide a quantitative basis and decision-making reference for the formulation of green development policies in the Asian region.

Stepwise identification of prodromal dementia: Testing a practical model for primary care.

Prodromal dementia is largely underdiagnosed in primary care. To develop a clinical model for detecting prodromal dementia within the operative boundaries of primary care practice. The study employed the Functional Activities Questionnaire (FAQ) and Montreal Cognitive Assessment (MoCA) to evaluate a "functional-cognitive" step-down screening model, in which the MoCA is administered subsequent to reported symptoms on the FAQ. It classified participants from the Alzheimer's Disease Imaging Initiative to three diagnostic categories: (1) healthy cognition (n = 396), (2) mild cognitive impairment without conversion (n = 430), and (3) prodromal dementia assessed 24 months before diagnosis (n = 164). Analyses indicated that the step-down model (Model 1) performed significantly better than an alternative model that applied the FAQ as a single measure (Model 2) and compared well with another model that administered both screening measures to all participants (Model 3). Gradient Boosting Trees classifications yielded the following estimations for Model 1/Model 2/ Model 3, respectively: Sensitivity = 0.87/0.77/0.89, Specificity = 0.68/0.47/0.70, PPV = 0.73/0.40/0.75, NVP = 0.84/0.81/0.87, F1 Score = 0.79/0.52/0.81, AUC = 0.78/0.67/0.79. These analyses support the proposed model. The study offers algorithms for validated measures, which were developed from a well characterized clinical sample. Their accuracy will likely improve further with new data from diverse clinical settings. These results can serve primary care in a timely manner in light of the recent advances in pharmacological treatment of dementia and the expected increase in demand for screening.

HSD108 Impact of Predictive Modelling and Application of Preventative Measures in Reducing Fall Rates in Domiciliary Care

HSD108 Impact of Predictive Modelling and Application of Preventative Measures in Reducing Fall Rates in Domiciliary Care

Comparison of IL-6, IL-10, and TNFα Levels Between PLWHIV With and Without Kaposi Sarcoma and Healthy Controls.

Kaposi sarcoma (KS) is an angioproliferative disease caused by human herpesvirus 8 and is mediated by cytokines in an immunodeficient environment. This study aimed to compare IL-6, IL-10, and TNFα levels among patients with AIDS with disseminated KS (DKS), treatment naïve patients living with HIV without DKS, and healthy controls. Secondary outcomes were to compare cytokines levels in patients with DKS and unfavorable outcomes, and an analysis of the behavior of cytokines over time. This cohort study was performed at 2 centers in Mexico City. Three groups were included. Group 1: HIV+ treatment naïve with DKS, group 2: HIV+ treatment naïve without KS, and group 3: HIV negative, healthy controls. Plasmatic IL-6, IL-10, and TNFα levels were measured at baseline and over time in groups 1 and 2. Seventy-six patients were included: 39 (52%) in group 1, 17 (22%) in group 2, and 20 (26%) in group 3. The median baseline IL-6, IL-10, and TNFα levels were significantly higher in group 1. In group 1, baseline IL-6 was higher in patients who died than in survivors (14.4 vs 5.8 pg/mL P = 0.048). Patients with severe immune reconstitution inflammatory syndrome because of KS had higher IL-6 values than those without it (14.4 vs 5.8 pg/mL P = 0.004). In the repeated measures model in group 1, IL-10 levels were higher in patients who died ( P < 0.001) and developed immune reconstitution inflammatory syndrome-KS ( P = 0.01). IL-6, IL-10, and TNF α levels were markedly higher in patients with DKS. IL-6 and IL-10 levels were higher in patients with unfavorable outcomes.