Value Of Criteria Research Articles

Risk stratification using the academic research consortium high bleeding risk criteria in patients with atrial fibrillation undergoing percutaneous coronary intervention

Abstract Background Previous studies have reported that the academic research consortium high bleeding risk (ARC-HBR) criteria are useful to predict the risk of bleeding events in patients with coronary artery disease undergoing percutaneous coronary intervention (PCI). However, there are few studies investigating the predictive value of the ARC-HBR criteria in patients with atrial fibrillation (AF) undergoing PCI. Purpose The purpose of this study was to investigate whether the ARC-HBR criteria can be applied to long-term risk stratification in patients with AF undergoing PCI. Methods Patients with AF undergoing PCI at 15 institutions between January 2015 and March 2021 were enrolled. The ARC-HBR score was calculated by assigning 1 point for each major criterion and 0.5 points for each minor criterion. Clinical outcomes within 1 year, including major adverse cardiovascular events (MACE: all-cause death, myocardial infarction, stent thrombosis, and stroke) and major bleeding events (BARC 3 or 5), were evaluated. Results A total of 723 patients were included in this analysis. The best cut-off values of J-HBR score determined by ROC curve analysis to predict MACE and major bleeding events were both 3.0. Of 723 patients, 161 (22.3%) had ARC-HBR score ≥3.0. In Kaplan-Meier curve analyses, the incidence of MACE as well as major bleeding events was significantly higher (log-rank p<0.001 and p=0.010) in patients with ARC-HBR score ≥3.0 compared to those with ARC-HBR score <3 (Figure 1). Conclusion The ARC-HBR score may be useful in assessing the risk of MACE, including thrombotic events, as well as bleeding events in AF patients undergoing PCI.Figure 1

Statistical Models and Evaluation Criteria Used in Poultry Farming

In this thesis study, the statistical models and evaluation criteria used in poultry breeding were examined comprehensively, taking into account live weight gain, egg weight and egg numbers. For this purpose, as an example of live weight increase; 9-week live weight gains of Ross-308 broiler line, as an example of egg weight; The average of 20-week-old egg weights of brown Lohmann laying hens and 9-week egg yields of Japanese quail were used as an example of the number of eggs. In modeling, for live weight gain; 10 different models for egg production; 11 different models and 8 different models for egg weight were considered. In evaluating the models; error mean squares, coefficient of determination, corrected coefficient of determination, Akaike information criterion, corrected Akaike information criterion, Bayesian information criterion, accuracy factor, deviation factor and Durbin-Watson autocorrelation values were taken into consideration. As a result of the study, in terms of live weight gain; The cubic piecewise regression model is the best model in terms of egg yields; It was determined that the modified Compartmental model and the logistic model gave better results than the others in terms of egg weight. The worst models are in live weight gains; Brody, egg yields; It was concluded that there was a quadratic linear and Von Bertalanffy model for egg weight.

Risk Assessment of Urban Water and Energy Supply Using Copula Function: A Water–Energy Nexus Approach in an Arid City

Planning for the future of water and energy supply systems in urban areas requires a thorough assessment of associated risks. In this study, monthly water and energy demand data from 2011 to 2022 in an arid city was used to predict the corresponding demands from 2023 to 2032 using the seasonal auto-regressive integrated moving average (SARIMA) method. The aim is to estimate future water and energy supply risks both individually and jointly, using cumulative distribution functions (CDFs) derived from historical data. The main focus is to calculate the combined risk of water and energy, referred to as the water–energy nexus (WEN) risk. Based on the interdependent relationship between water and energy, the Copula function was utilized to model the bivariate distribution between these two variables. Pearson correlation analysis indicated a strong correlation between water and energy supplies. Among the distributions fitted to the data, the log-normal and gamma distributions were the best fit for water supply and energy supply systems, respectively, with the lowest Akaike information criterion (AIC) values. The Gumbel Copula, with a parameter of 1.66, was identified as the most suitable for modeling the joint distribution, yielding the lowest AIC value. The results indicate that the risks associated with energy supply, water supply, and their joint dependency could exceed 0.8% in the future, highlighting a potentially critical situation for the city. The trend analysis revealed that forecasted water and energy demands and their corresponding risks and the WEN risk are expected to have a significant upward trend in the future. Finally, local authorities need to explore alternative sources to supply water and energy in the future to address the ever-growing water and energy demands.

Effect of chemical modification on hydraulic conductivity of stratified porous media

ABSTRACT Understanding hydraulic conductivity is essential in porous media as it dictates the capacity of fluids to permeate through these substances. This research investigated the impact of chemical modification using fly ash on hydraulic conductivity. The coefficient of hydraulic conductivity along the bedding plane at different angles of orientations was predicted by employing machine learning techniques such as gene expression programming (GEP), artificial neural networks (ANNs), and regression tree (RT), considering various influencing parameters. As the amount of fly ash in the porous medium rises, the hydraulic conductivity decreases. The statistical results demonstrate that the proposed ANN model effectively forecasted the horizontal hydraulic conductivity. It achieved the highest R2 value (0.989), the lowest mean absolute percentage error value (5.772), the lowest scatter index value (0.040), and the lowest Akaike Information Criterion value (−2,359.914) compared to the GEP, RT, and previously established approaches. Moreover, a novel equation has been proposed for determining horizontal hydraulic conductivity, which can be used for any stratified medium, distinguishing this work from previous ones. These findings can inform global practices in mitigating groundwater contamination, enhancing irrigation efficiency, and improving the design of subsurface fluid flow systems, making it a valuable contribution to both academic and practical applications worldwide.

On formal modeling, analysis and optimization of reconfigurable manufacturing systems

ABSTRACT This paper deals with the formal specification and multi-objective optimization of reconfigurable manufacturing systems (RMSs). RMSs are characterized by their dynamic structure, crucial for responding to functional variations, adjusting production capacity and overcoming operational dysfuntions promptly and cos-effectively. The effective utilization of this dynamic capability depends on thorough study and optimization of RMS configurations. To tackle this challenge, a novel formalism called genetic reconfigurable object nets (Gen-RONs) is introduced. Gen-RONs formalism integrates the modeling, verification and reconfiguration capabilities of reconfigurable object nets with advanced multi-objective techniques from genetic algorithms. Within Gen-RONs, Petri nets serve to: (i) encode RMS configurations, (ii) manage RMS scheduling and (iii) employ graph transformation theory rules as genetic algorithm operators for real-time system reconfiguration. Thus, Gen-RONs formalism provides a robust framework for optimizing RMSs using genetic algorithms. To ensure deadlock-free RMS configurations, Gen-RONs incorporate a binary tree-based technique. Furthermore, Taguchi’s method is employed to fine-tune genetic algorithm parameters. The contribution of this paper is demonstrated through a case study involving an RMS and the widely used genetic algorithm NSGA-II. Significant gains in terms of the number of solutions (i.e. configurations) and the criteria values are achieved.

Bridge monitoring using mobile sensing data with traditional system identification techniques

AbstractMobile sensing has emerged as an economically viable alternative to spatially dense stationary sensor networks, leveraging crowdsourced data from today's widespread population of smartphones. Recently, field experiments have demonstrated that using asynchronous crowdsourced mobile sensing data, bridge modal frequencies, and absolute mode shapes (the absolute value of mode shapes, i.e., mode shapes without phase information) can be estimated. However, time‐synchronized data and improved system identification techniques are necessary to estimate frequencies, full mode shapes, and damping ratios within the same context. This paper presents a framework that uses only two time‐synchronous mobile sensors to estimate a spatially dense frequency response matrix. Subsequently, this matrix can be integrated into existing system identification methods and structural health monitoring platforms, including the natural excitation technique eigensystem realization algorithm and frequency domain decomposition. The methodology was tested numerically and using a lab‐scale experiment for long‐span bridges. In the lab‐scale experiment, synchronized smartphones atop carts traverse a model bridge. The resulting cross‐spectrum was analyzed with two system identification methods, and the efficacy of the proposed framework was demonstrated, yielding high accuracy (modal assurance criterion values above 0.94) for the first six modes, including both vertical and torsional. This novel framework combines the monitoring scalability of mobile sensing with user familiarity with traditional system identification techniques.

Analysis of hydrodynamics and thermal–hydraulic performance of twisted angle fins within an annular conduit

AbstractThis paper investigated the influence of various twisted angles of fin inserts integrated on the inner heated pipe wall of a double-pipe heat exchanger by analysing the thermal–hydraulic performance through numerical simulations. Results showed twisted angle fin (TAF) induced turbulent fluid flow phenomena, generating transverse and longitudinal vortices, along with swirling flow. This collaboration between the vortices and swirling flow effectively prevents heat trapping and enhances heat transfer from the inner pipe wall through the intensive fluid mixing. Despite longitudinal swirling vortices and turbulence significantly enhance local and global heat transfer performance, they led to increased pressure drop. However, TAF twisting reduces pressure drop by streamlining flow. The performance evaluation criterion (PEC) value is a dimensionless quantity that facilitates the comprehensive evaluation of optimal configurations by comparing the increment in Nusselt number and the increment in friction factor. PEC values greater than 1 indicate that the increase in Nusselt number exceeded the increase in friction factor. Among tested configurations, the twisted fin angles of 60° (TAF60) exhibited the highest improvement in Nusselt number and friction factor, also achieving the highest PEC of 1.59712 at Reynolds number of 1194.71. TAF40 and TAF50 were identified as optimal configurations for enhancing the thermal–hydraulic efficiency, with average PEC values of 1.26893 and 1.27030, respectively. Overall, the study indicated a consistent enhancement trend with increasing twisted angles and emphasizes the significant thermal performance improvement of TAF configurations compared to the smooth conduit. Furthermore, the results showed a converging tendency across all TAF configurations in the percentage improvement in Nusselt number and friction factor, as well as PEC compared to the baseline No fin configuration with increasing Reynolds number, suggesting that future improvements in thermal–hydraulic performance are more dependent on geometric angles than fluid flow velocity.

Preventive Preservation of Rammed Earth Historical Heritage Through Continuous Monitoring, Architectural Inspections, and Data Fusion

Rammed earth construction, an ancient and sustainable building technique, faces significant preservation challenges, particularly in historical contexts. This study aims to enhance the preventive preservation of rammed earth historical heritage through a comprehensive methodology combining continuous monitoring, architectural inspections, and data fusion. By integrating nondestructive testing techniques such as ultrasound, thermography, and ground-penetrating radar with operational modal analysis and modeling, the proposed approach allows for early detection and assessment of structural vulnerabilities. This methodology was applied to the Tower of Muhammad in the Alhambra of Granada, Spain, demonstrating its effectiveness in identifying and quantifying damage and predicting structural health. Using multi-source data (documentation, inspections, nondestructive tests, and continuous monitoring), a finite element model was built, calibrated (achieving an avg. error in modal frequencies of 1.28% and a minimum modal assurance criterion value of 0.94), and used to develop a surrogate model able to predict the modal properties of the tower in 0.02 s, becoming compatible with continuous system identification. The presented results highlight the importance of continuous data acquisition and advanced diagnostic tools for safeguarding rammed earth structures against environmental and anthropogenic threats. This study advocates for the adoption of digital twins in historical preservation, facilitating informed decision-making and sustainable management of cultural heritage.

Analysis Of Symbolic Value In Purchasing Imitation Louis Vuitton Bags: Economic Sociology Perspective

This research aims to explain the symbolic value in influencing the business of buying imitation Louis Vuitton bags which is seen using Beckert's (2009) four market valuation criteria. Based on a survey conducted by the Indonesian Anti-Counterfeiting Society (MIAP), economic losses due to imitation goods in Indonesia continue to increase every year until reaching a peak in 2014 of 65.1 billion rupiah, in 2020 it was recorded at 291 trillion, with a tax loss of 967 billion rupiah and employment of more than 2 million. Control over counterfeit goods is getting stricter. As explained by Cicilia King, Communications Manager for Louis Vuitton (Indonesia), especially in Europe, the company provides education, including to officers at airports, so that they are able to identify whether an item is genuine or fake. Louis Vuitton, according to various records, is the most counterfeited famous brand ( Kompas.com ). Young consumers are increasingly buying imitation products from luxury brands. Because late childhood is a time of searching for identity and a time of change (Asyia et al., 2022; Sofianita, 2015). This research uses Beckert's theory in the article The social order of markets (2009). Researchers used a qualitative approach with a case study type of research. The findings in this research explain that market valuation criteria consisting of standardization, cognitive anchoring, normative legitimacy, and social positioning are explained in this case study. KEYWORDS : Symbolic Value, Imitation, Louis Vuitton, Qualitative, Case Study

Hemophagocytic Lymphohistiocytosis (HLH): A Clinical and Pathological Grading System Based on the Presence of Hemophagocytosis

Abstract Introduction/Objective Hemophagocytic lymphohistiocytosis (HLH) is a heterogeneous group of disorders resulting from uncontrolled immune activation leading to severe hyperinflammation. The syndrome can be primary (genetic) or secondary to infections, malignancies, or autoimmune diseases. The diagnosis of HLH is challenging due to its nonspecific clinical presentation and the overlap with other conditions. This study aims to establish a reliable diagnostic approach for HLH by evaluating the accuracy of bone marrow histomorphological criteria in diagnosing the disease. Methods/Case Report We conducted a retrospective analysis of clinical and pathological data from patients diagnosed with HLH over a 12year period and included 38 patients with suspected HLH. A grading system for hemophagocytosis was developed based on the extent and frequency of hemophagocytic activity observed in bone marrow biopsies. Hemophagocytosis is categorized into four grades: Grade 0 indicates its absence, Grade 1 describes mild hemophagocytosis with less than 2 histiocytes containing hemophagocytosis per slide, Grade 2 denotes moderate hemophagocytosis with 3 to 5 histiocytes per slide, and Grade 3 signifies severe hemophagocytosis with more than 5 histiocytes per slide. Clinical data, comprising laboratory parameters and treatment outcomes, were analyzed in relation to the histologic grading of hemophagocytosis. Results (if a Case Study enter NA) Among the cases, grade 1 had 1 resolved case, 4 cases meeting 2 criteria all resolved, and 13 cases meeting 4 or more criteria resulted in 5 deaths and 8 resolutions. Grade 2 included 10 cases, with 2 meeting 2 criteria and resolving, and 8 meeting 4 or more criteria resulting in 5 deaths and 3 resolutions. Grade 3 comprised 10 cases, with 3 meeting 3 criteria and resolving, 3 meeting 5 or 7 criteria resulting in 1 death and 2 resolutions each, and 4 meeting 6 or 8 criteria resulting in 2 deaths and 2 resolutions each. Conclusion In our retrospective analysis of bone marrow biopsies from 38 patients with suspected HLH, our results indicate that the presence and extent of hemophagocytosis strongly suggest HLH. Implementing these criteria significantly improved diagnostic accuracy, reducing misdiagnosis rates and enabling timely therapy initiation. This study underscores the value of bone marrow histomorphological criteria in diagnosing HLH and stresses their importance in the standard diagnostic process for suspected HLH cases.

Time-series forecasting of particulate organic carbon on the Sunda Shelf: Comparative performance of the SARIMA and SARIMAX models

Conducting in-depth studies of carbon dynamics in the Southeast Asia’s Sunda Shelf waters is challenging. Particulate organic carbon (POC) is a key component that can be monitored in the region, but ocean assessment requires advanced research and POC monitoring, especially in relation to ocean dynamics and forecasts. Accurate forecasting of POC in marine environments is difficult due to the complexity of oceanic processes and the influence of various environmental factors. Statistical forecasting models such as Seasonal Autoregressive Integrated Moving Average (SARIMA) or SARIMA with Exogenous Factors (SARIMAX) are useful for this purpose. This study compares these two time-series forecasting models to assess the role of exogenous factors in predicting POC variability in Indonesian seas. The models were specified as SARIMA (3, 1, 3)x(2, 0, 0, 60) and SARIMAX (3, 1, 3)x(2, 0, 0, 60). We obtained Akaike Information Criterion (AIC) values of 1237.767 for the SARIMA model and 1207.341 for SARIMAX[exog=SST]. The SARIMA model's validation metrics were 6.94 % for MAPE, 10.80 for RMSE, and 0.65 for the correlation coefficient, outperforming the SARIMAX model. While SARIMAX incorporates additional environmental variables, SARIMA outperforms it based on MAPE, RMSE, and correlation coefficients. Our findings reveal that only sea surface temperature can significantly influence POC forecasts, thus providing a new perspective on oceanic carbon dynamics. From 2022–2030, POC levels are expected to range between 108.3 and 135.9 mg/m³, with a mean value of 120.9±5.4 mg/m³, lower than that observed from 2002 to 2022, which was 118.8±11.9 mg/m³. The highest peak in POC is predicted for the end of 2026 and 2027. The annual trend shows that the highest POC values correspond to the northwest monsoon season, with the lowest during the intermonsoon period.

Non-linear programming model proposal for mutual support distance of air defence systems

With the advancements in technology, the deployment of air defence systems required for the defence of a country after procurement is considered as an important problem in terms of defence effectiveness. It is seen that criteria such as coverage, strike effectiveness and logistics network are taken into account while deploying. In addition, principles such as remote countermeasures, defence in depth and all-round defence are also taken into account. In this study, two different deployment models are proposed for point and area air defence. In this model, the optimum deployment distance at which other systems can support each other in addition to a deployed air defence system is determined. In the nonlinear target programming model proposed for point air defence, the number of missiles is considered to be reasonably balanced for perimeter defence, while for area defence, the nonlinear optimization problem is addressed by calculating the equally important coverage and strike effectiveness criteria values. In this study, it is observed that the approach based on mutual support distance has been used for the first time in the defence literature. According to the results obtained, it is observed that this proposed model for determining the mutual support distance solves the deployment problem optimally.

Assessment of heart rate measurements by commercial wearable fitness trackers for early identification of metabolic syndrome risk

Metabolic syndrome increases the risks of cardiovascular diseases, type 2 diabetes, and certain cancers. The early detection of metabolic syndrome is clinically relevant, as it enables timely and targeted interventions. In the current study, we aimed to investigate the association between metabolic syndrome and heart rate measured using wearable devices in a real-world setting and compare this association with that for clinical resting heart rate. Data from 564 middle-aged adults who wore wearable devices for at least 7 days with a minimum daily wear time of 20 h were analyzed. The results showed significantly elevated all-day, sleeping, minimum, and inactive heart rates in men with pre-metabolic or metabolic syndrome compared with those in normal individuals, whereas sleeping heart rate and heart rate dips were significantly increased and decreased, respectively, in women with metabolic syndrome. After adjusting for confounders, every 10-beats-per-minute increment in all-day, sleeping, minimum, and inactive heart rates in men corresponded to odds ratios of 2.80 (95% confidence interval 1.53–5.44), 3.06 (1.57–6.40), 4.21 (1.87–10.47), and 3.09 (1.64–6.29), respectively, for the presence of pre-metabolic or metabolic syndrome. In women, the association was significant only for heart rate dips (odds ratio = 0.49 [95% confidence interval 0.25–0.96] for every 10% increment). Models incorporating inactive or minimum heart rate in men and heart rate dip in women demonstrated better fits, as indicated by lower Akaike information criterion values (170.3 in men and 364.9 in women), compared with models that included clinical resting heart rate (173.4 in men and 369.1 in women). These findings suggest that the heart rate indices obtained from wearable devices may facilitate early identification of metabolic syndrome.

Uterine layers hypervascularization in atypical placentation: the comparison of magnetic resonance imaging with vascular pathomorphology

Rationale: One in five women worldwide delivers through cesarean section, which is associated to a high rate of placenta previa and abnormal placenta attachment to the uterine wall. The grade of placenta accreta spectrum (PAS) correlates with blood loss volume, which could be related to vascularization characteristics. Up to now, there have been no studies on the diagnostic value of magnetic resonance criteria for hypervascularization of the uterine wall and their correlation with an assumed grade of PAS according to the International Federation of Gynecology and Obstetrics (FIGO) classification. Also, abnormal vessels location and their wall structure have not been studied with state-of-the-art pathomorphological methods. Aim: To develop a classification for various types of the uterine wall hypervascularization depending on the depth of placental invasion assessed by magnetic resonance imaging (MRI). Methods: We retrospectively analyzed medical files of 66 patients aged 18 to 45 years, who were assumed to have PAS based on their sonography results. To clarify the extent and localization of the placental invasion, all patients had MRI performed at 24 to 32 weeks of gestation. In all patients, the PAS grade was verified pathologically; in 30 of them (45,5%), a detailed pathological examination was additionally performed. The PAS grades were classified according to Morbidly Adherent Placenta Imaging Reporting and Data System (MAPI-RADS). The MRI data were correlated with the PAS (FIGO) grade estimated from intraoperative data and with intraoperative blood loss. At the final study step, the MRI data was correlated with abnormal pathomorphology, with the assessment of the degree of vascularization and the visual picture of abnormal uteroplacental vasculature. Results: We have proposed a classification of MRI signs of hypervascularization in the lower uterine segment correlating with the depth of placenta accreta. Type 1. Single small vessels in the myometrium, medium caliber arteries in the projection of the uterine serosa (normal variation for the 3rd trimester of gestation). Type 2. Numerous small confluent vessels, mainly in the uteroplacental region, and retroplacental hematomas (typical for placenta accreta, or FIGO PAS 1). Type 3. Intrauterine hypervascularization with a deficient myometrium thickness, predominantly vessels of the middle layer (typical for placenta increta, or FIGO PAS 2). Type 4. Thinning of the lower uterine segment due to significant bulging of the placenta in the presence of curved anastomosing vessels of vast caliber over 4 mm (typical for placenta increta – FIGO PAS 2, as well as placenta percreta – FIGO PAS 3a). Type 5. Hypervascularization outside the uterus, over its surface and in the parametrial tissues: at the border with the bladder, uterine isthmus, including signs of fibrosis and growing into the posterior bladder wall (typical for various grades of placenta percreta – FIGO PAS 3b, 3c). Conclusion: The proposed classification of uterine wall hypervascularization in accordance with the grades of placenta accreta spectrum (FIGO PAS) could be useful for its practical implementation by radiologists.

Biweight midcorrelation-based CRITIC method: a case study for electrification of BIPV in Iran

Criteria weights are essential in various multi-criteria decision-making (MCDM) approaches. The amount of weight indicates the criterion's importance, and the performance of MCDM techniques depends on the correct estimation of criteria weights and criteria amount in the decision matrix. The distance correlation-based CRiteria Importance Through Inter-criteria Correlation (CRITIC) technique is a modified version of the CRITIC method. Since Pearson's correlation is sensitive to noisy and outlier data, this paper proposes using the biweight midcorrelation as a robust alternative to Pearson's correlation. The weights obtained from the proposed biweight midcorrelation method make using the full range of MCDM techniques possible. This study examined the performance of the proposed method in comparison with eight criteria weighting techniques on the electric supply for a Building-Integrated PhotoVoltaic (BIPV) problem. Results from three different tests (i.e. distance correlation, Spearman rank-order correlation, and symmetric mean absolute percentage error (sMAPE)) indicated that the proposed method could produce more valid criteria weights and ranks than other methods. The value of the sMAPE criterion for the proposed method is 0.1096. Sensitivity analysis also revealed that the proposed method provides more robust criteria weights and ranks with a larger decision matrix.

A large-scale supplier evaluation approach for circular economy in the presence of circular criteria interactions and weight consistency

Circular economy (CE) is an economic model in which we achieve sustainable development through resource recovery, reuse, and remanufacturing. Large-scale supplier evaluation is crucial for ensuring the sustainability of the CE supply chain and efficient utilization of resources. Especially, criterion interaction and consistency of criterion weights are two key factors of large suppliers’ evaluation in CE. However, current research often overlooks these key factors, this study proposes a large-scale supplier evaluation approach in CE to address these issues. The novel aspects of the proposed approach come with considering the interaction between circular and non-circular criteria, as well as eliminating the impact of large-scale complex information on the consistency of criterion weights. Firstly, large-scale hesitant evaluation information is fused by evidence reasoning, and interaction rules between circular and non-circular criteria are established. Then, the interaction weights of the criteria are obtained based on the interaction of circular criteria, and the comprehensive criteria weights are determined by an improved best-worst method. Next, the decision makers’ weights are generated by the utility value of the circular criterion. Finally, the results of numerical example and analysis show that 86% of the supplier ranking results are stable, and the consistency of the proposed approach is 0.9757, indicating that the proposed approach exhibits high validity and reliability. It emphasizes the significance of the supplier’s circular ability in CE and reduces the interference of large-scale complex information on the consistency of evaluation results.

Heatwave and upper urinary tract stones morbidity: effect modification by heatwave definitions, disease subtypes, and vulnerable populations.

As heatwave occurs with increased frequency and intensity, the disease burden for urolithiasis, a heat-specific disease, will increase. However, heatwave effect on urolithiasis subtypes morbidity and optimal heatwave definition for urolithiasis remain unclear. Distributed lagged linear models were used to assess the associations between 32 defined heatwave and upper urinary tract stones morbidity. Relative risk (RR) and attributable fraction (AF) of upper urinary tract stone morbidity associated with heatwave of different intensities (low, middle, and high) were pooled by meta-analysis. Optimal heatwave definition was selected based on the combined score of AF, RR, and quasi-Akaike Information Criterion (QAIC) value. Stratified analyses were conducted to investigate the modification effects of gender, age, and disease subtypes. Association between heatwave and upper urinary tract stones morbidity was mainly for ureteral calculus, and AF was highest for low-intensity heatwave. This study's optimal heatwave was defined as average temperature > 93rd percentile for ≥ 2 consecutive days, with AF of 7.40% (95% CI:2.02%, 11.27%). Heatwave was associated with ureteral calculus morbidity in males and middle-aged adults. While heatwave effect was statistically insignificant in females and other age groups. Managers should develop appropriate definitions to address heatwave based on regional characteristics and focus on heatwave effects on urolithiasis.

Nomogram based on burn characteristics and the national early warning score to predict survival in severely burned patients

BackgroundExtensive burns are associated with a high mortality rate. Early prediction and action can reduce mortality. The National Early Warning Score (NEWS) is considered the best early warning score for predicting mortality. However, there has been no assessment conducted on the clinical prognostic significance of NEWS in individuals suffering from severe burns. The objective of this research was to establish a nomogram based on burn characteristics and the NEWS to predict survival in severely burned patients. MethodsA retrospective analysis was performed on 335 patients diagnosed with extensive burns from 2005 to 2021 in the Department of Burn Surgery of XX Hospital. Univariate and multivariate analyses were used to determine independent prognostic factors. A nomogram was developed using these prognostic factors and its internal validity was assessed through bootstrap resampling. ResultsThe results of multivariate analysis showed that the independent factors affecting the prognosis of severe burn patients were age, full-thickness burn, creatinine, absorptive injury, tracheotomy, and the NEWS, all of which were identified to create the nomogram. The Akaike Information Criterion and Bayesian Information Criterion values of the nomogram demonstrated superior goodness-of-fit in predicting severe burns compared to NEWS, with lower scores (195.21 vs. 201.24; 221.91 vs. 224.12, respectively). The bootstrap-adjusted concordance index (C-index) of the nomogram yielded a higher value of 0.923 (95% CI 0.892–0.953), compared to NEWS which had a C-index of 0.699 (95% CI 0.628–0.770). The calibration curves demonstrated excellent agreement between predicted probabilities and observed outcomes in the nomogram analysis. Furthermore, decision curve analysis indicated promising clinical utility for the proposed nomogram model. By applying an appropriate cutoff value derived from receiver operating characteristics curve analysis, it was observed that the high-risk group identified by the nomogram exhibited a significantly higher mortality rate than the low-risk group. ConclusionThis study introduces an innovative nomogram that predicts the survival rate of individuals with severe burn injuries by combining clinical attributes and laboratory examinations, demonstrating superior efficacy compared to conventional NEWS systems.

Predictive Value of Current KDIGO CKD Screening Criteria in Women and Men across Ethnic Groups: The HELIUS Study

Predictive Value of Current KDIGO CKD Screening Criteria in Women and Men across Ethnic Groups: The HELIUS Study

Vegetation productivity determines the response of butterflies along elevation gradients in the trans‐Himalayas, Nepal

AbstractEnvironmental parameters along elevational gradients affect the number of butterflies and the variety of species. However, which variables play significant roles and how they operate can be difficult to untangle. Here, we examine the relationships between observed butterfly richness (overall and subgroups) at different elevation gradients and remotely sensed environmental variables (vegetation productivity, surface temperature, landscape heterogeneity, and moisture stress) using generalized linear models. We surveyed butterflies with a fixed‐point count method in 19 elevation bands within 1600–5200 m above sea level in Manang district, trans‐Himalayan region, north‐central Nepal. The number of butterflies in each elevation band was studied and estimated, then interpolated across the lowest and highest elevation to estimate butterfly species richness. Then, the selection of models was performed on butterfly richness and elevations to test the best model support based on the lowest value of the Akaike information criterion and a multimodel averaging for other environmental variables. Altogether, 94 butterfly species, representing 20 subfamilies and six families, were recorded throughout the study periods. We obtained cubic model support for overall species richness, Papilionidae, and Hesperiidae, quadratic to Nymphalidae and Pieridae, and the linear model to Lycaenidae. In our study, vegetation productivity was found to have a significant positive impact on butterfly communities. Our study further suggests species richness of Papilionidae and Hesperiidae has a strong positive correlation with surface temperature and landscape heterogeneity and negative associations with moisture stress but other subgroups of butterfly communities including overall species richness showed insignificant relationships with these variables. This study provides significant information related to the responses of montane butterflies to environmental variables along elevational gradients from the Himalayas Nepal. However, further detailed studies on the functional behaviors of butterflies potentially offer more insights into their distribution patterns and ecological relationship in the montane environment.