Online pharmacies are an important part of the modern healthcare system. They interact with customers through well-designed web interfaces to deliver the healthcare customers need. In addition to well-designed web interfaces, online pharmacies rely on an effective supply chain system to provide medical supplies and services, and especially effective inventory management for supply systems. As green supply chain management (GSCM) becomes increasingly considered by countries, how to develop a sustainable inventory model that takes into account the revenue growth of an online pharmacy while preventing waste and reducing energy costs has become very important. In line with this trend, the study develops a sustainable inventory model that focuses on both economic aspect (profit) and environmental aspect (losses from excessive inventory) within a framework of a single period multi-product inventory model. Specifically, the sustainable inventory model applies the visual-attention-dependent demand (VADD) rate to characterize customer demand in an online trading environment, thereby seeking a profitable marketing strategy and reducing losses due to excessive inventory. Since the complexity of model optimization will drastically increase due to the inclusion of many products in the problem, a Genetic Algorithm (GA) based solution procedure is proposed to increase the feasibility of the proposed model in solving real problems. The sustainable inventory model and the solution procedure are illustrated, compared, and discussed with an online pharmacy example. Additionally, a sensitivity analysis is formulated to study the influence of model parameters on the model solution, the loss of unsold inventory that results in a waste of resources and energy, and the profit of online pharmacies.

Lower LVEF, larger scar and/or more dyssynchrony assessed by MPS were related to the development of ventricular arrhythmia for patients with CRT, and further defibrillator implantation may be considered for these patients.

The characteristics of cardiac reverse remodeling after CRT as assessed by MPI are associated with the prevalence of ventricular arrhythmia.

For patients with coronary artery disease, larger scar burdens are associated with higher risk of ventricular arrhythmia. Left ventricular (LV) dyssynchrony is associated with increased risk of sudden cardiac death in patients with heart failure. The purpose of this study was to assess the values of LV dyssynchrony and myocardial scar assessed by myocardial perfusion SPECT (MPS) in predicting the development of ventricular arrhythmia in ischemic cardiomyopathy.Twenty-two patients (16 males, mean age: 66 ± 13) with irreversible ischemic cardiomyopathy received cardiac resynchronization therapy (CRT) for at least 12 months were enrolled for MPS. Quantitative parameters, including LV dyssynchrony with phase standard deviation (phase SD) and bandwidth, left ventricular ejection fraction (LVEF), and scar (% of total areas), were generated by Emory Cardiac Toolbox. Ventricular tachycardia (VT) and ventricular fibrillation (VF) recorded in the CRT device during follow-up were used as the reference standard of diagnosing ventricular arrhythmia. Stepwise logistic regression analysis was performed for determining the independent predictors of VT/VF and receiver operating characteristic (ROC) curve analysis was used for generating the optimal cut-off values for predicting VT/VF.Nine (41%) of the 22 patients developed VT/VF during the follow-up periods. Patients with VT/VF had significantly lower LVEF, larger scar, larger phase SD, and larger bandwidth (all P < 0.05). Logistic regression analysis showed LVEF and bandwidth were independent predictors of VT/VF. ROC curve analysis showed the areas under the curves were 0.71 and 0.83 for LVEF and bandwidth, respectively. The optimal cut-off values were <36% and > 139° for LVEF and bandwidth, respectively. The sensitivity, specificity, positive predictive value, and negative predictive value were 100%, 39%, 53%, and 100%, respectively, for LVEF; and were 78%, 92%, 88%, and 86%, respectively, for bandwidth.LV dyssynchrony as assessed by phase analysis of MPS is helpful for predicting ventricular arrhythmia in ischemic cardiomyopathy after CRT. Further implantation of defibrillator may be considered for those patients with bandwidth >139°.

The characteristics of myocardial substrates as assessed by MPI differed significantly between different levels of cardiac RR post-CRT. Myocardial scar played an important role in the development of ERR. Different cardiac RR levels contributed to different incidences of ventricular arrhythmia, and the combination of ERR and MRR provided highest anti-arrhythmic effects.

This study attempts to investigate whether healthcare expenditures (HCE) are related to economic growth in China using a newly developed Bootstrap autoregressive distributed lag (ARDL) test for China over the period of 1990–2019. To avoid omitted variable bias, we use the ratio of the population of 65 years old over the total population (aging ratio) as a control variable. Empirical result indicates that no cointegration among these three variables. Granger causality test based on Bootstrap ARDL model demonstrates that one-way Granger causality running from HCE to aging ratio and from economic growth to both HCE and aging ratio. Empirical results have important policy implications for China understudy

The paper considers the causal relationship about CO2 emissions, traffic density and urbanization development in China's provinces by the quantile causality test The method can capture the structural breaks under different quantiles from the nonlinear perspective. The robust results don't find the causality relationship between traffic density and CO2 emissions. Urbanization will increase CO2 emission at the high quantile level while the impact of CO2 emissions on urbanization presents a symmetric relationship. The promoting effect of transportation on urbanization only occurs at the beginning of urbanization. It shows the environmental pollution is a key factor to the whole process of urbanization. With the advancement of urbanization, the increase of traffic line density has no significant impact on the urbanization process. The results can provide references for the government in the layout of local traffic lines and the improvement of urbanization.

Objective: Heart rate serves as a critical prognostic factor in heart failure patients. We hypothesize that elevated heart rate in critically ill heart failure patients upon discharge from the intensive care unit (ICU) could be linked to adverse outcomes. Design: We implemented a retrospective cohort study using data collected between 2008 and 2019 from the Medical Information Mart for Intensive Care IV (MIMIC-IV version 2.0) database. We examined the association between the last heart rate prior to ICU discharge and in-hospital mortality, total mortality, and ICU readmission. Setting: ICU at Beth Israel Deaconess Medical Center Patients: Adult patients admitted to the ICU diagnosed with heart failure. Interventions: None Measurements and Main Results: From the 76,943 ICU stays, we enrolled 2,365 patients in this study. We observed correlations between in-hospital mortality and ICU discharge heart rate of 83.56±15.81 bpm (survivors) vs. 93.84±17.28 bpm (nonsurvivors, p<0.001). Total mortality showed similar trends, with 83.67±15.36 bpm (survivors) vs. 85.23±17.25 bpm (nonsurvivors, p=0.027), as did ICU readmissions at 83.55±15.77 bpm (nonreadmitted) vs. 88.64±17.49 bpm (readmitted, p<0.001). Given multivariate analysis, the ICU discharge heart rate strongly predicted in-hospital mortality (OR 1.035 [95% CI 1.024-1.046], p < 0.001), total mortality (OR 1.007 [95% CI 1.001-1.014], p = 0.027) and ICU readmission (OR 1.015 [95% CI 1.007-1.023], p < 0.001). Patients with an ICU discharge heart rate >90 bpm demonstrated significantly higher in-hospital mortality (OR 2.986 [95% CI 2.066-4.315], p < 0.001), total mortality (OR 1.341 [95% CI 1.083-1.661], p = 0.007), and ICU readmission rates (OR 1.638 [95% CI 1.270-2.114], p < 0.001). Conclusions: The findings suggest that heart failure patients with an elevated heart rate (>90 bpm) at ICU discharge are more likely to experience increased in-hospital mortality, total mortality, and ICU readmissions, indicating potential negative outcomes.