Long-Term Outcomes of Drug-Coated Balloon Angioplasty in The Treatment of Small Vessel Coronary Artery Disease

Long-Term Outcomes of Drug-Coated Balloon Angioplasty in The Treatment of Small Vessel Coronary Artery Disease Objectives: To determine the outcomes in patients with small-vessel disease (SVD) who underwent percutaneous coronary intervention (PCI) with a drug-coated balloon (DCB) and correlate these adverse outcomes with various risk factors. Methodology: The prospective cohort study was conducted at the Rawalpindi Institute of Cardiology (RIC) from January 2020 to December 2022. After being approved by the Hospital Ethics Committee, fifty-four patients who presented with SVD were enrolled using non-probability consecutive sampling. Written informed consent was obtained from the patients. They were treated with DCB and observed clinically on follow-ups at 15, 30, 60, and 90 days, & later after every 6 months for up to 2 years. Only those patients who presented with symptoms underwent repeat angiography. The outcomes assessed were cardiovascular mortality, myocardial infarction (MI), and target lesion revascularization (TLR). Results: Cardiovascular mortality occurred in 2(3.7%), MI in 3(5.6%) and TLR in 2(3.7%) patients. There was a significant association between cardiovascular mortality, MI, and TLR with diabetes mellitus and BMI. Age was only significantly related to cardiovascular mortality. Conclusion: A drug-coated balloon is an effective and feasible treatment modality for small vessel disease. The incidence of outcomes of cardiovascular mortality, MI, and TLR after DCB is low, making it a safe modality. Advanced age, obesity, and diabetes mellitus alone or with hypertension are the predicting factors of adverse outcomes after DCB in patients with SVD. Keywords: Drug-coated balloon, DCB, Small vessel coronary artery disease, SV

Improved MRO inventory management system in oil and gas company : increased service level and reduced average inventory investment

This study proposes a methodology for the oil and gas businesses to keep their production plant productive with a minimum investment in carrying maintenance, repair, and operating inventory planning. The goal is to assist the exploration and production companies in minimizing the investment in keeping maintenance, repair, and operating (MRO) inventory for improving production plant uptime. The MRO inventory is the most expensive asset and it requires substantial investment. It helps in keeping the oil and gas production plant productive by performing planned and unplanned maintenance activities. A (Q, r) model with a stock-out and backorder cost approach is combined with a continuous inventory review policy for the analysis of class A items of oil and gas production plant MRO inventory. The class A items are identified through popular ABC analysis based on annual dollar volume. The demand for the inventory is modeled through Poisson distribution with consideration of constant lead time. The (Q, r) model in both stock-out cost and backorder cost approaches assigned higher order frequency and lower service level to low annual demand and highly expensive items. The stock-out cost approach shows an 8.88% increase in the average service level and a 56.9% decrease in the company average inventory investment. The backorder cost approach results in a 7.77% increase in average service level and a 57% decrease in average inventory investment in contrast to the company’s existing inventory management system. The results have a direct impact on increasing plant uptime and productivity and reducing company maintenance cost through properly managing maintenance stock. The analysis is carried out on the oil and gas production plant’s MRO inventory data, but it can be applied to other companies’ inventory data as well. All the results reflected in this research are based on the inventory ordering policy of two orders per year. The inventory ordering frequency per year may be other than two orders per year depending on the type of organization

Modeling: Enabler for Sustainable Water Supply & Demand Management (An Overview)

Water supply and demand management (WSDM) is only effective when tackled with holistic system understanding considering social, economic, hydrological, and economic sub-systems. System Dynamics Model (SDM), also known as System Dynamics (SD), which is a Systems Thinking Approach (STA), is actively used for this purpose by water resource analysts. This paper provides a comprehensive review of the application of SDM to water supply and demand management, with a focus on groundwater (GW) sustainability. Further, the quantitative models used in conjunction with SDM are explored. Over sixty nine papers spanning over the last 20 years were analyzed. The quantitative models complemented the SDM includes Agent-Based Modeling (ABM), Bayesian Networking (BN), Analytical Hierarchy Approach (AHP), simulation-optimization M-Objective Optimization (MOO) and solved using Genetic Algorithm (GA), Particle-Swarm-Optimization (PSO) and Non-dominated Sorting Genetic Algorithm (NSGA-II). Although Climate change significantly affects water management strategies, this study revealed that only 51% of the reviewed articles considered it, while the problem conceptualization using the Causal-Loop-Diagram (CLD) is performed by only 58% of the studies. Moreover, 70% of the reviewed articles used the Stock-Flow-Diagram (SFD) to perform the quantitative system analysis. Stakeholder engagement plays a significant role in understanding the consumers’ core issues and divergent views and needs but is incorporated by only 36% of the studies. The key findings for sustainable development in terms of water resource management included, per capita water reduction, water conservation through public awareness campaigns, usage of treated wastewater, adoption of efficient irrigation practices including drip irrigation, cultivation of low33 water consuming crops in water-stressed regions, and regulations to control groundwater over34 exploitation. In future work, developing a hybrid SDM-Optimization framework is suggested to simulate and optimize the dynamic socio-economic interactions and help policymakers devise strategic water planning and management policies that ensure sustainable development

Ten years risk assessment of atherosclerotic cardiovascular disease using Astro-CHARM and pooled cohort equation in a south Asian sub-population

Background: Atherosclerotic cardiovascular diseases (ASCVD) are on the rise in low and middle-income countries attributed to modern sedentary lifestyle and dietary habits. This has led to the need of assessment of the burden of at-risk population so that prevention measures can be developed. The objective of this study was to assess ten years risk assessment of ASCVD using Astro-CHARM and Pooled Cohort Equation (PCE) in a South Asian sub-population.Methods: A total of 386 residents of all six districts of Karachi with no ASCVD were enrolled in the study through an exponential non-discriminative referral snowball sampling technique. The inclusion criteria consisted of age 40 years or above and either gender. Study participants were enrolled after obtaining informed written consent and those study participants who were found to have either congenital heart disease or valvular heart diseases or ischemic heart disease were excluded from the study based on initial screening. For the calculation of 10 years risk of ACVD based on Astro-CHARM and PCE, the variables were obtained including medical history and coronary artery calcium and C-reactive protein measurements.Results: Mean estimated 10-year risk of fatal or non-fatal myocardial infarction or stroke as per the Astro-CHARM was 13.98 ± 8.01%, while mean estimated 10-year risk of fatal or non-fatal myocardial infarction or stroke as per the PCE was 22.26 ± 14.01%. Based on Astro-CHARM, 11.14% of the study participants were labeled as having high risk, while PCE estimated 20.73% of study participants as having high risk of ASCVD.Conclusion: Despite the fact that our findings showed substantial differences in ten-year risk of ASCVD between Astro-CHARM and PCE, both calculators can be used to develop a new population and specific risk estimators for this South Asian sub-population. Our study provides the first step towards developing a risk assessment guided decision-making protocol for primary prevention of ASCVD in this population

Application of exact and multi-heuristic approaches to a sustainable closed loop supply chain network design

Closed-loop supply chains (CLSC) are gaining popularity due to their efficiency in addressing economic, environmental, and social concerns. An important point to ponder in the distribution of CLSC is that imperfect refrigeration and bad road conditions may result in product non-conformance during the transit and thus such products are to be returned to the supply node. This may hinder the level of customer satisfaction. This paper presents a sustainable closed-loop supply chain framework coupled with cross-docking subject to product non-conformance. A cost model is proposed to investigate the economic and environmental aspects of such systems. The transportation cost is analyzed in terms of total carbon emissions. A set of metaheuristics are administered to solve the model and a novel lower bound is proposed to relax the complexity of the proposed model. The results of different size problems are compared with the branch and bound approach and the proposed lower bound. The results indicate that the proposed research framework, mathe-matical model, and heuristic schemes can aid the decision-makers in a closed-loop supply chain context

Infective endocarditis post-transcatheter aortic valve implantation (TAVI), microbiological profile and clinical outcomes: A systematic review.

BACKGROUND:The data on infective endocarditis after transcatheter aortic valve implantation (TAVI) is scarce and limited to case reports and case series in the literature. It is the need of the hour to analyze the available data on post-TAVI infective endocarditis from the available literature. The objectives of this systematic review were to evaluate the incidence of infective endocarditis after transcatheter aortic valve implantation, its microbiological profile and clinical outcomes. It will help us to improve the antibiotic prophylaxis strategies and treatment options for infective endocarditis in the context of TAVI. METHODS:EMBASE, Medline and the CENTRAL trials registry of the Cochrane Collaboration were searched for articles on infective endocarditis in post-TAVI patients till October 2018. Eleven articles were included in the systematic review. The outcomes assessed werethe incidence of infective endocarditis, its microbiological profile andclinical outcomes including major adverse cardiac event (MACE), net adverse clinical event (NACE), surgical intervention and valve-in-valve procedure. RESULTS:The incidence of infective endocarditis varied from 0%-14.3% in the included studies, the mean was3.25%. The average duration of follow-up was 474 days (1.3 years). Enterococci were the most common causative organism isolated from 25.9% of cases followed by Staphylococcus aureus (16.1%) and coagulase-negative Staphylococcus species (14.7%). The mean in-hospital mortality and mortality at follow-up was 29.5% and 29.9%, respectively. The cumulative incidence of heart failure, stroke and major bleeding were 37.1%, 5.3% and 11.3%,respectively. Only a single study by Martinez-Selles et al. reported arrhythmias in 20% cases. The septic shock occurred in 10% and 27.7% post-TAVI infective endocarditis patients according to 2 studies. The surgical intervention and valve-in-valve procedure were reported in 11.4% and 6.4% cases, respectively. CONCLUSION:The incidence of post-TAVI infective endocarditis is low being 3.25% but it is associated with high mortality and complications. The most common complication is heart failure with a cumulative incidence of 37.1%. Enterococciare the most common causative organism isolated from 25.9% of cases followed by Staphylococcus aureus in 16.1% of cases. Appropriate measures should be taken to prevent infective endocarditis in post-TAVI patients including adequate antibiotics prophylaxis directed specifically against these organisms. STUDY REGISTRATION:PROSPERO registration number CRD42018115943

CYCLE TIME OPTIMIZATION FOR IMPERFECT MANUFACTURING SETUP FOCUSING WORK-IN-PROCESS INVENTORY

Imperfect production processes have been focused during recent decades for optimum lot size calculation based on average cost minimization. However, cycle time optimization has been ignored relatively when processes are imperfect and inspection as a process is considered. Furthermore, the role of work-in-process inventory with respect to cycle time has always been signifcant. Hence, this paper integrates work-in-process inventory and imperfect production setup in order to optimize cycle time based on average cost minimization. A mathematical model is developed that incorporate rework operation, rejected products produced, and inspection processes in addition to work-in-process inventory. Cycle time is optimized based on total system cost minimization. Numerical example is also used to illustrate the impact of the developed model as compared to the previously developed model. The impact of work-in-process inventory and processes imperfection on optimum cycle time is highlighted by an example

FACTORS IDENTIFICATION FOR COAL BRIQUETTES MANUFACTURING USING STATISTICAL EXPERIMENTAL DESIGN APPROACH

Coal briquettes are mostly manufactured through conventional methods in developing countries including Pakistan. Shortages of energy resources across the globe have pushed companies to manufacture those products with least possible costs by using signifcant factors. Indeed, the role of statistical design of experiment in general and factorial design in particular is vital in identifying these signifcant factors in comparison to the conventional techniques. This paper provides a statistical approach towards manufacturing of coal briquettes in Northern Province of Pakistan. Binder composition, pressure, particle size, and coal type are analyzed for higher calorifc value and compressive strength simultaneously. Experiments are conducted in order to obtain the response of desired variables for the given three levels of each factor. Full factorial design approach with analysis of variance (ANOVA) is deployed to get the optimum values of the response variables under the given conditions