Abstract Background: The novel coronavirus 2 (SARS?CoV?2) pandemic is a pulmonary disease, which leads to cardiac, hematologic, and renal complications. Anticoagulants are used for COVID-19 infected patients because the infection increases the risk of thrombosis. The world health organization (WHO), recommend prophylaxis dose of anticoagulants: (Enoxaparin or unfractionated Heparin for hospitalized patients with COVID-19 disease. This has created an urgent need to identify effective medications for COVID-19 prevention and treatment. The value of COVID-19 treatments is affected by cost-effectiveness analysis (CEA) to inform relative value and how to best maximize social welfare through evidence-based pricing decisions. Objective: compare the clinical outcome and the costs of two anticoagulants (heparin and (enoxaparin)) used to treat hospitalized patients with COVID-19 infection. Patients and method: The study was a retrospective review of medical records of adult, non-pregnant, COVID-19 infected hospitalized patients who had baseline and last outcome measurements at Alamal Epidemiology Center, Al-Najaf city from (Augast 2020 to June 2021). The outcome measures included D-dimer, length of stay (LOS), and mortality rate. Only the cost of the medical treatment was considered in the analysis. The pharmacoeconomics analysis was done in three different cost-effectiveness analysis methods. Microsoft Excel spreadsheet and Statistical Package for the Social Sciences software (SPSS), was used to conduct statistical analysis. Kaplan Meier test was used to compare the mortality rate. T-TEST was used to compare the outcomes of the two groups. Results and discussion: two groups were compared, the first group consists of 72 patients who received heparin, and the second group consists of 72 patients who received enoxaparin. COVID-19 infected patients had a higher abnormal average D-dimer (2534.675 ng/dl). No significant differences between both genders with regards to the basal average D-dimer (males= 2649.95 ng/dl, females= 2374.1mg/dl, P-value>0.05). There was a significant difference between patient's ages 60 years and patients <60. (3177.33 ng/dl, 1763.06 ng/dl, P-value <0.05). It seems that, higher D-dimer levels were associated with a higher mortality rate (died=3166.263 ng/dl, survived= 1729.94 ng/dl, P-value <0.05). Heparin was more effective in decreasing D-dimer levels than enoxaparin which inversely increased the D-dimer levels (-24.4 ng/dl/day, +154.701 ng/dl/day, P-value <0.05). Additionally, heparin was more effective in increasing the survival rate compared to enoxaparin (55% vs, 35%, P-value<0.05). Heparin was associated with a longer duration of stay in hospital than enoxaparin but with no significant difference (13.7 days, 12.3 days, P-value >0.05). Concerning the cost, treatment with heparin cost less than enoxaparin (2.08 U.S $, 9.44 U.S $)/per patient/per day. Conclusion: Originator heparin was a more cost-effective anticoagulant therapy compared to originator enoxaparin, it was associated with a lower cost and better effect, treatment with Heparin resulted in positive INB= 11.3, where a positive result means that heparin is more cost-effective than Enoxaparin. All three methods of pharmacoeconomic analysis decide that heparin was more cost-effective than enoxaparin in treating COVID-19 infected patients.
This paper describes a new proposed structure of the Proportional Integral Derivative (PID) controller based on modified Elman neural network for the DC-DC buck converter system which is used in battery operation of the portable devices. The Dolphin Echolocation Optimization (DEO) algorithm is considered as a perfect on-line tuning technique therefore, it was used for tuning and obtaining the parameters of the modified Elman neural-PID controller to avoid the local minimum problem during learning the proposed controller. Simulation results show that the best weight parameters of the proposed controller, which are taken from the DEO, lead to find the best action and unsaturated state that will stabilize the Buck converter system performan
... Show MoreThe effectiveness of (200 m) of the events of extreme intensity and this is characterized by training in the anaerobic energy system prevailing in the result of this privacy as these are based on the physical abilities and functional indicators identified in this direction and hence the importance of research in the evaluation of training programs on the basis of physical abilities and some indicators of the functionality of the hostile 200 m . The study aimed to: 1. Evaluation of training programs according to physical abilities and some functional indicators of hostile men.The researchers used the descriptive analytical method to suit the nature of the research. The researchers selected them research sample by the deliberate method of the
... Show MoreThis study was conducted in the botanical garden, Department of biology, College of Science/ Mustansiriyah University in from (15 February to 15 March, 2019) under the natural environmental conditions in the greenhouse in order to evaluate the effectiveness of parsley aqueous extract as a promoter for rooting. The study included the use of aqueous extract of a plant Parsley (Petroselinum crispum) extract was used in concentrations (1.25, 2.5 g / l), compare with IBA in concentration (100 mg / L) with dipping time 24 hour for all treatments. The cutting stems were included Rosmarinus officinalis, Nerium oleander, Olea europaea, Plumeria alba, Hibiscus rosa, Pelargonium graveolens, and Myrtus communis. The following measurements were
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This research aims to study the reflection of accounting for contingent assets and liabilities and provisions on Faithful Representation characteristic of accounting information, To achieve this goal has been questionnaire design has been distributed to research sample, which consists of (50) li
... Show MoreA particle swarm optimization algorithm and neural network like self-tuning PID controller for CSTR system is presented. The scheme of the discrete-time PID control structure is based on neural network and tuned the parameters of the PID controller by using a particle swarm optimization PSO technique as a simple and fast training algorithm. The proposed method has advantage that it is not necessary to use a combined structure of identification and decision because it used PSO. Simulation results show the effectiveness of the proposed adaptive PID neural control algorithm in terms of minimum tracking error and smoothness control signal obtained for non-linear dynamical CSTR system.
The question of estimation took a great interest in some engineering, statistical applications, various applied, human sciences, the methods provided by it helped to identify and accurately the many random processes.
In this paper, methods were used through which the reliability function, risk function, and estimation of the distribution parameters were used, and the methods are (Moment Method, Maximum Likelihood Method), where an experimental study was conducted using a simulation method for the purpose of comparing the methods to show which of these methods are competent in practical application This is based on the observations generated from the Rayleigh logarithmic distribution (RL) with sample sizes
... Show MoreThe present study employed the NAG-4SX3-3D analyzer to precisely measure the energy response of the sensor. The goal was to enhance the understanding of this technology by providing expert information about the device. This technology offers an economical, quick, accurate, and sensitive approach. By utilizing the turbidity method, Cyproheptadine hydrochloride (CPH) was quantified in pharmaceutical samples without the need for additional substances. CPH is expected to undergo a direct reaction with calcium hexacyanoferrate, resulting in the formation of white precipitates. The linear range for CPH measurement falls within the range of (0.008–30) mM. The relative standard deviation (RSD) for six repetitions at concentrations of (6 and
... Show MoreChurning of employees from organizations is a serious problem. Turnover or churn of employees within an organization needs to be solved since it has negative impact on the organization. Manual detection of employee churn is quite difficult, so machine learning (ML) algorithms have been frequently used for employee churn detection as well as employee categorization according to turnover. Using Machine learning, only one study looks into the categorization of employees up to date. A novel multi-criterion decision-making approach (MCDM) coupled with DE-PARETO principle has been proposed to categorize employees. This is referred to as SNEC scheme. An AHP-TOPSIS DE-PARETO PRINCIPLE model (AHPTOPDE) has been designed that uses 2-stage MCDM s
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