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.
Churning 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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Magnetic abrasive finishing (MAF) is one of the advanced finishing processes, which produces a high level of surface quality and is primarily controlled by a magnetic field. This paper study the effect of the magnetic abrasive finishing system on the material removal rate (MRR) and surface roughness (Ra) in terms of magnetic abrasive finishing system for eight of input parameters, and three levels according to Taguchi array (L27) and using the regression model to analysis the output (results). These parameters are the (Poles geometry angle, Gap between the two magnetic poles, Grain size powder, Doze of the ferromagnetic abrasive powder, DC current, Workpiece velocity, Magnetic poles velocity, and Finishi
... Show MoreThe complexity and partially defined nature of jet grouting make it hard to predict the performance of grouted piles. So the trials of cement injection at a location with similar soil properties as the erecting site are necessary to assess the performance of the grouted piles. Nevertheless, instead of executing trial-injected piles at the pilot site, which wastes money, time, and effort, the laboratory cement injection devices are essential alternatives for evaluating soil injection ability. This study assesses the performance of a low-pressure laboratory grouting device by improving loose sandy soil injected using binders formed of Silica Fume (SF) as a chemical admixture (10% of Ordinary Portland Cement OPC mass) to di
... Show MoreA novel fractal design scheme has been introduced in this paper to generate microstrip bandpass filter designs with miniaturized sizes for wireless applications. The presented fractal scheme is based on Minkowski-like prefractal geometry. The space-filling property and self-similarity of this fractal geometry has found to produce reduced size symmetrical structures corresponding to the successive iteration levels. The resulting filter designs are with sizes suitable for use in modern wireless communication systems. The performance of each of the generated bandpass filter structures up to the 2nd iteration has been analyzed using a method of moments (MoM) based software IE3D, which is widely adopted in microwave research and in
... Show MoreThe Neutron Fermi Age, t, and the neutron slowing down density, q (r, t) , have been measured for some materials such as Graphite and Iron by using gamma spectrometry system UCS-30 with NaI (Tl) detector. This technique was applied for Graphite and Iron materials by using Indium foils covered by Cadmium and the measurements done at the Indium resonance of 1.46 eV. These materials are exposed to a plane 241Am/Be neutron source with recent activity 38 mCi. The measurements of the Fermi Age were found to be t = 297 ± 21 cm2 for Graphite, t = 400 ± 28 cm2 for Iron. Neutron slowing down density was also calculated depending on the recent experimental t value and distance.
Encryption of data is translating data to another shape or symbol which enables people only with an access to the secret key or a password that can read it. The data which are encrypted are generally referred to as cipher text, while data which are unencrypted are known plain text. Entropy can be used as a measure which gives the number of bits that are needed for coding the data of an image. As the values of pixel within an image are dispensed through further gray-levels, the entropy increases. The aim of this research is to compare between CAST-128 with proposed adaptive key and RSA encryption methods for video frames to determine the more accurate method with highest entropy. The first method is achieved by applying the "CAST-128" and
... Show MoreThe prevalence of using the applications for the internet of things (IoT) in many human life fields such as economy, social life, and healthcare made IoT devices targets for many cyber-attacks. Besides, the resource limitation of IoT devices such as tiny battery power, small storage capacity, and low calculation speed made its security a big challenge for the researchers. Therefore, in this study, a new technique is proposed called intrusion detection system based on spike neural network and decision tree (IDS-SNNDT). In this method, the DT is used to select the optimal samples that will be hired as input to the SNN, while SNN utilized the non-leaky integrate neurons fire (NLIF) model in order to reduce latency and minimize devices
... Show MoreDocument source identification in printer forensics involves determining the origin of a printed document based on characteristics such as the printer model, serial number, defects, or unique printing artifacts. This process is crucial in forensic investigations, particularly in cases involving counterfeit documents or unauthorized printing. However, consistent pattern identification across various printer types remains challenging, especially when efforts are made to alter printer-generated artifacts. Machine learning models are often used in these tasks, but selecting discriminative features while minimizing noise is essential. Traditional KNN classifiers require a careful selection of distance metrics to capture relevant printing
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