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A Pharmacoeconomics Study for Anticoagulants used for Hospitalized COVID-19 Patients in Al-Najaf Al-Ashraf city –Iraq(Conference Paper )#
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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.

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Publication Date
Sat Dec 11 2021
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
The Formulation and Characterization of Nimodipine Nanoparticles for the Enhancement of solubility and dissolution rate
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Nimodipine (NMD) is a dihydropyridine calcium channel blocker useful for the prevention and treatment of delayed ischemic effects. It belongs to class ? drugs, which is characterized by low solubility and high permeability. This research aimed to prepare Nimodipine nanoparticles (NMD NPs) for the enhancement of solubility and dissolution rate. The formulation of nanoparticles was done by the solvent anti-solvent technique using either magnetic stirrer or bath sonicator for maintaining the motion of the antisolvent phase. Five different stabilizers were used to prepare NMD NPs( TPGS, Soluplus®, HPMC E5, PVP K90, and poloxamer 407). The selected formula F2, in which  Soluplus 

has been utilized as a stabilizer, has a par

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Publication Date
Fri Mar 29 2024
Journal Name
Iraqi Journal Of Science
Evaluating the Performance and Behavior of CNN, LSTM, and GRU for Classification and Prediction Tasks
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     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod

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Publication Date
Sun Jan 01 2023
Journal Name
Aip Conference Proceedings
Fast lightweight encryption device based on LFSR technique for increasing the speed of LED performance
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LED is an ultra-lightweight block cipher that is mainly used in devices with limited resources. Currently, the software and hardware structure of this cipher utilize a complex logic operation to generate a sequence of random numbers called round constant and this causes the algorithm to slow down and record low throughput. To improve the speed and throughput of the original algorithm, the Fast Lightweight Encryption Device (FLED) has been proposed in this paper. The key size of the currently existing LED algorithm is in 64-bit & 128-bit but this article focused mainly on the 64-bit key (block size=64-bit). In the proposed FLED design, complex operations have been replaced by LFSR left feedback technology to make the algorithm perform more e

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Publication Date
Mon Jan 01 2018
Journal Name
Matec Web Of Conferences
Assessing the performance of commercial Agisoft PhotoScan software to deliver reliable data for accurate3D modelling
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3D models delivered from digital photogrammetric techniques have massively increased and developed to meet the requirements of many applications. The reliability of these models is basically dependent on the data processing cycle and the adopted tool solution in addition to data quality. Agisoft PhotoScan is a professional image-based 3D modelling software, which seeks to create orderly, precise n 3D content from fixed images. It works with arbitrary images those qualified in both controlled and uncontrolled conditions. Following the recommendations of many users all around the globe, Agisoft PhotoScan, has become an important source to generate precise 3D data for different applications. How reliable is this data for accurate 3D mo

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Publication Date
Mon May 01 2023
Journal Name
Ain Shams Engineering Journal
Neural network modeling of rutting performance for sustainable asphalt mixtures modified by industrial waste alumina
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Publication Date
Fri Jun 28 2024
Journal Name
The Iraqi Journal Of Veterinary Medicine
Aryl Hydrocarbon Receptor Modulation and Resveratrol Influence on Dnah1 Expression: Implications for Male Reproductive Health
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Male reproductive health is intricately regulated by molecular and physiological processes, with the aryl hydrocarbon receptor (AhR) playing a crucial role. AhR is activated by various ligands and influences the onset and progression of diseases. The aim of this study was to evaluate the role of AhR on spermatogenesis in adult male rats were affected by resveratrol (RES) and CH223191, an AhR antagonist. The study include forty rats were randomly divided into four equal groups: Control group, DMSO group, RES group and AhR‾ group, the rats received respective treatments intraperitoneally twice weekly for 60 days, and various parameters related to male reproductive health were evaluated. The AhR that activation by the RES treatment w

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Publication Date
Sat Oct 01 2022
Journal Name
Structures
Behaviour and design of the ‘lockbolt’ demountable shear connector for sustainable steel-concrete composite structures
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In order to promote sustainable steel-concrete composite structures, special shear connectors that can facilitate deconstruction are needed. A lockbolt demountable shear connector (LB-DSC), including a grout-filled steel tube embedded in the concrete slab and fastened to a geometrically compatible partial-thread bolt, which is bolted on the steel section's top flange of a composite beam, was proposed. The main drawback of previous similar demountable bolts is the sudden slip of the bolt inside its hole. This bolt has a locked conical seat lug that is secured inside a predrilled compatible counter-sunk hole in the steel section's flange to provide a non-slip bolt-flange connection. Deconstruction is achieved by demounting the tube from the t

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Mon Jan 01 2024
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Fusion: Practice And Applications
Proposed Framework for Semantic Segmentation of Aerial Hyperspectral Images Using Deep Learning and SVM Approach
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Wed May 10 2023
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Lactic acid-based deep eutectic solvents and activated carbon for soap removal from crude biodiesel
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Publication Date
Thu Jun 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
The Use of the Regression Tree and the Support Vector Machine in the Classification of the Iraqi Stock Exchange for the Period 2019-2020
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 The financial markets are one of the sectors whose data is characterized by continuous movement in most of the times and it is constantly changing, so it is difficult to predict its trends , and this leads to the need of methods , means and techniques for making decisions, and that pushes investors and analysts in the financial markets to use various and different methods in order to reach at predicting the movement of the direction of the financial markets. In order to reach the goal of making decisions in different investments, where the algorithm of the support vector machine and the CART regression tree algorithm are used to classify the stock data in order to determine

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