Background : It has been suggested that pretreatment with a statin agent prior to
myocardial infarction limits myocardial
creatine kinase release, and thus may act to
limit myocardial infarct size in humans.
Objective : To examine the effect of very
early statin initiation for acute myocardial
infarction (AMI), to the extent of
myonecrosis as manifested by peak serum
creatine kinase levels.
Methods : Patients with AMI admitted to AlKindy teaching hospital cardiac care unit
from 1st February 2007 to 28th February
2008, who fulfilled the inclusion criteria
cited in the present study, were randomly
assigned into two study groups. The statin
group patients have received a single oral
dose of 40 mg atorvastatin at time of
admission and repeated for the next days
until discharge, patients not receiving statin
were considered as controls, blood samples
were obtained on admission and every 8 h for
another three consecutive samples to identify
peak creatine kinase levels.
Results : Patients who had statin therapy
initiated immediately after hospital
admission have similar peak creatine kinase
concentrations as compared to those not
receiving statin therapy ( P= 0.332).
Conclusion : statin initiation in AMI patients
fails to show any observable effect on
creatine kinase release, the need of an
extended period for the statin agent to
achieve the predictable outcome may suggest
the necessity of statin pretreatment in
patients at high risk for AMI
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Recently, Knowledge Management Systems (KMS) consider one of the major fields of study in educational institutions, caused by the necessity to identify their knowledge value and success. Hence, based on the updated DeLone and McLean’s Information Systems Success Model (DMISSM), this study set out to assess the success of the Perceived Usefulness of Knowledge Management Systems (PUKMS) in Iraqi universities. To achieve this objective, the quantitative method is selected as the research design. In total, 421 university administration staff members from 13 Iraqi private universities were conducted. This study highlights a number of significant results depending on structural equation modeling which confirms that system, information, and s
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Software-defined networking (SDN) presents novel security and privacy risks, including distributed denial-of-service (DDoS) attacks. In response to these threats, machine learning (ML) and deep learning (DL) have emerged as effective approaches for quickly identifying and mitigating anomalies. To this end, this research employs various classification methods, including support vector machines (SVMs), K-nearest neighbors (KNNs), decision trees (DTs), multiple layer perceptron (MLP), and convolutional neural networks (CNNs), and compares their performance. CNN exhibits the highest train accuracy at 97.808%, yet the lowest prediction accuracy at 90.08%. In contrast, SVM demonstrates the highest prediction accuracy of 95.5%. As such, an
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In this study, chemical oxidation was employed for the synthesis of polypyrrole (PPy) nanofiber. Furthermore, PPy has been subjected to treatment using nanoparticles of neodymium oxide (Nd2O3), which were produced and added in a certain ratio. The inquiry centered on the structural characteristics of the blend of polypyrrole and neodymium oxide after their combination. The investigation utilises X-ray diffraction (XRD), FTIR, and Field Emission Scanning Electron Microscopy (FE-SEM) for PPy, 10%, 30%, and 50% by volume of Nd2O3. According to the electrochemical tests, it has been noted that the nanocomposites exhibit a substantial amount of pseudocapacitive activity.
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