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D-dimer and Ferritin Levels in Prediction of COVID-19 Severity
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Abstract<sec> <title>BACKGROUND:

The most common cause of upper respiratory tract infection is coronavirus, which has a crown appearance due to the existence of spikes on its envelope. D-dimer levels in the plasma have been considered a prognostic factor for COVID-19 patients.

AIM OF THE STUDY:

The aim of the study is to demonstrate the role of COVID-19 on coagulation parameters D-dimer and ferritin with their association with COVID-19 severity and disease progression in a single-center study.

PATIENTS AND METHODS:

This study included 200 COVID-19 patients in a private single center from January 01, 2021, to January 01, 2022, in Baghdad-Iraq. D-dimer and ferritin were analyzed in those patients and evaluated their association with the need for oxygen therapy and intensive care unit (ICU) admission.

RESULTS:

Two hundred COVID-19 patients met the criteria for inclusion in this research. The total mean age of all patients was 60.1 ± 11.6 years and the sex distribution was 130 (65%) males and 70 (35%) females. Regarding D-dimer and ferritin, there were significantly higher values in patients in respiratory care units (4748 ± 7.2) (215.7 ± 4.2) (P = 0.0001) in comparison with another group who did not need oxygen or ICU admission (345 ± 3.6) (98.4 ± 1.7), respectively.

CONCLUSIONS:

High levels of D-dimer and ferritin may be used as tools to predict unfavorable clinical outcomes of the disease and poor prognosis.

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Publication Date
Mon Dec 25 2017
Journal Name
Al-khwarizmi Engineering Journal
A new Cumulative Damage Model for Fatigue Life Prediction under Shot Peening Treatment
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 Abstract

In this paper, fatigue damage accumulation were studied using many methods i.e.Corton-Dalon (CD),Corton-Dalon-Marsh(CDM), new non-linear model and experimental method. The prediction of fatigue lifetimes based on the two classical methods, Corton-Dalon (CD)andCorton-Dalon-Marsh (CDM), are uneconomic and non-conservative respectively. However satisfactory predictions were obtained by applying the proposed non-linear model (present model) for medium carbon steel compared with experimental work. Many shortcomings of the two classical methods are related to their inability to take into account the surface treatment effect as shot peening. It is clear that the new model shows that a much better and cons

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Publication Date
Sun Apr 30 2023
Journal Name
Iraqi Geological Journal
Evaluating Machine Learning Techniques for Carbonate Formation Permeability Prediction Using Well Log Data
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Machine learning has a significant advantage for many difficulties in the oil and gas industry, especially when it comes to resolving complex challenges in reservoir characterization. Permeability is one of the most difficult petrophysical parameters to predict using conventional logging techniques. Clarifications of the work flow methodology are presented alongside comprehensive models in this study. The purpose of this study is to provide a more robust technique for predicting permeability; previous studies on the Bazirgan field have attempted to do so, but their estimates have been vague, and the methods they give are obsolete and do not make any concessions to the real or rigid in order to solve the permeability computation. To

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Publication Date
Fri Mar 01 2024
Journal Name
Baghdad Science Journal
Deep Learning Techniques in the Cancer-Related Medical Domain: A Transfer Deep Learning Ensemble Model for Lung Cancer Prediction
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Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a

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Publication Date
Mon Apr 04 2022
Journal Name
Journal Of Educational And Psychological Researches
The Effect of the Interaction between the Use of the Improve Strategy in Teaching Mathematics and Achievement Levels on the Acquisition of Algebraic Concepts and Habits of Mind among Tenth Grade Students in Oman
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The current study aims to investigate the effect of the interaction between the use of the improve strategy in teaching mathematics and the level of academic achievement on the acquisition of algebraic concepts and habits of mind among tenth-grade students in Oman. The study adopted the experimental method, based on a quasi-experimental design with two groups: experimental and control groups and pre-post-measurement. The study sample consisted of (28) 10th-grade students as an experimental group and 26 of 10th-grade students as a control group in Al-Tufail bin Amr School in South Al Batinah. The differences in the pretest and posttest gains were analyzed using mean, standard deviation, ANCOVA, t-test, effect size (eta-square), and two-wa

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Publication Date
Fri Oct 01 2021
Journal Name
Journal Of Al-rafidain University College For Sciences ( Print Issn: 1681-6870 ,online Issn: 2790-2293 )
The Use of Logistic Regression Model in Estimating the Probability of Being Affected By Breast Cancer Based On the Levels of Interleukins and Cancer Marker CA15-3
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Breast cancer has got much attention in the recent years as it is a one of the complex diseases that can threaten people lives. It can be determined from the levels of secreted proteins in the blood. In this project, we developed a method of finding a threshold to classify the probability of being affected by it in a population based on the levels of the related proteins in relatively small case-control samples. We applied our method to simulated and real data. The results showed that the method we used was accurate in estimating the probability of being diseased in both simulation and real data. Moreover, we were able to calculate the sensitivity and specificity under the null hypothesis of our research question of being diseased o

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Publication Date
Sun Nov 09 2025
Journal Name
Journal Of Nephropharmacology
Association between anti-erythropoietin antibody levels and treatment response in hemodialysis patients with end-stage renal disease: A cross-sectional study from Iraq
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Introduction: The therapeutic efficacy of erythropoietin (EPO) may be diminished by the formation of anti-erythropoietin antibodies (AEAs), potentially resulting in therapy failure. Objectives: This retrospective study included 84 hemodialysis patients with end-stage renal disease (ESRD) treated with recombinant EPO and aimed to evaluate the association between serum AEA and treatment response. Patients and Methods: This cross-sectional study included eighty-four Iraqi patients with ESRD who had been on recombinant human EPO for more than 6 months and had hemoglobin levels below 11 g/dL. Serum AEA levels were measured in all patients to evaluate their association with treatment response and to investigate correlations with demograph

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Publication Date
Wed Jun 01 2022
Journal Name
Jordan Journal Of Biological Sciences
Comparison of the Folate and Homocysteine Levels with A80G -RFC1 Gene Polymorphism between the Sample of Iraqi Children with and without Down Syndrome
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Many international studies indicated that the polymorphisms of some genes disturbed the folate homocysteine (Hcy) metabolism and increased the vulnerability to Down syndrome (DS). We aimed to measure the serum levels of folate and Hcy in DS children and compare the levels with age and sex-matched apparently normal healthy children. We also aimed to study the A80G polymorphism of the gene reduced folate carrier (RFC1) in the DS children as a risk factor. Forty children with DS (24 were boys, and 16 were girls) with the age range between 5-13 years, and 26 normal healthy children (16 boys and ten girls) were included in this study. The results show that the highest genotype in the control group was AG (53.85%) followed by AA and GG (30.

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Publication Date
Tue Nov 01 2022
Journal Name
Optik
Design new D-π-A materials for sensitizers for dye-sensitized solar cells: Quantum chemical study
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Within this paper, we developed a new series of organic chromophores based on triphenyleamine (TPA) (AL1, AL-2, AL-11 and AL-22) by engineering the structure of the electron donor (D) unit via replacing a phenyle ring or inserting thiophene as a π-linkage. For the sake of scrutinizing the impact of the TPA donating ability and the spacer upon the photovoltaic, absorptional, energetic, and geometrical characteristic of these sensitizers, density functional theory (DFT) and time-dependent DFT (TD-DFT) have been utilized. According to structural characteristics, incorporating the acceptor, π-bridge and TPA does not result in a perfect coplanar conformation in AL-22. We computed EHOMO, ELUMO and bandgap (Eg) energies by performing frequency a

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Publication Date
Sat Dec 01 2018
Journal Name
Al-khwarizmi Engineering Journal
A study of Land Zoning in the base of Traffic Noise Pollution Levels using ArcGIS: Kirkuk City as a Case Study
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This study is an approach to assign the land area of  Kirkuk city [ a city located in the northern of Iraq, 236 kilometers north of  Baghdad  and 83 kilometers  south of  Erbil [ Climatic atlas of  Iraq, 1941-1970  ]  into different  multi zones by using Satellite image and Arc Map10.3,  zones of different traffic noise pollutions. Land zonings process like what achieved in this paper will help and of it’s of a high interest point for the future of Kirkuk city especially urban

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Publication Date
Mon Apr 01 2019
Journal Name
Biochemical & Cellular Archives
The impact of follicular fluid growth differentiation factor 8 levels on IVF /ICSI outcomes
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Clinical index is needed to predict the outcome of pregnancy after in vitro fertilization/intracytoplasmic sperm injection-embryo transfer (IVF/ICSI-ET) for infertile patients. Growth differentiation factor-8 (GDF-8), also known as myostatin, is one of transforming growth factor-â superfamily localized in antral follicles in normal and PCOS ovaries but its function in female reproductive system is still unknown. Aim of the study is to assess the correlation between levels of GDF8 in follicular fluid (FF) with outcomes of in vitro fertilization (IVF/ICSI) in women with and without PCOS. A prospective case control study was performed enrolling (40) patients with PCOS and (40) non-PCOS women (male infertility) undergoing IVF/ICSI. The collect

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