SUMMARY. The objectives of the present study were to assess the possible predictors of COVID-19 severity and duration of hospitalization and to identify the possible correlation between patient parameters, disease severity and duration of hospitalization. The study included retrospective medical record extraction of previous coron avirus COVID-19 patients in Basra hospitals, Iraq from March 1st and May 31st, 2020. The information of the participants was investigated anonymously. All the patients’ characteristics, treatments, vital signs and laboratory tests (hematological, renal and liver function tests) were collected. The analysis was conducted using the SPSS (version 22, USA). Spearman correlation was used to measure the relationships between different blood lab data predictors, the disease severity and the duration of hospitalization. The Kruskal Wallis Test was used to measure the difference in the severity of the disease according to the serum ferritin level. Overall, 499 patients were includ ed in the current study: 58.4% were female and 41.6% were male. Nearly half of the patients had chronic disease particularly diabetes mellitus (20.8%) and hypertension (23.6%). With regards to hematological tests, there was a significant correlation between lymphocyte level and disease severity, duration of hospitalization, ferritin, platelets and neutrophil level. In addition, serum urea and creatinine have significant (p-value < 0.05) positive correlation with the disease (COVID-19) severity. Similarly, there is a significant difference in the severity of the disease ac cording to the ferritin level. Thus, patients with more severe symptoms had higher level of blood ferritin. Further more, patients with co-existing diseases have experienced more severe COVID-19 symptoms. This indicates that, lymphocyte and ferritin levels are good predictors of COVID-19 severity. This study finding indicated that evalua tion of blood laboratory indices (CBC including lymphocytes and ferritin) and renal/liver function parameters in the beginning of the COVID-19 could predict the severity and duration of hospitalization. In addition, patients with multiple comorbidities are at higher risk of longer days of hospitalization. An early attention to the patient parameter and lab data may help in tailoring treatments and promote possible interventions to triage hospitaliza tion and save more lives particularly Iraqi might experience a second wave of the pandemic.
In this research, the covariance estimates were used to estimate the population mean in the stratified random sampling and combined regression estimates. were compared by employing the robust variance-covariance matrices estimates with combined regression estimates by employing the traditional variance-covariance matrices estimates when estimating the regression parameter, through the two efficiency criteria (RE) and mean squared error (MSE). We found that robust estimates significantly improved the quality of combined regression estimates by reducing the effect of outliers using robust covariance and covariance matrices estimates (MCD, MVE) when estimating the regression parameter. In addition, the results of the simulation study proved
... Show MoreUrban land price is the primary indicator of land development in urban areas. Land prices in holly cities have rapidly increased due to tourism and religious activities. Public agencies are usually facing challenges in managing land prices in religious areas. Therefore, they require developed models or tools to understand land prices within religious cities. Predicting land prices can efficiently retain future management and develop urban lands within religious cities. This study proposed a new methodology to predict urban land prices within holy cities. The methodology is based on two models, Linear Regression (LR) and Support Vector Regression (SVR), and nine variables (land price, land area,
... Show MoreClean water supply is one of the major factors contributing significantly to society’s socio-economic transformation by improving living standards, health, and increasing productivity. It is imperative to plan and construct appropriate water supply systems in modern society, which supply various segments of society with safe drinking water according to their requirements to ensure adequate and quality water supply. In the current study, here was an attempt to develop a model for geographic information systems to manage the assets of the water distribution networks in the Karrada region and to evaluate the network geometrically, and from the results of the engineering analysis of the
The temperature distributions are to be evaluated for the furnace of Al-Mussaib power plant. Monte Carlo simulation procedure is used to evaluate the radiation heat transfer inside the furnace, where the radiative transfer is the most important process occurring there. Weighted sum of gray-gases model is used to evaluate the radiative properties of the non gray gas in the enclosure. The energy balance equations are applied for each gas, and surface zones, and by solving these equations, both the temperature, and the heat flux are found.
Good degree of accuracy has been obtained, when comparing the results obtained by the simulation with the data of the designing company, and the data obtained by the zonal method. In
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Abstract
This research studies Abu Baker Al-Siddiq’s commandments to the leaders of his armies. The research is organized into an Introduction, three sections, and a Conclusion.
The Introduction presents a definition of Style and Commandment terminologies. It also presents a brief biography of Abu Baker Al-Siddiq may Allah be pleased with him.
The first section explains the characteristics of the Composition and its rhetorical significance. In this Section, I study the types of predicate and the methods of construction in Abu Baker’s commandments and the rhetoric in using the connection and disconnection modifiers in his expressions.
The second section e
... Show MoreThe object of the presented study was to monitor the changes that had happened in the main features (water, vegetation, and soil) of Al-Hammar Marsh region. To fulfill this goal, different satellite images had been used in different times, MSS 1973, TM 1990, ETM+ 2000, 2002, and MODIS 2009, 2010. A new technique of the unsupervised classification called (Color Extracting Technique) was used to classify the satellite images. MATLAP programming used the technique and separated Al-Hammar Marsh from other water features (rivers, irrigated lands, etc.) when calculated the changes in the water content of the study region. ArcGIS 9.3 (arcMAP, arcToolbox) were used to achieve this work and calculate area of each class.