Background: Childhood meningitis is a major
cause of morbidity and mortality, Hemophilus
influenza b (Hib) is the most common cause in
many countries, especially below 5 years and
before the development of conjugated Hib vaccine,
it is followed by Streptococcus Pneumonia, and
then N. meningitides, in addition to other
microorganisms.
Objective: To identify the causative organisms
of bacterial meningitis and to identify the factors
predisposing significantly to the incidence of
bacterial meningitis.
Method: This cross sectional , study was done in
Al-Elwia Pediatric Hospital during the period 1st
of January 2007 to 30th of June 2007.Eighty four
patients with presumptive diagnosis of meningitis
were included in this study, from the age of 2
months -12 years, History about some risk factors
were taken in details. Analysis of cerebrospinal
Fluid (CSF) with Gram stains & cultures were
done in all cases.
Results: The number of cases of meningitis was
50 (20 proved meningitis & 30 partially treated
meningitis), while 34 patients are found to have no
meningitis.
Streptococcus pneumoniae was identified in
45%, Hemophilus Influenza b in 20%, while
Nisseria meningitides 5%, other organisms include
Escherichia coli, Staphylococcus aureus,
Klebsiella, & salmonella.
Many factors affecting the occurrence of
bacterial meningitis & these include: age, sex,
residence, body weight and home overcrowding.
Conclusions: Streptococcus pneumoniae was
found to be the predominant microorganism
causing bacterial meningitis in children aged 2
months-12 years, followed by Hemophilus
influenza b, while N. meningitides were one of the
rare bacteria which had been identified. E. coli was
found to be the major cause in cases of ventriculoperitoneal
(VP) shunt meningitis.
This research aims to study the important of the effect of analysis of covariance manner for one of important of design for multifactor experiments, which called split-blocks experiments design (SBED) to deal the problem of extended measurements for a covariate variable or independent variable (X) with data of response variable or dependent variable Y in agricultural experiments that contribute to mislead the result when analyze data of Y only. Although analysis of covariance with discussed in experiments with common deign, but it is not found information that it is discussed with split-Blocks experiments design (SBED) to get rid of the impact a covariance variable. As part application actual field experiment conducted, begun at
... Show MoreThe research study and analysis of the integration of marketing communications and their impact on the marketing performance of a number of telecom companies, as included in the research problem to know the role of marketing communications community in achieving sales and market share, profitability and customer satisfaction. The importance of research begins to be the right choice for the elements of marketing communications, lead to savings in time, effort and money and create a more idea about the effectiveness of the application of the concept of integration. The research to determine the role of marketing communications in promoting the integration of the marketing performance of companies in the field of sales and marke
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... Show MoreThis study was to examine the effect of a mental training program, including a combination of autogenic training and imagery, on a number of mental skills and on the development of personality traits-psychological hardiness as well as conscientiousness, openness to experience, and neuroticism-in Adolescent male volleyball players. 60 adolescent male volleyball players (aged 15–17) participated in a two-group, pretest-posttest design. The experimental group (n = 30) completed 8-week mental skills training program, including imagery, self-talk, attention control, and relaxation, while the control group (n = 30) followed regular training. Psychological hardiness and selected personality traits were measured pre-and post-intervention using va
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... Show MoreThyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise
... Show MoreIn this study, a new adsorbent derived from sunflower husk powder and coated in CuO nanoparticles (CSFH) was investigated to evaluate the simultaneous adsorption of Levofloxacin (LEV), Meropenem (MER), and Tetracycline (TEC) from an aqueous solution. Significant improvements in the adsorption capacity of the sunflower husk were identified after the powder particles had been coated in CuO nanoparticles. Kinetic data were correlated using a pseudo-second-order model, and was successful for the three antibiotics. Moreover, high compatibility was identified between the LEV, MER, and TEC, isotherm data, and the Langmuir model, which produced a better fit to suit the isotherm curves. In addition, the spontaneous and exothermic nature of the adsor
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