Background: Coronavirus disease 2019 (COVID-19) is
one of the updated challenges facing the whole world.
Objective: To identify the characteristics risk factors that
present in humans to be more liable to get an infection
than others.
Methods: A cross-sectional study was conducted for
positively confirmed 35 patients with polymerase chain
reaction in Wasit province at AL-Zahraa Teaching
Hospital from the period of March 13th till April 20th. All
of them full a questionnaire regarded by risk factors and
other comorbidities. Data were analyzed by SPSS version
23 using frequency tables and percentage. For numerical
data, the median, and interquartile range (IQR) were used.
Differences between categorical groups were performed by
fissure exact test.
Results: The median age of the patients was 43 years old
and interquartile range (25-56 years). Majority of the
patients were female (60%) and (51%) of them were from
the same region (AL-ezza). The dominant blood group
among patients was (O) (40%). About 11.4% of patients
had a travel history especially to Islamic Republic of Iran,
while (77.1%) had contact with positive cases. The highest
percentage of comorbidities among patients was
hypertension (40%), and the most presenting symptoms
were cough and fever. About 51% of patients were with
mild symptoms. Diabetes, coronary heart diseases, and
chronic renal diseases were significantly related to disease
severity (P-value=0.02, 0.001, 0.01 respectively).
Conclusion: Being a female, overweight or obese, and
with blood group (O) are the major risk factors among
patients. Comorbidities can play an important role in the
severity of disease especially hypertension, diabetes,
coronary heart diseases, and chronic renal diseases.
In this article, we introduce and study two new families of analytic functions by using strong differential subordinations and superordinations associated with Wanas differential operator/. We also give and establish some important properties of these families.
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It is considered as one of the statistical methods used to describe and estimate the relationship between randomness (Y) and explanatory variables (X). The second is the homogeneity of the variance, in which the dependent variable is a binary response takes two values (One when a specific event occurred and zero when that event did not happen) such as (injured and uninjured, married and unmarried) and that a large number of explanatory variables led to the emergence of the problem of linear multiplicity that makes the estimates inaccurate, and the method of greatest possibility and the method of declination of the letter was used in estimating A double-response logistic regression model by adopting the Jackna
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