Background: Polycystic ovary syndrome (PCOS) is
the most common form of chronic anovulation
associated with androgen excess; it occurs in about 5
– 10% 0f reproductive age women. Metabolic
syndrome is characterized by insulin resistance,
hypertension, obesity, abnormalities of blood clotting
and dyslipidemia.
Adult women with PCOS have an increased
prevalence of the metabolic syndrome(MBS).
Objectives: To detect the prevalence of metabolic
syndrome in women with proved PCOS, attending the
Specialized Center for Endocrinology and Diabetes, in
Baghdad.
Materials and methods : A total number of 40
women with proved PCOS were included in this study
which was conducted in the Specialized Center for
Endocrinology and Diabetes-Baghdad, over a period
of 5 months(from April till September 2005).In
addition to measuring waist circumference and body
mass index(BMI),all patients were tested for the
levels of C-peptide, Fasting plasma glucose(FPG),
Serum luteinizing hormone(LH), Follicle st –
imulating hormone(FSH), Prolactin(PRL),
Progesterone, estradiol(E2), testosterone,T3,T4 and
TSH .
Also lipid profile, glycated hemoglobin(HbA1c) were
estimated to all patients. Glucose tolerance test(GTT)
using 75 gm of glucose was performed on all patients.
Results: Out of 40 women with PCOS,eleven
patients(27.5%) have impaired GTT. Twenty patients
(50%) out of 40 fulfil the criteria of the International
Diabetes Fideration(IDF)
Consensus Definition of the metabolic
syndrome(MBS)-2005.
Thirty-Seven patients(92.5%) have a waist
circumference more than 80 cm.
Thirty-two patients(80%) have secondary amenorrhea.
Hirsuitism and increased BMI(body mass index) were
present in 33 patients(82.5%)
The mean C-peptide level was higher in those patients
who had impaired GTT(11 patients),meaning that
GTT can be used to detect insulin resistance specially
in Labs. where measurements of insulin levels are not
available.
Conclusions :
1. Metabolic syndrome is present in 50% of our
patients,using the IDF Consensus Definition of
the metabolic syndrome-2005.
2. Glucose tolerance test can be used to detect the
presence of insulin resistance specially in Labs.
where measurements of insulin levels are not
available.
3. Insulin resistance is present in 27.5% in women
with PCOS who were included in our study.
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Background: Significant advancements have been observed in the additive manufacturing (AM) technology industry in recent decades. Due to the inherent variations among each AM manufacturing technique, new areas of investigation continually arise and require consideration. Additionally, the novel applications of additive manufacturing present new difficulties and possibilities for targeted focus. The aim of this manuscript is to conduct a comprehensive literature review that describes the various processing methods, precision levels, types of materials utilized, and potential applications of 3D printing technology in the field of dentistry. Data: An online search was conducted on databases including Research Gate, Google Scholar, and
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The research problem lay in the existing of this direct relation between the increasing and the big variety of the goods and the producing companies which mean the increase of the competition and the directing techniques of the commercial advertisings, which become spread everywhere and in an age characterized with the great varieties in the tests and the stances which requires the designers to seek designing accomplishments that are characterized with creativeness , seriousness and unsallity through the designer depending in constructing his / her texts and his/ her visual items on reference forms metaphors to achieve his / her designing purposes.
So the researcher through her primary flying study seek the identifying the manner of
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A stochastic process {Xk, k = 1, 2, ...} is a doubly geometric stochastic process if there exists the ratio (a > 0) and the positive function (h(k) > 0), so that {α 1 h-k }; k ak X k = 1, 2, ... is a generalization of a geometric stochastic process. This process is stochastically monotone and can be used to model a point process with multiple trends. In this paper, we use nonparametric methods to investigate statistical inference for doubly geometric stochastic processes. A graphical technique for determining whether a process is in agreement with a doubly geometric stochastic process is proposed. Further, we can estimate the parameters a, b, μ and σ2 of the doubly geometric stochastic process by using the least squares estimate for Xk a
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