Background : Coronary artery disease is theunderlying cause in approximately two thirds of
patients with systolic heart failure ;
Coronary artery angiogriphy may be useful to
define the presence ,
Anatomical characteristics ,and functional
significance of Coronary artery disease in
selected heart failure patients with or without signs
and aymptoms of Coronary artery disease.
Objectives: to verify the clinical usefulness of
coronary angiography (CA) in congestive heart
failure (CHF) patients with no history of ischemic
heart disease and to identify predictive factors for
performing coronary angiography to patients with
congestive heart failure with no obvious ischemia.
Methods :this is a cross-sestional study conducted
Ibn al –Bitar center for cardiac surgery during a
period between November 2009 and November
2010 ;all included patients have symptomatic LV
dyfunctional with NYHA functional class II or
more with no clinical evidence of IHD .History,
physical examination had been performed for each
patient , in addition ti blood tests ,ECG ,CXR,
echocardiography and Coronary angiogriphy
Results :Among 112 patients with symptomatic
LV dysfunction of unknown cause enrolled in this
study male :female ratio 3:1 their age (17 -77 years
)there were 14 patients (12.5%)with significant
Coronary artery disease , statistical analysis
between CADand non CAD group show :the CAD
were more common in male 11 patients (78% )
smokers(1)Were female , 25 patients (22.3%) were
diabetic , 25 diabetic (22.3%) were hypertensive
,50 diabetic (44.6%) were smokers . 4 diabetic3.5) with family history of dilatedhyperlipidemia and 3 diabetic (2.6%) ) with
family history ischemic heart disease (IHD in
close relative at age <50 years in men and <55
years in women ) as demographic distribution of
patients in table 1 .coronary angiography show
that are 14 patients (12.5%) with significant
coronary artery disease (CAD) and 98 patients
(87.5%) with significant coronary artery disease
. as shown in figure 1 . eleven patients (78%) of
patients (22%) were female statistical analysis
shows that the male is more predominant in
CAD groups as shown in table 2 . twelve
patients (85.7%) of patients with CAD were
smokers while only 38 patients (38.7%) were
smokers in non CAD group . statistical analysis
shows there is significant difference between
the two groups ( p value < 0.01 ) as shown in
table 3 .nine patients (64.2%) of patients with
CAD were diabetics while 16 patients
(16.3%)were diabetics in non CAD group ,
statistical analysis shows there is significant
difference between the two groups (p value <
0.005) as shown in table (3) .there is no
statistical between the mean of left ventricular
ejection fraction of CAD group ( 37 ±10 %) and
that of non CAD (36±9 % ) , p value > 0.5 as
shown in table 6 . figure 2 revealed that LAD
lesion was most common coronary artery lesion
which represent 12 (85%) followed by in order
of frequency LCX 42 % ,RCA 28% and LMS
7% ; in addition to that 57% with single vessel
disease ,14.2% with 2 vessel disease and
28.4%with r vessel disease (2)Leads , ST
depression ≥1 mm or deep T wave inversion
had been excluded
(
The analysis of survival and reliability considered of topics and methods of vital statistics at the present time because of their importance in the various demographical, medical, industrial and engineering fields. This research focused generate random data for samples from the probability distribution Generalized Gamma: GG, known as: "Inverse Transformation" Method: ITM, which includes the distribution cycle integration function incomplete Gamma integration making it more difficult classical estimation so will be the need to illustration to the method of numerical approximation and then appreciation of the function of survival function. It was estimated survival function by simulation the way "Monte Carlo". The Entropy method used for the
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Oscillation criteria are obtained for all solutions of the first-order linear delay differential equations with positive and negative coefficients where we established some sufficient conditions so that every solution of (1.1) oscillate. This paper generalized the results in [11]. Some examples are considered to illustrate our main results.
Because the Coronavirus epidemic spread in Iraq, the COVID-19 epidemic of people quarantined due to infection is our application in this work. The numerical simulation methods used in this research are more suitable than other analytical and numerical methods because they solve random systems. Since the Covid-19 epidemic system has random variables coefficients, these methods are used. Suitable numerical simulation methods have been applied to solve the COVID-19 epidemic model in Iraq. The analytical results of the Variation iteration method (VIM) are executed to compare the results. One numerical method which is the Finite difference method (FD) has been used to solve the Coronavirus model and for comparison purposes. The numerical simulat
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During the last few years, the greener additives prepared from bio-raw materials with low-cost and multifunctional applications have attracted considerable attention in the field of lubricant industry. In the present work, copolymers derived from sunflower and linseed oils with decyl methacrylate were synthesized by a thermal method using benzoyl peroxide (BPO) as a radical initiator. Direct polymerization of fatty acid double bonds in the presence of a free radical initiator results in the development of environmentally friendly copolymeric additives (Co-1 and Co-2). Fourier Transform Infrared (FTIR) and Proton Nuclear Magnetic Resonance (1H-NMR) were used to characterize the resulting copolymers. Thermal decomposition of copolymers was de
... Show MoreThe deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Conv
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