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
(
Artificial Intelligence Algorithms have been used in recent years in many scientific fields. We suggest employing flower pollination algorithm in the environmental field to find the best estimate of the semi-parametric regression function with measurement errors in the explanatory variables and the dependent variable, where measurement errors appear frequently in fields such as chemistry, biological sciences, medicine, and epidemiological studies, rather than an exact measurement. We estimate the regression function of the semi-parametric model by estimating the parametric model and estimating the non-parametric model, the parametric model is estimated by using an instrumental variables method (Wald method, Bartlett’s method, and Durbin
... Show MoreRecent studies have revealed some conflicting results about the health effects of caffeine. These studies are inconsistent in terms of design and population and source of consumed caffeine. In the current study, we aimed to evaluate the possible health effects of dietary caffeine intake among overweight and obese individuals.
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Evolution in the modern era Which led to the rapid change in the forms of industrial products For many reasons, So put current research into question the view (What are the design requirements that define the formal change in the Iron clothes)? To reach the aim of In the design cornerstonesUnderlying the formal changethe Iron of the clothes, In the first section shed light on the development stages of systems design lists the historic stages of development and energy operator devices irons and mechanism of action and internal components, while in the second part, which was entitled (The role of technology and the factors influencing the change formality of Iron) touched on the three topics which technology modern industrial and receiver,
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The prediction process of time series for some time-related phenomena, in particular, the autoregressive integrated moving average(ARIMA) models is one of the important topics in the theory of time series analysis in the applied statistics. Perhaps its importance lies in the basic stages in analyzing of the structure or modeling and the conditions that must be provided in the stochastic process. This paper deals with two methods of predicting the first was a special case of autoregressive integrated moving average which is ARIMA (0,1,1) if the value of the parameter equal to zero, then it is called Random Walk model, the second was the exponential weighted moving average (EWMA). It was implemented in the data of the monthly traff
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HTH Ahmed Dheyaa Al-Obaidi,", Ali Tarik Abdulwahid', Mustafa Najah Al-Obaidi", Abeer Mundher Ali', eNeurologicalSci, 2023
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In information security, fingerprint verification is one of the most common recent approaches for verifying human identity through a distinctive pattern. The verification process works by comparing a pair of fingerprint templates and identifying the similarity/matching among them. Several research studies have utilized different techniques for the matching process such as fuzzy vault and image filtering approaches. Yet, these approaches are still suffering from the imprecise articulation of the biometrics’ interesting patterns. The emergence of deep learning architectures such as the Convolutional Neural Network (CNN) has been extensively used for image processing and object detection tasks and showed an outstanding performance compare
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