Research Article
Openaccess
Association between Acute Coronary Syndrome and
Helicobacter Pylori Chronic Infection? What data mining
tells us?
Hossam Mansour1, Ramadan Ghaleb2†, Mohamed Fakhry3, Elsayed Elgohary4,
Ali Ismael4, Abd-Elrazek Abd-Elrazek5*
1Department of Cardiology, 6th October University, Egypt
2Department of Cardiology, Aswan University, Egypt
3Department of Tropical Medicine, Al-Azhar University, Asuit Branch, Egypt
4Department of Internal Medicine, Zagazig University, Egypt
5Department of Tropical Medicine, Aswan University, Egypt
†; Equally Contributing First Author
2Department of Cardiology, Aswan University, Egypt
3Department of Tropical Medicine, Al-Azhar University, Asuit Branch, Egypt
4Department of Internal Medicine, Zagazig University, Egypt
5Department of Tropical Medicine, Aswan University, Egypt
†; Equally Contributing First Author
*Corresponding author:Abd Elrazek M Ali Hussein MD. PHD, Liver Transplant, Department of Tropical and GIT diseases, Researcher; data mining in medicine, Aswan Faculty of Medicine, Aswan University; Aswan, PO 81528, Egypt, Tel: +201116414192, Fax: (+2)0973480134; E-mail:
@
Received: 23 March, 2017 ; Accepted: 12 April, 2017; Published: 21 April, 2017
Citation: Hossam Mansour, Elrazek Abd-Elrazek, et.al. (2017) Association between Acute Coronary Syndrome and Helicobacter Pylori Chronic Infection? What data mining tells us?. J Cardiovascular Thoracic Surgery 2(1):1-3. DOI: 10.15226/2573-864X/2/1/00110
Abstract
Background: Acute Coronary Syndrome (ACS) is one of life
threating conditions affecting all populations, even those without
related risk factors. Meanwhile some studies shed light on chronic
infections such as H.Pylori, Chlamydia , Epstein Bar virus and other
micro-organisms may play a role initiating or and overexposing ACS,
still not explaining the overall dilemma.
Aim: We aimed to evaluate any role association between H. Pylori chronic infection and ACS using artificial intelligence programs.
Patients and Methods: Between August 2016 and March 2017, 125 patients presented with ACS were evaluated for Pylori ELIZA tests to discover any association using high performance computing analysis of Rapid I Software analysis.
Conclusion: Data mining analyses approved such an association between long duration intermittent chest pain related-ACS and Chronic Pylori positive IgG test, however many studied are ongoing for more explanation and much understanding.
Keywords: ACS; H. Pylori; Data mining
Aim: We aimed to evaluate any role association between H. Pylori chronic infection and ACS using artificial intelligence programs.
Patients and Methods: Between August 2016 and March 2017, 125 patients presented with ACS were evaluated for Pylori ELIZA tests to discover any association using high performance computing analysis of Rapid I Software analysis.
Conclusion: Data mining analyses approved such an association between long duration intermittent chest pain related-ACS and Chronic Pylori positive IgG test, however many studied are ongoing for more explanation and much understanding.
Keywords: ACS; H. Pylori; Data mining
Abbreviations
ACS: Acute Coronary Syndrome; CHD: Chronic Heart disease;
CVD: Cardiovascular diseases; DM: Data mining; H.Pylori: Helicobacter
Pylori; PCI: Percutaneous Coronary Intervention
Introduction
Risk factors such as hypocholesteremia, hypertriglyceridemia, LDL
and HDL, smoking, hypertension, family history or even co-morbidities
like sedentary life, social stress and obesity do not explain ACS in many
circumstances. Helicobacter pylori (H. pylori ) is a Gram-negative spiral
bacterium colonizing gastric mucosa of nearly half of human population
was discovered by Marshall and Warren and for their breakthrough
discovery associated peptic ulcerations induced by H.pylori, awarded
Nobel Prize in 1999 [1,2]. A characteristic feature of H. pylori infection
is an excessive inflammatory response may affect gastrointestinal tract
or even extra-gastric organs. However the majority of H. pylori infections
remain asymptomatic. Currently extra-gastric H.Pylori manifestations
are well known such as sideroplastic anemia and vitamin B12 deficiency.
Nevertheless cardiac diseases and atherosclerosis have been also
reported [3,4]. Data mining programs being a break through resolution
of bioinformatics related- big data analyses or even for prediction future
medicine, may discover such dilemma of association, dissociation or
partially associated organ- microorganism conditional disorders.
Artificial Intelligence (AI) Analyses
There are many Software intelligent programs related-big data
analyses, one of those well-known- programs is Rapid I, Berlin, Germany
with its rapidly consequent versions being one of the most popular
computational analysis using with great success worldwide.
In current study we used both Naïve Bayes (10-cross validation method) and decision tree of stumping computational engineering application.
In current study we used both Naïve Bayes (10-cross validation method) and decision tree of stumping computational engineering application.
Patients and Methods
Prospectively for 125 patients; 95 Male; (74%) and 30 Female
(24%), presented with typical chest pain. ECG and or PCI; Percutaneous
Coronary Intervention revealed ACS have been investigated to H.Pylori
infection by Ab test of both acute and chronic infection ; IgM and IgG
tests respectively to evaluate the association between ACS and H.pylori
infection
Results
According to data mining analysis of 125 patients presented
with typical chest pain, we have to consider H.Pylori chronic infection as a
risk factor for ACS of patients presented with long duration of intermittent
chest pain; if H.Pylori IgG is being equal or more than 1.4 units it is highly
indicated for ACS due to chronic H.Pylori infection (Possible independent
factor). However if H.Pylori is being Positive but less than 1.4 units,
another factor (Age) should be considered (Diagram 1 of chart wise;
decision tree).
IgG appear to be superior than IgM inducing ACS
IgG appear to be superior than IgM inducing ACS
Diagram:
Discussion
H.Pylori is a Gram Negative, microaerophilic bacterium found
mainly in the stomach, and may be present in other parts of the body,
(Extra-Gastric H.Pylori). Recently, there is a documented association
between chronic H.pylorichrnoic infections and extra gastric disorders
including cardiovascular (CVD) diseases, has been recently investigated
[5]. Since risk factors related-CVS do not explain all cases of coronary
heart disease (CHD) the concept that atherogenesis may have infectious
adjuvant role, recently helicobacter cinaedi may play a role in a proatherogenic
antigen should be considered. The role of virus and bacterial
pathogens including Helicobacter pylori (H. pylori), Epstein bar virus
and other microbiotas are now considered as important co-adjuvant
factors may implicated in the development of CHD. However it is still
not clear if such chronic infections may influence the course of CHD via
different mechanisms suchas direct chronic inflammatory reactions,
cross antigenicity of immune complex processes or through modification
of classic CHD risk factors such as hyperlipidemia [6]. The interesting
finding of Mendall and colleagues published in 1994 showed that CHD
patients have elevated levels of serum anti-H. Pylori antibodies [7].
According to these pioneer findings, some authors confirm and some
exclude the existence of this connection making the matter in a debate
discussion. Moreover still there is no consensus proofs on the role of H.
pylori in either initiation or progression of CHD. In order to describe the
involvement of H. pylori in the development of CHD, it is necessary to
find the largest number of reliable research studies; big data confirming
this relationship. For our knowledge there is no study have used data
mining analysis of such big data related ACS and Pylori, that artificial
intelligence of Rapid I used in the current study can find the accurate or
possible situation associations, hence according to our results only ACS of
long duration of intermittent typical chest pain may becaused by Pylori
chronic infection [8-20]. Data mining is the breakthrough in economy,
biology, trading, business, astronomy and medicine [21-23]. Data mining
can predict disease related-mortality and morbidity that will influence
the overall medical progress [24-26]. In current research decision tree
of Rapid I software program can detect the cut off point for ACS related
– chronic Pylori infection at 1.4IU of IgG test, hence there was a good
correlation between long duration of chronic chest pain and ACS due to
Pylori, nevertheless values less than 1.4IU but still positive to IgG should
be evaluated using age as a second predictor factor for ACS (Figure 1).
Figure 1: showing a brief explanation of our dedicated ongoing project
study
Nevertheless Pylori should be treated not only for the therapy
of gastrointestinal diseases and for prevention of gastric lymphoma only,
but also because Pylori may be considered a risk factor for ACS especially
in those without fully explained risk factors. However many studies should
be planned to estimate the real role of Pylori and other opportunistic or
chronic infection in developing ACS.
Limitation of the study
1. Hence data mining mainly deals with big data analyses, but preliminary
results may be helpful in ongoing research studies.
2. All patients were Egyptians.
2. All patients were Egyptians.
Future Recommendation
There is a multi-center big project study to detect H.Pylori
and other micro-organisms in atheromatous coronary plaque (Ongoing
Egyptian Multi-center Project; Aswan university, Zewail City for
Biomedicine and Technology, Zagazig University, 6th October university
, other university hospitals , Ministry of health hospitals and private
hospitals)
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