Are proton pump inhibitors among the risk factors for acute coronary syndrome?
==============================================================================

* Banan M. Alamoudi
* Nahla K. Ibrahim
* Bakr B. M. Kalo

## A multi-centric case-control study between patients attending governmental hospitals in western Saudi Arabia

## Abstract

**Objectives:** To identify the predictors of acute coronary syndrome (ACS) and to determine the relationship between usage of proton pump inhibitors (PPIs) and the occurrence of a first non-fatal ACS event among patients that attended governmental hospitals in Jeddah, Saudi Arabia.

**Methods:** A matched, multi-centric case-control study was performed between January and June of 2015 in Jeddah involving 2 governmental hospitals and the main university hospital. A total of 118 cases aged ≥18 years who were recently diagnosed with ACS were selected. For each case, one control matched by age and gender was selected. Information from an interview questionnaire and from reviewing patients’ medical records was recorded on a standardized data collection sheet.

**Results:** Risk factors for ACS and the relationship between usage of PPIs and the occurrence of a first non-fatal ACS event were measured in 236 cases and matched controls. Current smoking (OR: 4.5; 95% CI: 1.92-10.98), excessive body weight (OR: 2.99; 95% CI: 1.38-6.45), and dyslipidemia (OR: 2.51; 95% CI: 1.07-5.84) were the predictors of ACS. Hypertension, diabetes, and moderate-to-high physical activity were associated with ACS. However, there was no statistical association between use of PPIs and occurrence of the first non-fatal ACS event (p>0.05).

**Conclusions:** There was no association between PPIs and the occurrence of a first non-fatal ACS event. Smoking, increased weight, and dyslipidemia are considered predictors of ACS. Furthermore, ACS is associated with self-reported diabetes, hypertension, and physical activity.

Acute coronary syndrome (ACS) remains one of the chief causes of death worldwide.1 Hypertension, dyslipidemia, obesity, smoking, and diabetes are considered risk factors for cardiovascular diseases such as ACS.2 In Saudi Arabia, approximately 50% of people live with 3 or more cardiovascular (CV) risk factors.3 Moreover, according to the “Saudi Project for Assessment of Coronary Events (SPACE) Registry,” 70% of cardiac patients have diabetes and 66% smokers.4 In addition, hypertension was the biggest risk factor encountered by researchers in the Middle East.5 Globally, the rise in the amount of deaths is appointed more to hypertension than to other risk factors of CV diseases.6

Some studies have reported that proton pump inhibitors (PPIs) could play a role in ACS. Proton pump inhibitors are a group of drugs that are most commonly prescribed in clinical practice. Proton pump inhibitors are preferred when compared to other medications such as histamine H2 receptor antagonists because of their efficacy in suppressing gastric acid secretions.7 Proton pump inhibitors are used to treat many diseases of the digestive tract, including dyspepsia, gastro-esophageal reflux disease (GERD), peptic ulcers, and Helicobacter pylori (H. pylori) infection.8 When PPIs are used for a long period, side effects such as bone fractures and low levels of blood magnesium may occur.9,10 Proton pump inhibitors can reduce the effectiveness of antiplatelet drugs among patients with ACS.11,12 This effect was attributed to CYP2C19, which is a hepatic enzyme that can be inhibited by PPIs. CYP2C19 is required to activate clopidogrel, an antiplatelet agent.13 However, in patients with ACS, PPIs also lower the influence of ticagrelor, “an antiplatelet agent that does not require hepatic activation.”14 Several of the latest studies suggest that all members of PPIs raise CV risk for patients who are suffering from ACS in spite of the fact that some of the PPI members do not considerably obstruct CYP2C19.11,15,16 Accordingly, it is not known if the risk of adverse CV events extends to the general population who ingests PPIs.

A recent study carried out on animals and on *ex-vivo* human tissues revealed the presence of a plausible biological mechanism that might explain the association between PPIs, ACS, and other CV events.17 Proton pump inhibitors hinder the activity of dimethylarginine dimethylaminohydrolase (DDAH). Dimethylarginine dimethylaminohydrolase is an enzyme that is important for a healthy CV system.17 Unfortunately, DDAH metabolizes “asymmetrical dimethylarginine (ADMA), an endogenous competitive inhibitor of nitric oxide synthase (NOS)”.17 When endothelial NOS is inhibited, the risk of vascular inflammation and thrombosis is higher. This mechanism could justify the greater risk of unwanted myocardial events in heart patients using PPIs. In fact, plasma ADMA is a risk factor for CV diseases and the death of patients who suffer from ACS, as well as for healthy people.18-20

Most of the literature addresses the relationship between PPIs and clopidogrel. However, based on extensive literature review, few studies have addressed the relationship between PPIs alone and ACS.11,17 Therefore, such a study is necessary. The aims of this study are identifying the predictors of ACS and determining the relationship between the use of PPIs and the first non-fatal ACS event among patients attending general governmental hospitals in Jeddah, Saudi Arabia.

## Methods

We used a multi-centric case-control study design. Data was collected between January and June 2015, and the study complied with the Declaration of Helsinki. It was approved by the Institutional Review Board (IRB) of the King Abdulaziz University Hospital (KAUH) (Reference No. 343-14) and by the Directorate of Health Affairs in Jeddah that covers the 2 Ministry of Health (MOH) hospitals (Reference No. A00229). On-line databases such as “PubMed, Clinical Key, Google, Web of Science, and Cochrane Library” were comprehensively searched and reviewed for the period from 2004 to 2018 for studies that explored the relationship between PPIs and ACS.

Three hospitals were selected from Jeddah, Saudi Arabia. A simple random sampling technique, using a table of random digits, was used to select the hospitals. Two of the selected hospitals belonged to MOH and one was the main university hospital, the KAUH.

The sample size was calculated through EpiTools statistical calculation,21 with a suggested power of 80 and a 2-sided confidence level of 95%. The ratio of cases to controls was 1:1, with the percentage of control group exposed to PPIs as 44%.22 The odds ratio was suggested to be 2, based on a similar study.23 The calculated total sample size was 260 (130 cases and 130 controls). Twelve controls had no old files and/or had a previous history of ACS, stroke, or heart disease. In addition, we excluded 12 cases of patients who had died during the hospital stay. Therefore, a total of 118 cases and 118 controls were included.

All eligible consecutively admitted cases of ACS who agreed to participate were selected from the cardiac care unit (CCU), cardiac and medical wards, and emergency department (ED). Cases of ACS were defined as “any patients with unstable angina, non-ST-segment elevation myocardial infarction (NSTEMI) or ST-segment elevation myocardial infarction (STEMI).” A cardiologist diagnosed this admission according to electrocardiography (ECG) changes with a rise in cardiac biomarkers of necrosis (serum creatine phosphokinase, troponins, and myoglobin).

For each selected case, one control was selected, matched by ±5 years in age and gender from the same hospital. The controls included any hospitalized patients admitted without any clinical symptoms or suspicion of cardiovascular diseases (CVDs) or any heart disease in their present and past medical history (they were selected through purposive sampling). The controls were selected from the ED and inpatient medical wards.

Data was collected through a validated data collection sheet. Validity was assessed by 2 experts. The sheet was completed through an interview questionnaire that was answered by both case and control participants and by a review of medical record. It contained sections about personal and socio-economic data and family history of CVDs. Medical history was also determined by assessing hypertension, diabetes mellitus (DM), and hyperlipidemia. Patients were also asked about their use of aspirin or clopidogrel and about their lifestyle habits, such as smoking. Physical activity level was established through “the short form of the International Physical Activity Questionnaire (IPAQ)”.24

### Statistical analysis

Hypertension was defined as “systolic blood pressure (SBP) ≥140 mm Hg and/or diastolic blood pressure (DBP) ≥90 mm Hg.”25 The glycemic profile was classified according to the American Diabetes Association. Patients were determined to be diabetic if their fasting blood glucose (FBG) level was ≥7 mmol/L, their glycated hemoglobin (HbA1c) was ≥6.5%, or their random plasma glucose was ≥11.1 mmol/L.26 Body mass index (BMI) was estimated by dividing weight in kilograms by the square of height in meters. Body mass index was categorized into 3 categories: normal (<25), overweight (25-29.9), and obese (≥30).27 Dyslipidemia was defined as follows: high total cholesterol if ≥5.2 mmol/L, high triglyceride levels if ≥1.7 mmol/L, high low-density lipoprotein (LDL) if ≥4.12 mmol/L, and low levels of high-density lipoprotein (HDL) if ≤1.03 mmol/L28 Current smokers were defined as “those who smoked at least one cigarette per day”, and former smokers were defined as “those who had stopped smoking more than one year”. Participants who do not belong to the previous categories were classified as non-current smokers. Regarding physical activity, participants were classified according to the scoring system provided by IPAQ as having low, moderate, or high physical activity.24

### Statistical analysis

We evaluated the data with IBM SPSS Statistics for Windows, Version 20 (IBM Corp., Armonk, N.Y., USA). Normally distributed continuous variables were displayed as means and standard deviations (SDs), and categorical variables were displayed as frequency tables. Associations between categorical variables were assessed by a chi-squared test and between continuous variables by a Student’s t-test. Estimations for logistic regression analysis were used to determine the predictors of ACS according to PPI use and other covariates. We displayed the outcome results as crude and adjusted odds ratios (aORs) and confidence intervals (95% CI).

## Results

We included a total of 118 cases aged ≥18 years with ACS (first attack) and an equal number of controls matched by age and gender. The age varied between 18 and 84 with a mean±SD of 54±11.7 years for cases and 54±12 years for controls. Males accounted for 76% and females accounted for 24% of the total number of cases and controls (with no statistically significant difference for age and gender between cases and controls). Saudis represented 38.6% of the sample. The results showed that approximately 50.8% of the cases of ACS were considered STEMI and 28.8% were NSTEMI and only 20% of them had unstable angina. The most frequently used type of PPI was omeprazole (66%), followed by pantoprazole (23%).

**Table 1** reveals that participants with cases of ACS used the PPIs less frequently than the controls (19% versus 29%,) with no statistically significant differences (*p*=0.07). The table also shows that cases of ACS were associated with increased BMI (*p*<0.001). Participants with cases of ACS were about 3 times more overweight and obese compared to the controls. Similarly, smokers were about 3.5 times more likely to have ACS than non-smokers. Moreover, almost half of the cases (42%) had dyslipidemia compared to one-fifth of the controls (18%), with statistically significant differences. Regarding physical activity, the relationship between moderate to high physical activity and ACS was statistically significant. **Table 1** also shows that more than half (56.8%) of the cases were hypertensive compared to 42% of the controls. In addition, diabetes was more apparent among cases than controls.

View this table:
[Table 1](http://smj.org.sa/content/40/11/1098/T1)

Table 1 
Comparison between cases and controls regarding the possible associated factors of acute coronary syndrome (ACS) in Jeddah hospitals, Saudi Arabia.

## Discussion

Regarding the risk factors for ACS, the current study revealed significant associations between hypertension, diabetes, dyslipidemia, current smoking, and excessive body weight (BMI >25 kg/m2) and increased risk of ACS. Similarly, Kastorini et al29 reported significant associations between hypertension, diabetes, dyslipidemia, and smoking and CVDs in Greece.

Regarding family history, our study showed an absence of a significant association between family history of premature heart disease and ACS, which disagrees with the results of Kastorini et al.29 The cause of such a discrepancy might be because we asked specifically about family history of premature heart disease. Results from Oman in 2010 also found an association between family history and coronary heart disease.30 This difference between our study and their study could be because they made comparisons between the young (<40 years of age) and the old (>40 years of age), but our study addressed the relation of family history without differentiating the age of the study sample.

Our results found that moderate-to-high physical activity increased the risk of ACS. Most of our ACS patients recalled that they were physically exerting themselves just before the ACS event. Our study showed that 30.5% of the sample were smokers, which correlates with the results of Alsuwaidi et al study.31 Additionally, 43.2% of our ACS cases were current smokers compared to 54% of ACS patients in Alsuwaidi et al study.31

The current study revealed an absence of statistical association between the use of PPIs and the first attack of non-fatal ACS. Similarly, Simon et al32 conducted a large nationwide cohort study in France and inferred that PPI use was not associated with increased risk of CVDs. However, a Taiwanese study concluded that PPIs might be independently associated with increased risk of myocardial infarction (MI).33 Researchers performed a propensity score matched analysis with an adjusted hazard ratio (aHR) =1.58; 95% CI: 1.11-2.25. Furthermore, the aOR was 4.61 (95% CI:1.76-12.07) for the 7-day window and 3.47 (95% CI: 1.76-6.83) for the 14-day window from the case-crossover part of their study. The differences between our study and the Taiwanese study could be due to the ample sizes, study duration, and the source of information. Moreover, Shah et al34 published a study in 2015 that utilized a data mining approach to examine the association between use of PPI for GERD and MI incidence among the U.S. population. They discovered that patients who used PPIs had a slightly increased risk for MI (aOR: 1.16; 95% CI: 1.09-1.24).34 Other studies showed associations between ACS and other CVDs among patients known to use PPI concomitantly with the antiplatelet drug clopidogrel.12,16,23,35-39

View this table:
[Table 2](http://smj.org.sa/content/40/11/1098/T2)

Table 2 
Calculated odds ratios regarding the possible associated factors of acute coronary syndrome (ACS) in Jeddah hospitals, Saudi Arabia.

Our data obtained from the medical records (such as lipid profile and HbA1c) did not show any significance between cases and controls. This result agrees with results from an older international standardized case-control study.40 It is possible that the actual blood pressure and lipid profile usually measured after the ACS event might have fallen in some patients due to the drugs used in the acute phase or due to the infarction itself. Similarly, the blood glucose level could be high because of the stress of having the disease.40

The interpretations of our conclusions could be used to distribute important messages to public health officials, which could lead to healthier lifestyles and CVD prevention policies.

The power for the comparison of PPI use in cases of ACS and controls was lower than expected. This could be due to the calculation of a sample size with a relatively high OR, in addition to the exclusions and dropouts previously mentioned in the methodology. Moreover, there is recall bias in the case-control study especially with the doses, duration, and the frequency of PPI use. However, to minimize recall bias, the interviewer exhibited pictures of all the brands of PPIs available in the pharmacies in KSA. Additionally, we used the show cards that are associated with the global physical activity questionnaire by the World Health Organization,41 which could have confused the patients during the interview and did not help in physical activity recall, especially for the controls. No data was collected on medications and herbals that could influence ACS and cardiotoxicity other than PPI and anticoagulants. Moreover, we cannot exclude selection bias; the study included only the patients who survived the first non-fatal event of ACS. Controls were hospitalized and selected by purposive sampling based on their age, gender, and the ability to cooperate with the study team.

In conclusion, there was no relationship between the use of PPIs and the development of the first attack of non-fatal ACS. Regarding the risk factors of ACS, smoking is considered the first predictor, followed by excessive body weight and dyslipidemia. Furthermore, ACS is associated with self-reported DM, hypertension, and moderate-to-high physical activity.

It is necessary to conduct more studies, especially cohort studies, and to assess the effect of PPIs alone on the occurrence of ACS. Proton pump inhibitors can yet be used in patients who suffer from gastro-esophageal disorders to alleviate symptoms and enhance their quality of life; however, further investigations regarding drug safety of the PPIs for acute and chronic use should continue. Finally, we should encourage the continuation of health education and promotion to modify the current known risk factors that influence the occurrences of ACS.

## Acknowledgment

*We would like to thank all patients who participated in the study and all officials and data collectors who facilitated it. We would like to thank Proofreading Services ([http://www.ProofreadingServices.com](http://www.ProofreadingServices.com)) for English language editing*.

## Footnotes

*   **Disclosure.** Authors have no conflict of interests, and the work was not supported or funded by any drug company.

*   Received July 19, 2019.
*   Accepted September 25, 2019.


*   Copyright: © Saudi Medical Journal

This is an open-access article distributed under the terms of the Creative Commons Attribution-Noncommercial-Share Alike 3.0 Unported, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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