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Article

Association between Non-Steroidal Anti-Inflammatory Drug Use and Major Cardiovascular Outcomes in Patients with Acute Coronary Syndrome in the Arabian Gulf

by
Ibrahim Al-Zakwani
1,2,3,*,
Juhaina Salim Al-Maqbali
1,2,
Wael AlMahmeed
4,
Najib AlRawahi
5,
Abdullah Al-Asmi
6 and
Mohammad Zubaid
7
1
Department of Pharmacology & Clinical Pharmacy, College of Medicine & Health Sciences, Sultan Qaboos University, Muscat 123, Oman
2
Department of Pharmacy, Sultan Qaboos University Hospital, Muscat 123, Oman
3
Gulf Health Research, Muscat 111, Oman
4
Heart & Vascular Institute, Cleveland Clinic, Abu Dhabi 112412, United Arab Emirates
5
National Heart Center, Royal Hospital, Muscat 111, Oman
6
Department of Medicine, College of Medicine & Health Sciences, Sultan Qaboos University, Muscat 123, Oman
7
Department of Medicine, Faculty of Medicine, Kuwait University, Safat 24923, Kuwait
*
Author to whom correspondence should be addressed.
J. Clin. Med. 2023, 12(17), 5446; https://doi.org/10.3390/jcm12175446
Submission received: 15 July 2023 / Revised: 15 August 2023 / Accepted: 18 August 2023 / Published: 22 August 2023
(This article belongs to the Section Cardiovascular Medicine)

Abstract

:
Objectives: Studies on the association between non-steroidal anti-inflammatory drugs (NSAIDs) and major adverse cardiovascular events (MACE) in the Arabian Gulf are scarce. The aim of this study was to evaluate the association between NSAIDs use and MACE in acute coronary syndrome (ACS) patients in the Arabian Gulf region. Methods: Data were analyzed from 3007 consecutive patients diagnosed with ACS admitted to 29 hospitals in four Arabian Gulf countries from January 2012 to January 2013, as well as being on prior NSAIDs use during the index admission. The MACE included stroke/transient ischemic attacks (TIAs), myocardial infarction (MI), all-cause mortality and readmissions for cardiac reasons. Results: The overall mean age of the cohort was 62 ± 12 years, and 9.6% (n = 290) of the patients were on prior NSAID use during the index admission. At 12-months follow-up, after adjusting for confounding factors, patients on NSAIDs were significantly more likely to have had MACE (adjusted OR (aOR), 1.89; 95% confidence interval (CI): 1.44–2.48; p < 0.001). Specifically, the higher event rates observed were stroke/TIA (aOR, 2.50; 95% CI: 1.51–4.14; p < 0.001) and readmissions for cardiac reasons (aOR, 2.09; 95% CI: 1.59–2.74; p < 0.001), but not MI (aOR, 1.26; 95% CI: 0.80–1.99; p = 0.320) and all-cause mortality (aOR, 0.79; 95% CI: 0.46–1.34; p = 0.383). Conclusions: NSAIDs use was associated with significant stroke/TIA events as well as readmissions for cardiac reasons. However, NSAIDs were not associated with increased MIs or all-cause mortality rates in patients with ACS in the Arabian Gulf.

1. Introduction

Acute coronary syndrome (ACS) is one of the leading causes of morbidity and mortality in Asia as well as globally [1,2], accounting for approximately seven million deaths and 129 million disability-adjusted life years (DALYs) annually worldwide [3,4]. ACS is also associated with significant economic burden on both direct and indirect healthcare costs, with economic analyses suggesting that hospitalizations and readmissions for ACS account for 60–90% of total annual health care costs [5,6,7].
Non-steroidal anti-inflammatory drugs (NSAIDs) are one of a group of medications that is widely used and easily available over the counter (OTC). More than 70 million prescriptions for NSAIDs are written annually, and taking into account OTC medications, 30 billion doses of NSAIDs are consumed annually in the United States alone [8]. They are used, in the short- and long-term, for a variety of indications, including pain and rheumatoid arthritis, amongst many others. Besides gastrointestinal bleeding, which is partially alleviated by the use of proton pump inhibitors (PPIs), NSAIDs have also been associated with major adverse cardiovascular events (MACE) including stroke [9,10]. The cardiovascular risk may not only be limited to non-selective NSAIDS but also to selective cyclooxygenase 2 (COX-2) inhibitors [11].
The fact that NSAIDs are widely accessible worldwide coupled with their undesirable association with gastrointestinal, renal and cardiovascular side effects makes its continued investigation warranted. There is currently limited research on the use of NSAIDs in ACS population not only in the Arabian Gulf, but in the world at large. Hence, the aim of this study was to evaluate the association between NSAIDs use and MACE, including readmissions for cardiac reasons in patients with ACS in the Arabian Gulf.

2. Methods

The Gulf COAST registry methods have already been previously reported [12]. In summary, the Gulf COAST registry was a prospective, multicenter, multinational, longitudinal cohort study of consecutive citizens from the Arabian Gulf (Bahrain, Kuwait, Oman and United Arab Emirates) admitted to 29 hospitals with a diagnosis of ACS from January 2012 to January 2013. The registry enrolled a total of 4044 patients who were ≥18 years of age with ACS diagnosed according to American College of Cardiology (ACC) clinical data standards [13]. All other diagnoses, including stroke, transient ischemic attack, myocardial infarction, mortality, diabetes mellitus, hypertension, dyslipidemia and heart failure, were also based on key data elements as defined by the ACC clinical data standards [13]. Education was defined as any formal education from primary school and above. Alcohol use was defined as low as any drink/s per week. Apart from excluding non-citizens as well as patients who were not willing/able to provide consent, there were no other exclusion criteria. The study was approved by the local institutional ethics committees of participating centers in the four Arabian Gulf countries.
Data collected included patient demographics (age, gender, employment status, marital status, education status, health insurance, body mass index (BMI), tobacco and alcohol use), medical history and risk factors related to MACE, prior medication use, laboratory data, clinical presentation and management during hospital stay including medications, reperfusion therapy and procedures and discharge medications. Follow up was performed at 12-months from the date of enrolment, and was carried out via clinic visits or telephone interviews.
The main predictor variable was NSAID use, while the outcomes collected included 12-months cumulative stroke/transient ischemic attack (TIA), myocardial infarction (MI), all-cause mortality and readmissions for cardiac reasons as well as overall MACE.

Statistical Analysis

For categorical variables, frequencies and percentages were reported. Differences among groups were analyzed using Pearson’s χ2 tests (or Fisher’s exact tests for expected cells of <5). For continuous variables, mean and standard deviation were used to present the data while analyses were performed using Student’s t-test. Continuous variables that were not normally distributed were summarized as median and interquartile range, and analyses were conducted using Wilcoxon–Mann–Whitney tests. The association between NSAID use and MACE (stroke/TIA, MI, all-cause mortality, readmissions for cardiac reasons and overall MACE) was evaluated via multivariate logistic regression utilizing the simultaneous method and adjusting for the GRACE risk score for in-hospital mortality, which has been validated in an Arabian Gulf ACS Registry [14]. Apart from the GRACE risk score variables (which are derived from age, heart rate, systolic blood pressure (BP), serum creatinine, cardiac arrest at admission, ST segment deviation on EKG, abnormal cardiac enzymes and Killip class), the logistic models were also adjusted for gender, smoking status, marital status, employment status, education status, BMI, diabetes mellitus, peripheral artery disease, percutaneous coronary intervention (PCI)/coronary artery bypass graft (CABG), prior event and use of evidence-based cardiac medications at hospital discharge (aspirin, clopidogrel, beta blocker, statin, angiotensin converting enzyme inhibitor (ACEI) or angiotensin receptor blocker (ARB)).
The goodness-of-fit of the multivariable logistic models was examined using the Hosmer–Lemeshow goodness-of-fit statistic [15] as well as the C-index [16]. An a priori two-tailed level of significance was set at the 0.05 level. Statistical analyses were conducted using STATA version 16.1 (StataCorp., 2013, Stata Statistical Software, College Station, TX, USA).

3. Results

Out of the 4044 subjects enrolled by the Gulf COAST registry, the present analysis only included patients with non-missing NSAID information (N = 3007). A total of 9.6% (n = 290) of the patients were on prior NSAID use during the index admission. The overall mean age of the cohort was 62 ± 12 years, of which 62% (n = 1851) were males. A total of 22% (n = 647) of the patients were employed and 83% (n = 2495) were married. Thirty-four percent of the patients (n = 1037) were current or prior smokers, and 2.9% (n = 87) were alcohol consumers. Comorbid conditions were common, particularly hypertension (81%; n = 2433), dyslipidemia (70%; n = 2101) and diabetes mellitus (63%; n = 1903).
As shown in Table 1, patients on NSAIDs (compared to patients not on NSAIDs) were more likely to be female (44% vs. 38%; p = 0.049), educated (54% vs. 46%; p = 0.013), associated with dyslipidemia (77% vs. 69%; p = 0.009), hypertension (86% vs. 80%; p = 0.016) and heart failure (20% vs. 14%; p = 0.012). However, patients on NSAIDs were less likely to be associated with diabetes mellitus (57% vs. 64%; p = 0.018) and non-ST-elevation MI (41% vs. 52%; p < 0.001).
Table 2 shows medication utilization prior to admission and the post-discharge data are stratified by NSAIDs use. Prior to the index admission, patients on NSAIDs were also more likely to have been on aspirin (85% vs. 79%; p = 0.023) and clopidogrel (35% vs. 28%; p = 0.015). While 98% (n = 2705) of the cohort was treated optimally with the dual antiplatelet combination (aspirin and clopidogrel concurrently), only 52% (n = 1427) of the patients were prescribed the 5-drug regimen (aspirin, clopidogrel, ACEI/ARB, statin, beta blocker) concurrently, which was significantly higher among patients on NSAIDs than those not on NSAIDs (62% vs. 51%; p = 0.001).
The overall MACE rate was 41.1% (n = 1195), with significant differences among the groups as shown in Table 3. Adjusting for demographic and clinical characteristics as well as socioeconomic measures (insurance type, employment, education and marital status), at 12-months follow-up, patients on NSAIDs were significantly more likely to have had MACE (adjusted OR (aOR), 1.89; 95% confidence interval (CI): 1.44–2.48; p < 0.001). The higher event rates were specifically observed in stroke/TIA (aOR, 2.50; 95% CI: 1.51–4.14; p < 0.001) and in readmissions for cardiac reasons (aOR, 2.09; 95% CI: 1.59–2.74; p < 0.001), but not in MI (aOR, 1.26; 95% CI: 0.80–1.99; p = 0.320) and 12-months all-cause mortality (aOR, 0.79; 95% CI: 0.46–1.34; p = 0.383).

4. Discussion

To the best of our knowledge, this is the only study in the Arabian Gulf to have evaluated the association between NSAIDs use and the development of MACE in patients with ACS. At 12-months follow-up, patients on prior use of NSAIDs were associated with increased risk of stroke/TIA events and readmissions for cardiac reasons when compared to patients who were not on NSAIDs. However, NSAIDs use was not associated with increased MI or all-cause mortality rates in patients with ACS in the Arabian Gulf.
Similar to the current findings, a number of other meta-analyses and review articles have also reported that the use of various types of NSAIDs (both non-selective as well as COX-2 inhibitors) are associated with the development of stroke/TIA events compared to patients not using NSAIDs [17,18,19,20,21,22]. The potential mechanisms for NSAID-associated increase in stroke risk are hypothesized to be due to vasoconstriction secondary to inhibition of prostacyclin-induced vasodilation, hypertension induced by direct renal effects on sodium excretion leading to volume expansion and thrombosis due to prostaglandin-mediated platelet aggregation [23]. This study did not document the actual types of NSAIDs used, and this shortcoming may pose a significant limitation, as some have been more associated with stroke/TIA events than others [18]. Furthermore, this study also did not report the duration of use of NSAIDs. However, no safe window on concomitant use of NSAIDs has been reported, with even short-term (0–3 days) use being associated with increased risk of bleeding compared with no NSAIDs use [24].
Our findings showed a significant association between the use of NSAIDs in patients with ACS and readmissions due to cardiac reasons, which can be partly explained by the type, dose and duration of use of NSAIDs, which were not documented in our study. Furthermore, the risk of cardiac complications is higher in the first week of NSAIDs use, but not for all types of NSAIDs, as reported in some studies [10]. A population-based matched case–control study in Finland [25] showed that hospitalizations due to myocardial infarctions in patients using NSAIDs accounted for 17,000 hospitalizations annually. The current study did not show any differences in myocardial infarction rates between the groups, not only at baseline (Table 1), but also at 1-year follow-up (Table 3); however, the NSAIDs group was associated with a higher prevalence of hypertension and heart failure (Table 1), which has been reported as the main reason behind readmissions in patients with ACS [26].
In conclusion, NSAIDs use was associated with a significant increase in stroke/TIA events, as well as readmissions for cardiac reasons. However, NSAIDs were not associated with increased MI or all-cause mortality rates in patients with ACS in the Arabian Gulf. These findings should be interpreted in light of the study’s limitations.

5. Limitations

As this was a retrospective study and the fact that the analyses were also adjusted for various confounding factors, bias could still have existed between the groups, as we were not able to control for unmeasured confounding variables. Instead of all-cause mortality, it would have been more pertinent to have reported cardiovascular mortality. Even though all types of NSAIDs are implicated in cardiovascular events, it would have been more informative to have reported the different types of NSAIDs involved. Furthermore, NSAIDs use was only reported during the index hospital admission; they could have been stopped or changed during the 1-year follow-up. However, as reported earlier, there is no safe window on the concomitant use of NSAIDs; even a short-term use period of a few days has been associated with an increased risk of bleeding [24]. A total of 3.2% (n = 97) of the subjects were lost to follow-up at 12-months, and this could have biased the outcomes; however, there were no significant differences in the demographic and clinical characteristics between the patients that were lost to follow-up against the group that remained during the 12-months follow-up period (Table 4).

Author Contributions

Conceptualization, M.Z., I.A.-Z., J.S.A.-M. and W.A.; methodology, M.Z., I.A.-Z. and J.S.A.-M.; software, I.A.-Z. and J.S.A.-M.; validation, M.Z., I.A.-Z., J.S.A.-M., W.A., N.A. and A.A.-A.; formal analysis, I.A.-Z.; investigation, M.Z., W.A., N.A. and A.A.-A.; resources, M.Z., W.A. and N.A.; data curation, M.Z., W.A. and N.A.; writing—original draft preparation, M.Z., I.A.-Z., J.S.A.-M., W.A. and A.A.-A.; writing—review and editing, M.Z., I.A.-Z., J.S.A.-M., W.A., N.A. and A.A.-A.; visualization, M.Z., I.A.-Z., J.S.A.-M. and W.A.; supervision, M.Z. and I.A.-Z.; project administration, M.Z. and I.A.-Z.; funding acquisition, M.Z., W.A. and N.A. All authors have read and agreed to the published version of the manuscript.

Funding

Gulf COAST is an investigator-initiated study that was supported by AstraZeneca and Kuwait University (project code XX02/11). Neither Kuwait University nor AstraZeneca had any role in the study design, data collection, data analysis, or writing of the article.

Institutional Review Board Statement

The study was approved by the local institutional ethics committees of participating centers in the four Arabian Gulf countries (Kuwait, Joint Committee for the Protection of Human Subjects in Research, VDR/JC/89, 13/10/2011; Oman, Ethical Review & Approve Committee, Ministry of Health Research, MH/DGP/R&S/PROPOSAL_APPROVED/1/2012, 9/1/2012; Bahrain, Secondary Care Medical Research Subcommittee, Ministry of Health, 23/12/2011; Abu Dhabi UAE, Institutional Review Board/Research Ethics Committee, Sheikh Khalifa Medical City, REC-24.11.2011 [RS 189], 24/11/2011; Abu Dhabi UAE, Institutional Review Board, Medical Services Corps, General Head Quarters Armed Forces, 18/11/2011; Al Ain UAE, Al Ain Medical District Human Research Ethics Committee, Faculty of Medicine & Health Sciences, United Arab Preprints (www.preprints.org (accessed on 20 May 2023)) | NOT PEER-REVIEWED | Posted: 25 July 2023 doi:10.20944/preprints202307.1647.v1 3 Emirates University, Protocol No. 11/48, 24/11/2011; Dubai UAE, Medical Research Committee, Dubai Health Authority, MRC-11/2011_2, 30/11/202011).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

Data were anonymized for this study. All data are available upon request to the corresponding author.

Acknowledgments

The authors would like to thank the patients, physicians, nurses and support staff who participated in the Gulf COAST Registry for their invaluable cooperation.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Global Burden of Disease Study 2013 Collaborators. Global, regional, and national incidence, prevalence, and years lived with disability for 301 acute and chronic diseases and injuries in 188 countries, 1990–2013: A systematic analysis for the Global Burden of Disease Study 2013. Lancet 2015, 386, 743–800. [Google Scholar] [CrossRef] [PubMed]
  2. Ohira, T.; Iso, H. Cardiovascular disease epidemiology in Asia: An overview. Circ. J. 2013, 77, 1646–1652. [Google Scholar] [CrossRef]
  3. Lozano, R.; Naghavi, M.; Foreman, K.; Lim, S.; Shibuya, K.; Aboyans, V.; Abraham, J.; Adair, T.; Aggarwal, R.; Ahn, S.; et al. Global and regional mortality from 235 causes of death for 20 age groups in 1990 and 2010: A systematic analysis for the Global Burden of Disease Study 2010. Lancet 2012, 380, 2095–2128. [Google Scholar] [CrossRef] [PubMed]
  4. Murray, C.J.; Vos, T.; Lozano, R.; Naghavi, M.; Flaxman, A.D.; Michaud, C.; Ezzati, M.; Shibuya, K.; Salomon, J.A.; Abdalla, S.; et al. Disability-adjusted life years (DALYs) for 291 diseases and injuries in 21 regions, 1990–2010: A systematic analysis for the Global Burden of Disease Study 2010. Lancet 2012, 380, 2197–2223. [Google Scholar] [CrossRef] [PubMed]
  5. Page, R.L., 2nd; Ghushchyan, V.; Gifford, B.; Allen, R.R.; Raut, M.; Crivera, C.; Naim, A.B.; Nair, K.V. The economic burden of acute coronary syndromes for employees and their dependents: Medical and productivity costs. J. Occup. Environ. Med. 2013, 55, 761–767. [Google Scholar] [CrossRef]
  6. Johnston, S.S.; Curkendall, S.; Makenbaeva, D.; Mozaffari, E.; Goetzel, R.; Burton, W.; Maclean, R. The direct and indirect cost burden of acute coronary syndrome. J. Occup. Environ. Med. 2011, 53, 2–7. [Google Scholar] [CrossRef]
  7. Zhao, Z.; Winget, M. Economic burden of illness of acute coronary syndromes: Medical and productivity costs. BMC Health Serv. Res. 2011, 11, 35. [Google Scholar] [CrossRef]
  8. Wiegand, T.J.; Vernetti, C.M. Nonsteroidal Anti-Inflammatory Drug (NSAID) Toxicity. Medscape. 2020. Available online: https://emedicine.medscape.com/article/816117-print (accessed on 14 July 2020).
  9. Fanelli, A.; Ghisi, D.; Aprile, P.L.; Lapi, F. Cardiovascular and cerebrovascular risk with nonsteroidal anti-inflammatory drugs and cyclooxygenase 2 inhibitors: Latest evidence and clinical implications. Ther. Adv. Drug Saf. 2017, 8, 173–182. [Google Scholar] [CrossRef]
  10. Bally, M.; Dendukuri, N.; Rich, B.; Nadeau, L.; Helin-Salmivaara, A.; Garbe, E.; Brophy, J.M. Risk of acute myocardial infarction with NSAIDs in real world use: Bayesian meta-analysis of individual patient data. BMJ 2017, 357, j1909. [Google Scholar] [CrossRef]
  11. Park, K.; Bavry, A.A. Risk of stroke associated with nonsteroidal anti-inflammatory drugs. Vasc. Health Risk Manag. 2014, 10, 25–32. [Google Scholar]
  12. Zubaid, M.; Thani, K.B.; Rashed, W.; Alsheikh-Ali, A.; Alrawahi, N.; Ridha, M.; Akbar, M.; Alenezi, F.; Alhamdan, R.; Almahmeed, W.; et al. Design and Rationale of Gulf locals with Acute Coronary Syndrome Events (Gulf Coast) Registry. Open Cardiovasc. Med. J. 2014, 8, 88–93. [Google Scholar] [CrossRef] [PubMed]
  13. Writing Committee Members; Weintraub, W.S.; Karlsberg, R.P.; Tcheng, J.E.; Boris, J.R.; Buxton, A.E.; Dove, J.T.; Fonarow, G.C.; Goldberg, L.R.; Heidenreich, P.; et al. ACCF/AHA 2011 key data elements and definitions of a base cardiovascular vocabulary for electronic health records: A report of the American College of Cardiology Foundation/American Heart Association Task Force on Clinical Data Standards. J. Am. Coll. Cardiol. 2011, 58, 202–222. [Google Scholar] [CrossRef] [PubMed]
  14. Panduranga, P.; Sulaiman, K.; Al-Zakwani, I.; Zubaid, M.; Rashed, W.; Al-Mahmeed, W.; Al-Lawati, J.; Al-Motarreb, A.; Haitham, A.; Suwaidi, J.; et al. Utilization and determinants of in-hospital cardiac catheterization in patients with acute coronary syndrome from the Middle East. Angiology 2010, 61, 744–750. [Google Scholar] [CrossRef] [PubMed]
  15. Lemeshow, S.; Hosmer, D.W., Jr. A review of goodness of fit statistics for use in the development of logistic regression models. Am. J. Epidemiol. 1982, 115, 92–106. [Google Scholar] [CrossRef]
  16. Hanley, J.A.; McNeil, B.J. The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology 1982, 143, 29–36. [Google Scholar] [CrossRef]
  17. Schink, T.; Kollhorst, B.; Varas Lorenzo, C.; Arfè, A.; Herings, R.; Lucchi, S.; Romio, S.; Schade, R.; Schuemie, M.J.; Straatman, H.; et al. Risk of ischemic stroke and the use of individual non-steroidal anti-inflammatory drugs: A multi-country European database study within the SOS Project. PLoS ONE 2018, 13, e0203362. [Google Scholar] [CrossRef]
  18. Varga, Z.; Sabzwari, S.R.A.; Vargova, V. Cardiovascular Risk of Nonsteroidal Anti-Inflammatory Drugs: An Under-Recognized Public Health Issue. Cureus 2017, 9, e1144. [Google Scholar] [CrossRef]
  19. Trelle, S.; Reichenbach, S.; Wandel, S.; Hildebrand, P.; Tschannen, B.; Villiger, P.M.; Egger, M.; Jüni, P. Cardiovascular safety of non-steroidal anti-inflammatory drugs: Network meta-analysis. BMJ 2011, 342, c7086. [Google Scholar] [CrossRef]
  20. Kearney, P.M.; Baigent, C.; Godwin, J.; Halls, H.; Emberson, J.R.; Patrono, C. Do selective cyclo-oxygenase-2 inhibitors and traditional non-steroidal anti-inflammatory drugs increase the risk of atherothrombosis? Meta-analysis of randomised trials. BMJ 2006, 332, 1302–1308. [Google Scholar] [CrossRef]
  21. Varas-Lorenzo, C.; Riera-Guardia, N.; Calingaert, B.; Castellsague, J.; Pariente, A.; Scotti, L.; Sturkenboom, M.; Perez-Gutthann, S. Stroke risk and NSAIDs: A systematic review of observational studies. Pharmacoepidemiol. Drug Saf. 2011, 20, 1225–1236. [Google Scholar] [CrossRef]
  22. Coxib and Traditional NSAID Trialists’ (CNT) Collaboration; Bhala, N.; Emberson, J.; Merhi, A.; Abramson, S.; Arber, N.; Baron, J.A.; Bombardier, C.; Cannon, C.; Farkouh, M.E.; et al. Vascular and upper gastrointestinal effects of non-steroidal anti-inflammatory drugs: Meta-analyses of individual participant data from randomised trials. Lancet 2013, 382, 769–779. [Google Scholar] [PubMed]
  23. Fitzgerald, G.A. Coxibs and cardiovascular disease. N. Engl. J. Med. 2004, 21, 1709–1711. [Google Scholar] [CrossRef] [PubMed]
  24. Schjerning Olsen, A.M.; Gislason, G.H.; McGettigan, P.; Fosbøl, E.; Sørensen, R.; Hansen, M.L.; Køber, L.; Torp-Pedersen, C.; Lamberts, M. Association of NSAID use with risk of bleeding and cardiovascular events in patients receiving antithrombotic therapy after myocardial infarction. JAMA 2015, 313, 805–814. [Google Scholar] [CrossRef] [PubMed]
  25. Helin-Salmivaara, A.; Virtanen, A.; Vesalainen, R.; Grönroos, J.M.; Klaukka, T.; Idänpään-Heikkilä, J.E.; Huupponen, R. NSAID use and the risk of hospitalization for first myocardial infarction in the general population: A nationwide case-control study from Finland. Eur. Heart J. 2006, 27, 1657–1663. [Google Scholar] [CrossRef] [PubMed]
  26. Johnsen, S.P.; Larsson, H.; Tarone, R.E.; McLaughlin, J.K.; Nørgård, B.; Friis, S.; Sørensen, H.T. Risk of hospitalization for myocardial infarction among users of rofecoxib, celecoxib, and other NSAIDs: A population-based case-control study. Arch. Intern. Med. 2005, 165, 978–984. [Google Scholar] [CrossRef]
Table 1. Demographic and clinical characteristics of the acute coronary syndrome cohort stratified by non-steroidal anti-inflammatory drug (NSAID) use.
Table 1. Demographic and clinical characteristics of the acute coronary syndrome cohort stratified by non-steroidal anti-inflammatory drug (NSAID) use.
Characteristic,
n (%) Unless Specified Otherwise
All
(N = 3007)
NSAID Usep-Value
No
(n = 2717)
Yes
(n = 290)
Demographic
 Age, mean ± SD, years62 ± 1262 ± 1263 ± 120.124
 Female gender1156 (38%)1029 (38%)127 (44%)0.049
 Educated1410 (47%)1254 (46%)156 (54%)0.013
 Employed647 (22%)592 (22%)55 (19%)0.266
 Married2495 (83%)2252 (83%)243 (84%)0.696
 BMI, mean ± SD, kg/m229.1 ± 7.029.1 ± 7.128.7 ± 6.30.305
 Smoking (current or prior)1037 (34%)939 (35%)98 (34%)0.794
 Alcohol87 (2.9%)75 (2.8%)12 (4.1%)0.183
Past medical history
 Prior MI1026 (34%)933 (34%)93 (32%)0.438
 Dyslipidemia2101 (70%)1879 (69%)222 (77%)0.009
 Premature CAD446 (15%)405 (15%)41 (14%)0.726
 Hypertension2433 (81%)2183 (80%)250 (86%)0.016
 Heart failure441 (15%)384 (14%)57 (20%)0.012
 Diabetes mellitus1903 (63%)1738 (64%)165 (57%)0.018
 Stroke/TIA274 (9.1%)254 (9.0%)29 (10%)0.580
Clinical (parameters) at presentation
 HR, mean ± SD, bpm86 ± 2186 ± 2185 ± 220.229
 SBP, mean ± SD, mmHg142 ± 28142 ± 28143 ± 290.519
 DBP, mean ± SD, mmHg80 ± 1680 ± 1680 ± 170.800
 Crea, p50 (IQR), µmol/L86 (68–113)86 (68–113)85 (68–104)0.772
 LVEF, mean ± SD, %49 ± 1348 ± 1350 ± 13<0.001
 GRACE risk, mean ± SD130 ± 42130 ± 42130 ± 430.789
 CRUSADE risk score38 ± 1538 ± 1538 ± 150.735
 Major bleed62 (2.1%)54 (2.0%)8 (2.8%)0.380
Killip class 0.320
 I—no heart failure2270 (75%)2063 (76%)207 (71%)
 II—rales457 (15%)403 (15%)54 (19%)
 III—pulmonary edema250 (8.3%)224 (8.2%)26 (9.0%)
 IV—cardiogenic shock30 (1.0%)27 (1.0%)3 (1.0%)
Discharged diagnosis * <0.001
 LBBB MI19 (0.7%)16 (0.6%)3 (1.1%)
 NSTEMI1474 (51%)1358 (52%)116 (41%)
 STEMI476 (17%)433 (17%)43 (15%)
 Unstable angina908 (32%)789 (30%)119 (42%)
SD, standard deviation; BMI, body mass index; MI, myocardial infarction; CAD, coronary artery disease; TIA, transient ischemic attack; HR, heart rate; bpm, beats per minute; SBP, systolic blood pressure; DBP, diastolic blood pressure; Crea, first serum creatinine; p50, median; IQR, interquartile range; LVEF, left ventricular ejection fraction; GRACE, global registry of acute coronary events; LBBB, left bundle branch block; NSTEMI, non-ST myocardial infarction; STEMI, ST-elevation myocardial infarction. BMI was missing in 47 subjects, HR in 4 subjects, SBP and DBP in 5 subjects, creatinine in 10 subjects, LVEF was missing in 468 subjects, GRACE in 14 subjects, 64 subjects in CRUSADE risk score. * The ‘discharged diagnosis’ excluded 129 patients that died in-hospital during the index admission while 1 patient had ‘discharged diagnosis’ missing. Percentages might not add up to 100% due to rounding off.
Table 2. Medication utilization of the acute coronary syndrome cohort stratified by non-steroidal anti-inflammatory drug (NSAID) use.
Table 2. Medication utilization of the acute coronary syndrome cohort stratified by non-steroidal anti-inflammatory drug (NSAID) use.
Characteristic,
n (%) Unless Specified Otherwise
All
(N = 3007)
NSAID Usep-Value
No
(n = 2717)
Yes
(n = 290)
Prior medications
 Aspirin2397 (80%)2151 (79%)246 (85%)0.023
 Clopidogrel863 (29%)762 (28%)101 (35%)0.015
 ACEIs1562 (52%)1437 (53%)125 (43%)0.002
 ARBs573 (19%)485 (18%)88 (30%)<0.001
 Beta blockers1828 (61%)1639 (60%)189 (65%)0.108
 Statins2428 (81%)2186 (80%)242 (83%)0.219
 Other LLDs60 (2.0%)57 (2.1%)3 (1.0%)0.273
 Oral nitrates1049 (35%)670 (42%)379 (27%)<0.001
 CCBs599 (20%)523 (19%)76 (26%)0.005
 H2-receptor antagonists410 (14%)331 (12%)79 (27%)<0.001
 Proton pump inhibitors617 (21%)527 (19%)90 (31%)<0.001
Discharged medications (N = 2747) *
 Aspirin2645 (96%)2388 (96%)257 (98%)0.197
 Clopidogrel2009 (73%)1792 (72%)217 (83%)<0.001
 ACEIs1795 (65%)1624 (65%)171 (65%)0.907
 ARBs499 (18%)443 (18%)56 (21%)0.168
 Beta blockers2324 (85%)2089 (84%)235 (89%)0.025
 Statins2675 (97%)2414 (97%)261 (99%)0.050
 Other LLDs75 (2.7%)67 (2.7%)8 (3.0%)0.745
 Oral nitrates1722 (63%)1562 (63%)160 (61%)0.509
 CCBs509 (19%)462 (19%)47 (18%)0.770
 Dual antiplatelets2705 (98%)2445 (98%)260 (99%)0.589
 5-drug regimen1427 (52%)1265 (51%)162 (62%)0.001
 H2-receptor antagonists582 (21%)517 (21%)65 (25%)0.142
 Proton pump inhibitors356 (13%)315 (13%)41 (16%)0.183
ACEI, angiotensin-converting enzyme inhibitor; ARB, angiotensin II receptor blocker; LLD, lipid lowering drug; CCBs, calcium channel blockers; Dual antiplatelets, aspirin and clopidogrel concurrently; 5 drug regimen, concurrent prescribing of aspirin, clopidogrel, ACEI/ARB, statin, beta blocker. The discharged medications excluded patients that died in-hospital (n = 129) during the index admission as well as patients that had missing drug information (n = 131), while patients on discharged ARB, statins, other LLTs, oral nitrates, CCBs, proton pump inhibitors and H2 receptor blockers had one further patient excluded due to missing drug information. Percentages might not add up to 100% due to rounding off.
Table 3. Association between non-steroidal anti-inflammatory drug (NSAID) use and 12-month cumulative major adverse cardiovascular events (MACE) in acute coronary syndrome patients in the Arabian Gulf.
Table 3. Association between non-steroidal anti-inflammatory drug (NSAID) use and 12-month cumulative major adverse cardiovascular events (MACE) in acute coronary syndrome patients in the Arabian Gulf.
Outcome Univariate Statistics (NSAID Use)Multivariate Logistic Regression
All (N = 2910)No (n = 2627)Yes (n = 283)p-ValueAdj. OR [95% CI]Adj. p-ValueHLROC
Stroke/TIA143 (4.9%)115 (4.4%)28 (9.9%)<0.0012.50 [1.51–4.14]<0.0010.9170.75
Myocardial infarction249 (8.6%)223 (8.5%)26 (9.2%)0.6901.26 [0.80–1.99]0.3200.1020.71
All-cause Mortality395 (13.6%)366 (14.0%)29 (10.3%)0.0860.79 [0.46–1.34]0.3830.0750.78
Re-admissions823 (28.3%)705 (26.8%)118 (41.7%)<0.0012.09 [1.59–2.74]<0.0010.6650.61
Total MACE1195 (41.1%)1052 (40.1%)143 (50.5%)0.0011.89 [1.44–2.48]<0.0010.3910.67
Adj. OR, adjusted odds ratio; CI, confidence interval; HL, Hosmer–Lemeshow p-value; ROC, area under the receiver operating curve (also known as c-statistic); TIA, transient ischemic attack; re-admissions, re-admissions for cardiac reasons. MACE included stroke/TIA, myocardial infarction, mortality and re-admissions for cardiac reasons. For 6-month and 12-month follow-up, the events were cumulative. Multivariate analyses were conducted using logistic regression models utilizing the simultaneous method. The covariates in the models included GRACE risk score (derived from age, heart rate, systolic blood pressure, serum creatinine, cardiac arrest at admission, ST segment deviation on EKG, abnormal cardiac enzymes and Killip class) as well as gender, smoking status, marital status, employment status, education status, body mass index, diabetes mellitus, peripheral artery disease, percutaneous coronary intervention/coronary artery bypass graft, prior event and use of evidence-based cardiac medications at hospital discharge (aspirin, clopidogrel, beta blocker, statin, angiotensin converting enzyme inhibitor (ACEI) or angiotensin receptor blocker (ARB)). Over the 1-year follow-up period, there were losses to follow-up of 97 (3.2%) patients.
Table 4. Demographic and clinical characteristics between the non-steroidal anti-inflammatory drug group remaining at the end of the year and the cohort that was lost to follow-up (LTF).
Table 4. Demographic and clinical characteristics between the non-steroidal anti-inflammatory drug group remaining at the end of the year and the cohort that was lost to follow-up (LTF).
Characteristic,
Mean ± SD Unless Specified Otherwise
LTF
(n = 97)
3.2%
Remaining
(n = 2910)
96.8%
p-Value
Demographic
 Age, years62 ± 1162 ± 120.940
 Female gender, n (%)38 (39%)1118 (38%)0.880
 BMI, kg/m229.4 ± 5.529.1 ± 7.10.646
Clinical, n (%)
 Prior MI32 (33%)994 (34%)0.811
 Hypertension81 (84%)2352 (81%)0.509
 Diabetes mellitus69 (71%)1834 (63%)0.103
 Stroke/TIA8 (8.3%)266 (9.1%)0.764
Presentation, n (%)
 SBP, mmHg143 ± 29142 ± 280.960
 DBP, mmHg80 ± 1780 ± 160.832
 Killip ≥ 2, n (%)23 (24%)714 (25%)0.853
 GRACE risk score132 ± 41130 ± 420.668
 CRUSADE risk score39 ± 1538 ± 150.603
 Major bleeding 3 (3.1%)59 (2.0%)0.451
 Prior PCI30 (31%)793 (27%)0.424
SD, standard deviation; BMI, body mass index; MI, myocardial infarction; TIA, transient ischemic attack; SBP, systolic blood pressure; DBP, diastolic blood pressure; GRACE, global registry of acute coronary events; PCI, percutaneous coronary intervention (includes any prior PCI). BMI was missing in 47 subjects, SBP and DBP in 5 subjects, GRACE risk score in 14 subjects and 64 subjects in the CRUSADE risk score. Percentages may not add up too 100% due to rounding off.
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MDPI and ACS Style

Al-Zakwani, I.; Al-Maqbali, J.S.; AlMahmeed, W.; AlRawahi, N.; Al-Asmi, A.; Zubaid, M. Association between Non-Steroidal Anti-Inflammatory Drug Use and Major Cardiovascular Outcomes in Patients with Acute Coronary Syndrome in the Arabian Gulf. J. Clin. Med. 2023, 12, 5446. https://doi.org/10.3390/jcm12175446

AMA Style

Al-Zakwani I, Al-Maqbali JS, AlMahmeed W, AlRawahi N, Al-Asmi A, Zubaid M. Association between Non-Steroidal Anti-Inflammatory Drug Use and Major Cardiovascular Outcomes in Patients with Acute Coronary Syndrome in the Arabian Gulf. Journal of Clinical Medicine. 2023; 12(17):5446. https://doi.org/10.3390/jcm12175446

Chicago/Turabian Style

Al-Zakwani, Ibrahim, Juhaina Salim Al-Maqbali, Wael AlMahmeed, Najib AlRawahi, Abdullah Al-Asmi, and Mohammad Zubaid. 2023. "Association between Non-Steroidal Anti-Inflammatory Drug Use and Major Cardiovascular Outcomes in Patients with Acute Coronary Syndrome in the Arabian Gulf" Journal of Clinical Medicine 12, no. 17: 5446. https://doi.org/10.3390/jcm12175446

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