Published online before print February 7, 2008, doi: 10.1161/STROKEAHA.107.497040
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
(Stroke. 2008;39:845.)
© 2008 American Heart Association, Inc.
Original Contributions |
Nonaspirin Nonsteroidal Anti-inflammatory Drugs and Hemorrhagic Stroke Risk
The Acute Brain Bleeding Analysis Study
From Department of Preventive Medicine (N.-K.C., B.-J.P.) and Department of Neurology (B.-W.Y.), Seoul National University College of Medicine, Seoul, Korea; Department of Neurology (S.-W.J.), Dongguk University International Hospital, Dongguk University College of Medicine, Goyang, Korea; Department of Neurology (K.-H.Y.), Hallym University Sacred Heart Hospital, Hallym University College of Medicine, Anyang, Korea.
Correspondence to Byung-Woo Yoon, Department of Neurology, Seoul National University Hospital, 28 Yeongeon-dong, Jongno-gu, Seoul, 110-744, Korea. E-mail bwyoon{at}snu.ac.kr
 |
Abstract |
|---|
 Top Abstract IntroductionSubjects and MethodsResultsDiscussionReferences |
|---|
Background and Purpose— The relationship between nonaspirin nonsteroidal anti-inflammatory drugs (NANSAIDs) and hemorrhagic stroke (HS) remains unclear. We examined the risk of HS associated with the use of NANSAIDs in Koreans.
Methods— We performed a nationwide, multicenter case-control study from 2002 to 2004. This study included 940 nontraumatic acute HS cases in patients aged 30 to 84 years, with an absence of a history of stroke or hemorrhage-prone brain lesions, alongside 940 community controls, matched to each case by age and sex. Pretrained interviewers obtained information on prescription drugs as well as over-the-counter drugs taken within 14 days before the onset of stroke. We adjusted potential confounders, including family histories of stroke, histories of hypertension, smoking, alcohol consumption, high salt intake, and laborious work hours. The adjusted ORs and their 95% CIs were calculated by conditional logistic regression.
Results— The proportion of NANSAIDs exposure within 14 days was 2.9% for HS patients and 2.0% for the controls. The adjusted odds ratios of stroke in NANSAIDs users compared with nonusers was 1.12 (95% CI, 0.77 to 1.65) for all HS, 1.03 (95% CI, 0.49 to 2.18) for subarachnoid hemorrhage, and 1.19 (95% CI, 0.76 to 1.87) for intracerebral hemorrhage.
Conclusions— No increased risk of HS either subarachnoid hemorrhage or intracerebral hemorrhage was found among NANSAIDs users.
Key Words: anti-inflammatory agents • case-control studies • hemorrhagic • nonsteroidal • stroke
|
Introduction |
|---|
|
TopAbstractIntroductionSubjects and MethodsResultsDiscussionReferences |
|---|
Substantial concerns exist over aspirin or cyclooxygenase (COX)-2 selective nonsteroidal anti-inflammatory drugs and their relations to cardiovascular diseases. However, the impact of nonaspirin nonsteroidal anti-inflammatory drugs (NANSAIDs) on hemorrhagic stroke (HS) has received little attention despite the widespread use of this therapeutic treatment for pain, fever, and inflammation within the general population.
Most NANSAIDs inhibit both COX-1 and COX-2.1 Like NANSAIDs, aspirin acts as an inhibitor of COX; however, the inhibition of platelet COX-1 by aspirin results in antiplatelet effects associated with a reduction in thrombotic events.2 This pharmacological mechanism might increase the risk of HS and decrease the risk of ischemic stroke. Both aspirin and NANSAIDs bind to the same active site on COX;2 therefore, NANSAIDs could have a similar effect as aspirin on hemorrhagic stroke.3,4
Until now, few epidemiological studies have focused on the risk of HS in subjects using NANSAIDs. These studies showed no associations with the use of NANSAIDs and HS.4–6 However, they assessed the information of NANSAIDs exposure using self-reports5 or prescriptions databases to 1999.4,6 Accordingly, they failed to include over-the-counter (OTC) drugs4,6 and selective COX-2 NANSAIDs.4–6 Also, they used discharge diagnoses and proxy measures,6 and only prescription data for current and previous uses of other medications4 for adjusting confounders. For that reason, these studies could not adjust for the precise status of diseases, dietary habits, and physical activity. As we know, only 1 study has assessed both subarachnoid hemorrhage (SAH) and intracerebral hemorrhage (ICH),4 whereas the others only focused on the risk of ICH.5,6 Therefore, we performed a nationwide, multicenter, and matched case-control study in Korea to evaluate the association of NANSAIDs use and HS risk, including SAH and ICH.
|
Subjects and Methods |
|---|
|
TopAbstractIntroductionSubjects and MethodsResultsDiscussionReferences |
|---|
The Acute Brain Bleeding Analysis study is a nationwide multicenter matched case-control study designed to investigate the risk of HS attributable to phenylpropanolamine contained in cold remedies in Korea.7 The cases recruited for this study came from 33 hospitals, including 10 centers scattered regionally and covering considerable areas of South Korea from 2002 to 2004. This study was approved by the Institutional Review Board of every participating hospital and all study participants provided written informed consent to participate.
Identification of Cases
HS was defined as either SAH or ICH. The diagnosis of SAH was based on clinical symptoms via either a brain image (CT, MRI) or evidence of xanthochromia on a lumbar puncture. ICH was diagnosed based on clinical symptoms and the detection of blood in the brain parenchyma or ventricles by CT or MRI. Eligible criteria for the patients included age ranges of 30 to 84 years, absence of a history of stroke or hemorrhage-prone brain lesions, no causal relationship to trauma, and the ability to communicate and complete an interview within 30 days after the onset of the stroke.
Selection of Controls
One community control was matched to each case for sex and age within 5 years. The controls were recruited from siblings, friends, or neighbors of the case subject, in descending order of preference. The eligible criteria for the controls included absence of a history of stroke, absence of dementia or other neurological diseases, and the ability to communicate and complete an interview within 30 days after the onset of the stroke in the matched case.
Data Collection
Trained nurse interviewers administered structured questionnaires, which were evaluated for feasibility by an expert panel, to all participants. To avoid interviewer bias, the interviewers and subjects were kept blind to the hypothesis of this study. They were informed that the aim of this study was to investigate the effect of lifestyles and medications on the risk of HS.
The date showing the initial symptoms of HS were used as the index date for the cases. Each control was questioned based on the index date of their matched case. The information on the following risk factors was obtained from the interview for both cases and controls: age, sex, weight, height, level of education, occupation, smoking status, alcohol consumption, physical activity, duration of work, sleep habits, eating habits, family history of stroke, history of hypertension, diabetes mellitus, hyperlipidemia, heart disease, upper respiratory tract infections within 1 month, and all medications taken on the index date or during the 14 days before the index date. Especially high salt intake was coded as "yes" if the subjects answered that they liked salty food. From the quantitative history of physical activity surveys, we obtained information on physical activity performed in the past 6 months. Physical activity for 
7 hours per week was classified as the high amount group.
We ascertained the exposure history to medications before the index date for all prescribed or OTC dugs. We tried to obtain the prescriptions from all of the subjects. When prescriptions were unavailable or medications were purchased OTC without prescription, the subjects were asked to bring in the medication packages. If these packages were unavailable, we asked the subjects to provide the exact name of the drug and manufacturer and select their medications from a book containing photographs of the packages.
Definition of Drug Exposure
Exposure to NANSAIDs was defined as being exposed to NANSAIDs within 14 days before the index date. The time window of exposure to NANSAIDs was defined as the interval from the last exposure date to that of the index date. We classified NANSAIDs according to selectivity of COX. Nonselective NANSAIDs include aceclofenac, acemetacin, diclofenac, flufenamic acid, ibuprofen, ketoprofen, mefenamic acid, nabumetone, naproxen, piroxicam, pranoprofen, and zaltoprofen. COX-2 preferential and selective NANSAIDs include celecoxib, lornoxicam, meloxicam, nimesulide, rofecoxib, and talniflumate.8
Statistical Analysis
Conditional logistic regression was used to calculate ORs and 95% CIs for HS among users and nonusers of NANSAIDs. Initially, we compared demographic, clinical, and behavioral features of case and control subjects using the Pearson 
2 test, Fisher exact test, or Student t test when appropriate. Variables whose probability values were <0.1 and clinically important were selected as potential adjusting variables. We then selected variables with statistically significant differences between exposed and unexposed persons (P<0.1) with clinical importance among them. Finally, the model included family histories of stroke, histories of hypertension, smoking, alcohol consumption, high salt intake, and laborious work hours as the adjusting variables. Stratified analyses were conducted by different exposure time windows, the classes of NANASID, and the type of HS. Different logistic models were used according to the HS subtype. We adjusted for family history of stroke, history of hypertension, high salt intake, and laborious work hours for both SAH and ICH, and added smoking for the SAH group, and alcohol consumption for the ICH group. The unadjusted and adjusted estimates were calculated for each subgroup. All analyses were performed with SAS version 9.1 (SAS Institute Inc).
|
Results |
|---|
|
TopAbstractIntroductionSubjects and MethodsResultsDiscussionReferences |
|---|
In total, 940 HS cases and 940 controls were recruited. Of these cases, 442 (40.7% males; age, 50.8±10.6 years) had SAH and 498 (58.0% males; age, 57.1±11.4 years) had ICH. Table 1 shows the characteristics of the cases and the controls according to hemorrhagic stroke subtype.
The cases and controls were generally similar with regard to baseline characteristics for both SAH and ICH groups, including age, sex, body mass index, history of diabetes mellitus, history of hyperlipidemia, history of cardiovascular disease, arthritis status, upper respiratory tract infections within 30 days before the index date, use or nonuse of aspirin, and use or nonuse of antiplatelets and anticoagulants. Compared with the control subjects, the case patients were more likely to report a family history of stroke, a history of hypertension, high salt intake, and laborious work of 7 hours per day (P<0.1) for both SAH and ICH groups. Subjects who were current smokers and current alcohol drinkers were more likely to have SAH and ICH, respectively.
|
Table 2 shows the association between NANSAIDs and HS in all of the subjects according to exposure status. Twenty-seven patients (2.9%) with HS were NANSAID users compared with 19 (2.0%) controls, giving a crude OR of 1.18 (95% CI, 0.80 to 1.73). The adjusted OR was 1.12 (95% CI, 0.77 to 1.65) after adjusting for potential confounders. The adjusted ORs for HS according to prescriptions for NANSAIDs within 3 or 14 days before the index date were 1.04 (95% CI, 0.64 to 1.71) and 1.27 (95% CI, 0.70 to 2.30), respectively, compared with nonusers. The adjusted ORs for HS using NANSAIDs were 1.21 (95% CI, 0.79 to 1.87) for nonselective NANSAIDs and 0.89 (95% CI, 0.40 to 2.00) for preferential or selective COX-2 NANSAIDs.
|
The results of the subgroup analyses according to type of HS are summarized in Table 3. The adjusted OR in subjects with SAH was 1.03 (95% CI, 0.49 to 2.18), and ICH was 1.19 (95% CI, 0.76 to 1.87), which showed no statistical significance. The ORs from the subjects after excluding all aspirin users (36 cases and 30 controls) and their matched cases or controls were shown to be consistent with the ORs from all of subjects (data not shown).
|
|
Discussion |
|---|
|
TopAbstractIntroductionSubjects and MethodsResultsDiscussionReferences |
|---|
The results of this matched case-control study show that NANSAIDs are not a risk factor for HS, either in SAH or ICH. The absence of an association was evident in all separate analyses with different exposure times and different classes of NANSAIDs.
This study supports the findings of previous epidemiological studies,4–6 suggesting that use of NANSAIDs is not associated with an increased risk of HS. Although the study by Saloheimo et al9 showed use of NANSAIDs was associated with an increased risk for ICH, the majority of NANSAIDs users concurrently used aspirin in mainly high doses (>1225 mg/wk), which led the researchers to conclude that the elevated risk associated with NANSAIDs use was primarily attributable to concurrent use with aspirin.10
Most of the beneficial and harmful effects of NANSAIDs are related to their inhibition of the COX-1 and COX-2.11 Along with the inhibition of platelet COX-1 activity, there is a decrease in platelet aggregation, leading to reduced thromboembolic potential and a commensurate prolonged bleeding time.12 The effect of aspirin on platelet COX-1 is irreversible, thus the inhibition of COX-1 by aspirin is sustained for 
10 days, the average lifespan of platelets.2,12 Like aspirin, NANSAIDs bind rapidly to COX; however, this binding is reversible and, therefore, short-lived in relation to that of aspirin.2 Consequently, the thrombotic effects of aspirin and NANSAIDs could reveal themselves differently in HS. However, whether the apparently absent antithrombotic effect of NANSAIDs is attributable to the incomplete inhibition of COX-1 or to the concomitant inhibition of COX-2 is unknown.4
This study has several strengths. First, it was a prospective, nationwide case-control study. All cases of HS were confirmed by CT, MRI, or by postmortem examination, so the diagnostic accuracy is high. Furthermore, the neurologists were blinded to the drug exposure information when they evaluated all of the potential cases, according to predefined criteria. Although most previous studies have only assessed the risk of ICH,5,6,9 we compared the ORs in the specific subgroups of HS, both ICH and SAH.
Furthermore, we collected drug exposure data directly from our study participants. This made it possible to record prescribed as well as nonprescribed OTC NANSAIDs. Previous studies were limited in their obtainment of information on OTC NANSAIDs,4,6 which means that the presumptive unexposed group may have included those actually exposed to NANSAIDs. Such misclassification of users as nonusers of NANSAIDs would tend to bias the estimates of NANSAID effects toward the null.13 We minimized interviewer bias by blinding interviewers from the research hypothesis. In addition, before starting the Acute Brain Bleeding Analysis study, a pilot study was conducted to examine the feasibility to confirm items and the order of questionnaire.7
In our study, several risk factors, such as family histories of stroke, history of hypertension, smoking, alcohol consumption, high salt intake, and laborious work hours, associated with HS, were included in the multivariate analysis. Family history of stroke is a risk factor associated with HS.14 Hypertension is also a well-established independent risk factor for both ICH and SAH.15,16 With regard to salt intake and hypertension, many well-designed cross-sectional and longitudinal observational studies have reported that salt intake may increase blood pressure or contribute to hypertension.17–20 Also, physical activity may modify hypertension for HS and directly lower stroke risk as well.21 Recent meta-analysis showed moderate and high levels of physical activity were associated with reduced risks of HS.21,22 Smoking and alcohol drinking are known risk factors for ICH and SAH.23–27 We adjusted all of these risk factors in our statistical analysis.
However, these results must be interpreted in light of some limitations. First, this study presented a lower rate of NANSAIDs exposure than other studies.4–6 The problem could decrease the power of this study. This difference was caused by the definitions of current NANSAIDs users. Some of the other studies labeled current NANSAIDs users even if the subject’s prescription lasted until the index date or ended within 30 days before the index date.4,6 However, we defined exposure to NANSAIDs as being exposed to NANSAIDs within 14 days before the index date. Second, we included patients who were hospitalized and had the mental capacity for responding to a direct interview to avoid information bias from proxy interviewers. In this regard, we included those patients with milder strokes but may have overlooked patients with severe neurological deficits or those who died before they had reached a hospital. Thus, the study participants were not representative of all HS patients. Therefore, our findings do not apply to all HS patients, particularly those having severe or fatal neurological statuses. Third, we collected our information about potential confounders and drug exposure after the onset of HS. This recall bias might have affected the results; therefore, to minimize this effect, we kept the interviewers and participants blind to the major hypothesis of this study. The information on OTC NANSAIDs use from pharmacies was collected by depending on the participants’ memories. Packages of major NANSAIDs were used to aid subjects’ recall of the brand names but failed to cover all of the NANSAIDs in the market. However, we included many kinds of frequently used OTC NANSAIDs packages and the effect of missing OTC drugs used is likely small within our study. In conclusion, we found the use of NANSAIDs does not increase the risk of HS, either SAH or ICH.
|
Acknowledgments |
|---|
Sources of Funding
This study was partially supported by the Korean Food and Drug Administration.
Disclosure
None.
|
Footnotes |
|---|
Continuing medical education (CME) credit is available for this article. Go to http://cme.ahajournals.org to take the quiz.
Received June 24, 2007; revision received August 8, 2007; accepted August 14, 2007.
|
References |
|---|
|
TopAbstractIntroductionSubjects and MethodsResultsDiscussionReferences |
|---|
1. Cryer B. Nonsteroidal anti-inflammatory drugs and gastrointestinal disease. In: Feldman M, Scharschmidt BF, Sleisenger MH, eds. Sleisenger and Fordtran’s gastrointestinal and liver disease pathophysiology/diagnosis/management, 6th ed. Philadelphia: WB Saunders; 1998: 343–357.
2. Corman SL, Fedutes BA, Ansani NT. Impact of nonsteroidal antiinflammatory drugs on the cardioprotective effects of aspirin. Ann Pharmacother. 2005; 39: 1073–1079.
3. Garcia Rodriguez LA, Jick H. Risk of upper gastrointestinal bleeding and perforation associated with individual non-steroidal anti-inflammatory drugs. Lancet. 1994; 343: 769–772.[CrossRef][Medline] [Order article via Infotrieve]
4. Bak S, Andersen M, Tsiropoulos I, Garcia Rodriguez LA, Hallas J, Christensen K, Gaist D. Risk of stroke associated with nonsteroidal anti-inflammatory drugs: a nested case-control study. Stroke. 2003; 34: 379–386.
5. Thrift AG, McNeil JJ, Forbes A, Donnan GA. Risk of primary intracerebral haemorrhage associated with aspirin and non-steroidal anti-inflammatory drugs: case-control study. BMJ. 1999; 318: 759–764.
6. Johnsen SP, Pedersen L, Friis S, Blot WJ, McLaughlin JK, Olsen JH, Sorensen HT. Nonaspirin nonsteroidal anti-inflammatory drugs and risk of hospitalization for intracerebral hemorrhage: a population-based case-control study. Stroke. 2003; 34: 387–391.
7. Yoon BW, Bae HJ, Hong KS, Lee SM, Park BJ, Yu KH, Han MK, Lee YS, Chung DK, Park JM, Jeong SW, Lee BC, Cho KH, Kim JS, Lee SH, Yoo KM; Acute Brain Bleeding Analysis (ABBA) Study Investigators. Phenylpropanolamine contained in cold remedies and risk of hemorrhagic stroke. Neurology. 2007; 68: 146–149.
8. Hardman JG, Limbird LE, Gilman AG. Goodman & Gilman’s the pharmacological basis of therapeutics, 9th ed. New York City: McGraw-Hill; 1996: 621.
9. Saloheimo P, Juvela S, Hillbom M. Use of aspirin, epistaxis, and untreated hypertension as risk factors for primary intracerebral hemorrhage in middle-aged and elderly people. Stroke. 2001; 32: 399–404.
10. Bak S. Nonsteroidal anti-inflammatory drugs as risk factors for spontaneous intracerebral hemorrhage and aneurysmal subarachnoid hemorrhage [letter]. Stroke. 2003; 34: e34–e36.[CrossRef][Medline] [Order article via Infotrieve]
11. Garcia Rodriguez LA, Hernandez-Diaz S. Nonsteroidal antiinflammatory drugs as a trigger of clinical heart failure. Epidemiology. 2003; 14: 240–246.[CrossRef][Medline] [Order article via Infotrieve]
12. Gorelick PB, Weisman SM. Risk of hemorrhagic stroke with aspirin use: an update. Stroke. 2005; 36: 1801–1807.
13. Ilkhanoff L, Lewis JD, Hennessy S, Berlin JA, Kimmel SE. Potential limitations of electronic database studies of prescription non-aspirin non-steroidal anti-inflammatory drugs (NANSAIDs) and risk of myocardial infarction (MI). Pharmacoepidemiol Drug Saf. 2005; 14: 513–522.[CrossRef][Medline] [Order article via Infotrieve]
14. Pfohman M, Criddle LM. Epidemiology of intracranial aneurysm and subarachnoid hemorrhage. J Neurosci Nurs. 2001; 33: 39–41.[Medline] [Order article via Infotrieve]
15. Woo D, Sauerbeck LR, Kissela BM, Khoury JC, Szaflarski JP, Gebel J, Shukla R, Pancioli AM, Jauch EC, Menon AG, Deka R, Carrozzella JA, Moomaw CJ, Fontaine RN, Broderick JP. Genetic and environmental risk factors for intracerebral hemorrhage: preliminary results of a population-based study. Stroke. 2002; 33: 1190–1196.
16. Kissela BM, Sauerbeck L, Woo D, Khoury J, Carrozzella J, Pancioli A, Jauch E, Moomaw CJ, Shukla R, Gebel J, Fontaine R, Broderick J. Subarachnoid hemorrhage: a preventable disease with a heritable component. Stroke. 2002; 33: 1321–1326.
17. Sacks FM, Svetkey LP, Vollmer WM, Appel LJ, Bray GA, Harsha D, Obarzanek E, Conlin PR, Miller ER 3rd, Simons-Morton DG, Karanja N, Lin PH, DASH-Sodium Collaborative Research Group. Effects on blood pressure of reduced dietary sodium and the Dietary Approaches to Stop Hypertension (DASH) diet. N Engl J Med. 2001; 344: 3–10.
18. Krauss RM, Eckel RH, Howard B, Appel LJ, Daniels SR, Deckelbaum RJ, Erdman JW Jr, Kris-Etherton P, Goldberg IJ, Kotchen TA, Lichtenstein AH, Mitch WE, Mullis R, Robinson K, Wylie-Rosett J, St. Jeor S, Suttie J, Tribble DL, Bazzarre TL. AHA Dietary Guidelines. revision 2000: A statement for healthcare professionals from the Nutrition Committee of the American Heart Association. Circulation. 2000; 102: 2284–2299.
19. Whelton PK, He J, Appel LJ, Cutler JA, Havas S, Kotchen TA, Roccella EJ, Stout R, Vallbona C, Winston MC, Karimbakas J; National High Blood Pressure Education Program Coordinating Committee. Primary prevention of hypertension: clinical and public health advisory from The National High Blood Pressure Education Program. JAMA. 2002; 288: 1882–1888.
20. Chobanian AV, Bakris GL, Black HR, Cushman WC, Green LA, Izzo JL Jr, Jones DW, Materson BJ, Oparil S, Wright JT Jr, Roccella EJ; National Heart, Lung, and Blood Institute Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure; National High Blood Pressure Education Program Coordinating Committee. The Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure: the JNC 7 report. JAMA. 2003; 289: 2560–2572.
21. Lee CD, Folsom AR, Blair SN. Physical activity and stroke risk: a meta-analysis. Stroke. 2003; 34: 2475–2481.
22. Wendel-Vos GC, Schuit AJ, Feskens EJ, Boshuizen HC, Verschuren WM, Saris WH, Kromhout D. Physical activity and stroke. A meta-analysis of observational data. Int J Epidemiol. 2004; 33: 787–798.
23. Shinton R, Beevers G. Meta-analysis of relation between cigarette smoking and stroke. BMJ. 1989; 298: 789–794.
24. Gill JS, Shipley MJ, Tsementzis SA, Hornby RS, Gill SK, Hitchcock ER, Beevers DG. Alcohol consumption—a risk factor for hemorrhagic and non-hemorrhagic stroke. Am J Med. 1991; 90: 489–497.[Medline] [Order article via Infotrieve]
25. Feigin VL, Rinkel GJ, Lawes CM, Algra A, Bennett DA, van Gijn J, Anderson CS. Risk factors for subarachnoid hemorrhage: an updated systematic review of epidemiological studies. Stroke. 2005; 36: 2779–2786.
26. Kiyohara Y, Kato I, Iwamoto H, Hayakama K, Fujishima M. The impact of alcohol and hypertension on stroke incidence in a general Japanese population. The Hisayama Study. Stroke. 1995; 26: 368–372.
27. Klatsky AL, Armstrong MA, Friedman GD, Sidney S. Alcohol drinking and risk of hemorrhagic stroke. Neuroepidemiology. 2002; 21: 115–122.[CrossRef][Medline] [Order article via Infotrieve]
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||