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      Triggering Myocardial Infarction by Marijuana

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          Abstract

          Marijuana use in the age group prone to coronary artery disease is higher than it was in the past. Smoking marijuana is known to have hemodynamic consequences, including a dose-dependent increase in heart rate, supine hypertension, and postural hypotension; however, whether it can trigger the onset of myocardial infarction is unknown. In the Determinants of Myocardial Infarction Onset Study, we interviewed 3882 patients (1258 women) with acute myocardial infarction an average of 4 days after infarction onset. We used the case-crossover study design to compare the reported use of marijuana in the hour preceding symptoms of myocardial infarction onset to its expected frequency using self-matched control data. Of the 3882 patients, 124 (3.2%) reported smoking marijuana in the prior year, 37 within 24 hours and 9 within 1 hour of myocardial infarction symptoms. Compared with nonusers, marijuana users were more likely to be men (94% versus 67%, P<0.001), current cigarette smokers (68% versus 32%, P<0.001), and obese (43% versus 32%, P=0.008). They were less likely to have a history of angina (12% versus 25%, P<0.001) or hypertension (30% versus 44%, P=0.002). The risk of myocardial infarction onset was elevated 4.8 times over baseline (95% confidence interval, 2.4 to 9.5) in the 60 minutes after marijuana use. The elevated risk rapidly decreased thereafter. Smoking marijuana is a rare trigger of acute myocardial infarction. Understanding the mechanism through which marijuana causes infarction may provide insight into the triggering of myocardial infarction by this and other, more common stressors.

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          Most cited references20

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          Estimation of a common effect parameter from sparse follow-up data.

          Breslow (1981, Biometrika 68, 73-84) has shown that the Mantel-Haenszel odds ratio is a consistent estimator of a common odds ratio in sparse stratifications. For cohort studies, however, estimation of a common risk ratio or risk difference can be of greater interest. Under a binomial sparse-data model, the Mantel-Haenszel risk ratio and risk difference estimators are consistent in sparse stratifications, while the maximum likelihood and weighted least squares estimators are biased. Under Poisson sparse-data models, the Mantel-Haenszel and maximum likelihood rate ratio estimators have equal asymptotic variances under the null hypothesis and are consistent, while the weighted least squares estimators are again biased; similarly, of the common rate difference estimators the weighted least squares estimators are biased, while the estimator employing "Mantel-Haenszel" weights is consistent in sparse data. Variance estimators that are consistent in both sparse data and large strata can be derived for all the Mantel-Haenszel estimators.
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            Plaque fissuring--the cause of acute myocardial infarction, sudden ischaemic death, and crescendo angina.

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              Control sampling strategies for case-crossover studies: an assessment of relative efficiency.

              The case-crossover study design is a method to assess the effect of transient exposures on the risk of onset of acute events. Control information for each case is based on his/her past exposure experience, and a self-matched analysis is conducted. Empiric evaluation of five approaches to the analysis of case-crossover data from a study of heavy physical exertion and acute myocardial infarction onset is shown. The data presented are from the Onset Study, a case-crossover study of the determinants of myocardial infarction onset conducted in 45 centers from August 1989 to October 1992. In model 1, exactly one control period (matched on clock-time) was sampled per case. In models 2-4, up to 25 control periods were sampled, and the effect of clock-time on the baseline hazard of infarction was modeled. In model 5, a census of the person-time experienced by each subject over the year preceding the infarction was sampled. The 95% confidence interval for model 1 was 2.7 times wider, and the relative efficiency, defined as v infinity/vM, where vM represents the asymptotic variance estimate of the estimated log relative risk with M control periods sampled per case, was only about 14% of model 5. In models 2-4, the efficiency increased with the number of control periods, regardless of the modeling assumptions. Even with many control periods sampled, models 2-4 achieved only half the efficiency of model 5. The control sampling strategy in any given case-crossover study should be selected with the trade-offs between precision and potential biases of the estimates in mind.
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                Author and article information

                Journal
                Circulation
                Circulation
                Ovid Technologies (Wolters Kluwer Health)
                0009-7322
                1524-4539
                June 12 2001
                June 12 2001
                : 103
                : 23
                : 2805-2809
                Affiliations
                [1 ]From the Institute for the Prevention of Cardiovascular Disease, Cardiovascular Division, Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School (M.A.M., R.A.L.); the Department of Epidemiology (M.A.M., M.M.) and the Department of Health and Social Behavior (J.B.S.), Harvard School of Public Health; and the Division of Cardiology, Department of Medicine, Massachusetts General Hospital, Harvard Medical School (J.E.M.), Boston, Mass.
                Article
                10.1161/01.CIR.103.23.2805
                11401936
                8812ed1f-33c4-4d29-96bb-2da46fb007bd
                © 2001
                History

                Molecular medicine,Neurosciences
                Molecular medicine, Neurosciences

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