1,813 research outputs found

    Lack of association between first myocardial infarction and past use of erythromycin, tetracycline, or doxycycline.

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    To evaluate the association of prior treatment with antibiotics active against Chlamydia pneumoniae with the risk for incident myocardial infarction, we conducted a population-based case-control study. We found that use of erythromycin, tetracycline, or doxycycline during the previous 5 years was not associated with risk for first myocardial infarction. These results suggest little or no association between the use of these antibiotics and the risk for first myocardial infarction in the primary prevention setting

    Phenotype standardization for statin-induced myotoxicity

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    Statins are widely used lipid-lowering drugs that are effective in reducing cardiovascular disease risk. Although they are generally well tolerated, they can cause muscle toxicity, which can lead to severe rhabdomyolysis. Research in this area has been hampered to some extent by the lack of standardized nomenclature and phenotypic definitions. We have used numerical and descriptive classifications and developed an algorithm to define statin-related myotoxicity phenotypes, including myalgia, myopathy, rhabdomyolysis, and necrotizing autoimmune myopathy.</p

    Using built environment characteristics to predict walking for exercise

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    Background: Environments conducive to walking may help people avoid sedentary lifestyles and associated diseases. Recent studies developed walkability models combining several built environment characteristics to optimally predict walking. Developing and testing such models with the same data could lead to overestimating one's ability to predict walking in an independent sample of the population. More accurate estimates of model fit can be obtained by splitting a single study population into training and validation sets (holdout approach) or through developing and evaluating models in different populations. We used these two approaches to test whether built environment characteristics near the home predict walking for exercise. Study participants lived in western Washington State and were adult members of a health maintenance organization. The physical activity data used in this study were collected by telephone interview and were selected for their relevance to cardiovascular disease. In order to limit confounding by prior health conditions, the sample was restricted to participants in good self-reported health and without a documented history of cardiovascular disease. Results: For 1,608 participants meeting the inclusion criteria, the mean age was 64 years, 90 percent were white, 37 percent had a college degree, and 62 percent of participants reported that they walked for exercise. Single built environment characteristics, such as residential density or connectivity, did not significantly predict walking for exercise. Regression models using multiple built environment characteristics to predict walking were not successful at predicting walking for exercise in an independent population sample. In the validation set, none of the logistic models had a C-statistic confidence interval excluding the null value of 0.5, and none of the linear models explained more than one percent of the variance in time spent walking for exercise. We did not detect significant differences in walking for exercise among census areas or postal codes, which were used as proxies for neighborhoods. Conclusion: None of the built environment characteristics significantly predicted walking for exercise, nor did combinations of these characteristics predict walking for exercise when tested using a holdout approach. These results reflect a lack of neighborhood-level variation in walking for exercise for the population studied.University of Washington Royalty Research fund award; by contracts R01-HL043201, R01-HL068639, and T32-HL07902 from the National Heart, Lung, and Blood Institute; and by grant R01-AG09556 from the National Institute on Aging

    Predicting Future Years of Life, Health, and Functional Ability: A Healthy Life Calculator for Older Adults

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    Introduction Planning for the future would be easier if we knew how long we will live and, more importantly, how many years we will be healthy and able to enjoy it. There are few well-documented aids for predicting our future health. We attempted to meet this need for persons 65 years of age and older. Methods Data came from the Cardiovascular Health Study, a large longitudinal study of older adults that began in 1990. Years of life (YOL) were defined by measuring time to death. Years of healthy life (YHL) were defined by an annual question about self-rated health, and years of able life (YABL) by questions about activities of daily living. Years of healthy and able life (YHABL) were the number of years the person was both Healthy and Able. We created prediction equations for YOL, YHL, YABL, and YHABL based on the demographic and health characteristics that best predicted outcomes. Internal and external validity were assessed. The resulting CHS Healthy Life Calculator (CHSHLC) was created and underwent three waves of beta testing. Findings A regression equation based on 11 variables accounted for about 40% of the variability for each outcome. Internal validity was excellent, and external validity was satisfactory. As an example, a very healthy 70-year-old woman might expect an additional 20 YOL, 16.8 YHL, 16.5 YABL, and 14.2 YHABL. The CHSHLC also provides the percent in the sample who differed by more than 5 years from the estimate, to remind the user of variability. Discussion The CHSHLC is currently the only available calculator for YHL, YABL, and YHABL. It may have limitations if today’s users have better prospects for health than persons in 1990. But the external validity results were encouraging. The remaining variability is substantial, but this is one of the few calculators that describes the possible accuracy of the estimates. Conclusion The CHSHLC, currently at http://diehr.com/paula/healthspan, meets the need for a straightforward and well-documented estimate of future years of healthy and able life that older adults can use in planning for the future

    Back to thiazide-diuretics for hypertension: reflections after a decade of irrational prescribing

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    BACKGROUND: Whether newer antihypertensive drugs, such as calcium channel blockers, angiotensin converting enzyme inhibitors and α blockers are more effective than thiazides and ÎČ blockers in preventing coronary disease, has been debated for years. DISCUSSION: Recently several trials addressing this issue have been finalised, and they provide a convincing answer: the newer drugs are no better than the older ones. In the largest trial to date (ALLHAT), thiazide-type diuretic was found to offer advantages over newer drugs. The medical community should now be capable of reaching consensus, and recommend thiazides as the first line therapy for the treatment of hypertension. Prescribing physicians, cardiologists, drug companies and health authorities are all partly responsible for the years of irrational prescribing that we have witnessed. SUMMARY: All stakeholders should now contribute in order to achieve what is clearly in the public's interest: implementing the use of thiazides in clinical practice

    The Tell-Tale Heart: Population-Based Surveillance Reveals an Association of Rofecoxib and Celecoxib with Myocardial Infarction

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    Background. COX-2 selective inhibitors are associated with myocardial infarction (MI). We sought to determine whether population health monitoring would have revealed the effect of COX-2 inhibitors on population-level patterns of MI. Methodology/Principal Findings. We conducted a retrospective study of inpatients at two Boston hospitals, from January 1997 to March 2006. There was a population-level rise in the rate of MI that reached 52.0 MI-related hospitalizations per 100,000 (a two standard deviation exceedence) in January of 2000, eight months after the introduction of rofecoxib and one year after celecoxib. The exceedence vanished within one month of the withdrawal of rofecoxib. Trends in inpatient stay due to MI were tightly coupled to the rise and fall of prescriptions of COX-2 inhibitors, with an 18.5 % increase in inpatient stays for MI when both rofecoxib and celecoxib were on the market (P,0.001). For every million prescriptions of rofecoxib and celecoxib, there was a 0.5 % increase in MI (95%CI 0.1 to 0.9) explaining 50.3 % of the deviance in yearly variation of MI-related hospitalizations. There was a negative association between mean age at MI and volume of prescriptions for celecoxib and rofecoxib (Spearman correlation, 20.67, P,0.05). Conclusions/Significance. The strong relationship between prescribing and outcome time series supports a population-level impact of COX-2 inhibitors on MI incidence. Further, mean age at MI appears to have been lowered by use of these medications. Use of a population monitoring approach as an adjunct t

    The Pharmacogenetics of Statin Therapy on Clinical Events: No Evidence that Genetic Variation Affects Statin Response on Myocardial Infarction

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    Background: The pharmacogenetic effect on cardiovascular disease reduction in response to statin treatment has only been assessed in small studies. In a pharmacogenetic genome wide association study (GWAS) analysis within the Genomic Investigation of Statin Therapy (GIST) consortium, we investigated whether genetic variation was associated with the response of statins on cardiovascular disease risk reduction. Methods: The investigated endpoint was incident myocardial infarction (MI) defined as coronary heart disease death and definite and suspect non-fatal MI. For imputed single nucleotide polymorphisms (SNPs), regression analysis was performed on expected allelic dosage and meta-analysed with a fixed-effects model, inverse variance weighted meta-analysis. All SNPs with p-values <5.0 × 10(−4) in stage 1 GWAS meta-analysis were selected for further investigation in stage-2. As a secondary analysis, we extracted SNPs from the Stage-1 GWAS meta-analysis results based on predefined hypotheses to possibly modifying the effect of statin therapy on MI. Results: In stage-1 meta-analysis (eight studies, n = 10,769, 4,212 cases), we observed no genome-wide significant results (p < 5.0 × 10(−8)). A total of 144 genetic variants were followed-up in the second stage (three studies, n = 1,525, 180 cases). In the combined meta-analysis, no genome-wide significant hits were identified. Moreover, none of the look-ups of SNPs known to be associated with either CHD or with statin response to cholesterol levels reached Bonferroni level of significance within our stage-1 meta-analysis. Conclusion: This GWAS analysis did not provide evidence that genetic variation affects statin response on cardiovascular risk reduction. It does not appear likely that genetic testing for predicting effects of statins on clinical events will become a useful tool in clinical practice

    Meta-analysis of genome-wide association studies from the CHARGE consortium identifies common variants associated with carotid intima media thickness and plaque

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    Carotid intima media thickness (cIMT) and plaque determined by ultrasonography are established measures of subclinical atherosclerosis that each predicts future cardiovascular disease events. We conducted a meta-analysis of genome-wide association data in 31,211 participants of European ancestry from nine large studies in the setting of the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium. We then sought additional evidence to support our findings among 11,273 individuals using data from seven additional studies. In the combined meta-analysis, we identified three genomic regions associated with common carotid intima media thickness and two different regions associated with the presence of carotid plaque (P < 5 × 10 -8). The associated SNPs mapped in or near genes related to cellular signaling, lipid metabolism and blood pressure homeostasis, and two of the regions were associated with coronary artery disease (P < 0.006) in the Coronary Artery Disease Genome-Wide Replication and Meta-Analysis (CARDIoGRAM) consortium. Our findings may provide new insight into pathways leading to subclinical atherosclerosis and subsequent cardiovascular events
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