In randomized trials of secondary prevention, pravastatin sodium and aspirin reduce risks of cardiovascular disease. Pravastatin has a predominantly delayed antiatherogenic effect, and aspirin has an immediate antiplatelet effect, raising the possibility of additive clinical benefits.
Methods
In 5 randomized trials of secondary prevention with pravastatin (40 mg/d), comprising 73 900 patient-years of observation, aspirin use was also prescribed in varying frequencies, and data were available on a large number of confounding variables. We tested whether pravastatin and aspirin have additive benefits in the 2 large trials (Long-term Intervention With Pravastatin in Ischaemic Disease trial and the Cholesterol and Recurrent Events trial) that were designed to test clinical benefits. We also performed meta-analyses of these 2 trials and 3 smaller angiographic trials that collected clinical end points. In all analyses, multivariate models were used to adjust for a large number of cardiovascular disease risk factors.
Results
Individual trials and all meta-analyses demonstrated similar additive benefits of pravastatin and aspirin on cardiovascular disease. In meta-analysis, the relative risk reductions for fatal or nonfatal myocardial infarction were 31% for pravastatin plus aspirin vs aspirin alone and 26% for pravastatin plus aspirin vs pravastatin alone. For ischemic stroke, the corresponding relative risk reductions were 29% and 31%. For the composite end point of coronary heart disease death, nonfatal myocardial infarction, coronary artery bypass graft, percutaneous transluminal coronary angioplasty, or ischemic stroke, the relative risk reductions were 24% and 13%. All relative risk reductions were statistically significant.
Conclusion
More widespread and appropriate combined use of statins and aspirin in secondary prevention of cardiovascular disease will avoid large numbers of premature deaths.
Abstract Epidemiological studies often rely on self‐reported cardiovascular disease (CVD) information, but this may be inaccurate. We investigated the accuracy of self‐reported CVD (myocardial infarction, stroke, coronary artery bypass surgery and coronary artery angioplasty) during the follow up of the Australian Diabetes, Obesity and Lifestyle (AusDiab) study. Self‐reported CVD events, including the date of the event and hospital admission details, were collected with an interviewer‐administered questionnaire. Of the 276 self‐reported CVD events, 188 (68.1%) were verified by adjudication of medical records. Furthermore, linkage to the statewide Western Australian Hospital Morbidity Database (WAHMD) showed that CVD events were unlikely to be missed, with only 0.2% of those denying any CVD event being recorded as having had an event on the WAHMD. The adjudication of medical records was as accurate as record linkage to the WAHMD for validation of self‐reported CVD, but combining the results from both methods of ascertainment improved CVD event identification.
BACKGROUND: Low-density lipoprotein cholesterol (LDL-C) and lipoprotein(a) (Lp[a]) levels are independently associated with atherosclerotic cardiovascular disease (ASCVD). However, the relationship between Lp(a) level, LDL-C level, and ASCVD risk at different thresholds is not well defined. METHODS: A participant-level meta-analysis of 27 658 participants enrolled in 6 placebo-controlled statin trials was performed to assess the association of LDL-C and Lp(a) levels with risk of fatal or nonfatal coronary heart disease events, stroke, or any coronary or carotid revascularization (ASCVD). The multivariable-adjusted association between baseline Lp(a) level and ASCVD risk was modeled continuously using generalized additive models, and the association between baseline LDL-C level and ASCVD risk by baseline Lp(a) level by Cox proportional hazards models with random effects. The joint association between Lp(a) level and statin-achieved LDL-C level with ASCVD risk was evaluated using Cox proportional hazards models. RESULTS: Compared with an Lp(a) level of 5 mg/dL, increasing levels of Lp(a) were log-linearly associated with ASCVD risk in statin- and placebo-treated patients. Among statin-treated individuals, those with Lp(a) level >50 mg/dL (≈125 nmol/L) had increased risk across all quartiles of achieved LDL-C level and absolute change in LDL-C level. Even among those with the lowest quartile of achieved LDL-C level (3.1–77.0 mg/dL), those with Lp(a) level >50 mg/dL had greater ASCVD risk (hazard ratio, 1.38 [95% CI, 1.06–1.79]) than those with Lp(a) level ≤50 mg/dL. The greatest risk was observed with both Lp(a) level >50 mg/dL and LDL-C level in the fourth quartile (hazard ratio, 1.90 [95% CI, 1.46–2.48]). CONCLUSIONS: These findings demonstrate the independent and additive nature of Lp(a) and LDL-C levels for ASCVD risk, and that LDL-C lowering does not fully offset Lp(a)-mediated risk.
Background Gender influences cardiovascular disease (CVD) through norms, social relations, roles and behaviours. This study identified gender-specific aspects of socialisation associated with CVD. Methods A longitudinal study was conducted, involving 9936 (5,231 women and 4705 men) initially healthy, community-dwelling Australians aged 70 years or more from the ASPirin in Reducing Events in the Elderly (ASPREE) study and ASPREE Longitudinal Study of Older Persons, with a median follow-up time of 6.4 years. Variable categorisation, variable selection (using machine learning (ML) models; Elastic Net and extreme gradient boosting) and Cox-regression were employed separately by binary gender to identity socialisation factors (n=25 considered) associated with CVD. Results Different socialisation factors were identified using the ML models. In the Cox model, for both genders, being married/partnered was associated with a reduced risk of CVD (men: HR 0.76, 95% CI 0.60 to 0.96; women: HR 0.67, 95% CI 0.58 to 0.95). For men, having 3–8 relatives they felt close to and could call on for help (HR 0.76, 95% CI 0.58 to 0.99; reference <3 relatives), having 3–8 relatives they felt at ease talking with about private matters (HR 0.70, 95% CI 0.55 to 0.90; reference <3 relatives) or playing games such as chess or cards (HR 0.82, 95% CI 0.67 to 1.00) was associated with reduced risk of CVD. For women, living with others (HR 0.71, 95% CI 0.55 to 0.91) or having ≥3 friends they felt at ease talking with about private matters (HR 0.74, 95% CI 0.58 to 0.95; reference <3 friends) was associated with a lower risk of CVD. Conclusions This study demonstrates the need to prioritise gender-specific social factors to improve cardiovascular health in older adults.
Introduction Studies have linked air pollution with the incidence of acute coronary artery events and cardiovascular mortality but the association with out-of-hospital cardiac arrest (OHCA) is less clear. Aim To examine the association of air pollution with the occurrence of OHCA. Methods Electronic bibliographic databases (until February 2013) were searched. Search terms included common air pollutants and OHCA. Studies of patients with implantable cardioverter defibrillators and OHCA not attended by paramedics were excluded. Two independent reviewers (THKT and TAW) identified potential studies. Methodological quality was assessed by the Newcastle-Ottawa Scale. Results Of 849 studies, 8 met the selection criteria. Significant associations between particulate matter (PM) exposure (especially PM 2.5 ) and OHCA were found in 5 studies. An increase of OHCA risk ranged from 2.4% to 7% per interquartile increase in average PM exposure on the same day and up to 4 days prior to the event. A large study found ozone increased the risk of OHCA within 3 h prior to the event. The strongest risk OR of 3.8–4.6% per 20 parts per billion ozone increase of the average level was within 2 h prior to the event. Similarly, another study found an increased risk of 18% within 2 days prior to the event. Conclusions Larger studies have suggested an increased risk of OHCA with air pollution exposure from PM 2.5 and ozone.
Background Analysis of recurrent event data is frequently needed in clinical and epidemiological studies. An important issue in such analysis is how to account for the dependence of the events in an individual and any unobserved heterogeneity of the event propensity across individuals. Methods We applied a number of conditional frailty and nonfrailty models in an analysis involving recurrent myocardial infarction events in the Long-Term Intervention with Pravastatin in Ischaemic Disease study. A multiple variable risk prediction model was developed for both males and females. Results A Weibull model with a gamma frailty term fitted the data better than other frailty models for each gender. Among nonfrailty models the stratified survival model fitted the data best for each gender. The relative risk estimated by the elapsed time model was close to that estimated by the gap time model. We found that a cholesterol-lowering drug, pravastatin (the intervention being tested in the trial) had significant protective effect against the occurrence of myocardial infarction in men (HR = 0.71, 95% CI 0.60—0.83). However, the treatment effect was not significant in women due to smaller sample size (HR = 0.75, 95% CI 0.51—1.10). There were no significant interactions between the treatment effect and each recurrent MI event (p = 0.24 for men and p = 0.55 for women). The risk of developing an MI event for a male who had an MI event during follow-up was about 3.4 (95% CI 2.6—4.4) times the risk compared with those who did not have an MI event. The corresponding relative risk for a female was about 7.8 (95% CI 4.4—13.6). Limitations The number of female patients was relatively small compared with their male counterparts, which may result in low statistical power to find real differences in the effect of treatment and other potential risk factors. Conclusions The conditional frailty model suggested that after accounting for all the risk factors in the model, there was still unmeasured heterogeneity of the risk for myocardial infarction, indicating the effect of subject-specific risk factors. These risk prediction models can be used to classify cardiovascular disease patients into different risk categories and may be useful for the most effective targeting of preventive therapies for cardiovascular disease.
Objective: To determine how well the current Pharmaceutical Benefits Scheme (PBS) eligibility criteria for subsidy of lipid-lowering drugs compare with current national guidelines for determining the population at high risk of developing cardiovascular disease (CVD). Design and participants: Analyses of the population-based, cross-sectional Australian Diabetes, Obesity and Lifestyle (AusDiab) study, conducted in 1999–2000. The 1991 Framingham risk prediction equation was used to compute 5-year risk of developing first-time CVD in 8286 participants aged 30–74 years with neither CVD nor diabetes. Based on the National Heart Foundation of Australia and Cardiac Society of Australia and New Zealand guidelines, people with either 5-year CVD risk ≥ 15% or with 5-year CVD risk of 10%–< 15% and the metabolic syndrome were defined as having estimated high absolute CVD risk. Main outcome measures: 5-year CVD risk; estimated population with high CVD risk. Results: Among participants without prevalent CVD or diabetes, 7.9% of men and 1.5% of women had a 5-year CVD risk ≥ 15%. Of the estimated residential Australian population in 2000 aged 30–74 years without CVD or diabetes, 717 000 people were considered to be at high absolute CVD risk. Among the high-risk AusDiab participants without CVD or diabetes, only 16.9% of men and 15.4% of women were being treated with lipid-lowering drugs. Of the 9.6% of participants free of CVD and diabetes who were untreated but eligible for subsidy under PBS criteria, only 27.4% had an estimated high absolute CVD risk. Conclusion: Strategies for CVD prevention using lipid-lowering medications can be improved by adoption of the absolute-risk approach.
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