PubMed · 15829489
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Koon-Hou Mak. 2005-04-13. Bridging the practice chasm.. https://doi.org/10.1093/eurheartj%2Fehi294
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In this article, we present a frailty model using the generalized gamma distribution as the frailty distribution. It is a power generalization of the popular gamma frailty model. It also includes other frailty models such as the lognormal and Weibull frailty models as special cases. The flexibility of this frailty distribution makes it possible to detect a complex frailty distribution structure which may otherwise be missed. Due to the intractable integrals in the likelihood function and its derivatives, we propose to approximate the integrals either by Monte Carlo simulation or by a quadrature method and then determine the maximum likelihood estimates of the parameters in the model. We explore the properties of the proposed frailty model and the computation method through a simulation study. The study shows that the proposed model can potentially reduce errors in the estimation, and that it provides a viable alternative for correlated data. The merits of proposed model are demonstrated in analysing the effects of sublingual nitroglycerin and oral isosorbide dinitrate on angina pectoris of coronary heart disease patients based on the data set in Danahy et al. (sustained hemodynamic and antianginal effect of high dose oral isosorbide dinitrate. Circulation 1977; 55:381-387).
BACKGROUND: Coronary heart disease (CHD) is a major cause of morbidity and mortality in Australia and it is recommended that all persons with unstable angina (UA) or myocardial infarction (MI) participate in secondary prevention as offered in cardiac rehabilitation (CR) programs. However, the majority of patients do not access standard CR and have higher baseline coronary risk and poorer knowledge of CHD than those persons due to commence CR. The objective of this study is to investigate whether a modular guided self-choice approach to secondary prevention improves coronary risk profile and knowledge in patients who do not access standard CR. METHODS/DESIGN: This randomised controlled trial with one year follow-up will be conducted at a tertiary referral hospital. Participants eligible for but not accessing standard CR will be randomly allocated to either a modular or conventional care group. Modular care will involve participation in individualised modules that involve choice, goal-setting and coaching. Conventional care will involve ongoing heart disease management as directed by the participant's doctors. Both modular and conventional groups will be compared with a contemporary reference group of patients attending CR. Outcomes include measured modifiable risk factors, relative heart disease risk and knowledge of risk factors. DISCUSSION: We present the rationale and design of a randomised controlled trial testing a modular approach for the secondary prevention of coronary heart disease following acute coronary syndrome.
AIMS: To determine the relative impact of time to hospital arrival, baseline cardiovascular risk (i.e.TIMI mortality risk index), intracerebral haemorrhage risk, and comorbid disease burden on the likelihood of not receiving reperfusion therapy among ST-segment elevation myocardial infarction (STEMI) patients without contraindications to treatment. METHODS AND RESULTS: Retrospective population-based cohort of 3994 patients admitted to 103 acute care hospitals with chest pain and STEMI within 12 h of symptom onset in Ontario, Canada, between 1999 and 2001. Patients with one or more documented absolute or relative contraindication (n = 909) were excluded from the analyses. Reperfusion therapy was defined as the receipt of either fibrinolysis or primary percutaneous coronary intervention. Multivariable analysis and likelihood chi2 was used to quantify the importance of each factor in predicting the non-utilization of therapy. In total, 23.1% of patients received no reperfusion therapy. Listed in order from greatest to least importance, predictors of non-utilization of reperfusion therapy included increasing time to hospital presentation (likelihood chi2 31.6, P < 0.001), higher intracerebral haemorrhage risk (likelihood chi2 27.1, P < 0.001), higher baseline cardiovascular risk (likelihood chi2 25.4, P < 0.001), and greater number of chronic comorbid conditions (likelihood chi2 15.4, P < 0.001). The importance of each factor on non-utilization was independent, additive, not explained by age effects alone, or driven by subgroups traditionally under-represented in clinical trials. CONCLUSION: Care gaps in the use of reperfusion therapy widen with both increasing baseline cardiovascular risk and increasing intracerebral haemorrhage risk. Future studies should examine whether the implementation of clinical decision tools which allow for more accurate risk-benefit tradeoff predictions improve the treatment gaps when using life-saving therapies in this patient population.