Adherence to cardioprotective medications and mortality among patients with diabetes and ischemic heart disease

BACKGROUND: Patients with diabetes and ischemic heart disease (IHD) are at high risk for adverse cardiac outcomes. Clinical practice guidelines recommend multiple cardioprotective medications to reduce recurrent events. We evaluated the association between cardioprotective medication adherence and mortality among patients with diabetes and IHD. METHODS: In a retrospective cohort study of 3,998 patients with diabetes and IHD, we evaluated use of ACE inhibitors or angiotensin receptor blockers, β-blockers, and statin medications. Receipt of cardioprotective medications was based on filled prescriptions. Medication adherence was calculated as the proportion of days covered (PDC) for filled prescriptions. The primary outcome of interest was all-cause mortality. RESULTS: The majority of patients (92.8%) received at least 1 cardioprotective medication. Patients receiving any medications had lower unadjusted mortality rates compared to patients not receiving any medications (7.9% vs. 11.5%; p = 0.03). In multivariable analysis, receipt of any cardioprotective medication remained associated with lower all-cause mortality (OR 0.65; 95% CI 0.43–0.99). Among patients receiving cardioprotective medications, the majority (80.3%) were adherent (PDC ≥ 0.80). Adherent patients had lower unadjusted mortality rates (6.7% vs. 12.1%; p < 0.01). In multivariable analysis, medication adherence remained associated with lower all-cause mortality (OR 0.52; 95% CI 0.39–0.69) compared to non-adherence. In contrast, there was no mortality difference between patients receiving cardioprotective medications who were non-adherent compared to patients not receiving any medications (OR 1.01; 95% CI 0.64–1.61). CONCLUSION: In conclusion, medication adherence is associated with improved outcomes among patients with diabetes and IHD. Quality improvement interventions are needed to increase medication adherence in order for patients to maximize the benefit of cardioprotective medications

Nonparametric Simulation of Signal Transduction Networks with Semi-Synchronized Update

Simulating signal transduction in cellular signaling networks provides predictions of network dynamics by quantifying the changes in concentration and activity-level of the individual proteins. Since numerical values of kinetic parameters might be difficult to obtain, it is imperative to develop non-parametric approaches that combine the connectivity of a network with the response of individual proteins to signals which travel through the network. The activity levels of signaling proteins computed through existing non-parametric modeling tools do not show significant correlations with the observed values in experimental results. In this work we developed a non-parametric computational framework to describe the profile of the evolving process and the time course of the proportion of active form of molecules in the signal transduction networks. The model is also capable of incorporating perturbations. The model was validated on four signaling networks showing that it can effectively uncover the activity levels and trends of response during signal transduction process

Equilibrium analysis for common-pool resources

We present an aggregative normal form game to describe the investment decision making sit- uation for a CPR: we will consider a non-cooperative approach searching a Nash equilibrium of it, as well as a cooperative one searching a fully cooperative equilibrium. An application in the Environmental Economics will be illustrated and, in this context, we will introduce a threshold investment as a random variable and we will study the resulting game with aggregative uncertainty looking for a Nash equilib- rium and a fully cooperative equilibrium

Gender differences in appropriate shocks and mortality among patients with primary prophylactic implantable cardioverter-defibrillators: Systematic review and meta-analysis

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