Pre-Admission and Post-Hospital Management of Heart Failure in Patients not Enrolled in Specialist Programs

Aim: To review the management of heart failure in patients not enrolled in specialist multidisciplinary programs. Method: A prospective clinical audit of patients admitted to hospital with either a current or past diagnosis of heart failure and not enrolled in a specialist heart failure program or under the direct care of the cardiology unit. Results: 81 eligible patients were enrolled (1 August to 1 October 2008). The median age was 81 9.4 years and 48% were male. Most patients (63%) were in New York Heart Association Class II or Class III heart failure. On discharge, 59% of patients were prescribed angiotensin converting enzyme inhibitors and 43% were prescribed beta-blockers. During hospitalisation, 8.6% of patients with a past diagnosis of heart failure were started on an angiotensin converting enzyme inhibitor and 4.9% on a beta-blocker. There was evidence of suboptimal dosage on admission and discharge for angiotensin converting enzyme inhibitors (19% and 7.4%) and beta-blockers (29% and 17%). The results compared well with international reports regarding the under-treatment of heart failure. Conclusion: The demonstrated practice gap provides excellent opportunities for the involvement of pharmacists to improve the continuation of care for heart failure patients discharged from hospital in the areas of medication management review, dose titration and monitoring.

Generalized binomial Tau-leap method for biochemical kinetics incorporating both delay and intrinsic noise

The delay stochastic simulation algorithm (DSSA) by Barrio et al. [Plos Comput. Biol.2, 117–E (2006)] was developed to simulate delayed processes in cell biology in the presence of intrinsic noise, that is, when there are small-to-moderate numbers of certain key molecules present in a chemical reaction system. These delayed processes can faithfully represent complex interactions and mechanisms that imply a number of spatiotemporal processes often not explicitly modeled such as transcription and translation, basic in the modeling of cell signaling pathways. However, for systems with widely varying reaction rate constants or large numbers of molecules, the simulation time steps of both the stochastic simulation algorithm (SSA) and the DSSA can become very small causing considerable computational overheads. In order to overcome the limit of small step sizes, various τ-leap strategies have been suggested for improving computational performance of the SSA. In this paper, we present a binomial τ- DSSA method that extends the τ-leap idea to the delay setting and avoids drawing insufficient numbers of reactions, a common shortcoming of existing binomial τ-leap methods that becomes evident when dealing with complex chemical interactions. The resulting inaccuracies are most evident in the delayed case, even when considering reaction products as potential reactants within the same time step in which they are produced. Moreover, we extend the framework to account for multicellular systems with different degrees of intercellular communication. We apply these ideas to two important genetic regulatory models, namely, the hes1 gene, implicated as a molecular clock, and a Her1/Her 7 model for coupled oscillating cells.