Life expectancy for community-based patients with heart failure from time of diagnosis

AIMS: Heart failure has been demonstrated in previous studies to have a dismal prognosis. However, the modern-day prognosis of patients with new onset heart failure diagnosed in the community managed within a disease management programme is not known. The purpose of this study is to report on prognosis of patients presenting with new onset heart failure in the community who are subsequently followed in a disease management program.

METHODS AND RESULTS: A review of patients referred to a rapid access heart failure diagnostic clinic between 2002 and 2012 was undertaken. Details of diagnosis, demographics, medical history, medications, investigations and mortality data were analysed. A total of 733 patients were seen in Rapid Access Clinic for potential new diagnosis of incident of heart failure. 38.9% (n=285) were diagnosed with heart failure, 40.7% (n=116) with HF-REF and 59.3% (n=169) with HF-PEF. There were 84 (29.5%) deaths in the group of patients diagnosed with heart failure; 41 deaths (35.3%) occurred in patients with HF-REF and 43 deaths (25.4%) occurred in patients with HF-PEF. In patients with heart failure, 52.4% (n=44) died from cardiovascular causes. 63.8% of HF patients were alive after 5 years resulting on average in a month per year loss of life expectancy over that period compared with aged matched simulated population.

CONCLUSIONS: In this community-based cohort, the prognosis of heart failure was better than reported in previous studies. This is likely due to the impact of prompt diagnosis, the improvement in therapies and care within a disease management structure.

Progression of left atrial volume index in a population at risk for heart failure:a substudy of the STOP-HF (St Vincent's Screening TO Prevent Heart Failure) trial

AIMS: Limited data are available concerning the evolution of the left atrial volume index (LAVI) in pre-heart failure (HF) patients. The aim of this study was to investigate clinical characteristics and serological biomarkers in a cohort with risk factors for HF and evidence of serial atrial dilatation.

METHODS AND RESULTS: This was a prospective substudy within the framework of the STOP-HF cohort (NCT00921960) involving 518 patients with risk factors for HF electively undergoing serial clinical, echocardiographic, and natriuretic peptide assessment. Mean follow-up time between assessments was 15 ± 6 months. 'Progressors' (n = 39) were defined as those with serial LAVI change ≥3.5 mL/m(2) (and baseline LAVI between 20 and 34 mL/m(2)). This cut-off was derived from a calculated reference change value above the biological, analytical, and observer variability of serial LAVI measurement. Multivariate analysis identified significant baseline clinical associates of LAVI progression as increased age, beta-blocker usage, and left ventricular mass index (all P < 0.05). Serological biomarkers were measured in a randomly selected subcohort of 30 'Progressors' matched to 30 'Non-progressors'. For 'Progressors', relative changes in matrix metalloproteinase 9 (MMP9), tissue inhibitor of metalloproteinase 1 (TIMP1), and the TIMP1/MMP9 ratio, markers of interstitial remodelling, tracked with changes in LAVI over time (all P < 0.05).

CONCLUSION: Accelerated LAVI increase was found to occur in up to 14% of all pre-HF patients undergoing serial echocardiograms over a relatively short follow-up period. In a randomly selected subcohort of 'Progressors', changes in LAVI were closely linked with alterations in MMP9, TIMP1, and the ratio of these enzymes, a potential aid in highlighting this at-risk group.

A Real-Time Synthesis Oriented Tanpura Model

Physics-based synthesis of tanpura drones requires accurate simulation of stiff, lossy string vibrations while incorporating sustained contact with the bridge and a cotton thread. Several challenges arise from this when seeking efficient and stable algorithms for real-time sound synthesis. The approach proposed here to address these combines modal expansion of the string dynamics with strategic simplifications regarding the string-bridge and string-thread contact, resulting in an efficient and provably stable time-stepping scheme with exact modal parameters. Attention is given also to the physical characterisation of the system, including string damping behaviour, body radiation characteristics, and determination of appropriate contact parameters. Simulation results are presented exemplifying the key features of the model.

Improved Real-time State-of-Charge Estimation of LiFePO4 Battery Based on a Novel Thermoelectric Model

Li-ion batteries have been widely used in electric vehicles, and battery internal state estimation plays an important role in the battery management system. However, it is technically challenging, in particular, for the estimation of the battery internal temperature and state-ofcharge (SOC), which are two key state variables affecting the battery performance. In this paper, a novel method is proposed for realtime simultaneous estimation of these two internal states, thus leading to a significantly improved battery model for realtime SOC estimation. To achieve this, a simplified battery thermoelectric model is firstly built, which couples a thermal submodel and an electrical submodel. The interactions between the battery thermal and electrical behaviours are captured, thus offering a comprehensive description of the battery thermal and electrical behaviour. To achieve more accurate internal state estimations, the model is trained by the simulation error minimization method, and model parameters are optimized by a hybrid optimization method combining a meta-heuristic algorithm and the least square approach. Further, timevarying model parameters under different heat dissipation conditions are considered, and a joint extended Kalman filter is used to simultaneously estimate both the battery internal states and time-varying model parameters in realtime. Experimental results based on the testing data of LiFePO4 batteries confirm the efficacy of the proposed method.