Structured telephone support and telemonitoring are effective in reducing the risk of all-cause mortality and CHF-related hospitalisations in patients with CHF; they improve quality of life, reduce costs, and evidence-based prescribing.

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Aim: Out-of-hospital cardiac arrest (OHCA) during COVID-19 has been reported by countries with high case numbers and overwhelmed healthcare services. Imposed restrictions and treatment precautions may have also influenced OHCA processes-of-care. We investigated the impact of the COVID-19 pandemic period on incidence, characteristics, and survival from OHCA in Victoria, Australia. Methods: Using data from the Victorian Ambulance Cardiac Arrest Registry, we compared 380 adult OHCA patients who received resuscitation between 16th March 2020 and 12th May 2020, with 1218 cases occurring during the same dates in 2017À2019. No OHCA patients were COVID-19 positive. Arrest incidence, characteristics and survival rates were compared. Regression analysis was performed to understand the independent effect of the pandemic period on survival. Results: Incidence of OHCA did not differ during the pandemic period. However, initiation of resuscitation by Emergency Medical Services (EMS) significantly decreased (46.9% versus 40.6%, p = 0.001). Arrests in public locations decreased in the pandemic period (20.8% versus 10.0%; p < 0.001), as did initial shocks by public access defibrillation/first-responders (p = 0.037). EMS caseload decreased during the pandemic period, however, delays to key interventions (time-to-first defibrillation, time-to-first epinephrine) significantly increased. Survival-to-discharge decreased by 50% during the pandemic period (11.7% versus 6.1%; p = 0.002). Survivors per million person-years dropped in 2020, resulting in 35 excess deaths per million person-years. On adjusted analysis, the pandemic period remained associated with a 50% reduction in survival-to-discharge. Conclusion: The COVID-19 pandemic period did not influence OHCA incidence but appears to have disrupted the system-of-care in Australia. However, this could not completely explain reductions in survival.

These unique data suggest that urban Africans in Soweto develop AF at a relatively young age. Conventional strategies used to manage and treat AF need to be carefully evaluated in this setting.

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These data are indicative of a largely underappreciated AF prevalence in Australia. They mandate a more systematic effort to both understand and respond to an evolving AF burden.

BackgroundGender-based clinical differences are increasingly being identified as having significant influence on the outcomes of patients with cardiovascular disease (CVD), including atrial fibrillation (AF).ObjectiveTo perform detailed clinical phenotyping on a cohort of hospitalised patients with chronic forms of AF to understand if gender-based differences exist in the clinical presentation, thrombo-embolic risk and therapeutic management of high risk patients hospitalised with chronic AF.MethodsWe are undertaking the Standard versus Atrial Fibrillation spEcific managemenT studY (SAFETY) - a multi-centre, randomised controlled trial of an AF-specific management intervention versus usual care. Extensive baseline profiling of recruited patients was undertaken to identify gender-specific differences for risk delineation.ResultsWe screened 2,438 patients with AF and recruited 335 into SAFETY. Of these, 48.1% were women who were, on average, 5 years older than their male counterparts. Women and men displayed divergent antecedent profiles, with women having a higher thrombo-embolic risk but being prescribed similar treatment regimens. More women than men presented to hospital with co-morbid thyroid dysfunction, depression, renal impairment and obesity. In contrast, more men presented with coronary artery disease (CAD) and/or chronic obstructive pulmonary disease (COPD). Even when data was age-adjusted, women were more likely to live alone (odds ratio [OR] 2.33; 95% confidence interval [CI] 1.47 to 3.69), have non-tertiary education (OR 2.69; 95% CI 1.61 to 4.48) and be symptomatic (OR 1.93; 95% CI 1.06 to 3.52).ConclusionHealth care providers should be cognisant of gender-specific differences in an attempt to individualise and, hence, optimise the management of patients with chronic AF and reduce potential morbidity and mortality.

BackgroundComprehensive epidemiological data to describe the burden of heart failure (HF) in Australia remain lacking despite its importance as a major health issue. Herewith, we estimate the current and future burden of HF in Australia using best available data.MethodsAustralian-specific and the most congruent international epidemiological and health utilisation data were applied to the Australian population (adults aged ≥ 45 years, 8.9 of 22.7 million total population in 2014) on an age and sex-specific basis. We estimated the current incident and prevalent cases of clinically overt/symptomatic HF (predominately those with reduced ejection fraction), hospital activity (diagnosis of HF as a primary or secondary reason for admission) and health care costs in 2014 and future prevalence and burden of HF projected to 2030.ResultsWe estimated that over 61,000 (6.9 per 1000 person-years) adult Australians aged ≥ 45 years (58 % women) are diagnosed with HF with clinically overt signs and symptoms every year. On a conservative basis, 480,000 (6.3 %, 95 % CI 2.6 to 10.0 %) Australians (66 % men) are now affected by the syndrome with > 150,000 hospitalisations in excess of 1 million days in hospital per annum. The annual cost of managing HF in the community is approximately $900 million and nearly $2.7 billion ($1.5 versus $1.2 billion, men versus women) when considering the additional cost of in-patient care. We predict that the prevalence and future burden of HF will continue to increase over the next 10–15 years to nearly 750,000 people with an estimated annual health care cost of $3.8 billion.ConclusionsAustralia is not immune to the growing magnitude and implications of a sustained epidemic of HF in an ageing population. However, its public health and economic burden will remain ill-defined until more definitive Australian-specific data are generated.