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Nurse-led disease management programs (DMPs) decrease readmission after acute decompensated heart failure (HF). We sought whether readmissions could be further reduced by lung ultrasound (LUS)-guided decongestion before discharge and during DMP. Of 290 patients hospitalized with acute decompensated HF, 122 at high risk for readmission or mortality were randomized to receive usual care (UC) (n = 64) or UC plus intervention (DMP-Plus) (n = 58), comprising LUS-guided management before discharge and during at-home follow-up. Residual congestion was identified by ≥10 B-lines detected in 8 lung zones. The outcomes included a composite of readmission and/or mortality at 30 and 90 days, and 90-day HF readmission. Residual congestion was detected equally among the patient groups. The 30-day composite outcome occurred in 28% DMP-plus patients and 22% UC patients (odd ratio [OR], 1.36; 95% confidence interval [CI], 0.59–3.1; P =.5) and the 90-day HF readmission outcome occurred in 22% and 31%, respectively (odds ratio, 0.63; 95% CI, 0.28–1.43; P =.3). Residual congestion, identified at predischarge LUS examination in high-risk patients, was associated with early (<14-day) HF readmission (relative risk, 1.19; 95% CI, 1.06–1.32; P =.002) and multiple (≥2) readmissions over 90 days of follow-up (relative risk, 1.09; 95% CI, 1.01–1.16; P =.012), independent of demographics and comorbidities. Readmission in patients with incomplete decongestion before discharge occurs within the first 2 weeks. However, our DMP-plus strategy did not improve the primary outcome. [ABSTRACT FROM AUTHOR]

Aims: Heart failure (HF) is a common cause of morbidity and mortality, related to a broad range of sociodemographic, lifestyle, cardiometabolic, and comorbidity risk factors, which may differ according to the presence of atherosclerotic cardiovascular disease (ASCVD). We assessed the association between incident HF with baseline status across these domains, overall and separated according to ASCVD status. Methods and results: We included 5758 participants from the Baker Biobank cohort without HF at baseline enrolled between January 2000 and December 2011. The primary endpoint was incident HF, defined as hospital admission or HF‐related death, determined through linkage with state‐wide administrative databases (median follow‐up 12.2 years). Regression models were fitted adjusted for sociodemographic variables, alcohol intake, smoking status, measures of adiposity, cardiometabolic profile measures, and individual comorbidities. During 65 987 person‐years (median age 59 years, 38% women), incident HF occurred among 784 participants (13.6%) overall. Rates of incident HF were higher among patients with ASCVD (624/1929, 32.4%) compared with those without ASCVD (160/3829, 4.2%). Incident HF was associated with age, socio‐economic status, alcohol intake, smoking status, body mass index (BMI), waist circumference, waist–hip ratio, systolic blood pressure (SBP), and low‐ and high‐density lipoprotein cholesterol (LDL‐C and HDL‐C), with non‐linear relationships observed for age, alcohol intake, BMI, waist circumference, waist–hip ratio, SBP, LDL‐C, and HDL‐C. Risk factors for incident HF were largely consistent regardless of ASCVD status, although diabetes status had a greater association with incident HF among patients without ASCVD. Conclusions: Incident HF is associated with a broad range of baseline sociodemographic, lifestyle, cardiometabolic, and comorbidity factors, which are mostly consistent regardless of ASCVD status. These data could be useful in efforts towards developing risk prediction models that can be used in patients with ASCVD. [ABSTRACT FROM AUTHOR]

Objectives: To compare age‐adjusted all‐cause and CVD mortality, relative to the general female population, for women registered for fertility treatment who received it and those who did not. Design: Prospective cohort study; analysis of Monash IVF clinical registries data, 1975–2018, linked with National Death Index mortality data. Participants: All women who registered for fertility treatment at Monash IVF (Melbourne, Victoria), 1 January 1975 – 1 January 2014, followed until 31 December 2018. Main outcome measures: Standardised mortality ratios (SMRs) for all‐cause and CVD mortality, for women who did or did not undergo fertility treatment; SMRs stratified by area‐level socio‐economic disadvantage (SEIFA Index of Relative Socioeconomic Disadvantage [IRSD]) and (for women who underwent treatment), by stimulated cycle number and mean oocytes/cycle categories. Results: Of 44 149 women registered for fertility treatment, 33 520 underwent treatment (66.4%), 10 629 did not. After adjustment for age, both all‐cause (SMR, 0.58; 95% CI, 0.54–0.62) and CVD mortality (SMR, 0.41; 95% CI, 0.32–0.53) were lower than for the general female population. All‐cause mortality was similar for women registered with Monash IVF who did (SMR, 0.55; 95% CI, 0.50–0.60) or did not undergo fertility treatment (SMR, 0.63; 95% CI, 0.56–0.70). The SMR was lowest for both treated and untreated women in the fifth IRSD quintile (least disadvantage), but the difference was statistically significant only for untreated women. CVD mortality was lower for registered women who underwent fertility treatment (SMR, 0.29; 95% CI, 0.19–0.43) than for those who did not (SMR, 0.58; 95% CI, 0.42–0.81). Conclusion: Fertility treatment does not increase long term all‐cause or CVD mortality risk. Lower mortality among women registered for fertility treatment probably reflected their lower socio‐economic disadvantage. [ABSTRACT FROM AUTHOR]

Background  Nurse-led health and lifestyle modification programmes can prevent cardio-metabolic diseases and be advantageous where health disparities exist. Aims  To assess the effectiveness of a nurse-driven health and lifestyle modification programme in improving cardio-metabolic risk parameters for higher-risk regional residing adults. Methods  We conducted an open, parallel-group randomized controlled trial in two sites. Participants were aged 40–70 years with no prior cardiovascular disease who had any three or more of; central obesity, elevated triglycerides, reduced high-density lipoprotein cholesterol, elevated blood pressure (BP) and dysglycaemia. Intervention participants received individual face-to-face and telephone coaching for improving cardio-metabolic risk. Control group participants received standard care and general information about risk factor management. The primary endpoint was the percentage of participants who achieved the target risk factor thresholds or clinically significant minimum changes for any three or more cardio-metabolic risk factors during 24 months of follow-up. Results  Participant average age was 57.6 (SD 7.6) years, 61% were female and 71% were employed. The primary endpoint was achieved by 76% intervention (97 of 127) and 71% usual care (92 of 129) participants [adjusted risk ratio (RR): 1.08; 95% CI 0.94, 1.24; P  = 0.298]. Improved BP in the intervention group was more likely than in the control group (84% vs. 65%) (adj. RR: 1.28; 95% CI 1.11, 1.48; P  = 0.001) but no other cardio-metabolic component. Conclusion  Nurse intervention to modify cardio-metabolic risk parameters had no enhanced effectiveness compared with usual care. However, participation was associated with improvements in cardio-metabolic abnormalities, with particular emphasis on BP. Trial Registration Registered with the Australian New Zealand Clinical Trial Registry (ACTRN12616000229471). [ABSTRACT FROM AUTHOR]

Summary: Poor sleep increases cardio‐metabolic risk, but limited information on the impact of sleep for the improvement of cardio‐metabolic health exists. This analysis examined the impact of sleep on a health and lifestyle modification programme to reduce cardio‐metabolic disease risk factors. Secondary analysis of the MODERN randomised controlled trial to reduce cardio‐metabolic risk was undertaken at baseline and 24‐month follow‐up. Participants aged 40–70 years (n = 121) with three or more cardio‐metabolic risk factors were randomised to a health and lifestyle modification intervention (n = 59) or usual care (n = 62), and underwent 7 day/night actigraphy to assess total sleep time, sleep efficiency (%), number of awakenings/night and physical activity levels. Blood pressure, blood lipid and glycaemic levels, anthropometric and diet measures were collected. The mean age was 59 ± 7 years and 37% were male. Baseline sleep measures were not different between groups. At the 24‐month follow‐up, both groups showed improvements in cardio‐metabolic risk factors, albeit the change in blood pressure was greater in the intervention compared with the usual care group (systolic blood pressure: –11 versus –4 mmHg, p =.014). There were no differences between groups for diet, physical activity or sleep parameters. An increase in sleep efficiency was independently associated with lower systolic blood pressure (β = −2.117, p =.002) and higher high‐density lipoprotein levels (β = 0.040, p =.033); an increase in total sleep time was associated with lower low‐density lipoprotein levels (β = −0.003, p =.038) at 24 months. Overall, improvement in sleep quality over time was beneficial to reduce blood pressure and lipid levels. These findings highlight sleep as a potential target to reduce cardio‐metabolic risk. [ABSTRACT FROM AUTHOR]

Abstract Background Cardiovascular disease (CVD) is more prevalent in regional and remote Australia compared to metropolitan areas. The aim of Healthy Hearts was to determine age and sex specific CVD risk factor levels and the potential value of national risk clinics. Methods Healthy Hearts was an observational research study conducted in four purposefully selected higher risk communities in regional Victoria, Australia. The main outcome measures were the proportion of participants with CVD risk factors with group comparisons to determine the adjusted likelihood of elevated risk factor levels. Trained personnel used a standardized protocol over four weeks per community to measure CVD risk factor levels, estimate absolute CVD risk and provide feedback and advice. Results A total of 2125 self-selected participants were assessed (mean age 58 ± 15 years, 57% women). Overall, CVD risk factors were highly prevalent. More men than women had ≥ 2 modifiable CVD risk factors (76% vs. 68%, p Conclusions High CVD risk factor levels were confirmed for regional Victoria. Close engagement with individuals and communities provides scope for the application of regional risk management clinics to reduce the burden of CVD risk in regional Australia.

Poor sleep is associated with increased risk of cardiovascular disease (CVD). Indigenous Australians have 1.3 times higher risk of CVD compared to non‐indigenous Australians. However, there are limited data describing sleep problems and cardiometabolic risk in this population. This study aimed to investigate sleep quantity and quality in indigenous Australians and assess its association with cardiometabolic risk. Two hundred and forty‐five indigenous Australians aged > 18 years were recruited via convenience sampling from communities in the Northern Territory and Queensland. Sleep quantity and quality was assessed subjectively with questionnaires including the Epworth Sleepiness Scale. In a sub‐population (n = 46), objective sleep assessment was performed over three nights of actigraphy. Cardiometabolic risk measures included glycated haemoglobin, lipids, anthropometric measurements and sitting blood pressure. Sleep duration measured subjectively and objectively averaged 7.5 ± 2.0 hr/night; however, over one‐third of participants (self‐report 35%; actigraphy 39%) obtained < 7 hr/night. Overall, more than a third of participants experienced poor‐quality sleep, with 27% reporting severe daytime sleepiness (ESS score > 10) and a high number of objectively measured awakenings/night (6 ± 4). Short sleep duration (<6 hr/night) measured both subjectively and objectively was an independent predictor of diastolic (β = 5.37, p =.038) and systolic blood pressure (β = 14.30, p =.048). More objectively measured night‐time awakenings were associated with increased glycated haemoglobin levels (β = 0.07, p =.020) and greater sleep fragmentation was associated with lower high‐density lipoprotein levels (β = −0.01, p =.025). A large proportion of indigenous Australians experienced short sleep durations and had significant sleep disruption. Poor sleep quantity and quality may contribute to heightened cardiometabolic risk in this population. [ABSTRACT FROM AUTHOR]

Aims: Heart failure (HF) readmission commonly arises owing to insufficient patient knowledge and failure of recognition of the early stages of recurrent fluid congestion. In previous work, we developed a score to predict short‐term hospital readmission and showed that higher‐risk patients benefit most from a disease management programme (DMP) that included enhancing knowledge and education by a nurse. We aim to evaluate the effectiveness of a novel, nurse‐led HF DMP in selected patients at high risk of short‐term hospital readmission, using ultrasound‐guided diuretic management and artificial intelligence to enhance HF knowledge in an outpatient setting. Methods and results: Risk‐HF is a prospective multisite randomized controlled trial that will allocate 404 patients hospitalized with acute decompensated HF, and ≥33% risk of readmission and/or death at 30 days, into risk‐guided nurse intervention (DMP‐Plus group) compared with usual care. Intervention elements include (i) fluid management with a handheld ultrasound (HHU) device at point of care; (ii) post‐discharge follow‐up; (iii) optimal programmed drug titration; (iv) better transition of care; (v) intensive self‐care education via an avatar‐based 'digital health coach'; and (vi) exercise guidance through the digital coach. Usual care involves standard post‐discharge hospital care. The primary outcome is reduced death and/or hospital readmissions at 30 days post‐discharge, and secondary outcomes include quality of life, fluid management efficacy, and feasibility and patient engagement. Assuming that our intervention will reduce readmissions and/or deaths by 50%, with a 1:1 ratio of intervention vs. usual care, we plan to randomize 404 patients to show a difference at a statistical power of 80%, using a two‐sided alpha of 0.05. We anticipate this recruitment will be achieved by screening 2020 hospitalized HF patients for eligibility. An 8 week pilot programme of our digital health coach in 21 HF patients, age > 75 years, showed overall improvements in quality of life (13 of 21), self‐care (12 of 21), and HF knowledge (13 of 21). A pilot of the use of HHU by nurses showed that it was feasible and accurate. Conclusions: The Risk‐HF trial will evaluate the effectiveness of a risk‐guided intervention to improve HF outcomes and will evaluate the efficacy of trained HF nurses delivering a fluid management protocol that is guided by lung ultrasound with an HHU at point of care. [ABSTRACT FROM AUTHOR]

Background: Atrial fibrillation represents a substantial clinical and public health issue. The definitive impact of body mass index on prognosis of patients with chronic (persistent or permanent) atrial fibrillation remains undetermined. Aim: The purpose of this study was to investigate the association of body mass index with health outcomes (mortality and re-hospitalisation) of patients with chronic atrial fibrillation. Methods: Using data from the Standard versus Atrial Fibrillation spEcific managemenT strategY (SAFETY) trial (a randomised controlled trial of home-based, atrial fibrillation-specific disease management), we performed post-hoc analyses of mortality and re-hospitalisation outcomes during minimum 24-month follow-up according to baseline body mass index profile. Results: Of 297 participants (mean age 71±11 years, 47% female, mean body mass index 29.6±6.7 kg/m2), 35.0% of participants were overweight (body mass index 25.0–29.9 kg/m2) and 43.1% were obese (body mass index≥30 kg/m2). During follow-up, n=42 died including 16/65 (24.6%) classified as normal body mass index, 16/104 (15.4%) classified as overweight and 10/128 (7.8%) classified as obese. Increasing body mass index was not associated with increased mortality but was associated with re-hospitalisation due to cardiovascular disease with greater length-of-stay (odds ratio 1.05; 95% confidence interval 1.00–1.09, p=0.032). Obese individuals experienced increased unplanned admissions compared to overweight individuals (incidence rate ratio 0.71; 95% confidence interval 0.53–0.96, p=0.028), and increased cardiovascular-related (incidence rate ratio 0.58; 95% confidence interval 0.39–0.86, p=0.007) and all-cause admissions (incidence rate ratio 0.63; 95% confidence interval 0.45–0.89, p=0.008) compared to those classified as normal body mass index. Conclusion: Overweight and obesity were not associated with survival in patients with chronic atrial fibrillation but were associated with more frequent hospital care and prolonged stay. [ABSTRACT FROM AUTHOR]

Objective: The objective of this study was to assess the cost-effectiveness of a long-term, nurse-led, multidisciplinary programme of home/clinic visits in preventing progressive cardiac dysfunction in patients at risk of developing de novo chronic heart failure (CHF). Methods: A trial-based analysis was conducted alongside a pragmatic, single-centre, open-label, randomized controlled trial of 611 patients (mean age: 66 years) with subclinical cardiovascular diseases (without CHF) discharged to home from an Australian tertiary referral hospital. A nurse-led home and clinic-based programme (NIL-CHF intervention, n = 301) was compared with standard care (n=310) in terms of life-years, quality-adjusted life-years (QALYs) and healthcare costs. The uncertainty around the incremental cost and QALYs was quantified by bootstrap simulations and displayed on a cost-effectiveness plane. Results: During a median follow-up of 4.2 years, there were no significant between-group differences in life-years (−0.056, p=0.488) and QALYs (−0.072, p=0.399), which were lower in the NIL-CHF group. The NIL-CHF group had slightly lower all-cause hospitalization costs (AUD$2943 per person; p=0.219), cardiovascular-related hospitalization costs (AUD$1142; p=0.592) and a more pronounced reduction in emergency/unplanned hospitalization costs (AUD$4194 per person; p=0.024). When the cost of intervention was added to all-cause, cardiovascular and emergency-related readmissions, the reductions in the NIL-CHF group were AUD$2742 (p=0.313), AUD$941 (p=0.719) and AUD$3993 (p=0.046), respectively. At a willingness-to-pay threshold of AUD$50,000/QALY, the probability of the NIL-CHF intervention being better-valued was 19%. Conclusions: Compared with standard care, the NIL-CHF intervention was not a cost-effective strategy as life-years and QALYs were slightly lower in the NIL-CHF group. However, it was associated with modest reductions in emergency/unplanned readmission costs. [ABSTRACT FROM AUTHOR]