Predictors and outcomes of quality of life in elderly patients with heart failure.

Study objective: This study aims to identify predictors of health related quality of life (HRQoL) among patients with heart failure (HF) and assess whether HRQoL was a predictor of rehospitalisation and mortality, and if age influenced the findings. Design: Observational cohort study. Setting: Seven hospitals in the Northern Sydney Local Health District, Sydney, Australia. Participants: Community dwelling patients who completed a Minnesota Living with HF questionnaire (MLHFQ) within 30 days of discharge after a HF hospitalisation. Main outcome measure: Multivariable linear regression models were used to identify predictors of MLHFQ scores (higher score = worse HRQoL) and adjusted Cox regression models to assess the impact of MLHFQ scores on one-year rehospitalisation and mortality. Separate analyses were conducted for those aged ≤80 or >80 years. Results: 1911 patients of mean age 79 years (57 % aged >80 years) were included in this analysis. Among those aged ≤80 years; younger age, lower haemoglobin and presenting symptoms at hospitalisation of exertional dyspnoea, peripheral oedema and fatigue were predictors of worse post-discharge MLHFQ scores. In patients aged >80 years, living alone, chronic kidney disease, exertional dyspnoea and peripheral oedema were predictors of worse MLHFQ scores. Worse MLHFQ scores predicted one-year HF readmissions in those aged >80 years (HR 1.22, 95 % CI 1.07-1.37) but not those aged ≤80 years (HR 0.90 95 % CI 0.71-1.10). Conclusions: In-hospital predictors can be identified for worse HRQoL post-discharge for HF. These vary according to age, and should be addressed prior to discharge.

Prevalence and seasonal variation of precipitants of heart failure hospitalization and risk of readmission.

AIMS: To determine the prevalence and seasonal variation in precipitants of heart failure (HF) hospitalization and the risk of subsequent HF hospitalizations. METHODS: We analysed the characteristics and outcomes of patients hospitalized with HF and enrolled in the Management of Cardiac Failure program in Sydney, Australia. Potential precipitants of HF hospitalization were identified, and Cox-regression analyses performed according to the precipitant. RESULTS: Among 6918 patients hospitalized with HF, 5384 (78%) had identified one or more precipitating factors leading to the hospitalization and 3648 (53%) had a single identifiable precipitant. Most precipitants were due to one or more of five prespecified causes - infection (n = 2014), ischemia (n = 1781), arrhythmia (n = 1724), medication related (n = 925) and diet non-compliance (n = 408). All precipitants were more common during winter (p < 0.001), especially infection related precipitants, of which 36% occurred during winter. Among patients with a single identifiable precipitant, one-year risk for HF readmission was lower when the precipitant was arrhythmia (16%) or infection (17%) than when the precipitant was ischemia (21%), dietary non-compliance (23%) or medication related (25%). The precipitant for HF rehospitalizations were more likely to be the same precipitant for the initial admission: infection vs no infection (HR 1.51, 95% CI 1.08-2.13), ischemia vs no ischemia (HR 2.79, 95% CI 1.83-4.25), arrhythmia vs no arrhythmia (HR 3.31, 95% CI 1.87-5.88) and medication related vs not medication related (HR 2.28, 95% CI 1.39-3.74). CONCLUSION: The precipitant of HF hospitalization influences the risk and precipitant of subsequent HF hospitalizations. Identifying and targeting interventions towards the precipitating factor may be an important strategy to prevent future HF hospitalizations.

15-Year Trends in Patients Hospitalised With Heart Failure and Enrolled in an Australian Heart Failure Management Program.

BACKGROUND: Heart failure (HF) is associated with high morbidity and mortality, and is a major contributor to health care costs. Since the area continues to be rapidly evolving, the aim of this study was to examine 15-year trends in demographics, precipitants, symptoms and outcomes of patients hospitalised with HF, and consider the individual and societal implications. METHODS: Data were prospectively collected by Heart Failure nurses from patients enrolled in the Management of Cardiac Function program (MACARF) in Northern Sydney, Australia. Analyses of trends were performed using Mantel-Hanzel tests and one-way analysis of variance. Multivariate Cox proportional hazard models were used to determine changes in readmission and mortality rates. RESULTS: From 2001 to 2015, 5,588 patients were hospitalised with HF and enrolled in the MACARF program. Over the 15-year period, the average age of enrolled patients increased by a decade (from 74 to 84 years), with an increase in hypertension (52% to 67%), chronic kidney disease (11% to 21%), atrial fibrillation/flutter (29% to 44%), and HF with preserved ejection fraction (24% to 35%) but a decrease in ischaemic heart disease (62% to 47%). Infection and atrial arrhythmias were the two most common precipitants of admission (27% and 18% of patients in 2013-15 respectively), while acute ischaemia became less common, and "unknown" precipitant increased to 35%. While increased exertional dyspnoea and peripheral oedema remained the most common presenting symptoms, weight gain, fatigue and chest pain were less frequently identified. Medication trends included an increase in spironolactone use and a decrease in angiotensin converting enzyme inhibitors. Average length of stay reduced while 1- and 3-year mortality rates improved to 11.3% and 26.6% respectively. In contrast, readmission rates have not improved, with current 30-day and 1-year rates of 9.9% and 42.6%. CONCLUSIONS: Significant temporal changes have occurred in the characteristics and outcome of patients with HF, which pose a challenge and opportunity to improve management. Although length of stay and mortality have improved, unchanged readmission rates highlight the importance of addressing the implications of the changing nature of patients with HF.

Predictors of Frequent Readmissions in Patients With Heart Failure.

BACKGROUND: Patients with heart failure (HF) have a high incidence of hospital readmissions. However risk models that explore predictors of a single readmission may be less useful at identifying the patients with frequent readmissions who contribute to a disproportionately large proportion of morbidity and health care costs. METHODS: A total of 6252 patients enrolled in the Management of Cardiac Failure Program (MACARF) in Northern Sydney Area Hospitals between 1998 and 2015 were randomly divided into derivation and validation cohorts to create and test a risk model for predictors of ≥2 readmissions or death within 1year of initial hospitalisation for HF. RESULTS: Multivariate predictors of frequent (≥2) readmissions or death were a history of ischaemic heart disease and chronic kidney disease, being unmarried, having anaemia, low serum albumin, elevated creatinine, prolonged hospital stay (>7 days), and not receiving beta blockers on discharge. Event rates increased with a higher risk score (p<0.001) and the prediction was similar in the validation and derivation cohorts (p=0.588). The C-statistic was 0.65. CONCLUSIONS: Our risk score may assist in focussing health care resources and interventions by identifying the subset of HF patients at increased risk for a disproportionately high burden of disease.

Characteristics and outcome for heart failure patients with mid-range ejection fraction.

AIMS: The aim of this study was to compare precipitants, presenting symptoms and outcomes of patients with heart failure and mid-range ejection fraction (HFmrEF), heart failure and preserved ejection fraction (HFpEF) and heart failure with reduced ejection fraction (HFrEF) in an Australian cohort. METHODS: We divided 5236 patients in the Management of Cardiac Failure program in Northern Sydney Australia, into HFmrEF (n = 780, 14.9%), HFpEF (n = 1956, 37.4%) and HFrEF (n = 2500, 47.8%), using a cutoff left ventricular ejection fraction of 40-49, at least 50 and less than 40%, respectively. RESULTS: For most characteristics, the HFmrEF patients were intermediate. Hypertension among the HFrEF, HFmrEF and HFpEF groups was present in 50.6, 61.7 and 68.9%, respectively; age more than 85 years was present in 35.1, 37.6 and 42.2%; atrial fibrillation in 35.3, 44.2 and 49.9%; and elevated serum creatinine (>100 µmol/l) in 59.2, 55.6 and 51.0%. For ischemic heart disease and ischemia as a precipitant of admission, HFmrEF patients were similar to the HFrEF group, and more common than in HFpEF. Mortality rates were not significantly different between the three groups. Readmission rates were highest for HFpEF (40.2%), followed by HFmrEF (42.4%) and HFrEF (45.4%), largely due to differences in nonheart failure readmission. CONCLUSION: Clinically, HFmrEF represents an intermediate phenotype, with the exception of resembling HFrEF with a higher incidence of ischemic heart disease.

Quality of life, social support and cognitive impairment in heart failure patients without diagnosed dementia.

Improving health-related quality of life (HRQL) is an important goal for heart failure (HF) patients, and understanding the factors that influence HRQL is essential to this process. We investigated the influence of social support and cognitive impairment on HRQL in community dwelling HF patients (n = 104) without diagnosed dementia. Patients were aged mean 80.93 years (SD 11.01) and were classified as New York Heart Association Class 1/II (45%) or III/IV (53%). Age, social support and cognition had important independent effects. Younger people had the most negative effects of HF in all areas of HRQL: emotional (B = -0.32), physical (B = -0.44) and overall (B = -1). Well-supported patients (general social support) had the least negative effect from HF on HRQL: emotional domain (B = -4.62) and overall (B = -11.72). Patients with normal cognition had more negative impact of HF on HRQL: physical domain (B = 5.51) and overall HRQL (B = 10.42). A clearer understanding of the relationships between age, social support and cognition and the effect on the impact of HF on HRQL is needed before interventions can be appropriately developed.

Mild cognitive impairment, screening, and patient perceptions in heart failure patients.

OBJECTIVE: Cognitive impairments are prevalent in heart failure (HF) patients, worsening outcomes but often undetected.The aim of this study was to screen HF outpatients for mild cognitive impairment (MCI), determine the areas of cognition affected, patient awareness of cognitive change, and associated factors. METHOD AND RESULTS: HF patients (n = 128) newly registered for the Management of Cardiac Function program, free from neurocognitive disorder, and with sufficient visual acuity were assessed with the use of the Montreal Cognitive Assessment tool (MoCA). MCI was classified as MoCA score ≤22. The sample was elderly (mean, 80.65 years; SD, 11.52). Mean MoCA score was 24.58 (SD 3.45), 22% were classified as impaired, 45% had noticed a change in cognition, and 15% reported that they were affected in their daily lives. Patients noticing this impact had lower MoCA scores (22.74, SD 3.0) than those who did not (25.17, SD 2.96; P ≤ .02). Most impairments occurred for delayed recall, visuospatial/executive function, and abstraction. The odds of impairment increased by the presence of ischemic heart disease (odds ratio, 4.18; 95% confidence interval, 1.15-15.69). CONCLUSIONS: In HF outpatients without a dementia diagnosis, MCI is prevalent. Screening for MCI and incorporation of compensatory strategies are essential.

Symptom patterns, duration and responses in newly diagnosed patients with heart failure.

This study investigated the symptom patterns and duration and associated predictors occurring prior to first heart failure (HF) admission. Data from the Managing Cardiac Function (MACARF) program from January to December 2007 were reviewed in relation to preadmission symptoms and contacts with health professionals. Patients (n = 242) were aged 78.7 years (SD 12 years), male (54%) and married (45%). Patients experienced up to seven symptoms (Mean 2.7, SD 1.4) for a median of 4.47 days (range 1-7) before admission, most commonly increased dyspnoea on exertion (88%), and for the shortest duration chest discomfort. Less than half (48%) contacted a health professional before hospitalization, most often a general practitioner (37%). The duration patients experienced before presenting to hospital was increased if they presented during business hours (beta = 2.68) or the evening (beta = 1.88) (and therefore less from midnight to 8:30 am), or with a change in symptom (beta = 1.4), whereas duration was reduced by chest discomfort (beta = -2.01) and older age (beta = -0.07). There is a significant time window during which patients and health professionals may detect and act on worsening HF symptoms. Newly diagnosed patients with HF need support to recognize and respond to these symptoms to avoid hospital admission.