Frequency, trends and institutional variation in 30-day all-cause mortality and unplanned readmissions following hospitalisation for heart failure in Australia and New Zealand

Qualitative Content Analysis of Unplanned Readmissions in Patients With Acute Heart Failure

BACKGROUND

Unplanned readmissions in patients with acute heart failure generate a substantial burden on healthcare systems and are associated with significant morbidity and mortality. Heart failure admissions are projected to increase over time with the ageing population. Understanding the factors contributing to readmissions after an index admission for heart failure is important, in order to develop strategies to address this phenomenon.

AIM

To understand the patient and organisational factors that contribute to readmissions in patients who are admitted with acute heart failure.

METHOD

Qualitative content analysis was performed on clinical notes from electronic medical records of all patients readmitted within 30 days after admission with acute heart failure at a single tertiary referral centre, between June 2022 and January 2023. Text related to patient and system-related factors contributing to readmissions were coded and organised into categories and sub-categories. The frequency of codes per patient was generated as a surrogate marker of the relative importance of codes within the dataset.

RESULTS

Overall, 64 patients were readmitted within the study timeframe. Three main categories emerged from the analysis, including patient-related medical factors contributing to readmission, patient-related psychosocial factors, and system-related factors. Patient-related medical factors were the most dominant category, with sub-categories of "non-heart failure causes of readmission", "frailty or functional decline", or "severe underlying cardiac pathology" occurring most frequently within the cohort (60.9%, 48.4%, 42.2%, respectively).

CONCLUSIONS

This study explores the patient-related medical, psychosocial, and system-related factors as significant contributors to readmissions in acute heart failure patients. It underscores the need for comprehensive and multi-faceted interventions to improve patient outcomes in this population and reduce healthcare burdens.

A Comparison of Prescribing Guideline-Advocated Treatment for Heart Failure at Discharge from Cardiology and Non-Cardiology Wards

BACKGROUND

Adherence to heart failure (HF) management guidelines is important to optimise clinical outcomes but can be variable in practice. This study compared prescribing guideline-advocated pharmacological and non-pharmacological management of HF between patients discharged from cardiology and non-cardiology wards.

METHOD

A retrospective audit of electronic medical records was undertaken of patients discharged from cardiology (n=100) or non-cardiology wards (n=100) of a tertiary hospital with a primary diagnosis of HF. Non-pharmacological management was quantified from documentation in medical records. Drug prescription was determined based on patients' discharge summaries. Comparisons between wards were conducted using Student's t-tests or Mann-Whitney U tests for continuous data and chi square tests or Fisher's tests for categorical data. Binary logistic regression modelling was applied.

RESULTS

Patients discharged from non-cardiology wards were older and had a higher incidence of hypertension, ischaemic heart disease, and renal insufficiency than those discharged from cardiology wards. The prescription of angiotensin-converting enzyme inhibitors (ACEIs)/angiotensin II receptor blockers (ARBs)/angiotensin receptor neprilysin inhibitors (ARNIs) and mineralocorticoid receptor antagonists at any dose (52% vs 80%; p<0.01, 25% vs 52%; p<0.01, respectively) were lower in non-cardiology than in cardiology wards, but there was no difference between wards for beta blockers. Referral to cardiac rehabilitation (4% vs 28%; p<0.01) before discharge was significantly lower in non-cardiology wards. Increased age was associated with less likelihood of the prescription of ACEIs/ARBs/ARNIs and mineralocorticoid receptor antagonists at any dose and ≥50% target dose. Better renal function was a predictor for ACEIs/ARBs/ARNIs at any dose and ≥50% target dose. Discharge ward was not in itself an independent predictor of drug prescription at any dose or for any drug class.

CONCLUSIONS

Prescription rates with key components of pharmacological and non-pharmacological HF management were lower in non-cardiology than in cardiology wards. For pharmacological management, this appeared related to higher patient complexity rather than the ward. Quality improvement programs to strengthen adherence to guideline-advocated treatment is warranted to optimise care, especially for higher complexity admitted to a non-cardiology ward.

Incidence, timing and variation in unplanned readmissions within 30-days following isolated coronary artery bypass grafting

Background

Coronary Artery Bypass Grafting (CABG) is the most common cardiac surgery, yet little is known about unplanned readmissions after CABG despite increasing clinical and policy focus on reducing readmissions. We assessed the incidence, timing, and reasons for unplanned readmission within 30 days of CABG and evaluated for variation in readmission rates across hospitals in Australia and New Zealand (ANZ).

Method

We identified isolated CABG procedures from 2013 to 2017 across all public and most private hospitals in ANZ. The primary outcome was unplanned (acute) readmissions within 30-days of discharge. Hospital specific risk standardised readmission rates (RSRRs) and 95% CI were estimated using a hierarchical generalized linear model accounting for differences in patient characteristics.

Results

52,104 patients (mean age 66.1 ± 9.9 years, 17.6 % female, 30.7 % acute) were included. The 30-day unplanned readmission rate was 12.7 % (n = 6,613) and was higher following urgent surgery (16.2 %, n = 2,595). Readmission rates peaked on days 2-4 with a median time to readmission of 9 (IQR: 4-17) days. Procedural complications and chest pain were the most common diagnoses on readmission. Risk adjustment model demonstrated satisfactory performance (C-statistic = 0.62). The median RSRR was 12.8 % (range: 6.1-20.3 %) across 37 hospitals. Only one hospital had its RSRR estimate lower than average and no hospitals had higher than average RSRR.

Conclusion

One-in-8 patients undergoing CABG experienced an unplanned readmission within 30-day, rising to one-in-6 following urgent CABG. There was little statistically significant institutional variation in RSRR. Nevertheless, many readmissions are likely related to care quality and potentially preventable, highlighting scope for clinical and policy interventions to reduce readmissions.

Spot urinary sodium-guided titration of intravenous diuretic therapy in acute heart failure: a pilot randomized controlled trial

BACKGROUND

Spot urinary sodium concentration (UNa) is advocated in guidelines to assess diuretic response and titrate dosage in acute heart failure (AHF). However, no randomized controlled trial data exist to support this approach. We performed a prospective pilot trial to investigate the feasibility of this approach.

METHODS AND RESULTS

Sixty patients with AHF (n = 30 in each arm) were randomly assigned to titration of loop diuretics for the first 48 h of admission according to UNa levels (intervention arm) or based on clinical signs and symptoms of congestion (standard care arm). Diuretic insufficiency was defined as UNa <50 mmol/L. Endpoints relating to diuretic efficacy, safety, and AHF outcomes were evaluated. UNa-guided therapy patients experienced less acute kidney injury (20% vs. 50%, P = 0.01) and a tendency towards less hypokalaemia (serum K+ <3.5 mmol, 7% vs. 27%, P = 0.04), with greater weight loss (3.3 kg vs. 2.1 kg, P = 0.01). They reported a greater reduction in the clinical congestion score (-4.7 vs. -2.6, P < 0.01) and were more likely to report marked symptom improvement (40% vs. 13.3%, P = 0.04) at 48 h. There was no difference in the length of hospital stay (median length of stay: 8 days in both groups, P = 0.98), 30-day mortality, or readmission rate.

CONCLUSION

UNa-guided titration of diuretic therapy in AHF is feasible and safer than titration based on clinical signs and symptoms of congestion, with more effective decongestion at 48 h. Further large-scale trials are needed to determine if the superiority of this approach translates into improved patient outcomes.

TRIAL REGISTRATION NUMBER

ACTRN12621000950864.

An explainable model for predicting Worsening Heart Failure based on genetic programming

Heart Failure (HF) poses a challenge for our health systems, and early detection of Worsening HF (WHF), defined as a deterioration in symptoms and clinical and instrumental signs of HF, is vital to improving prognosis. Predicting WHF in a phase that is currently undiagnosable by physicians would enable prompt treatment of such events in patients at a higher risk of WHF. Although the role of Artificial Intelligence in cardiovascular diseases is becoming part of clinical practice, especially for diagnostic and prognostic purposes, its usage is often considered not completely reliable due to the incapacity of these models to provide a valid explanation about their output results. Physicians are often reluctant to make decisions based on unjustified results and see these models as black boxes. This study aims to develop a novel diagnostic model capable of predicting WHF while also providing an easy interpretation of the outcomes. We propose a threshold-based binary classifier built on a mathematical model derived from the Genetic Programming approach. This model clearly indicates that WHF is closely linked to creatinine, sPAP, and CAD, even though the relationship of these variables and WHF is almost complex. However, the proposed mathematical model allows for providing a 3D graphical representation, which medical staff can use to better understand the clinical situation of patients. Experiments conducted using retrospectively collected data from 519 patients treated at the HF Clinic of the University Hospital of Salerno have demonstrated the effectiveness of our model, surpassing the most commonly used machine learning algorithms. Indeed, the proposed GP-based classifier achieved a 96% average score for all considered evaluation metrics and fully supported the controls of medical staff. Our solution has the potential to impact clinical practice for HF by identifying patients at high risk of WHF and facilitating more rapid diagnosis, targeted treatment, and a reduction in hospitalizations.

Incidence and predictors of unplanned 30-day hospital readmissions among heart failure patients in Ethiopia: a 5-year retrospective cohort study

The burden of heart failure increases over time and is a leading cause of unplanned readmissions worldwide. In addition, its impact has doubled in countries with limited health resources, including Ethiopia. Identifying and preventing the possible contributing factors is crucial to reducing unplanned hospital readmissions and improving clinical outcomes. The study aimed to assess the incidence and predictors of 30-day unplanned readmission among heart failure patients at selected South Wollo general hospitals in 2022. A hospital-based retrospective cohort study design was employed from January 1, 2016, to December 30, 2020. The data was collected from 572 randomly selected medical records using data extraction checklists. Data were entered in Epi-Data version 4.6 and analyzed with Stata version 17. The Kaplan-Meier and log-rank tests were used to estimate and compare the survival failure time. A Cox proportional hazard analysis was used to identify the predictors of readmission. The statistical significance level was declared at a p-value < 0.05 with an adjusted odds ratio and a 95% confidence interval. A total of 151 (26.40%) heart failure patients were readmitted within 30 days of discharge. Among the study participants, 302 (52.8%) were male, and 370 (64.7%) were rural residents. The mean age was 45.8 ± 14.1 SD years. In the multivariate Cox proportional hazards analysis being an age (> 65 years) (AHR: 3.172, 95% CI:.21, 4.55, P = 0.001), rural in residency (AHR: 2.47, 95%CI: 1.44, 4.24, P = 0.001), Asthma or Chronic Obstructive Pulmonary Disease (AHR: 1.62, 95% CI: 1.11, 2.35, P = 0.012), HIV/AIDS (AHR: 1.84, 95%CI: 1.24, 2.75, P = 0.003), Haemoglobin level 8-10.9 g/dL (AHR: 6.20, 95% CI: 3.74, 10.28, P = 0.001), and Mean platelet volume > 9.1 fl (AHR: 2.08, 95% CI: 1.27, 3.40, P = 0.004) were identified as independent predictors of unplanned hospital readmission. The incidence of unplanned hospital readmission was relatively high among heart failure patients. Elderly patients, rural residency, comorbidity, a higher mean platelet volume, and a low hemoglobin level were independent predictors of readmission. Working on these factors will help reduce the hazards of unplanned hospital readmission.

Short, Medium and Long-Term Cause-Specific Mortality Following First-Ever Heart Failure Hospitalisation in New Zealand

BACKGROUND

Heart failure (HF) is associated with high mortality, but there are limited reports on the underlying cause of death. This study reports short-, medium- and long-term cause-specific mortality following first-ever HF hospitalisation in New Zealand.

METHOD

First-ever HF hospitalisations were identified from hospital discharge coding between 2010 and 2013. Mortality outcomes were obtained via anonymised linkage to national datasets. Short (0-30 days), medium (31-364 days), and long-term (1-5 years) mortality rates were identified. Cause of death was identified from death certification coding and classified as cardiovascular and non-cardiovascular. Cox regression analysis was performed to adjust for confounding variables.

RESULTS

A cohort of 34,264 individuals with first-ever HF hospitalisation were identified. Mean age was 75.8±13 years and 50.5% were male. A total of 21,637 (63.1%) died within 5 years of hospitalisation; 4,122 (12.0%) within the first 30 days, 6,358 (18.6%) between 31-364 days, and 11,157 (32.6%) between 1 and 5 years. Older age, male gender, Māori ethnicity, higher socioeconomic deprivation and increased comorbidity were independent factors associated with higher all-cause mortality. Cardiovascular causes accounted for 51% of total deaths. Cardiovascular mortality was 6.0%, 9.5%, and 16.7% at 30 days, 31-364 days, and 1-5 years, respectively. The most common causes of non-cardiovascular mortality were neoplasms, chronic respiratory diseases and infections, accounting for 14.6%, 11.0%, and 5.5% of total deaths respectively. Comorbidity was associated with higher non-cardiovascular mortality (hazard ratio [HR] 3.35; 95% confidence interval [CI] 3.16-3.55) but not cardiovascular mortality (HR 0.79; 95% CI 0.72-0.86).

CONCLUSIONS

In New Zealand, mortality following first-ever HF hospitalisation is high. Non-cardiovascular death is common and there are ethnic inequities.

Hospital costs for unplanned re-admissions within 30 days of hospitalisations with heart failure, Australia, 2013-2017: a retrospective cohort study

OBJECTIVES

To assess the direct hospital costs for unplanned re-admissions within 30 days of hospitalisations with heart failure in Australia; to estimate the proportion of these costs attributable to potentially preventable re-admissions.

STUDY DESIGN

Retrospective cohort study; analysis of linked admitted patient data collections data.

SETTING, PARTICIPANTS

People admitted to hospital (all public and most private hospitals in Australia) with primary diagnoses of heart failure, 1 January 2013 - 31 December 2017, who were discharged alive and re-admitted to hospital at least once (any cause) within 30 days of discharge.

MAIN OUTCOME MEASURES

Estimated re-admission costs based on National Hospital Cost Data Collection, by unplanned re-admission category based on the primary re-admission diagnosis: potentially hospital-acquired condition; recurrence of heart failure; other diagnoses related to heart failure; all other diagnoses. The first two groups were deemed the most preventable.

RESULTS

The 165 612 eligible hospitalisations of people with heart failure during 2013-2017 (mean age, 79 years [standard deviation, 12 years]; 85 964 men [51.9%]) incurred direct hospital costs of $1881.4 million (95% confidence interval [CI], $1872.5-1890.2 million), or $376.3 million per year (95% CI, $374.5-378.1 million per year) and $11 360 per patient (95% CI, $11 312-11 408 per patient). A total of 41 125 people (24.8%) experienced a total of 58 977 unplanned re-admissions within 30 days of discharge from index admissions; these re-admissions incurred direct hospital costs of $604.4 million (95% CI, $598.2-610.5 million), or 32% of total index admission costs; that is, $120.9 million per year (95% CI, $119.6-122.1 million per year), and $14 695 per patient (95% CI, $14 535-14 856 per patient). Re-admissions with potentially hospital-acquired conditions (21 641 re-admissions) accounted for 40.1% of unplanned re-admission costs, recurrence of heart failure (18 666 re-admissions) for 35.6% of re-admission costs.

CONCLUSION

Unplanned re-admissions after hospitalisations with heart failure are expensive, incurring costs equivalent to 32% of those for the initial hospitalisations; a large proportion of these costs are associated with potentially preventable re-admissions. Reducing the number of unplanned re-admissions could improve outcomes for people with heart failure and reduce hospital costs.

Impact of the method of calculating 30-day readmission rate after hospitalization for heart failure. Data from the VancOuver CoastAL Acute Heart Failure (VOCAL-AHF) registry

BACKGROUND

Thirty-day readmission rate after heart failure (HF) hospitalization is widely used to evaluate healthcare quality. Methodology may substantially influence estimated rates. We assessed the impact of different definitions on HF and all-cause readmission rates.

METHODS

Readmission rates were examined in 1835 patients discharged following HF hospitalization using 64 unique definitions derived from five methodological factors: (1) International Classification of Diseases-10 codes (broad vs. narrow), (2) index admission selection (single admission only first-in-year vs. random sample; or multiple admissions in year with vs. without 30-day blanking period), (3) variable denominator (number alive at discharge vs. number alive at 30 days), (4) follow-up period start (discharge date vs. day following discharge), and (5) annual reference period (calendar vs. fiscal). The impact of different factors was assessed using linear regression.

RESULTS

The calculated 30-day readmission rate for HF varied more than two-fold depending solely on the methodological approach (6.5-15.0%). All-cause admission rates exhibited similar variation (18.8-29.9%). The highest rates included all consecutive index admissions (HF 11.1-15.0%, all-cause 24.0-29.9%), and the lowest only one index admission per patient per year (HF 6.5-11.3%, all-cause 18.8-22.7%). When including multiple index admissions and compared with blanking the 30-day post-discharge, not blanking was associated with 2.3% higher readmission rates. Selecting a single admission per year with a first-in-year approach lowered readmission rates by 1.5%, while random-sampling admissions lowered estimates further by 5.2% (P < 0.001).

CONCLUSION

Calculated 30-day readmission rates varied more than two-fold by altering methods. Transparent and consistent methods are needed to ensure reproducible and comparable reporting.

Contemporary management of acute heart failure in the emergency department and the potential impact of early diuretic therapy on outcomes

OBJECTIVE

Acute heart failure (AHF) is one of the most common conditions presenting to the ED and patients often require hospitalisation. Emerging evidence suggests early diagnosis and administration of diuretics are associated with improved patient outcomes. Currently, there is limited literature on the management of AHF in the Australian ED context.

METHODS

A retrospective review of consecutive AHF presentations to the ED in a metropolitan hospital. Patient demographics, clinical status and management were assessed including timeliness of diuretics administration and association with outcomes including ED length of stay (LOS) and inpatient mortality using linear regression.

RESULTS

One hundred and ninety-one presentations (median age 81 years, 50.8% male) were identified. Common cardiovascular comorbidities were prevalent. Fifty-four patients (28.3%) had ≥1 clinical high-risk feature at presentation. The median time from presentation to furosemide administration was 187 min (interquartile range 97-279 min); only 35 patients received diuretics within 60 min of presentation. Early diuretics was associated with shorter ED LOS (246 min vs 275 min, P = 0.03) and a lower but non-significant inpatient mortality (4.9% vs 6.3%, P = 0.21) and a non-significant increased rate of discharge home from ED (8.6% vs 4.7%, P = 0.15). The likelihood of discharge home was significantly more pronounced in patients receiving early diuretics without clinical high-risk features (16.7% vs 4.3%, P = 0.028).

CONCLUSION

Despite symptoms and signs being well recognised at presentation, time to diuretics was relatively long. Early diuretics administration was associated with improved patient outcomes, particularly in clinically more stable patients. Due to the limitations of the study design, results should be interpreted with caution and warrant further research to identify factors that delay timely administration of diuretics.

N-Terminal Pro B-Type Natriuretic Peptide as a Screening Tool for Inpatient Echocardiogram Requirement Among Patients With Suspected Heart Failure: Using NT-proBNP to Reduce Hospital Length of Stay

BACKGROUND

N-terminal pro-B-type natriuretic peptide (NT-proBNP) is a cardiac biomarker with diagnostic and prognostic utility in patients with heart failure (HF). Whether NT-proBNP can be used to triage inpatient transthoracic echocardiogram (TTE) requirements, and whether this impacts hospital length of stay (LOS), is not clear.

METHODS

Clinical and biochemical data were prospectively recorded on all inpatients at Wollongong Hospital, NSW, Australia, who had a TTE ordered for suspected HF over a 6-month period. NT-proBNP was used to triage TTE priority, where high-priority inpatient TTE, lower-priority inpatient TTE and outpatient (OP) TTE were performed for serum NT-proBNPs of ≥900, 300-899 and <300, respectively. Outcomes were compared with a baseline cohort of HF inpatients in whom TTE requirement was not guided by NT-proBNP.

RESULTS

A total of 236 patients were evaluated-31, 31, and 174 in the low, intermediate and high NT-proBNP cohorts, respectively, and 199 patients were in the baseline cohort. Average hospital LOS was significantly reduced in the study cohort compared to baseline (9.97 vs 13.87 days, p<0.001). Of the 31 patients with a very low NT-proBNP who were discharged for OP TTE, seven were readmitted within 30 days, though none were HF-related. There were no deaths at 30 days in the low or intermediate NT-proBNP groups.

CONCLUSIONS

Using NT-proBNP to triage requirements for inpatient TTE reduces hospital LOS. A very low NT-proBNP may help identify which patients with suspected HF can be safely discharged for OP TTE.

Lagging behind the Western countries: the knowledge gaps of gender differences in heart failure in Asia

Gender differences in heart failure (HF), ranging from epidemiological and pathophysiological factors to therapeutic response and prognosis, have been well documented in Western countries, especially in Europe and North America. The above gender differences in HF found in Westerners are rarely investigated in Asians. In this review, we explore the worrying knowledge gap on the gender differences in HF that existed in Asia in contrast with Western populations based on the following four aspects: epidemiology, risk factors, therapy, and prognosis. Finally, we conclude that investigations of gender differences in HF in Asia lag behind those in Europe and North America. Future work is required to establish and better use the high-level, population-based cohorts and develop our own high-quality, convincing clinical trials to deliver robust gender-specific conclusions in Asia.

Unplanned Readmissions and Long-Term Mortality Risk After Incident Heart Failure Hospitalisation in Western Australia, 2001-2015

AIMS

To investigate the frequency and predictors of unplanned readmissions after incident heart failure (HF) hospitalisation and the association between readmissions and mortality over two years.

METHODS

We performed a retrospective cohort study using Western Australian morbidity and mortality data to identify all patients, aged 25-94 years, who survived an incident (first-ever) HF hospitalisation (principal diagnosis) between 2001-2015. Ordinal logistic regression models determined the covariates independently associated with unplanned readmission(s). Cox proportional hazards models with time-varying exposures determined the hazard ratios (HR) of one or more readmissions for mortality over two years after incident HF.

RESULTS

Of 18,693 patients, 53.4% male, mean age 74.4 (standard deviation [SD] 13.6) years, 61.3% experienced 32,431 unplanned readmissions (39.7% cardiovascular-related) within two years. Leading readmission causes were HF (19.1%), respiratory diseases (12.6%), and ischaemic heart disease (9.6%). All-cause death occurred in 27.2% of the cohort, and the multivariable-adjusted mortality HR of 1 (versus 0) readmission was 2.5 (95% confidence interval [CI], 2.3-2.7) increasing to 5.0 (95% CI, 4.7-5.4) for 2+ readmissions. The adjusted mortality HR of 1 and 2+ (versus 0) HF-specific readmission was 2.0 (95% CI, 1.8-2.1) and 3.6 (95% CI, 3.2-3.9), respectively. Coexistent cardiovascular and other comorbidities were independently associated with increased readmission and mortality risk.

CONCLUSION

This study underlines the high burden of recurrent unplanned cardiovascular and other readmissions within two years after incident HF hospitalisation, and their additive adverse impact on mortality. Integrated multidisciplinary management of concomitant comorbidities, in addition to HF-targeted treatments, is necessary to improve long-term prognosis in HF patients.

Bone status in men with heart failure: results from the Studies Investigating Co-morbidities Aggravating Heart Failure

AIM

To assess bone status expressed as hip bone mineral density (BMD) in men with heart failure (HF).

METHODS AND RESULTS

A total of 141 male patients with HF underwent dual energy X-ray absorptiometry to assess their BMD. We analysed markers of bone metabolism. Patients were classified as lower versus higher BMD according to the median hip BMD (median = 1.162 g/cm2 ). Survival was assessed over 8 years of follow-up. Patients with lower BMD were older (71 ± 10 vs. 66 ± 9 years, p = 0.004), more likely to be sarcopenic (37% vs. 7%, p < 0.001) and to have lower peak oxygen consumption (absolute peak VO2 1373 ± 480 vs. 1676 ± 447 ml/min, p < 0.001), had higher osteoprotegerin and osteocalcin levels (both p < 0.05) compared to patients with higher BMD. Among 47 patients with repeated BMD assessments, a significant reduction in BMD was noted over 30 months of follow-up. In multivariate logistic regression analysis, serum osteocalcin remained independently related with lower BMD (odds ratio [OR] 1.738, 95% confidence interval [CI] 1.136-2.660, p = 0.011). Hip BMD and serum osteoprotegerin were independent predictors of impaired survival on Cox proportional hazard analysis (hazard ratio [HR] 0.069, 95% CI 0.011-0.444, p = 0.005, and HR 0.638, 95% CI 0.472-0.864, p = 0.004, respectively).

CONCLUSIONS

Patients with HF lose BMD over time. Markers of bone turnover can help in identifying patients at risk with osteocalcin being an independent marker of lower hip BMD and osteoprotegerin an independent predictor of death. HF patients with increased osteocalcin and osteoprotegerin may benefit from BMD assessment as manifest osteoporosis seems to be too late for clinically meaningful intervention in HF.

Impact of Malnutrition on Clinical Outcomes of Acutely Hospitalised Heart Failure Patients at Two Tertiary Hospitals in Australia: An Observational Study

BACKGROUND

Malnutrition is common in patients with heart failure (HF) but is often neglected, despite guidelines suggesting that all hospitalised patients should undergo nutritional screening within 24-hours of admission.

AIMS

This study investigated the nutritional screening rates and determined the immediate and long-term clinical outcomes in patients with HF admitted at two tertiary hospitals in Australia.

METHODS

Nutritional screening was assessed by the Malnutrition Universal Screening Tool (MUST) completion rates. Patients were classified into two categories based on their MUST scores (0=low malnutrition risk and ≥1=at risk of malnutrition). Propensity-score-matching (PSM) was used to match 20 variables depending upon the risk of malnutrition. Clinical outcomes included the days-alive-and-out-of-hospital at 90 days of discharge (DAOH90), length of hospital stay, in-hospital, 30-day and 180-day mortality and 30-day readmissions.

RESULTS

There were 5,734 HF admissions between 2013-2020, of whom, only 789 (13.8%) patients underwent MUST screening. The mean (SD) age was 76.2 (14.0) years and 51.9% were males. Five-hundred and fifty-four (554) (70.2%) patients were at low malnutrition risk and 235 (29.8%) at risk of malnutrition. In HF patients, who were at risk of malnutrition, the DAOH90 were lower by 5.9 days (95% CI -11.49 to -0.42, p=0.035) and 180-day mortality was significantly worse (coefficient 0.10, 95% CI 0.02-0.18, p=0.007) compared to those who were at low risk of malnutrition. However, other clinical outcomes were similar between the two groups.

CONCLUSION

Nutrition screening is poor in hospitalised HF patients and long-term but not short-term clinical outcomes were worse in malnourished HF patients.

Unplanned 30-day readmissions, comorbidity and impact on one-year mortality following incident heart failure hospitalisation in Western Australia, 2001-2015

BACKGROUND

Readmissions within 30 days after heart failure (HF) hospitalisation is considered an important healthcare quality metric, but their impact on medium-term mortality is unclear within an Australian setting. We determined the frequency, risk predictors and relative mortality risk of 30-day unplanned readmission in patients following an incident HF hospitalisation.

METHODS

From the Western Australian Hospitalisation Morbidity Data Collection we identified patients aged 25-94 years with an incident (first-ever) HF hospitalisation as a principal diagnosis between 2001 and 2015, and who survived to 30-days post discharge. Unplanned 30-day readmissions were categorised by principal diagnosis. Logistic and Cox regression analysis determined the independent predictors of unplanned readmissions in 30-day survivors and the multivariable-adjusted hazard ratio (HR) of readmission on mortality within the subsequent year.

RESULTS

The cohort comprised 18,241 patients, mean age 74.3 ± 13.6 (SD) years, 53.5% males, and one-third had a modified Charlson Comorbidity Index score of ≥ 3. Among 30-day survivors, 15.5% experienced one or more unplanned 30-day readmission, of which 53.9% were due to cardiovascular causes; predominantly HF (31.4%). The unadjusted 1-year mortality was 15.9%, and the adjusted mortality HR in patients with 1 and ≥ 2 cardiovascular or non-cardiovascular readmissions (versus none) was 1.96 (95% confidence interval (CI) 1.80-2.14) and 3.04 (95% CI, 2.51-3.68) respectively. Coexistent comorbidities, including ischaemic heart disease/myocardial infarction, peripheral arterial disease, pneumonia, chronic kidney disease, and anaemia, were independent predictors of both 30-day unplanned readmission and 1-year mortality.

CONCLUSION

Unplanned 30-day readmissions and medium-term mortality remain high among patients who survived to 30 days after incident HF hospitalisation. Any cardiovascular or non-cardiovascular readmission was associated with a two to three-fold higher adjusted HR for death over the following year, and various coexistent comorbidities were important associates of readmission and mortality risk. Our findings support the need to optimize multidisciplinary HF and multimorbidity management to potentially reduce repeat hospitalisation and improve survival.

Heart failure: an update from the last years and a look at the near future

In the last years, major progress occurred in heart failure (HF) management. Quadruple therapy is now mandatory for all the patients with HF with reduced ejection fraction. Whilst verciguat is becoming available across several countries, omecamtiv mecarbil is waiting to be released for clinical use. Concurrent use of potassium-lowering agents may counteract hyperkalaemia and facilitate renin-angiotensin-aldosterone system inhibitor implementations. The results of the EMPagliflozin outcomE tRial in Patients With chrOnic heaRt Failure With Preserved Ejection Fraction (EMPEROR-Preserved) trial were confirmed by the Dapagliflozin in Heart Failure with Mildly Reduced or Preserved Ejection Fraction (DELIVER) trial, and we now have, for the first time, evidence for treatment of also patients with HF with preserved ejection fraction. In a pre-specified meta-analysis of major randomized controlled trials, sodium-glucose co-transporter-2 inhibitors reduced all-cause mortality, cardiovascular (CV) mortality, and HF hospitalization in the patients with HF regardless of left ventricular ejection fraction. Other steps forward have occurred in the treatment of decompensated HF. Acetazolamide in Acute Decompensated Heart Failure with Volume Overload (ADVOR) trial showed that the addition of intravenous acetazolamide to loop diuretics leads to greater decongestion vs. placebo. The addition of hydrochlorothiazide to loop diuretics was evaluated in the CLOROTIC trial. Torasemide did not change outcomes, compared with furosemide, in TRANSFORM-HF. Ferric derisomaltose had an effect on the primary outcome of CV mortality or HF rehospitalizations in IRONMAN (rate ratio 0.82; 95% confidence interval 0.66-1.02; P = 0.070). Further options for the treatment of HF, including device therapies, cardiac contractility modulation, and percutaneous treatment of valvulopathies, are summarized in this article.

Characteristics and outcomes of patients with heart failure discharged from different speciality units in Australia: an observational study

BACKGROUND

Previous studies have reported differing clinical outcomes among hospitalized heart failure (HF) patients admitted under cardiology and general medicine (GM) without consideration of patients' frailty.

AIMS

To explore outcomes in patients admitted under the two specialities after taking into account their frailty and other characteristics.

METHODS

This retrospective study included all HF patients ≥18 years admitted between 1 January 2013 and 31 December 2019 at two Australian tertiary hospitals. Frailty was determined by use of the Hospital Frailty Risk Score (HFRS) and patients with HFRS ≥ 5 were classified as frail. Propensity score matching (PSM) was used to match 11 variables between the two specialities. The primary outcomes included the days-alive-and-out-of-hospital (DAOH90) at 90 days of discharge, 30-day mortality and readmissions.

RESULTS

Of 4913 HF patients, mean age 76.2 (14.1) years, 51% males, 2653 (54%) were admitted under cardiology compared to 2260 (46%) under GM. Patients admitted under GM were more likely to be older females, with a higher Charlson index and poor renal function than those admitted under cardiology. Overall, 23.8% patients were frail and frail patients were more likely to be admitted under GM than cardiology (33.6% vs. 15.3%, P < 0.001). PSM created 1532 well-matched patients in each group. After PSM, the DAOH90 was not significantly different among patients admitted in GM when compared to cardiology (coefficient -5.36, 95% confidence interval -11.73 to 1.01, P = 0.099). Other clinical outcomes were also similar between the two specialities.

CONCLUSIONS

Clinical characteristics of HF patients differ between GM and cardiology; however, clinical outcomes were not significantly different after taking into account frailty and other variables.

The association between urinary sodium concentration (UNa) and outcomes of acute heart failure: a systematic review and meta-analysis

AIMS

Urinary sodium concentration (UNa) is a simple test advocated to assess diuretics efficacy and predict outcomes in acute heart failure (AHF). We performed a systematic review and meta-analysis to examine the association of UNa with outcomes of AHF.

METHODS AND RESULTS

We searched Embase and Medline for eligible studies that reported the association between UNa and outcomes of urinary output, weight loss, worsening renal function, length of hospital stay, re-hospitalization, worsening heart failure, and all-cause mortality in AHF. Nineteen observational studies out of 1592 screened records were included. For meta-analyses of outcomes, we grouped patients into high vs. low UNa, with most studies defining high UNa as &gt;48-65 mmol/L. In the high UNa group, pooled data showed a higher urinary output (mean difference 502 mL, 95% CI 323-681, P &lt; 0.01), greater weight loss (mean difference 1.6 kg, 95% CI 0.3-2.9, P = 0.01), and a shorter length of stay (mean difference -1.4 days, 95% CI -2.8 to -0.1, P = 0.03). There was no significant difference in worsening kidney function (OR 0.54, 95% CI 0.25-1.16, P = 0.1). Due to the small number of studies, we did not report pooled estimates for re-hospitalization and worsening heart failure. High UNa was associated with lower odds of 30-day (OR 0.27; 95% CI 0.14-0.49, P &lt; 0.01), 90-day (OR 0.39,95% CI 0.25-0.59, P &lt; 0.01) and 12-month (OR 0.35; 95% CI 0.20-0.61, P &lt; 0.01) mortality.

CONCLUSION

High UNa after diuretic administration is associated with higher urinary output, greater weight loss, shorter length of stay, and lower odds of death. UNa is a promising marker of diuretic efficacy in AHF which should be confirmed in randomized trials.

Prevalence and impact of malnutrition on readmission among hospitalized patients with heart failure in China

AIMS

Malnutrition is common in patients with heart failure (HF) and is associated with poorer quality of life and increased mortality; however, an effective screening tool for malnutrition and its impact on the readmission of patients with HF is uncertain. Our objectives were to study (i) the nutritional status of Chinese hospitalized patients with HF and its impact on readmission and (ii) the validity of seven malnutrition screening tools.

METHODS AND RESULTS

In this study, univariate and multivariate analyses of Cox proportional hazards regression were used to determine important predictors of readmission. The endpoint was readmission due to HF or non-HF. A total of 402 patients were included (66.4% male, median age 62 years [range: 20-92 years], median NT-proBNP 5,229 ng/L). During a median follow-up of 159 days, 150 patients (37%) were readmitted to the hospital. After adjusting for confounders, only malnutrition assessed using the Controlling Nutritional Status (CONUT) nutrition score was independently associated with readmission (P = 0.0293). A base model for predicting readmission with a C-statistic of 0.680 and subsequent addition of various nutritional screening tools improved its performance over the base model. Patients with malnutrition had a twofold increased risk of readmission.

CONCLUSIONS

We found that the prevalence of malnutrition among hospitalized patients with HF in China is very high and that malnutrition significantly increases the risk of readmission in these patients. CONUT is a validated screening tool for malnutrition and may provide valuable prognostic information.

Long-term survival and life expectancy following an acute heart failure hospitalization in Australia and New Zealand

AIMS

Contemporary long-term survival following a heart failure (HF) hospitalization is uncertain. We evaluated survival up to 10 years after a HF hospitalization using national data from Australia and New Zealand, identified predictors of survival, and estimated the attributable loss in life expectancy.

METHODS AND RESULTS

Patients hospitalized with a primary diagnosis of HF from 2008-2017 were identified and all-cause mortality assessed by linking with Death Registries. Flexible parametric survival models were used to estimate survival, predictors of survival and loss in life expectancy. A total of 283 048 patients with HF were included (mean age 78.2 ± 12.3 years, 50.8% male). Of these, 48.3% (48.1-48.5) were surviving by 3 years, 34.1% (33.9-34.3) by 5 years and 17.1% (16.8-17.4) by 10 years (median survival 2.8 years). Survival declined with age with 53.4% of patients aged 18-54 years and 6.2% aged ≥85 years alive by 10 years (adjusted hazard ratio [aHR] for mortality 4.84, 95% confidence interval [CI] 4.65-5.04 for ≥85 years vs. 18-54 years) and was worse in male patients (aHR 1.14, 95% CI 1.13-1.15). Prior HF (aHR 1.20, 95% CI 1.18-1.22), valvular and rheumatic heart disease (aHR 1.11, 95% CI 1.10-1.13) and vascular disease (aHR 1.07, 95% CI 1.04-1.09) were cardiovascular comorbidities most strongly associated with long-term death. Non-cardiovascular comorbidities and geriatric syndromes were common and associated with higher mortality. Compared with the general population, HF was associated with a loss of 7.3 years in life expectancy (or 56.6% of the expected life expectancy) and reached 20.5 years for those aged 18-54 years.

CONCLUSION

Less than one in five patients hospitalized for HF were surviving by 10 years with patients experiencing almost 60% loss in life expectancy compared with the general population, highlighting the considerable persisting societal burden of HF. Concerted multidisciplinary efforts are needed to improve post-hospitalization outcomes of HF.

Nurse-Provided Lung and Inferior Vena Cava Assessment in Patients With Heart Failure

BACKGROUND

Residual congestion detected using handheld ultrasound may be associated with increased risk of readmission and death after hospitalization for acute decompensated heart failure (ADHF). However, effective application necessitates routine use by nonexperts delivering clinical care.

OBJECTIVES

The objective of this study was to determine the ability of heart failure (HF) nurses to deliver a predischarge lung and inferior vena cava (IVC) assessment (LUICA) to predict 90-day outcomes.

METHODS

In this multisite, prospective, observational study, HF nurses scanned 240 patients with ADHF (median age: 77 years; 56% men) using a 9-zone LUICA protocol. Obtained images were reviewed by independent nurses who were blinded to clinical characteristics and outcomes. Based on a B-line cut-off of 10, patients were dichotomized as congested (n = 115) or not congested (n = 125).

RESULTS

Congested patients were more likely to have previous cardiac operations, long-standing HF (>6 months), and renal impairment. At 90 days, HF readmission or mortality occurred in 42 congested patients (37%) compared with 18 noncongested patients (14%). Pulmonary congestion increased at 30-day (OR: 3.86; 95% CI: 1.65-8.99; P < 0.01) and 90-day (OR: 3.42; 95% CI: 1.82-6.4; P < 0.01) HF readmission or mortality risk and 90-day mortality (OR: 5.18; 95% CI: 1.44-18.69; P < 0.01). Pulmonary congestion increased the 90-day odds of HF readmission and/or death by 3.3- to 4.2-fold (P < 0.01), independent of demographics, HF characteristics, comorbidities, and event risk score. Over 90 days, days alive out of hospital were fewer (78.3 ± 21.4 days vs 85.5 ± 12.4 days; P < 0.01) in congested patients.

CONCLUSIONS

LUICA can be a powerful tool for detection of predischarge residual congestion. HF nurses can obtain images and provide diagnostic reports that are predictive of ADHF outcomes.

External Validation of the Hospital Frailty-Risk Score in Predicting Clinical Outcomes in Older Heart-Failure Patients in Australia

Frailty is common in older hospitalised heart-failure (HF) patients but is not routinely assessed. The hospital frailty-risk score (HFRS) can be generated from administrative data, but it needs validation in Australian health-care settings. This study determined the HFRS scores at presentation to hospital in 5735 HF patients ≥ 75 years old, admitted over a period of 7 years, at two tertiary hospitals in Australia. Patients were classified into 3 frailty categories: HFRS < 5 (low risk), 5−15 (intermediate risk) and >15 (high risk). Multilevel multivariable regression analysis determined whether the HFRS predicts the following clinical outcomes: 30-day mortality, length of hospital stay (LOS) > 7 days, and 30-day readmissions; this was determined after adjustment for age, sex, Charlson index and socioeconomic status. The mean (SD) age was 76.1 (14.0) years, and 51.9% were female. When compared to the low-risk HFRS group, patients in the high-risk HFRS group had an increased risk of 30-day mortality and prolonged LOS (adjusted OR (aOR) 2.09; 95% CI 1.21−3.60) for 30-day mortality, and an aOR of 1.56 (95% CI 1.01−2.43) for prolonged LOS (c-statistics 0.730 and 0.682, respectively). Similarly, the 30-day readmission rate was significantly higher in the high-risk HFRS group when compared to the low-risk group (aOR 1.69; 95% CI 1.06−2.69; c-statistic = 0.643). The HFRS, derived at admission, can be used to predict ensuing clinical outcomes among older hospitalised HF patients.

A Smartphone-Based Model of Care to Support Patients With Cardiac Disease Transitioning From Hospital to the Community (TeleClinical Care): Pilot Randomized Controlled Trial

Background

Patients hospitalized with acute coronary syndrome (ACS) or heart failure (HF) are frequently readmitted. This is the first randomized controlled trial of a mobile health intervention that combines telemonitoring and education for inpatients with ACS or HF to prevent readmission.

Objective

This study aims to investigate the feasibility, efficacy, and cost-effectiveness of a smartphone app–based model of care (TeleClinical Care [TCC]) in patients discharged after ACS or HF admission.

Methods

In this pilot, 2-center randomized controlled trial, TCC was applied at discharge along with usual care to intervention arm participants. Control arm participants received usual care alone. Inclusion criteria were current admission with ACS or HF, ownership of a compatible smartphone, age ≥18 years, and provision of informed consent. The primary end point was the incidence of unplanned 30-day readmissions. Secondary end points included all-cause readmissions, cardiac readmissions, cardiac rehabilitation completion, medication adherence, cost-effectiveness, and user satisfaction. Intervention arm participants received the app and Bluetooth-enabled devices for measuring weight, blood pressure, and physical activity daily plus usual care. The devices automatically transmitted recordings to the patients’ smartphones and a central server. Thresholds for blood pressure, heart rate, and weight were determined by the treating cardiologists. Readings outside these thresholds were flagged to a monitoring team, who discussed salient abnormalities with the patients’ usual care providers (cardiologists, general practitioners, or HF outreach nurses), who were responsible for further management. The app also provided educational push notifications. Participants were followed up after 6 months.

Results

Overall, 164 inpatients were randomized (TCC: 81/164, 49.4%; control: 83/164, 50.6%; mean age 61.5, SD 12.3 years; 130/164, 79.3% men; 128/164, 78% admitted with ACS). There were 11 unplanned 30-day readmissions in both groups (P=.97). Over a mean follow-up of 193 days, the intervention was associated with a significant reduction in unplanned hospital readmissions (21 in TCC vs 41 in the control arm; P=.02), including cardiac readmissions (11 in TCC vs 25 in the control arm; P=.03), and higher rates of cardiac rehabilitation completion (20/51, 39% vs 9/49, 18%; P=.03) and medication adherence (57/76, 75% vs 37/74, 50%; P=.002). The average usability rating for the app was 4.5/5. The intervention cost Aus $6028 (US $4342.26) per cardiac readmission saved. When modeled in a mainstream clinical setting, enrollment of 237 patients was projected to have the same expenditure compared with usual care, and enrollment of 500 patients was projected to save approximately Aus $100,000 (approximately US $70,000) annually.

Conclusions

TCC was feasible and safe for inpatients with either ACS or HF. The incidence of 30-day readmissions was similar; however, long-term benefits were demonstrated, including fewer readmissions over 6 months, improved medication adherence, and improved cardiac rehabilitation completion.

Trial Registration

Australian New Zealand Clinical Trials Registry ACTRN12618001547235; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=375945

Characteristics, outcomes and long-term survival of heart failure patients undergoing inpatient cardiac rehabilitation

OBJECTIVE

To investigate the association of CR participation with all-cause mortality after a hospitalization for HF and to describe the characteristics and functional and clinical outcomes of heart failure (HF) patients undergoing inpatient cardiac rehabilitation (CR).

DESIGN

Multicenter cohort study. The association between CR participation and all-cause mortality from discharge from the acute care setting was assessed using Cox regression analysis adjusting for established prognostic factors.

SETTING

Six inpatients rehabilitation facilities (IRF).

PARTICIPANTS

3,219 HF patients admitted to inpatient CR between January 2013 and December 2016. Of these patients, 1,455 had been transferred directly from acute care hospitals after a hospitalization for HF (CR-Group 1) and 1,764 had been admitted from the community due to worsening functional disability or worsening clinical conditions (CR-Group 2). Six hundred thirty-three patients not referred to CR after a hospitalization for HF served as control group (non-CR Group).

INTERVENTION

Cardiac rehabilitation.

MAIN OUTCOME MEASURE

long-term mortality. Secondary outcomes were: 1. Change in functional capacity, as assessed by change in 6-minute walking distance (6MWD) from admission to discharge; 2. Clinical outcomes of the index inpatient rehabilitation admission, including in-hospital mortality and unplanned (re)admission to the acute care.

RESULTS

Compared with the non-CR Group, the adjusted hazard ratios of mortality at 1, 3, and 5 years for CR-Group 1 patients were 0.82 (0.68-0.97), 0.81 (0.71-0.93), and 0.80 (0.70-0.91). 6MWD increased from 230 to 292 m (p<.001) and 43.4% of the patients gained >50 m improvement. Overall, 2.5% of the patients died in hospital and 4.7% of the patients experienced unplanned (re)admissions to acute care, with significant differences between Group 1 and Group 2.

CONCLUSIONS

Our data show that inpatient CR is effective in improving functional capacity and suggest that inpatient CR provided in the earliest period following a hospitalization for HF is associated with long-term improved survival.