Aetiology, timing and clinical predictors of early vs. late readmission following index hospitalization for acute heart failure: insights from ASCEND-HF

Prognostic value of left atrial reverse remodelling in patients hospitalized with acute decompensated heart failure

AIMS

Left atrial (LA) volume index (LAVI) in chronic heart failure (HF) predicts cardiovascular outcomes. However, the association between LAVI reduction during acute decompensated HF (ADHF) and its prognostic potential is limited. We hypothesized that LA reverse remodelling (LARR) after ADHF therapy would be associated with better clinical outcomes.

METHODS

This retrospective study analysed clinical outcomes and the LAVI reduction rate of 363 out of 861 patients hospitalized for ADHF who underwent two-point echocardiography at admission and discharge between January 2015 and December 2019. The mean age was 74.3 ± 13.6 years, and the mean ejection fraction (EF) was 38.9 ± 15.2%. The follow-up echocardiogram was performed 13.0 [9.5, 20] days after admission. As the median LAVI reduction rate was 7.02%, the LARR was defined as an LAVI reduction rate >7%.

RESULTS

During the 34.0 ± 20.2 months of follow-up, 117 patients (32.2%) reached the primary endpoint defined as cardiovascular death and rehospitalization for ADHF. Kaplan-Meier survival analysis showed that patients with LARR had a better prognosis. Multivariate analysis indicated that LARR was an independent predictor of cardiovascular events. Similar findings were observed in the subgroup analyses of patients with persistent/permanent atrial fibrillation and those with non-HF with reduced EF. Among patients who were brain natriuretic peptide (BNP) responders, defined as a relative reduction of >70% in BNP from admission to discharge, non-LARR was observed in 41.6%. BNP responders without LARR experienced worse prognoses.

CONCLUSIONS

LARR in the early vulnerable phase after hospitalization for ADHF was associated with better long-term clinical outcomes.

Characteristics and Factors of 30-Day Readmissions after Hospitalization for Acute Heart Failure in China

Background

Patients with acute heart failure (HF) are at high risk of 30-day readmission. Little is known about the characteristics and associated factors of 30-day readmissions among patients with acute HF in China.

Methods

We enrolled consecutive patients hospitalized for acute HF and discharged from 52 hospitals in China from August 2016 to May 2018. We describe the rate of 30-day readmission, the time interval from discharge to readmission, and the causes of readmission. We also analyzed the factors associated with readmission risk by fitting multivariate Cox proportional hazards models.

Results

We included 4875 patients with a median age of 67 years (interquartile range, 57-75), 3045 (62.5%) of whom were male. Within 30 days after discharge, 613 (12.6%) patients were readmitted for all causes, with a median from discharge to readmission of 12 (6-21) days. Most readmissions were attributed to cardiovascular causes (71.1%) and 60.0% to HF-related causes. Readmission occurred within 14 days of discharge in more than half of the patients (56.4%). Diabetes (hazard ratio [HR]: 1.25, 95% confidence interval [95% CI]: 1.06-1.50), anemia (HR: 1.26, 95% CI: 1.03-1.53), high New York Heart Association classification (HR: 1.48, 95% CI: 1.08-2.01), elevated N-terminal pro-B type natriuretic peptide (HR: 1.67, 95% CI: 1.24-2.25), and high-sensitivity cardiac troponin T (HR: 1.26, 95% CI: 1.01-1.58) were associated with increased risks of readmission. High systolic blood pressure (HR: 0.56, 95% CI: 0.38-0.81) and Kansas City Cardiomyopathy Questionnaire-12 scores (HR: 0.64, 95% CI: 0.44-0.94) were associated with decreased risk of readmission.

Conclusions

In China, almost one in eight patients with acute HF were readmitted within 30 days after discharge, mainly due to cardiovascular reasons, and approximately three-fifths of the readmissions occurred in the first 14 days. Both clinical and patient-centered characteristics were associated with readmission.

Impact of heart failure hospitalizations on clinical outcomes after mitral transcatheter edge-to-edge repair: Results from the EXPAND study

AIM

This analysis aimed to compare the clinical outcomes associated with heart failure (HF) readmissions and to identify associations with HF hospitalizations (HFH) in patients treated with the MitraClip™ NTR/XTR System in the EXPAND study.

METHODS AND RESULTS

The global, real-world EXPAND study enrolled 1041 patients with primary or secondary mitral regurgitation (MR) treated with the MitraClip NTR/XTR System. Echocardiograms were analysed by an independent echocardiographic core laboratory. The study population was stratified into HFH and No-HFH groups based on the occurrence of HFH 1 year post-index procedure. Clinical outcomes including MR severity, New York Heart Association (NYHA) functional class, Kansas City Cardiomyopathy Questionnaire (KCCQ) score, and all-cause mortality were compared (HFH: n = 181; No-HFH: n = 860). Both groups achieved consistent 1-year MR reduction to ≤1+ (HFH vs. No-HFH: 87.3% vs. 89.5%, p = 0.6) and significant 1-year improvement in KCCQ scores (+16.5 vs. +22.3, p = 0.09) and NYHA functional class. However, more patients in the No-HFH group had 1-year NYHA class ≤II (HFH vs. No-HFH: 67.9% vs. 81.9%, p < 0.01). All-cause mortality at 1 year was 36.8% in the HFH group versus 10.4% in the No-HFH group (p < 0.001). The HFH rate decreased by 63% at 1 year post-M-TEER versus 1 year pre-treatment (relative risk 0.4, p < 0.001). Independent HFH associations were MR ≥2+ at discharge, HFH 1 year prior to treatment, baseline NYHA class ≥III, baseline tricuspid regurgitation ≥2+, and baseline left ventricular ejection fraction ≤40%.

CONCLUSIONS

This study reports the impact of HFH on clinical outcomes post-treatment in the EXPAND study. Results demonstrate that the occurrence of HFH was associated with worse 1-year survival, and treatment with the MitraClip system substantially reduced HFH and improved patient symptoms and quality of life.

Predictors of All-Cause 30-Day Readmissions in Patients with Heart Failure at an Urban Safety Net Hospital: The Importance of Social Determinants of Health and Mental Health

Introduction

Heart failure (HF) is a frequent cause of readmissions. Despite caring for underresourced patients and dependence on government funding, safety net hospitals frequently incur penalties for failing to meet pay-for-performance readmission metrics. Limited research exists on the causes of HF readmissions in safety net hospitals. Therefore, we sought to investigate predictors of 30-day all-cause readmission in HF patients in the safety net setting.

Methods

We performed a retrospective chart review of patients admitted for HF from October 2018 to April 2019. We extracted data on demographics and medical comorbidities and performed patient-specific review of social determinants and mental health in 4 domains: race/ethnicity, housing status, substance use, and mental illness. Multivariable Poisson regression modeling was employed to evaluate associations with 30-day all-cause readmission.

Results

The study population included 290 patients, among whom the mean age was 59 years and 71% (n = 207) were male; 42% (120) were Black/African American (AA), 22% (64) were Hispanic/Latino, and 96% (278) had public insurance; 28% (79) were not housed, 19% (56) had a diagnosis of mental illness, and active substance use was common. The 30-day readmission rate was 25.5% (n = 88). Factors that were associated with increased risk of readmission included self-identifying as Black/AA (relative risk 2.28, 95% confidence interval 1.00-5.20) or Hispanic/Latino (2.53, 1.07-6.00), experiencing homelessness (2.07, 1.21-3.56), living in a shelter (3.20, 1.27-8.02), or intravenous drug use (IVDU) (2.00, 1.08-3.70).

Conclusion

Race/ethnicity, housing status, and substance use were associated with increased risk of 30-day all-cause readmission in HF patients in a safety net hospital. In contrast to prior studies, medical comorbidities were not associated with increased risk of readmission.

Key Factors to Consider When Implementing an Advanced Practice Registered Nurse-Led Heart Failure Clinic

Advanced practice registered nurses (APRNs) such as clinical nurse specialists and nurse practitioners excel at chronic disease management. Development of an APRN-led heart failure (HF) clinic is an ideal way to manage complex HF patients. However, there are important factors to consider when implementing an APRN-led HF clinic. The purpose of this paper is to provide a consolidation of recommendations to consider when developing and implementing an APRN-led HF clinic. A review of applicable literature within the last 10 years was conducted to determine the key factors to be considered when developing organizational structures and processes for an APRN-led HF clinic. The increasing need for primary care and internal medicine providers supports using APRNs to fill the gap and provide disease management for HF patients. Also, APRNs can impact the overall costs of HF treatment by optimizing postdischarge care and preventing hospitalizations and readmissions. Multiple studies supported implementation of APRN-led HF clinics for disease management to provide complex treatment strategies and comprehensive care to these patients.

Machine learning based readmission and mortality prediction in heart failure patients

This study intends to predict in-hospital and 6-month mortality, as well as 30-day and 90-day hospital readmission, using Machine Learning (ML) approach via conventional features. A total of 737 patients remained after applying the exclusion criteria to 1101 heart failure patients. Thirty-four conventional features were collected for each patient. First, the data were divided into train and test cohorts with a 70-30% ratio. Then train data were normalized using the Z-score method, and its mean and standard deviation were applied to the test data. Subsequently, Boruta, RFE, and MRMR feature selection methods were utilized to select more important features in the training set. In the next step, eight ML approaches were used for modeling. Next, hyperparameters were optimized using tenfold cross-validation and grid search in the train dataset. All model development steps (normalization, feature selection, and hyperparameter optimization) were performed on a train set without touching the hold-out test set. Then, bootstrapping was done 1000 times on the hold-out test data. Finally, the obtained results were evaluated using four metrics: area under the ROC curve (AUC), accuracy (ACC), specificity (SPE), and sensitivity (SEN). The RFE-LR (AUC: 0.91, ACC: 0.84, SPE: 0.84, SEN: 0.83) and Boruta-LR (AUC: 0.90, ACC: 0.85, SPE: 0.85, SEN: 0.83) models generated the best results in terms of in-hospital mortality. In terms of 30-day rehospitalization, Boruta-SVM (AUC: 0.73, ACC: 0.81, SPE: 0.85, SEN: 0.50) and MRMR-LR (AUC: 0.71, ACC: 0.68, SPE: 0.69, SEN: 0.63) models performed the best. The best model for 3-month rehospitalization was MRMR-KNN (AUC: 0.60, ACC: 0.63, SPE: 0.66, SEN: 0.53) and regarding 6-month mortality, the MRMR-LR (AUC: 0.61, ACC: 0.63, SPE: 0.44, SEN: 0.66) and MRMR-NB (AUC: 0.59, ACC: 0.61, SPE: 0.48, SEN: 0.63) models outperformed the others. Reliable models were developed in 30-day rehospitalization and in-hospital mortality using conventional features and ML techniques. Such models can effectively personalize treatment, decision-making, and wiser budget allocation. Obtained results in 3-month rehospitalization and 6-month mortality endpoints were not astonishing and further experiments with additional information are needed to fetch promising results in these endpoints.

Association of pre-hospital precipitating factors with short- and long-term outcomes of acute heart failure patients: A report from the WET-HF2 registry

BACKGROUND

Interest in clinical course preceding heart failure (HF) exacerbation has grown, with a greater emphasis placed on patients' clinical factors including precipitant factor (PF). Large-scale studies with precise PF documentation and temporal-outcome variation remain limited.

METHODS

We reviewed prospectively collected 2412 consecutive patient-level records from a multicenter Japanese registry of hospitalized patients with HF (West Tokyo Heart Failure2 Registry: 2018-2020). Patients were categorized based on PFs: behavioral (i.e., poor adherence to physical activity, medicine, or diet regimen), treatment-required (i.e., anemia, arrhythmia, ischemia, infection, thyroid dysfunction or other conditions as suggested exacerbating factors), and no-PF. The composite outcomes of HF rehospitalization and death within 1 year after discharge and HF rehospitalization were individually assessed.

RESULTS

Median patient age was 78 years (interquartile range: 68-85 years), and 1468 (61%) patients had documented PFs, of which 356 (15%) were considered behavioral. The behavioral PF group were younger, more male and had past HF hospitalization history compared to those in the other groups (all p < 0.05). Although risk of in-hospital death was lower in the behavioral PF group, their risk of composite outcome was not significantly different from the treatment-required group (hazard ratio [HR] 1.19 [95% confidence interval {CI} 0.93-1.51]) and the no-PF group (HR 1.28 [95%CI 1.00-1.64]). Furthermore, the risk of HF rehospitalization was higher in the behavioral PF group than in the other two groups (HR 1.40 [95%CI 1.07-1.83] and HR 1.39 [95%CI 1.06-1.83], respectively).

CONCLUSION

Despite a better in-hospital prognosis, patients with behavioral PFs were at significantly higher risk of HF rehospitalization.

Prognostic factors of readmission and mortality after first heart failure hospitalization: results from EPICAL2 cohort

AIMS

We aimed to identify prognostic individual factors in patients with first acute heart failure (HF) hospitalization, considering both death and readmission as part of the natural history of HF.

METHODS AND RESULTS

We used data from the observational, prospective, multicentre EPICAL2 cohort study from which we selected incident cases of acute HF alive at discharge. We relied on an illness-death model to identify prognostic factors on first readmission and on mortality before and after readmission. In 451 patients hospitalized for first acute HF, we observed within the year after discharge, 23 (5.1%) deaths before readmission and 270 (59.9%) first readmissions, of which 60 (22.2%) were followed by death of any cause. First, among patient characteristics, only Charlson index ≥ 8 was associated with first readmission [adjusted hazard ratio (aHR) = 1.6, 95% confidence interval (CI) (1.1-2.3), P = 0.011]. Second, Charlson index ≥ 8 [aHR = 4.2, 95% CI (1.2-14.8), P = 0.025], low blood pressure (BP) [aHR = 12.2, 95% CI (1.9-79.6), P = 0.009], high BP [aHR = 6.9, 95% CI (1.3-36.4), P = 0.023], and prescription of recommended dual or triple HF therapy at index discharge [aHR = 0.2, 95% CI (0.1-0.7), P = 0.014] were associated with mortality before any readmission. Third, Charlson index ≥ 8 [aHR = 2.4, 95% CI (1.1-5.6), P = 0.037] and the time to first readmission (per 30 days additional) [aHR = 1.2; 95% CI (1.1-1.4), P = 0.007] were associated with mortality after readmission.

CONCLUSIONS

Regardless of the prognostic state considered, we showed that comorbidities are of critical prognostic value in a real-world cohort of incident HF cases. This argues in favour of multidisciplinary care in HF.

Real-Life Data on Readmissions of Worsening Heart Failure Outpatients in a Heart Failure Clinic

Introduction Recurrent hospitalizations for worsening heart failure (WHF) represent a major global public health concern, resulting in significant individual morbimortality and socioeconomic costs. This real-life study aimed to determine the rate and predictors of readmission for WHF in a cohort of outpatients with chronic heart failure (CHF) followed in a heart failure clinic (HFC) at a university hospital. Methods We conducted a longitudinal, observational, and retrospective study of all consecutive CHF patients seen at the HFC of the São Francisco Xavier Hospital, Lisbon, by a multidisciplinary team in 2019. The patients were followed for one year and were on optimized therapy. The inclusion criteria for the study were patients who had been hospitalized and subsequently discharged at least three months prior to their enrollment. Patient demographics, heart failure (HF) characterization, comorbidities, pharmacological treatment, treatments of decompensated HF in the day hospital (DH), hospitalizations for WHF, and death were recorded. We applied logistic regression analysis to assess predictors of hospital readmission for HF. Results A total of 351 patients were included: 90 patients (26%) had WHF requiring treatment with intravenous diuretics in the DH; 45 patients (mean age: 79.1 ± 9.0 years) were readmitted for decompensated HF within one year (12.8%) with no gender difference, while 87.2% of the patients (mean age: 74.9 ± 12.1 years) were never readmitted. Readmitted patients were significantly older than those who were not (p=0.031). Additionally, they had a higher New York Heart Association (NYHA) functional classification (p<.001), were on a higher daily dose of furosemide (p=0.008) at the time of the inclusion visit, were more frequently affected by the chronic obstructive pulmonary disease (COPD) (p=0.004); had been treated more often in the DH for WHF (p<.001) and had a higher mortality rate (p<.001) at one year. Conclusions This study aimed to determine WHF patient readmission rates and predictors. According to our results, a higher NYHA class, the need for treatment in the DH for WHF, a daily dose of furosemide equal to or greater than 80 mg, and COPD were predictors of readmission for WHF. CHF patients continue to experience WHF and recurrent hospitalizations despite therapeutic advances and close follow-up in the HFC with the multidisciplinary team. Besides COPD, the HF readmission risk factors found were mainly related to advanced disease. Furthermore, the structured and multidisciplinary approach of our disease management program likely contributed to our relatively low rate of readmissions.

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.

Thirty-day readmission in patients with heart failure with preserved ejection fraction: Insights from the nationwide readmission database

BACKGROUND

There are rising numbers of patients who have heart failure with preserved ejection fraction (HFpEF). Poorly understood pathophysiology of heart failure with preserved and reduced ejection fraction and due to a sparsity of studies, the management of HFpEF is challenging.

AIM

To determine the hospital readmission rate within 30 d of acute or acute on chronic heart failure with preserved ejection fraction and its effect on mortality and burden on health care in the United States.

METHODS

We performed a retrospective study using the Agency for Health-care Research and Quality Health-care Cost and Utilization Project, Nationwide Readmissions Database for the year 2017. We collected data on hospital readmissions of 60514 adults hospitalized for acute or acute on chronic HFpEF. The primary outcome was the rate of all-cause readmission within 30 d of discharge. Secondary outcomes were cause of readmission, mortality rate in readmitted and index patients, length of stay, total hospitalization costs and charges. Independent risk factors for readmission were identified using Cox regression analysis.

RESULTS

The thirty day readmission rate was 21%. Approximately 9.17% of readmissions were in the setting of acute on chronic diastolic heart failure. Hypertensive chronic kidney disease with heart failure (1245; 9.7%) was the most common readmission diagnosis. Readmitted patients had higher in-hospital mortality (7.9% vs 2.9%, P = 0.000). Our study showed that Medicaid insurance, higher Charlson co-morbidity score, patient admitted to a teaching hospital and longer hospital stay were significant variables associated with higher readmission rates. Lower readmission rate was found in residents of small metropolitan or micropolitan areas, older age, female gender, and private insurance or no insurance were associated with lower risk of readmission.

CONCLUSION

We found that patients hospitalized for acute or acute on chronic HFpEF, the thirty day readmission rate was 21%. Readmission cases had a higher mortality rate and increased healthcare resource utilization. The most common cause of readmission was cardio-renal syndrome.

Trends, Predictors, and Outcomes of 30-Day Readmission With Heart Failure After Transcatheter Aortic Valve Replacement: Insights From the US Nationwide Readmission Database

BACKGROUND

Data on trends, predictors, and outcomes of heart failure (HF) readmissions after transcatheter aortic valve replacement (TAVR) remain limited. Moreover, the relationship between hospital TAVR discharge volume and HF readmission outcomes has not been established.

METHODS AND RESULTS

The Nationwide Readmission Database was used to identify 30‐day readmissions for HF after TAVR from October 1, 2015, to November 30, 2018, using International Classification of Diseases, Tenth Revision, Clinical Modification (ICD‐10‐CM) codes. A total of 167 345 weighted discharges following TAVR were identified. The all‐cause readmission rate within 30 days of discharge was 11.4% (19 016). Of all the causes of 30‐day rehospitalizations, HF comprised 31.4% (5962) of all causes. The 30‐day readmission rate for HF did not show a significant decline during the study period (P_trend=0.06); however, all‐cause readmission rates decreased significantly (P_trend=0.03). HF readmissions were comparable between high‐ and low‐volume TAVR centers. Charlson Comorbidity Index >8, length of stay >4 days during the index hospitalization, chronic obstructive pulmonary disease, atrial fibrillation, chronic HF, preexisting pacemaker, complete heart block during index hospitalization, paravalvular regurgitation, chronic kidney disease, and end‐stage renal disease were independent predictors of 30‐day HF readmission after TAVR. HF readmissions were associated with higher mortality rates when compared with non‐HF readmissions (4.9% versus 3.3%; P<0.01). Each HF readmission within 30 days was associated with an average increased cost of $13 000 more than for each non‐HF readmission.

CONCLUSIONS

During the study period from 2015 to 2018, 30‐day HF readmissions after TAVR remained steady despite all‐cause readmissions decreasing significantly. All‐cause readmission mortality and HF readmission mortality also showed a nonsignificant downtrend. HF readmissions were comparable across low‐, medium‐, and high‐volume TAVR centers. HF readmission was associated with increased mortality and resource use attributed to the increased costs of care compared with non‐HF readmission. Further studies are needed to identify strategies to decrease the burden of HF readmissions and related mortality after TAVR.

Tailored risk assessment of 90-day acute heart failure readmission or all-cause death to heart failure with preserved versus reduced ejection fraction

BACKGROUND

After incident heart failure (HF) admission, patients are vulnerable to readmission or death in the 90-day post-discharge. Although risk models for readmission or death incorporate ejection fraction (EF), patients with HF with preserved EF (HFpEF) and those with HF with reduced EF (HFrEF) represent distinct cohorts. To better assess risk, this study developed machine learning models and identified risk factors for the 90-day acute HF readmission or death by HF subtype.

METHODS AND RESULTS

Approximately 1965 patients with HFpEF and 1124 with HFrEF underwent an index admission. Acute HF rehospitalization or death occurred in 23% of HFpEF and 28% of HFrEF groups. Of the 101 variables considered, multistep variable selection identified 24 and 25 significant factors associated with 90-day events in HFpEF and HFrEF, respectively. In addition to risk factors common to both groups, factors unique to HFpEF patients included cognitive dysfunction, low-pulse pressure, β-blocker, and diuretic use, and right ventricular dysfunction. In contrast, factors unique to HFrEF patients included a history of arrhythmia, acute HF on presentation, and echocardiographic characteristics like left atrial dilatation or elevated mitral E/A ratio. Furthermore, the model tailored to HFpEF (area under the curve [AUC] = 0.770; 95% confidence interval [CI] 0.767-0.774) outperformed a model for the combined groups (AUC = 0.759; 95% CI 0.756-0.763).

CONCLUSION

The UF 90-day post-discharge acute HF Re admission or Death Risk Assessment (UF90-RADRA) models help identify HFpEF and HFrEF patients at higher risk who may require proactive outpatient management.

Early (0-7 day) and late (8-30 day) readmission predictors in acute coronary syndrome, atrial fibrillation, and congestive heart failure patients

OBJECTIVES

Thirty-day readmission following hospitalization for acute coronary syndrome (ACS), atrial fibrillation (AF), or congestive heart failure (CHF) is common, and many occur within one week of discharge. Using a cohort of patients hospitalized for ACS, AF, or CHF, we sought to identify predictors of 30-day, early (0-7 day), and late (8-30 day) all-cause readmission.

METHODS

We identified 3531 hospitalizations for ACS, AF, or CHF at a large academic medical center between 2008 and 2018. Multivariable logistic regression models were created to identify predictors of 30-day, early, and late unplanned, all-cause readmission, adjusting for discharge diagnosis and other demographics and comorbidities.

RESULTS

Of 3531 patients hospitalized for ACS, AF, or CHF, 700 (19.8%) were readmitted within 30 days, and 205 (29.3%) readmissions were early. Of all 30-day readmissions, 34.8% of ACS, 16.8% of AF, and 26.0% of the CHF cohorts' readmissions occurred early. Higher hemoglobin was associated with lower 30-day readmission [adjusted (adj) OR 0.92, 95% CI 0.88-0.97] while patients requiring intensive care unit (ICU) admission were more likely readmitted within 30 days (adj OR 1.31, 95% CI 1.03-1.67). Among patients with a 30-day readmission, females (adj OR 1.73, 95% CI 1.22, 2.47) and patients requiring ICU admission (adj OR 2.03, 95% CI 1.27, 3.26) were more likely readmitted early than late. Readmission predictors did not vary substantively by discharge diagnosis.

CONCLUSION

Patients admitted to the ICU were more likely readmitted in the early and 30-day periods. Other predictors varied between readmission groups. Since outpatient follow-up often occurs beyond 1 week of discharge, early readmission predictors can help healthcare providers identify patients who may benefit from particular post-discharge services.

Feasibility and effectiveness of a multidimensional post-discharge disease management programme for heart failure patients in clinical practice: the HerzMobil Tirol programme

AIMS

It remains unclear whether transitional care management outside of a clinical trial setting provides benefits for patients with acute heart failure (AHF) after hospitalization. We evaluated the feasibility and effectiveness of a multidimensional post-discharge disease management programme using a telemedical monitoring system incorporated in a comprehensive network of heart failure nurses, resident physicians, and secondary and tertiary referral centres (HerzMobil Tirol, HMT), METHODS AND RESULTS: The non-randomized study included 508 AHF patients that were managed in HMT (n = 251) or contemporaneously in usual care (UC, n = 257) after discharge from hospital from 2016 to 2019. Groups were retrospectively matched for age and sex. The primary endpoint was time to HF readmission and all-cause mortality within 6 months. Multivariable Cox proportional hazard models were used to assess the effectiveness. The primary endpoint occurred in 48 patients (19.1%) in HMT and 89 (34.6%) in UC. Compared with UC, management by HMT was associated with a 46%-reduction in the primary endpoint (adjusted HR 0.54; 95% CI 0.37-0.77; P < 0.001). Subgroup analyses revealed consistent effectiveness. The composite of recurrent HF hospitalization and death within 6 months per 100 patient-years was 64.2 in HMT and 108.2 in UC (adjusted HR 0.41; 95% CI 0.29-0.55; P < 0.001 with death considered as a competing risk). After 1 year, 25 (10%) patients died in HMT compared with 66 (25.7%) in UC (HR 0.38; 95% CI 0.23-0.61, P < 0.001).

CONCLUSIONS

A multidimensional post-discharge disease management programme, comprising a telemedical monitoring system incorporated in a comprehensive network of specialized heart failure nurses and resident physicians, is feasible and effective in clinical practice.

Readmission following both cardiac and non-cardiac acute dyspnoea is associated with a striking risk of death

Aims

Readmission and mortality are the most common and often combined endpoints in acute heart failure (AHF) trials, but an association between these two outcomes is poorly investigated. The aim of this study was to determine whether unplanned readmission is associated with a greater subsequent risk of death in patients with acute dyspnoea due to cardiac and non‐cardiac causes.

Methods and results

Derivation cohort (1371 patients from the LEDA study) and validation cohort (1986 patients from the BASEL V study) included acute dyspnoea patients admitted to the emergency department. Cox regression analysis was used to determine the association of 6 month readmission and the risk of 1 year all‐cause mortality in AHF and non‐AHF patients and those readmitted due to cardiovascular and non‐cardiovascular causes. In the derivation cohort, 666 (49%) of patients were readmitted at 6 months and 282 (21%) died within 1 year. Six month readmission was associated with an increased 1 year mortality risk in both the derivation cohort [adjusted hazard ratio (aHR) 3.0 (95% confidence interval, CI 2.2–4.0), P < 0.001] and the validation cohort (aHR 1.8, 95% CI 1.4–2.2, P < 0.001). The significant association was similarly observed in AHF (aHR 3.2, 95% CI 2.1–4.9, P < 0.001) and other causes of acute dyspnoea (aHR 2.9, 95% CI 1.9–4.5, P < 0.001), and it did not depend on the aetiology [aHR 2.2, 95% CI 1.6–3.1 for cardiovascular readmissions; aHR 4.1, 95% CI 2.9–5.7 for non‐cardiovascular readmissions (P < 0.001 for both)] or timing of readmission.

Conclusion​s

Our study demonstrated a long‐lasting detrimental association between readmission and death in AHF and non‐AHF patients with acute dyspnoea. These patients should be considered ‘vulnerable patients’ that require personalized follow‐up for an extended period.

Extra-cardiac targets in the management of cardiometabolic disease: Device-based therapies

Heart failure (HF) does not occur in a vacuum and is commonly defined and exacerbated by its co‐morbid conditions. Neurohormonal imbalance and systemic inflammation are some of the key pathomechanisms of HF but also commonly encountered co‐morbidities such as arterial hypertension, diabetes mellitus, cachexia, obesity and sleep‐disordered breathing. A cornerstone of HF management is neurohormonal blockade, which in HF with reduced ejection fraction has been tied to a reduction in morbidity and mortality. Pharmacological treatment effective in patients with HF with reduced ejection fraction did not show substantial effects in HF with preserved ejection fraction. Here, we review novel device‐based therapies using neuromodulation of extra‐cardiac targets to treat cardiometabolic disease.

Readmission and mortality among heart failure patients with history of hypertension in a statewide database

Objective was to examine the temporal trends in readmission and mortality of heart failure (HF) patients with history of hypertension. This study includes 51 141 patients with history of hypertension who were discharged with a first diagnosis of HF between January 1, 2000, and December 31, 2014. Data were obtained from the Myocardial Infarction Data Acquisition System (MIDAS), a statewide database of all hospitalizations for cardiovascular (CV) disease in New Jersey. The temporal trends of mortality, rates of HF-specific readmission, and all-cause readmissions up to 1 year after discharge were examined using multivariable logistic regression. The difference in all-cause mortality at 3 years between patients who were readmitted compared to those who were not readmitted at 1 year was examined. The number of patients with history of hypertension and HF remained unchanged during the study period. Male gender, black race, comorbidities, and admission to non-teaching hospitals were predictors of HF readmission and CV mortality (P < .05 for all). Readmission rate for any cause increased during the study period (P < .001) while rates of HF readmissions and mortality remained relatively unchanged. Patients that had been readmitted within a year exhibited a significantly higher 3-year mortality (P < .001). CV mortality among HF patients with history of hypertension did not change significantly between 2000 and 2014, while the rates of all-cause readmission increased. Patients who were readmitted had higher 3-year mortality (P < .001) than those who were not.

A nurse practitioner-led effort to reduce 30-day heart failure readmissions

BACKGROUND

Heart failure (HF) affects over 6.5 million Americans and is the leading reason for hospital admissions in patients over the age of 65. Readmission rates within 30 days are 21.4% nationally, and 12% of those are likely preventable. Veterans are especially vulnerable to developing cardiac diseases requiring hospitalization and subsequent readmission.

LOCAL PROBLEM

The Southern Arizona Veterans Administration Health Care System has over 5,600 patients diagnosed with HF and a 30-day readmission rate of 21.65%. The aim of this quality improvement project was to reduce 30-day all-cause readmissions by 1% over 8 weeks.

METHODS

To reduce HF readmissions, the plan-do-study-act rapid-cycle method of quality improvement was used.

INTERVENTIONS

A dedicated multidisciplinary HF clinic was formed with a cardiology nurse practitioner, clinical pharmacists, and a dietician. A veteran-centered shared decision-making tool for setting self-care goals was implemented.

RESULTS

The readmission rate of patients seen in the multidisciplinary clinic (n = 33) was reduced by 0.2%. The percentage of veterans seen within 14 days increased from 30% to 54.5%. The average number of days between discharge and cardiology follow-up improved from 45 to 19 days. Veterans were able to set at least one self-care goal 87% of the time. Patient satisfaction with the multidisciplinary clinic was high at 93%.

CONCLUSIONS

Implementing a dedicated, multidisciplinary HF clinic reduced readmissions, improved timeliness of visits, and was well received. Use of a veteran-centered patient engagement tool resulted in more veterans setting self-care goals.

Transitioning Patients with Heart Failure to Outpatient Care

The transition from hospitalization to outpatient care is a vulnerable time for patients with heart failure. This requires specific focus on the transitional care period. Here the authors propose a framework to guide process improvement in the transitional care period. The authors extend this framework by (1) examining the role new technology might play in transitional care, and (2) offering practical advice for teams building transitional care programs.

Reasons for readmission after hospital discharge in patients with chronic diseases-Information from an international dataset

Background

Chronic diseases are increasingly prevalent in Western countries. Once hospitalised, the chance for another hospitalisation increases sharply with large impact on well-being of patients and costs. The pattern of readmissions is very complex, but poorly understood for multiple chronic diseases.

Methods

This cohort study of administrative discharge data between 2009–2014 from 21 tertiary hospitals (eight USA, five UK, four Australia, four continental Europe) investigated rates and reasons of readmissions to the same hospital within 30 days after unplanned admission with one of the following chronic conditions; heart failure; atrial fibrillation; myocardial infarction; hypertension; stroke; chronic obstructive pulmonary disease (COPD); bacterial pneumonia; diabetes mellitus; chronic renal disease; anaemia; arthritis and other cardiovascular disease. Proportions of readmissions with similar versus different diseases were analysed.

Results

Of 4,901,584 admissions, 866,502 (17.7%) were due to the 12 chronic conditions. In-hospital, 43,573 (5.0%) patients died, leaving 822,929 for readmission analysis. Of those, 87,452 (10.6%) had an emergency 30-day readmission, rates ranged from 2.8% for arthritis to 18.4% for COPD. One third were readmitted with the same condition, ranging from 53% for anaemia to 11% for arthritis. Reasons for readmission were due to another chronic condition in 10% to 35% of the cases, leaving 30% to 70% due to reasons other than the original 12 conditions (most commonly, treatment related complications and infections). The chance of being readmitted with the same cause was lower in the USA, for female patients, with increasing age, more co-morbidities, during study period and with longer initial length of stay.

Conclusion

Readmission in chronic conditions is very common and often caused by diseases other than the index hospitalisation. Interventions to reduce readmissions should therefore focus not only on the primary condition but on a holistic consideration of all the patient’s comorbidities.

Usefulness of a personalized algorithm-based discharge checklist in patients hospitalized for acute heart failure

AIMS

The aim of this study is to evaluate the usefulness of a personalized discharge checklist (PCL) based on simple baseline characteristics on mortality, readmission for heart failure (HF), and quality of care in patients hospitalized for acute HF.

METHODS AND RESULTS

We designed an algorithm to generate PCL, based on 2016 HF European Society of Cardiology Guidelines and the screening of common comorbidities in elderly HF patients. We prospectively included 139 patients hospitalized for HF from May 2018 to October 2018. A PCL was fulfilled for each patient at admission and 24 to 48 hours before the planned discharge. A control cohort of 182 consecutive patients was retrospectively included from May 2017 to October 2017. The primary composite endpoint was mortality or readmission for HF at 6 months. The secondary endpoints were mortality, readmission for HF, and quality of care (evidence-based medications, management of HF comorbidities, and planned care plan). There was no difference among baseline characteristics between PCL and control cohorts; mean age was 78.1 ± 12.2 vs. 79.0 ± 12.5 years old (P = 0.46) and 61 patients (43.9%) vs. 63 (34.6%) had HF with left ventricular ejection fraction (LVEF) <40% (P = 0.24). During the 6 month follow-up period, 59 patients (42.4%) reached the primary endpoint in the PCL cohort vs. 92 patients (50.5%) in the control cohort [hazard ratio (HR): 0.79, 95% confidence interval (CI) (0.57-1.09), P = 0.15]. Subgroup analysis including only patients with either altered (<40%) or mid-range or preserved (≥40%) LVEF showed no significant difference among groups. There was a non-significant trend toward a reduction in HF readmission rate in the PCL group [38 patients (27.3%) vs. 64 patients (35.2%), HR: 0.73, 95%CI (0.49-1.09), P = 0.13]. There was no difference regarding survival or the use of evidence-based medications. A higher proportion of patients were screened and treated for iron and vitamin D deficiencies (53.2% vs. 35.7%, P < 0.01 and 73.4% vs. 29.7%, P < 0.01, respectively), as well as malnutrition supplemented in the PCL group. There was a higher referral to HF follow-up programme in the PCL group but not to telemedicine or cardiac rehabilitation programs.

CONCLUSIONS

In this preliminary study, the use of a PCL did not improve outcomes at 6 months in patients hospitalized for acute HF. There was a non-significant trend towards a reduction in HF readmission rate in the PCL group. In addition, the management of HF comorbidities was significantly improved by PCL with a better referral to follow-up programme. A multicentre study is warranted to assess the usefulness of a simple costless personalized checklist in a large HF patients' population.

Factors Associated With Predischarge Versus Postdischarge Scheduling for Early Follow-up Appointments

BACKGROUND

Per national guidelines, early follow-up appointments should be scheduled before discharge, but in previous research, appointments scheduled before discharge were not associated with appointment adherence.

OBJECTIVES

The purpose of this study was to determine whether patient, heart failure (HF), and hospital factors were associated with predischarge appointment scheduling.

METHODS

A secondary analysis of a medical record review included patients hospitalized for decompensated HF at 3 health system hospitals who had a scheduled office appointment post discharge at 14 days or less. Patient demographics, and social, HF, and hospital factors were studied for association with predischarge scheduling.

RESULTS

In multivariable modeling, the odds of having an appointment scheduled predischarge were based on 3 factors: nonwhite race, history of chronic renal insufficiency, and no admission within 14 days before HF hospitalization.

CONCLUSIONS

Appointment scheduling may be based on provider perceptions of readmission risk. Follow-up appointment scheduling practices should be based on systematic processes.

A novel nomogram to predict all-cause readmission or death risk in Chinese elderly patients with heart failure

Aims

Elderly patients with heart failure (HF) are associated with frequent all‐cause readmission or death. The present study sought to develop an accurate and easy‐to‐use model to predict all‐cause readmission or death risk in Chinese elderly patients with HF.

Methods and results

This was a prospective cohort study in patients with HF aged 65 or older. Demographic, co‐morbidity, laboratory, and medication data were collected. A Cox regression model was used to identify factors for the prediction of readmission or death at 30 days and 1 year. A nomogram was developed with bootstrap validation. Of the included 854 patients, the cumulative all‐cause readmission and mortality rates were 10.5% and 11.6% at 30 days and 34.9% and 19.7% at 1 year, respectively. The independent risk factors associated with both 30 day and 1 year readmission or death were older age, stroke, diastolic blood pressure < 60 mmHg, body mass index ≤ 18.5 kg/m², lower estimated glomerular filtration rate, and BNP > 400 pg/mL (all P < 0.05). Anaemia, abnormal neutrophils, and admission without angiotensin‐converting enzyme inhibitors/angiotensin receptor blockers were the specific independent risk factors of 30 day all‐cause readmission or death (all P < 0.05), whereas serum sodium ≤ 140 mmol/L and admission without beta‐blockers were the specific independent risk factors of 1 year all‐cause readmission or death (all P < 0.05). The C‐index of the 30 day and 1 year diagnosis prediction model was 0.778 [95% confidence interval (CI) 0.693–0.862] and 0.738 (95% CI 0.640–0.836), respectively.

Conclusions

We developed accurate and easy‐to‐use nomograms to predict all‐cause readmission or death in Chinese elderly patients with HF. The nomograms will assist in reducing the all‐cause readmission and mortality rates.

Acute heart failure

Acute heart failure (AHF) is a syndrome defined as the new onset (de novo heart failure (HF)) or worsening (acutely decompensated heart failure (ADHF)) of symptoms and signs of HF, mostly related to systemic congestion. In the presence of an underlying structural or functional cardiac dysfunction (whether chronic in ADHF or undiagnosed in de novo HF), one or more precipitating factors can induce AHF, although sometimes de novo HF can result directly from the onset of a new cardiac dysfunction, most frequently an acute coronary syndrome. Despite leading to similar clinical presentations, the underlying cardiac disease and precipitating factors may vary greatly and, therefore, the pathophysiology of AHF is highly heterogeneous. Left ventricular diastolic or systolic dysfunction results in increased preload and afterload, which in turn lead to pulmonary congestion. Fluid retention and redistribution result in systemic congestion, eventually causing organ dysfunction due to hypoperfusion. Current treatment of AHF is mostly symptomatic, centred on decongestive drugs, at best tailored according to the initial haemodynamic status with little regard to the underlying pathophysiological particularities. As a consequence, AHF is still associated with high mortality and hospital readmission rates. There is an unmet need for increased individualization of in-hospital management, including treatments targeting the causative factors, and continuation of treatment after hospital discharge to improve long-term outcomes.

Heart rate and blood pressure monitoring in heart failure

It has been long known that incessant tachycardia and severe hypertension can cause heart failure (HF). In recent years, it has also been recognized that more modest elevations in either heart rate (HR) or blood pressure (BP), if sustained, can be a risk factor both for the development of HF and for mortality in patients with established HF. Heart rate and BP are thus both modifiable risk factors in the setting of HF. What is less clear is the question whether routine systematic monitoring of these simple physiological parameters to a target value can offer clinical benefits. Measuring these parameters clinically during patient review is recommended in HF management in most HF guidelines, both in the acute and chronic phases of the disease. More sophisticated systems now allow long-term automatic or remote monitoring of HR and BP and whether this more detailed patient information can improve clinical outcomes will require prospective RCTs to evaluate. In addition, analysis of patterns of both HR and BP variability can give insights into autonomic function, which is also frequently abnormal in HF. This window into autonomic dysfunction in our HF patients can also provide further independent prognostic information and may in itself be target for future interventional therapies. This article, developed during a consensus meeting of the Heart Failure Association of the ESC concerning the role of physiological monitoring in the complex multi-morbid HF patient, highlights the importance of repeated assessment of HR and BP in HF, and reviews gaps in our knowledge and potential future directions.

Incidence and Clinical Significance of 30-Day and 90-Day Rehospitalization for Heart Failure Among Patients With Acute Decompensated Heart Failure in Japan - From the NARA-HF Study

BACKGROUND

Countermeasure development for early rehospitalization for heart failure (re-HHF) is an urgent and important issue in Western countries and Japan.Methods and Results:Of 1,074 consecutive NARA-HF study participants with acute decompensated HF admitted to hospital as an emergency between January 2007 and December 2016, we excluded 291 without follow-up data, who died in hospital, or who had previous HF-related hospitalizations, leaving 783 in the analysis. During the median follow-up period of 895 days, 241 patients were re-admitted for HF. The incidence of re-HHF was the highest within the first 30 days of discharge (3.3% [26 patients]) and remained high until 90 days, after which it decreased sharply. Within 90 days of discharge, 63 (8.0%) patients were re-admitted. Kaplan-Meier analysis revealed that patients with 90-day re-HHF had worse prognoses than those without 90-day re-HHF in terms of all-cause death (hazard ratio [HR] 2.321, 95% confidence interval [CI] 1.654-3.174; P<0.001) and cardiovascular death (HR 3.396, 95% CI 2.153-5.145; P<0.001). Multivariate analysis indicated that only male sex was an independent predictor of 90-day re-HHF.

CONCLUSIONS

The incidence of early re-HHF was lower in Japan than in Western countries. Its predictors are not related to the clinical factors of HF, indicating that a new comprehensive approach might be needed to prevent early re-HHF.

Highlights in heart failure

Heart failure (HF) remains a major cause of mortality, morbidity, and poor quality of life. It is an area of active research. This article is aimed to give an update on recent advances in all aspects of this syndrome. Major changes occurred in drug treatment of HF with reduced ejection fraction (HFrEF). Sacubitril/valsartan is indicated as a substitute to ACEi/ARBs after PARADIGM-HF (hazard ratio [HR], 0.80; 95% confidence interval [CI], 0.73 to 0.87 for sacubitril/valsartan vs. enalapril for the primary endpoint and Wei, Lin and Weissfeld HR 0.79, 95% CI 0.71-0.89 for recurrent events). Its initiation was then shown as safe and potentially useful in recent studies in patients hospitalized for acute HF. More recently, dapagliflozin and prevention of adverse-outcomes in DAPA-HF trial showed the beneficial effects of the sodium-glucose transporter type 2 inhibitor dapaglifozin vs. placebo, added to optimal standard therapy [HR, 0.74; 95% CI, 0.65 to 0.85;0.74; 95% CI, 0.65 to 0.85 for the primary endpoint]. Trials with other SGLT 2 inhibitors and in other patients, such as those with HF with preserved ejection fraction (HFpEF) or with recent decompensation, are ongoing. Multiple studies showed the unfavourable prognostic significance of abnormalities in serum potassium levels. Potassium lowering agents may allow initiation and titration of mineralocorticoid antagonists in a larger proportion of patients. Meta-analyses suggest better outcomes with ferric carboxymaltose in patients with iron deficiency. Drugs effective in HFrEF may be useful also in HF with mid-range ejection fraction. Better diagnosis and phenotype characterization seem warranted in HF with preserved ejection fraction. These and other burning aspects of HF research are summarized and reviewed in this article.

Analysis Of Re-Hospitalizations For Patients With Heart Failure Caused By Coronary Heart Disease: Data Of First Event And Recurrent Event

BACKGROUND

The re-hospitalization rate of patients with heart failure remains at a high level, and studies of the subject have focused mainly on event-time outcomes. In addition to using re-hospitalization data with the outcomes of the event-time-count, this study introduces the conditional frailty model, which could help obtain more reasonable results.

MATERIALS AND METHODS

This prospective observational cohort study enrolled 1484 patients with heart failure caused by coronary heart disease. The outcomes of heart failure readmissions and the case report form data were collected. Based on the traditional Cox model with event-time outcomes, the mixed effects of a conditional frailty model were added to analyze the event-time-count longitudinal data.

RESULTS

The Cox regression model showed that non-manual work, diastolic dysfunction, and better medical compensation increased the risk of heart failure readmission, whereas treatment with beta-blockers decreased the risk. The conditional frailty model further revealed that age, female sex, non-manual work, better medical compensation, longer QRS duration, and treatment with percutaneous coronary intervention increased the risk of heart failure readmission.

CONCLUSION

This study obtained more reliable, reasonable results based on longitudinal data and a mixed model. The results could provide more clinical epidemiological evidence for the management of heart failure.

Admission diagnoses among patients with heart failure: Variation by ACO performance on a measure of risk-standardized acute admission rates

BACKGROUND

A key quality metric for Accountable Care Organizations (ACOs) is the rate of hospitalization among patients with heart failure (HF). Among this patient population, non-HF-related hospitalizations account for a substantial proportion of admissions. Understanding the types of admissions and the distribution of admission types across ACOs of varying performance may provide important insights for lowering admission rates.

METHODS

We examined admission diagnoses among 220 Medicare Shared Savings Program ACOs in 2013. ACOs were stratified into quartiles by their performance on a measure of unplanned risk-standardized acute admission rates (RSAARs) among patients with HF. Using a previously validated algorithm, we categorized admissions by principal discharge diagnosis into: HF, cardiovascular/non-HF, and noncardiovascular. We compared the mean admission rates by admission type as well as the proportion of admission types across RSAAR quartiles (Q1-Q4).

RESULTS

Among 220 ACOs caring for 227,356 patients with HF, the median (IQR) RSAARs per 100 person-years ranged from 64.5 (61.7-67.7) in Q1 (best performers) to 94.0 (90.1-99.9) in Q4 (worst performers). The mean admission rates by admission types for ACOs in Q1 compared with Q4 were as follows: HF admissions: 9.8 (2.2) vs 14.6 (2.8) per 100 person years (P < .0001); cardiovascular/non-HF admissions: 11.1 (1.6) vs 15.9 (2.6) per 100 person-years (P < .0001); and noncardiovascular admissions: 42.7 (5.4) vs 69.6 (11.3) per 100 person-years (P < .0001). The proportion of admission due to HF, cardiovascular/non-HF, and noncardiovascular conditions was 15.4%, 17.5%, and 67.1% in Q1 compared with 14.6%, 15.9%, and 69.4% in Q4 (P < .007).

CONCLUSIONS

Although ACOs with the best performance on a measure of all-cause admission rates among people with HF tended to have fewer admissions for HF, cardiovascular/non-HF, and noncardiovascular conditions compared with ACOs with the worst performance (highest admission rates), the largest difference in admission rates were for noncardiovascular admission types. Across all ACOs, two-thirds of admissions of patients with HF were for noncardiovascular causes. These findings suggest that comprehensive approaches are needed to reduce the diverse admission types for which HF patients are at risk.

Relation of Volume Overload to Clinical Outcomes in Acute Heart Failure (From ASCEND-HF)

We aimed to study whether jugular venous distension (JVD) and peripheral edema were associated with worse outcomes in patients with acute heart failure in the Acute Study of Clinical Effectiveness of Nesiritide in Decompensated Heart Failure trial. Of 7,141 patients in Acute Study of Clinical Effectiveness of Nesiritide in Decompensated Heart Failure, 7,135 had complete data on baseline JVD and peripheral edema status. Patients were grouped according to baseline examination findings: (1) no JVD or peripheral edema; (2) JVD only; (3) peripheral edema only; (4) JVD and peripheral edema. We used unadjusted and adjusted logistic or Cox regression analyses to assess associations between groups and the outcomes of index length of stay (LOS), in-hospital mortality, 30- and 180-day all-cause mortality. Patients with peripheral edema (Groups 3 and 4) had higher body mass index, NT-proBNP and BNP values, and more co-morbid disease, and reduced left ventricular ejection fraction compared with patients in Groups 1-2. The median (25th-75th) LOS for Groups 1-4 was 6 (4-9), 5 (4-8), 7 (4-11), and 6 days (4-10), respectively. For the 30-day and 180-day outcomes, adjusted analyses found no significant difference in risk for patients presenting with JVD only or peripheral edema only as compared with patients without evidence of JVD or peripheral edema (p >0.05 for all). The presence of both JVD and peripheral edema was associated with an adjusted 24% increase in risk for all-cause mortality at 30 days, but no risk difference at 180 days. In conclusion, in patients with heart failure presenting to the hospital with dyspnea, the presence of peripheral edema is associated with a longer hospital LOS, but no difference in short- and long-term clinical outcomes when compared with patients wihout peripheral edema. The combination of peripheral edema and JVD identifies the highest risk cohort for poor clinical outcomes.

Factors influencing early and late readmissions in Australian hospitalised patients and investigating role of admission nutrition status as a predictor of hospital readmissions: a cohort study

OBJECTIVES

Limited studies have identified predictors of early and late hospital readmissions in Australian healthcare settings. Some of these predictors may be modifiable through targeted interventions. A recent study has identified malnutrition as a predictor of readmissions in older patients but this has not been verified in a larger population. This study investigated what predictors are associated with early and late readmissions and determined whether nutrition status during index hospitalisation can be used as a modifiable predictor of unplanned hospital readmissions.

DESIGN

A retrospective cohort study.

SETTING

Two tertiary-level hospitals in Australia.

PARTICIPANTS

All medical admissions ≥18 years over a period of 1 year.

OUTCOMES

Primary objective was to determine predictors of early (0-7 days) and late (8-180 days) readmissions. Secondary objective was to determine whether nutrition status as determined by malnutrition universal screening tool (MUST) can be used to predict readmissions.

RESULTS

There were 11 750 (44.8%) readmissions within 6 months, with 2897 (11%) early and 8853 (33.8%) late readmissions. MUST was completed in 16.2% patients and prevalence of malnutrition during index admission was 31%. Malnourished patients had a higher risk of both early (OR 1.39, 95% CI 1.12 to 1.73) and late readmissions (OR 1.23, 95% CI 1.06 to 128). Weekend discharges were less likely to be associated with both early (OR 0.81, 95% CI 0.74 to 0.91) and late readmissions (OR 0.91, 95% CI 0.84 to 0.97). Indigenous Australians had a higher risk of early readmissions while those living alone had a higher risk of late readmissions. Patients ≥80 years had a lower risk of early readmissions while admission to intensive care unit was associated with a lower risk of late readmissions.

CONCLUSIONS

Malnutrition is a strong predictor of unplanned readmissions while weekend discharges are less likely to be associated with readmissions. Targeted nutrition intervention may prevent unplanned hospital readmissions.

TRIAL REGISTRATION

ANZCTRN 12617001362381; Results.