Prospective development and validation of a model to predict heart failure hospitalisation

Combination of diuretics for acute heart failure: a protocol for a systematic review of randomised clinical trials with network meta-analysis and trial sequential analysis

INTRODUCTION

Acute heart failure (AHF) is a critical, costly condition with high mortality rates, affecting millions annually. Despite advances in cardiovascular care, AHF treatment lacks robust evidence. AHF commonly manifests with sudden heart failure symptoms such as pulmonary congestion, and the pathophysiology involves fluid overload. Initial treatment is based on intravenous diuretics typically, but the optimal combination of drugs remains uncertain.

METHODS AND ANALYSIS

We will systematically review randomised controlled trials enrolling patients with AHF and volume overload undergoing in-hospital diuretic treatment. We aim to investigate any diuretic intervention. Our search strategy includes the following databases: Embase, Medline, Latin American and Caribbean Health Sciences Literature, Web of Science and the Cochrane Central Register of Controlled Trials. The primary outcome is all-cause mortality. Secondary outcomes are serious adverse events, hospital readmission and kidney failure. Study results reported at the most extended follow-up will be used for all outcomes. If appropriate, we will conduct meta-analysis, trial sequential analysis and network meta-analysis.

ETHICS AND DISSEMINATION

No ethics approval is required for this study. The results will be published in a peer-reviewed journal in this field.

PROSPERO REGISTRATION NUMBER

CRD42023463979.

One-year rehospitalisation and mortality after acute heart failure hospitalisation: a competing risk analysis

OBJECTIVE

To identify factors that independently predict the risk of rehospitalisation and death after acute heart failure (AHF) hospital discharge in a real-world setting, considering death without rehospitalisation as a competing event.

METHODS

Single-centre, retrospective, observational study enrolling 394 patients discharged from an index AHF hospitalisation. Overall survival was evaluated using Kaplan-Meier and Cox regression models. For the risk of rehospitalisation, survival analysis considering competing risks was performed: rehospitalisation was the event of interest, and death without rehospitalisation was the competing event.

RESULTS

During the first year after discharge, 131 (33.3%) patients were rehospitalised for AHF and 67 (17.0%) died without being readmitted; the remaining 196 patients (49.7%) lived without further hospitalisations. The 1-year overall survival estimate was 0.71 (SE=0.02). After adjusting for gender, age and left ventricle ejection fraction, the results showed that the risk of death was higher in patients with dementia, higher levels of plasma creatinine (PCr), lower levels of platelet distribution width (PDW) and at Q4 of red cell distribution width (RDW). Multivariable models showed that the risk of rehospitalisation was increased in patients with atrial fibrillation, higher PCr or taking beta-blockers at discharge. Furthermore, the risk of death without AHF rehospitalisation was higher in males, those aged ≥80 years, patients with dementia or RDW at Q4 on admission (compared with Q1). Taking beta-blockers at discharge and having a higher PDW on admission reduced the risk of death without rehospitalisation.

CONCLUSION

When assessing rehospitalisation as a study endpoint, death without rehospitalisation should be considered a competing event in the analyses. Data from this study reveal that patients with atrial fibrillation, renal dysfunction or taking beta-blockers are more likely to be rehospitalised for AHF, while older men with dementia or high RDW are more prone to die without hospital readmission.

Reduction of heart failure guideline-directed medication during hospitalization: prevalence, risk factors, and outcomes

AIMS

Optimal management of heart failure with reduced ejection fraction (HFrEF) includes titration of guideline-directed medical therapy (GDMT) to the highest tolerated dose within the licensed range. During hospitalization, GDMT doses are often significantly altered, although it is unknown whether the cause of hospitalization influences this.

METHODS AND RESULTS

We recruited 711 people with stable HFrEF from specialist heart failure clinics and prospectively assessed events occurring during first unplanned hospitalization. Dose changes of ACE inhibitors or angiotensin receptor blockers (ACEi/ARB), beta-blockers, mineralocorticoid receptor antagonists, and loop diuretics were recorded during 414 hospitalizations, categorized as due to decompensated heart failure, other cardiovascular causes, infection, or other non-cardiovascular causes. Most hospitalizations resulted in no change to GDMT. ACEi/ARB dose was reduced in 21% of hospitalizations and was more common during non-cardiovascular hospitalization (25.4% vs. 13.9%; P = 0.005). ACEi/ARB dose reduction was associated with older age and lower left ventricular ejection fraction at study recruitment, and poorer renal function, lower systolic blood pressure, higher serum potassium, and less frequent care from a cardiologist during admission. People experiencing ACEi/ARB reduction had worse age-adjusted survival after discharge, without differences in heart failure re-hospitalization. De-escalation of beta-blockers occurred in 8% of hospitalizations, most often due to other non-cardiovascular causes; this was not associated with post-discharge survival or re-hospitalization with heart failure.

CONCLUSIONS

De-escalation of HFrEF GDMT is more common during non-cardiovascular hospitalization and for ACEi/ARB is associated with reduced survival. Post-discharge care plans should include robust plans to consider re-escalation of GDMT in these cases.

Atrial fibrillation and risk of progressive heart failure in patients with preserved ejection fraction heart failure

AIMS

Understanding of the pathophysiology of progressive heart failure (HF) in patients with heart failure with preserved ejection fraction (HFpEF) is incomplete. We sought to identify factors differentially associated with risk of progressive HF death and hospitalization in patients with HFpEF compared with patients with HF and reduced ejection fraction (HFrEF).

METHODS AND RESULTS

Prospective cohort study of patients newly referred to secondary care with suspicion of HF, based on symptoms and signs of HF and elevated natriuretic peptides (NP), followed up for a minimum of 6 years. HFpEF and HFrEF were diagnosed according to the 2016 European Society of Cardiology guidelines. Of 960 patients referred, 467 had HFpEF (49%), 311 had HFrEF (32%), and 182 (19%) had neither. Atrial fibrillation (AF) was found in 37% of patients with HFpEF and 34% with HFrEF. During 6 years follow-up, 19% of HFrEF and 14% of HFpEF patients were hospitalized or died due to progressive HF, hazard ratio (HR) 0.67 (95% CI: 0.47-0.96; P = 0.028). AF was the only marker that was differentially associated with progressive HF death or hospitalization in patients with HFpEF HR 2.58 (95% CI: 1.59-4.21; P < 0.001) versus HFrEF HR 1.11 (95% CI: 0.65-1.89; P = 0.7).

CONCLUSIONS

De novo patients diagnosed with HFrEF have greater risk of death or hospitalization due to progressive HF than patients with HFpEF. AF is associated with increased risk of progressive HF death or hospitalization in HFpEF but not HFrEF, raising the intriguing possibility that this may be a novel therapeutic target in this growing population.

Remotely Monitored Cardiac Implantable Electronic Device Data Predict All-Cause and Cardiovascular Unplanned Hospitalization

Background Unplanned hospitalizations are common in patients with cardiovascular disease. The "Triage Heart Failure Risk Status" (Triage-HFRS) algorithm in patients with cardiac implantable electronic devices uses data from up to 9 device-derived physiological parameters to stratify patients as low/medium/high risk of 30-day heart failure (HF) hospitalization, but its use to predict all-cause hospitalization has not been explored. We examined the association between Triage-HFRS and risk of all-cause, cardiovascular, or HF hospitalization. Methods and Results A prospective observational study of 435 adults (including patients with and without HF) with a Medtronic Triage-HFRS-enabled cardiac implantable electronic device (cardiac resynchronization therapy device, implantable cardioverter-defibrillator, or pacemaker). Cox proportional hazards models explored association between Triage-HFRS and time to hospitalization; a frailty term at the patient level accounted for repeated measures. A total of 274 of 435 patients (63.0%) transmitted ≥1 high HFRS transmission before or during the study period. The remaining 161 patients never transmitted a high HFRS. A total of 153 (32.9%) patients had ≥1 unplanned hospitalization during the study period, totaling 356 nonelective hospitalizations. A high HFRS conferred a 37.3% sensitivity and an 86.2% specificity for 30-day all-cause hospitalization; and for HF hospitalizations, these numbers were 62.5% and 85.6%, respectively. Compared with a low Triage-HFRS, a high HFRS conferred a 4.2 relative risk of 30-day all-cause hospitalization (8.5% versus 2.0%), a 5.0 relative risk of 30-day cardiovascular hospitalization (3.6% versus 0.7%), and a 7.7 relative risk of 30-day HF hospitalization (2.0% versus 0.3%). Conclusions In patients with cardiac implantable electronic devices, remotely monitored Triage-HFRS data discriminated between patients at high and low risk of all-cause hospitalization (cardiovascular or noncardiovascular) in real time.

2021 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure: Developed by the Task Force for the diagnosis and treatment of acute and chronic heart failure of the European Society of Cardiology (ESC). With the special contribution of the Heart Failure Association (HFA) of the ESC

Document Reviewers: Rudolf A. de Boer (CPG Review Coordinator) (Netherlands), P. Christian Schulze (CPG Review Coordinator) (Germany), Magdy Abdelhamid (Egypt), Victor Aboyans (France), Stamatis Adamopoulos (Greece), Stefan D. Anker (Germany), Elena Arbelo (Spain), Riccardo Asteggiano (Italy), Johann Bauersachs (Germany), Antoni Bayes-Genis (Spain), Michael A. Borger (Germany), Werner Budts (Belgium), Maja Cikes (Croatia), Kevin Damman (Netherlands), Victoria Delgado (Netherlands), Paul Dendale (Belgium), Polychronis Dilaveris (Greece), Heinz Drexel (Austria), Justin Ezekowitz (Canada), Volkmar Falk (Germany), Laurent Fauchier (France), Gerasimos Filippatos (Greece), Alan Fraser (United Kingdom), Norbert Frey (Germany), Chris P. Gale (United Kingdom), Finn Gustafsson (Denmark), Julie Harris (United Kingdom), Bernard Iung (France), Stefan Janssens (Belgium), Mariell Jessup (United States of America), Aleksandra Konradi (Russia), Dipak Kotecha (United Kingdom), Ekaterini Lambrinou (Cyprus), Patrizio Lancellotti (Belgium), Ulf Landmesser (Germany), Christophe Leclercq (France), Basil S. Lewis (Israel), Francisco Leyva (United Kingdom), AleVs Linhart (Czech Republic), Maja-Lisa Løchen (Norway), Lars H. Lund (Sweden), Donna Mancini (United States of America), Josep Masip (Spain), Davor Milicic (Croatia), Christian Mueller (Switzerland), Holger Nef (Germany), Jens-Cosedis Nielsen (Denmark), Lis Neubeck (United Kingdom), Michel Noutsias (Germany), Steffen E. Petersen (United Kingdom), Anna Sonia Petronio (Italy), Piotr Ponikowski (Poland), Eva Prescott (Denmark), Amina Rakisheva (Kazakhstan), Dimitrios J. Richter (Greece), Evgeny Schlyakhto (Russia), Petar Seferovic (Serbia), Michele Senni (Italy), Marta Sitges (Spain), Miguel Sousa-Uva (Portugal), Carlo G. Tocchetti (Italy), Rhian M. Touyz (United Kingdom), Carsten Tschoepe (Germany), Johannes Waltenberger (Germany/Switzerland) All experts involved in the development of these guidelines have submitted declarations of interest. These have been compiled in a report and published in a supplementary document simultaneously to the guidelines. The report is also available on the ESC website www.escardio.org/guidelines For the Supplementary Data which include background information and detailed discussion of the data that have provided the basis for the guidelines see European Heart Journal online.

Diabetes mellitus and the causes of hospitalisation in people with heart failure

INTRODUCTION

Diabetes mellitus (DM) is associated with increased risk of hospitalisation in people with heart failure and reduced ejection fraction (HFrEF). However, little is known about the causes of these events.

METHODS

Prospective cohort study of 711 people with stable HFrEF. Hospitalisations were categorised by cause as: decompensated heart failure; other cardiovascular; infection or other non-cardiovascular. Rates of hospitalisation and burden of hospitalisation (percentage of follow-up time in hospital) were compared in people with and without DM.

RESULTS

After a mean follow-up of 4.0 years, 1568 hospitalisations occurred in the entire cohort. DM (present in 32% [n=224]) was associated with a higher rate (mean 1.07 vs 0.78 per 100 patient-years; p<0.001) and burden (3.4 vs 2.2% of follow-up time; p<0.001) of hospitalisation. Cause-specific analyses revealed increased rate and burden of hospitalisation due to decompensated heart failure, other cardiovascular causes and infection in people with DM, whereas other non-cardiovascular causes were comparable. Infection made the largest contribution to the burden of hospitalisation in people with and without DM.

CONCLUSIONS

In people with HFrEF, DM is associated with a greater burden of hospitalisation due to decompensated heart failure, other cardiovascular events and infection, with infection making the largest contribution.

The role of sodium-glucose co-transporter 2 protein inhibitors in heart failure: more than an antidiabetic drug?

INTRODUCTION

Heart failure (HF) places a great burden on both the patient and on medical facilities worldwide, with admission due to worsening HF being one of the leading causes of hospitalization. Optimizing HF in the community remains a challenge, but with appropriate medications, specialist review, and community support, the number of hospital admissions could be reduced. Sodium glucose co-transporter protein 2 (SGLT2) inhibitors have been shown to play a role in patients with heart failure and reduce adverse cardiovascular outcomes. This article seeks to investigate the existing medical literature to understand the role of SGLT2 inhibitors in patients with heart failure with reduced ejection fraction (HFrEF).

AREAS COVERED

An electronic search was undertaken looking at recent literature studying the outcomes of SGLT2 inhibitors on patients with heart failure. No limits were placed on the timing of the publications or the type of article. Keywords and MeSH terms were used, and the results were summarized in the relevant section.

EXPERT OPINION

This study shows that SGLT2 inhibitors are a safe and effective medication in the setting of HFrEF and has been shown to reduce symptoms of heart failure thus improving quality of life and reducing admissions due to heart failure and cardiovascular mortality.

Diuretic therapy as prognostic enrichment factor for clinical trials in patients with heart failure with reduced ejection fraction

BACKGROUND

Loop diuretics are the mainstay of congestion treatment in patients with heart failure (HF). We assessed the association between baseline loop diuretic use and outcome. We also compared the increment in risk related to diuretic dose with conventional prognostic enrichment criteria used in the EMPHASIS-HF trial, which included patients with systolic HF and mild symptoms, such as prior hospitalization and elevated natriuretic peptides.

METHODS

Individual analyses were performed according to baseline loop diuretic usage (furosemide-equivalent dose > 40 mg, 1-40 mg, and no furosemide), and according to enrichment criteria adopted in the trial [i.e. recent hospitalization (< 30 days or 30 to 180 days prior to randomization) due to HF or other cardiovascular cause, or elevated natriuretic peptides]. The primary endpoint was a composite of cardiovascular death or HF hospitalization.

RESULTS

Loop diuretic usage at baseline (HR for > 40 mg furosemide-equivalent dose = 3.16, 95% CI 2.43-4.11; HR for 1-40 mg = 2.06, 95% CI 1.60-2.65) was significantly associated with a higher risk for the primary endpoint in a stepwise manner when compared to no baseline loop diuretic usage. In contrast, the differences in outcome rates were more modest when using history of hospitalization and/or BNP: all HR ranged from 1 (reference, non-HF related CV hospitalization > 30 days) to 2.04 (HF hospitalization < 30 days). The effect of eplerenone on the primary endpoint was consistent across subgroups in both analyses (P for interaction ≥ 0.2 for all).

CONCLUSIONS

Loop diuretic usage (especially at doses > 40 mg) identified patients at higher risk than history of HF hospitalization and/or high BNP blood concentrations.

Effect of disease-modifying agents and their association with mortality in multi-morbid patients with heart failure with reduced ejection fraction

Aims

An increasing proportion of patients with heart failure with reduced ejection fraction (HFrEF) have co‐morbidities. The effect of these co‐morbidities on modes of death and the effect of disease‐modifying agents in multi‐morbid patients is unknown.

Methods and results

We performed a prospective cohort study of ambulatory patients with HFrEF to assess predictors of outcomes. We identified four key co‐morbidities—ischaemic aetiology of heart failure, diabetes mellitus, chronic obstructive pulmonary disease (COPD), and chronic kidney disease (CKD)—that were highly prevalent and associated with an increased risk of all‐cause mortality. We used these data to explore modes of death and the utilization of disease‐modifying agents in patients with and without these co‐morbidities. The cohort included 1789 consecutively recruited patients who had an average age of 69.6 ± 12.5 years, and 1307 (73%) were male. Ischaemic aetiology of heart failure was the most common co‐morbidity, occurring in 1061 (59%) patients; 503 (28%) patients had diabetes mellitus, 283 (16%) had COPD, and 140 (8%) had CKD stage IV/V. During mean follow‐up of 3.8 ± 1.6 years, 737 (41.5%) patients died, classified as progressive heart failure (n = 227, 32%), sudden (n = 112, 16%), and non‐cardiovascular deaths (n = 314, 44%). Multi‐morbid patients were older (P < 0.001), more likely to be male (P < 0.001), and had higher New York Heart Association class (P < 0.001), despite having higher left ventricular (LV) ejection fraction (P = 0.001) and lower LV end‐diastolic diameter (P = 0.001). Multi‐morbid patients were prescribed lower doses of disease‐modifying agents, especially patients with COPD who received lower doses of beta‐adrenoceptor antagonists (2.7 ± 3.0 vs. 4.1 ± 3.4 mg, P < 0.001) and were less likely to be implanted with internal cardioverter defibrillators (7% vs. 13%, P < 0.001). In multivariate analysis, COPD and diabetes mellitus conferred a >2.5‐fold and 1.5‐fold increased risk of sudden death, whilst higher doses of beta‐adrenoceptor antagonists were protective (hazard ratio per milligram 0.92, 95% confidence interval 0.86–0.98, P = 0.009). Each milligram of bisoprolol‐equivalent beta‐adrenoceptor antagonist was associated with 9% (P = 0.001) and 11% (P = 0.023) reduction of sudden deaths in patients with <2 and ≥2 co‐morbidities, respectively.

Conclusions

Higher doses of beta‐adrenoceptor antagonist are associated with greater protection from sudden death, most evident in multi‐morbid patients. Patients with COPD who appear to be at the highest risk of sudden death are prescribed the lowest doses and less likely to be implanted with implantable cardioverter defibrillators, which might represent a missed opportunity to optimize safe and proven therapies for these patients.

Risk prediction models for heart failure admissions in adults with congenital heart disease

BACKGROUND

Heart failure (HF) is the leading cause of death in adult patients with congenital heart disease (ACHD). No risk prediction model exists for HF hospitalization (HFH) for ACHD patients. We aimed to develop a clinically relevant one-year risk prediction system to identify ACHD patients at high risk for HFH.

METHODS

Data source was the Quebec CHD Database. A retrospective cohort including all ACHD patients aged 18-64 (1995-2010) was constructed for assessing the cumulative risk of HFH adjusting for competing risk of death. To identify one-year predictors of incident HFH, multivariable logistic regressions were employed to a nested case-control sample of all ACHD patients aged 18-64 in 2009. The final model was used to create a risk score system based on adjusted odds ratios.

RESULTS

The cohort included 29,991 ACHD patients followed for 648,457 person-years. The cumulative HFH risk by age 65 was 12.58%. The case-control sample comprised 26,420 subjects, of whom 189 had HFHs. Significant one-year predictors were age ≥ 50, male sex, CHD lesion severity, recent 12-month HFH history, pulmonary arterial hypertension, chronic kidney disease, coronary artery disease, systemic arterial hypertension, and diabetes mellitus. The created risk score ranged from 0 to 19. The corresponding HFH risk rose rapidly beyond a score of 8. The risk scoring system demonstrated excellent prediction performance.

CONCLUSIONS

One eighth of ACHD population experienced HFH before age 65. Age, sex, CHD lesion severity, recent 12-month HFH history, and comorbidities constructed a risk prediction model that successfully identified patients at high risk for HFH.

Sodium-glucose cotransporter-2 inhibitors: Understanding the mechanisms for therapeutic promise and persisting risks

In a healthy person, the kidney filters nearly 200 g of glucose per day, almost all of which is reabsorbed. The primary transporter responsible for renal glucose reabsorption is sodium-glucose cotransporter-2 (SGLT2). Based on the impact of SGLT2 to prevent renal glucose wasting, SGLT2 inhibitors have been developed to treat diabetes and are the newest class of glucose-lowering agents approved in the United States. By inhibiting glucose reabsorption in the proximal tubule, these agents promote glycosuria, thereby reducing blood glucose concentrations and often resulting in modest weight loss. Recent work in humans and rodents has demonstrated that the clinical utility of these agents may not be limited to diabetes management: SGLT2 inhibitors have also shown therapeutic promise in improving outcomes in heart failure, atrial fibrillation, and, in preclinical studies, certain cancers. Unfortunately, these benefits are not without risk: SGLT2 inhibitors predispose to euglycemic ketoacidosis in those with type 2 diabetes and, largely for this reason, are not approved to treat type 1 diabetes. The mechanism for each of the beneficial and harmful effects of SGLT2 inhibitors-with the exception of their effect to lower plasma glucose concentrations-is an area of active investigation. In this review, we discuss the mechanisms by which these drugs cause euglycemic ketoacidosis and hyperglucagonemia and stimulate hepatic gluconeogenesis as well as their beneficial effects in cardiovascular disease and cancer. In so doing, we aim to highlight the crucial role for selecting patients for SGLT2 inhibitor therapy and highlight several crucial questions that remain unanswered.

Association between loop diuretic dose changes and outcomes in chronic heart failure: observations from the ESC-EORP Heart Failure Long-Term Registry

AIMS

Guidelines recommend down-titration of loop diuretics (LD) once euvolaemia is achieved. In outpatients with heart failure (HF), we investigated LD dose changes in daily cardiology practice, agreement with guideline recommendations, predictors of successful LD down-titration and association between dose changes and outcomes.

METHODS AND RESULTS

We included 8130 HF patients from the ESC-EORP Heart Failure Long-Term Registry. Among patients who had dose decreased, successful decrease was defined as the decrease not followed by death, HF hospitalization, New York Heart Association class deterioration, or subsequent increase in LD dose. Mean age was 66 ± 13 years, 71% men, 62% HF with reduced ejection fraction, 19% HF with mid-range ejection fraction, 19% HF with preserved ejection fraction. Median [interquartile range (IQR)] LD dose was 40 (25-80) mg. LD dose was increased in 16%, decreased in 8.3% and unchanged in 76%. Median (IQR) follow-up was 372 (363-419) days. Diuretic dose increase (vs. no change) was associated with HF death [hazard ratio (HR) 1.53, 95% confidence interval (CI) 1.12-2.08; P = 0.008] and nominally with cardiovascular death (HR 1.25, 95% CI 0.96-1.63; P = 0.103). Decrease of diuretic dose (vs. no change) was associated with nominally lower HF (HR 0.59, 95% CI 0.33-1.07; P = 0.083) and cardiovascular mortality (HR 0.62, 95% CI 0.38-1.00; P = 0.052). Among patients who had LD dose decreased, systolic blood pressure [odds ratio (OR) 1.11 per 10 mmHg increase, 95% CI 1.01-1.22; P = 0.032], and absence of (i) sleep apnoea (OR 0.24, 95% CI 0.09-0.69; P = 0.008), (ii) peripheral congestion (OR 0.48, 95% CI 0.29-0.80; P = 0.005), and (iii) moderate/severe mitral regurgitation (OR 0.57, 95% CI 0.37-0.87; P = 0.008) were independently associated with successful decrease.

CONCLUSION

Diuretic dose was unchanged in 76% and decreased in 8.3% of outpatients with chronic HF. LD dose increase was associated with worse outcomes, while the LD dose decrease group showed a trend for better outcomes compared with the no-change group. Higher systolic blood pressure, and absence of (i) sleep apnoea, (ii) peripheral congestion, and (iii) moderate/severe mitral regurgitation were independently associated with successful dose decrease.

Diabetes mellitus and risk of new-onset and recurrent heart failure: a systematic review and meta-analysis

Despite mounting evidence of the positive relationship between diabetes mellitus (DM) and heart failure (HF), the entire context of the magnitude of risk for HF in relation to DM remains insufficiently understood. The principal reason is because new‐onset HF (HF occurring in participants without a history of HF) and recurrent HF (HF re‐occurring in patients with a history of HF) are not discriminated. This meta‐analysis aims to comprehensively and separately assess the risk of new‐onset and recurrent HF depending on the presence or absence of DM. We systematically searched cohort studies that examined the relationship between DM and new‐onset or recurrent HF using EMBASE and MEDLINE (from 1 Jan 1950 to 28 Jul 2019). The risk ratio (RR) for HF in individuals with DM compared with those without DM was pooled with a random‐effects model. Seventy‐four and 38 eligible studies presented data on RRs for new‐onset and recurrent HF, respectively. For new‐onset HF, the pooled RR [95% confidence interval (CI)] of 69 studies that examined HF as a whole [i.e. combining HF with preserved ejection fraction (HFpEF) and HF with reduced ejection fraction (HFrEF)] was 2.14 (1.96–2.34). The large between‐study heterogeneity (I² = 99.7%, P < 0.001) was significantly explained by mean age [pooled RR (95% CI) 2.60 (2.38–2.84) for mean age < 60 years vs. pooled RR (95% CI) 1.95 (1.79–2.13) for mean age ≥ 60 years] (P < 0.001). Pooled RRs (95% CI) of seven and eight studies, respectively, that separately examined HFpEF and HFrEF risk were 2.22 (2.02–2.43) for HFpEF and 2.73 (2.71–2.75) for HFrEF. The risk magnitudes between HFpEF and HFrEF were not significantly different in studies that examined both HFpEF and HFrEF risks (P = 0.86). For recurrent HF, pooled RR (95% CI) of the 38 studies was 1.39 (1.33–1.45). The large between‐study heterogeneity (I² = 80.1%, P < 0.001) was significantly explained by the proportion of men [pooled RR (95% CI) 1.53 (1.40–1.68) for < 65% men vs. 1.32 (1.25–1.39) for ≥65% men (P = 0.01)] or the large pooled RR for studies of only participants with HFpEF [pooled RR (95% CI), 1.73 (1.32–2.26) (P = 0.002)]. Results indicate that DM is a significant risk factor for both new‐onset and recurrent HF. It is suggested that the risk magnitude is large for new‐onset HF especially in young populations and for recurrent HF especially in women or individuals with HFpEF. DM is associated with future HFpEF and HFrEF to the same extent.

Risk factors for hospital readmission of patients with heart failure: A cohort study

Aim:

The aim of this study was to develop a risk factor model for hospital readmission in patients with heart failure.

Background:

Identification of risk factors and predictors of readmission to hospital in patients with heart failure is very crucial for improved clinical outcomes.

Objective:

The objective of the current study was to investigate and delineate the risk factors that may be implicated in putting a patient at greater risk of readmission due to uncontrolled heart failure.

Materials and Methods:

This is a prospective follow-up cohort study of 170 patients with heart failure at a tertiary hospital in Al Ain city in the United Arab Emirates. We have developed a risk factor model based on the recommendations of validated published data. We have used univariate and multivariate logistic regression analyses on structured steps based on the published data. The main outcome was the risk factors for readmission to hospital due to heart failure.

Results:

A final predictive model (10 variables) was produced for unplanned readmission of patients with heart failure. The risk factors identified in the final model with their odds ratios (ORs) and confidence intervals (CIs) were as follows: four or more prescribed medicines (OR = 4.13; CI = 3.5–4.1; P = 0.003), more than twice daily dosing regimen (OR = 2.34; CI = 1.0–5.0; P = 0.023), poor knowledge of prescribed medications (OR = 4.24; CI = 1.213–14.781; P = 0.006), diabetes mellitus (OR = 3.78; CI = 1.6–8.7; P = 0.006), edema (OR = 2.64; CI = 1.2–5.6; P = 0.011), being house bound (OR = 2.77; CI = 1.2–6.2; P = 0.014), and being prescribed diuretics (OR = 3.69; CI = 1.4–9.2; P = 0.042).

Conclusion:

The specificity of the developed risk prediction model was 82.2%, the sensitivity was 74.3%, and the overall accuracy was 72.9%. The model can be emulated in population with similar characteristics to prevent early readmission of patient with heart failure.

Infection-Related Hospitalization in Heart Failure With Reduced Ejection Fraction: A Prospective Observational Cohort Study

BACKGROUND

Hospitalization is a common adverse event in people with heart failure and reduced ejection fraction, yet is often not primarily due to decompensated heart failure (HF). We investigated the long-term prognosis following infection-related hospitalization.

METHODS

We conducted a prospective observational cohort study of 711 people with heart failure and reduced ejection fraction recruited from 4 specialist HF clinics in the United Kingdom. All hospitalization episodes (n=1568) were recorded and categorized as primarily due to decompensated HF, other cardiovascular disease, infection-related, or other noncardiovascular disease. Survival was determined after the first hospitalization.

RESULTS

During 2900 patient-years of follow-up, there were a total of 14 686 hospital days. At least one hospitalization occurred in 467 people (66%); 25% of first hospitalizations were primarily due to infection and these were not associated with typical signs including tachycardia and pyrexia. Compared with other categories of hospitalization, infection-related was associated with older age, lower serum albumin, higher blood neutrophil counts, and greater prevalence of chronic obstructive pulmonary disease at recruitment. Median survival after first infection-related hospitalization was 18.6 months, comparable to that after first decompensated HF hospitalization, even after age-sex adjustment. The burden of all-cause rehospitalization was comparable irrespective of the category of first hospitalization, but infection more commonly caused re-hospitalization after index infection hospitalization.

CONCLUSIONS

Infection is a common driver of hospitalization in heart failure and reduced ejection fraction and often presents without classical signs. It is associated with high mortality rates, comparable to decompensated HF, and a major burden of rehospitalization caused by recurrent episodes of infection.

Clinical characteristics and prognostic factors in elderly patients with chronic heart failure -A report from the CHART-2 study

Background

Since most of the randomized clinical trials for heart failure (HF) were designed to exclude elderly patients, limited data are available on their clinical characteristics, prognosis, and prognostic factors.

Methods

We compared clinical characteristics, prognosis, and prognostic factors among Stage C/D HF patients in our CHART-2 Study (N = 4876, mean 69 years, women 32%, 6.3-year follow-up) by age (G1, ≤64 years, N = 1521; G2, 65–74 years, N = 1510; and G3, ≥75 years, N = 1845).

Results

From G1 to G3, the prevalence of women, left ventricular ejection fraction (LVEF) and plasma levels of B-type natriuretic peptide (BNP) increased (all P < 0.001). Similarly, 5-year mortality increased (9.9, 17.3 to 39.9%, P < 0.001) along with a decrease in proportion of cardiovascular death and an increase in non-cardiovascular death in both sexes. While all-cause and cardiovascular mortality was comparable between the sexes, women had significantly lower incidence of non-cardiovascular death than men in G2 and G3, which was attributable to the higher incidence of cancer death and pneumonia death in men than in women. Although NYHA functional class III-IV, chronic kidney disease, cancer, LVEF, and BNP had significant impacts on all-cause death in all groups, their impacts were less evident in G3 as compared with G1.

Conclusions

The elderly HF patients, as compared with younger HF patients, were characterized by more severe clinical background, increased proportion of non-cardiovascular death and worse prognosis with different impacts of prognostic factors across the age groups.

Assessing cardiovascular risks from a mid-thigh CT image: a tree-based machine learning approach using radiodensitometric distributions

The nonlinear trimodal regression analysis (NTRA) method based on radiodensitometric CT distributions was recently developed and assessed for the quantification of lower extremity function and nutritional parameters in aging subjects. However, the use of the NTRA method for building predictive models of cardiovascular health was not explored; in this regard, the present study reports the use of NTRA parameters for classifying elderly subjects with coronary heart disease (CHD), cardiovascular disease (CVD), and chronic heart failure (CHF) using multivariate logistic regression and three tree-based machine learning (ML) algorithms. Results from each model were assembled as a typology of four classification metrics: total classification score, classification by tissue type, tissue-based feature importance, and classification by age. The predictive utility of this method was modelled using CHF incidence data. ML models employing the random forests algorithm yielded the highest classification performance for all analyses, and overall classification scores for all three conditions were excellent: CHD (AUCROC: 0.936); CVD (AUCROC: 0.914); CHF (AUCROC: 0.994). Longitudinal assessment for modelling the prediction of CHF incidence was likewise robust (AUCROC: 0.993). The present work introduces a substantial step forward in the construction of non-invasive, standardizable tools for associating adipose, loose connective, and lean tissue changes with cardiovascular health outcomes in elderly individuals.

Evaluating risk prediction models for adults with heart failure: A systematic literature review

Background

The ability to predict risk allows healthcare providers to propose which patients might benefit most from certain therapies, and is relevant to payers’ demands to justify clinical and economic value. To understand the robustness of risk prediction models for heart failure (HF), we conducted a systematic literature review to (1) identify HF risk-prediction models, (2) assess statistical approach and extent of validation, (3) identify common variables, and (4) assess risk of bias (ROB).

Methods

Literature databases were searched from March 2013 to May 2018 to identify risk prediction models conducted in an out-of-hospital setting in adults with HF. Distinct risk prediction variables were ranked according to outcomes assessed and incorporation into the studies. ROB was assessed using Prediction model Risk Of Bias ASsessment Tool (PROBAST).

Results

Of 4720 non-duplicated citations, 40 risk-prediction publications were deemed relevant. Within the 40 publications, 58 models assessed 55 (co)primary outcomes, including all-cause mortality (n = 17), cardiovascular death (n = 9), HF hospitalizations (n = 15), and composite endpoints (n = 14). Few publications reported detail on handling missing data (n = 11; 28%). The discriminatory ability for predicting all-cause mortality, cardiovascular death, and composite endpoints was generally better than for HF hospitalization. 105 distinct predictor variables were identified. Predictors included in >5 publications were: N-terminal prohormone brain-natriuretic peptide, creatinine, blood urea nitrogen, systolic blood pressure, sodium, NYHA class, left ventricular ejection fraction, heart rate, and characteristics including male sex, diabetes, age, and BMI. Only 11/58 (19%) models had overall low ROB, based on our application of PROBAST. In total, 26/58 (45%) models discussed internal validation, and 14/58 (24%) external validation.

Conclusions

The majority of the 58 identified risk-prediction models for HF present particular concerns according to ROB assessment, mainly due to lack of validation and calibration. The potential utility of novel approaches such as machine learning tools is yet to be determined.

Registration number

The SLR was registered in Prospero (ID: CRD42018100709).

Risk Prediction in Transition: MAGGIC Score Performance at Discharge and Incremental Utility of Natriuretic Peptides

BACKGROUND

Risk stratification for hospitalized patients with heart failure (HF) remains a critical need. The Meta-Analysis Global Group in Chronic Heart Failure (MAGGIC) score is a robust model derived from patients with ambulatory HF. Its validity at the time of discharge and the incremental value of natriuretic peptides (NPs) in this setting is unclear.

METHODS

This was a single-center study examining a total of 4138 patients with HF from 2 groups; hospital discharge patients from administrative data (n = 2503, 60.5%) and a prospective registry of patients with ambulatory HF (n = 1635, 39.5%). The ambulatory registry patients underwent N-terminal pro-B-type NP (BNP) measurement at enrollment, and in the hospitalize discharge cohort clinical BNP levels were abstracted. The primary endpoint was all-cause mortality within 1 year. MAGGIC score performance was compared between cohorts utilizing Cox regression and calibration plots. The incremental value of NPs was assessed using calculated area under the curve and net reclassification improvement (NRI).

RESULTS

The hospitalized and ambulatory cohorts differed with respect to primary outcome (777 and 100 deaths, respectively), sex (52.1% vs 41.7% female) and race (35% vs 49.5% African American). The MAGGIC score showed poor discrimination of mortality risk in the hospital discharge (C statistic: 0.668, hazard ratio [HR]: 1.1 per point, 95% confidence interval [CI]: 0.652, 0.684) but fair discrimination in the ambulatory cohorts (C statistic: 0.784, HR: 1.16 per point, 95% CI: 0.74, 0.83), respectively, a difference that was statistically significant (P = .001 for C statistic, 0.002 for HR). Calibration assessment indicated that the slope and intercept (of MAGGIC-predicted to observed mortality) did not statistically differ from ideal in either cohort and did not differ between the cohorts (all P > .1). NP levels did not significantly improve prediction in the hospitalized cohort (P = .127) but did in the ambulatory cohort (C statistic: 0.784 [95% CI: 0.74, 0.83] vs 0.82 [95% CI: 0.78, 0.85]; P = .018) with a favorable NRI of 0.354 (95% CI: 0.202-0.469; P = .002).

CONCLUSION

The MAGGIC score showed poor discrimination when used in patients with HF at hospital discharge, which was inferior to its performance in patients with ambulatory HF. Discrimination within the hospital discharge group was not improved by including hospital NP levels.

Ischemic Heart Disease Modifies the Association of Atrial Fibrillation With Mortality in Heart Failure With Reduced Ejection Fraction

Background

The CASTLE‐AF (Catheter Ablation versus Standard Conventional Therapy in Patients With Left Ventricular Dysfunction and Atrial Fibrillation) trial recently reported that catheter ablation of atrial fibrillation (AF) improves survival in heart failure (HF) with reduced ejection fraction (HFrEF). However, established AF was not associated with mortality in trials of contemporary HFrEF pharmacotherapies. We investigated whether HFrEF pathogenesis may influence the conclusions of studies evaluating the prognostic impact of AF.

Methods and Results

Using a prospective cohort study of 791 patients with HFrEF, with AF determined using 24‐hour ambulatory ECG monitoring, univariable and multivariable Cox regression analyses were used to define the association between AF and mode‐specific mortality (mean follow‐up of 5.4 years). One‐year HF‐related hospitalization was assessed with binary logistic regression analysis. One‐year cardiac remodeling was assessed in a subgroup (n=378) using echocardiography. AF was present in 28.2% of patients, with 9.4% of these being paroxysmal. While AF was associated with increased risk of all‐cause mortality (hazard ratio, 1.27; 95% confidence interval 1.03–1.57), with diverging survival curves after 1 year of follow‐up, this association was lost in age‐sex–adjusted analyses. However, AF was associated with increased risk of age‐sex–adjusted all‐cause mortality in people with ischemic pathogenesis, with a statistically significant interaction between pathogenesis and AF. This was predominantly attributed to progressive HF deaths. After 1 year, HF hospitalization and cardiac remodeling were not associated with AF, even in people with ischemic pathogenesis.

Conclusions

AF is associated with increased risk of death in HFrEF of ischemic pathogenesis, predominantly due to progressive HF deaths during long‐term follow‐up. HFrEF pathogenesis should be considered in trial design and interpretation.

Biomarkers in diagnosing and treatment of acute heart failure

Acute heart failure (AHF) is a complex disorder involving different pathophysiological pathways. In recent years, there is an increased focus on biomarkers that help with diagnosis, risk stratification and disease monitoring of AHF. Finding a reliable set of biomarkers not only improves morbidity and mortality but it can also potentially reveal the new targets of therapy. In this paper, we have reviewed the biomarkers found useful for the diagnosis as well as for risk stratification and prognostication in patients with AHF. We have discussed the established biomarkers for AHF including cardiac troponins and natriuretic peptides and emerging biomarkers including adiponectin, mi-RNA, sST2, Gal-3, MR-proADM, OPG, CT-proAVP and H-FABP for the purposes of making diagnosis, their use as a guide of therapy or for determination of prognosis.

Can We Do More With Less While Building Predictive Models? A Study in Parsimony of Risk Models for Predicting Heart Failure Readmissions

Hospital readmission due to heart failure is a topic of concern for patients and hospitals alike: it is both the most frequent and expensive diagnosis for hospitalization. Therefore, accurate prediction of readmission risk while patients are still in the hospital helps to guide appropriate postdischarge interventions. As our understanding of the disease and the volume of electronic health record data both increase, the number of predictors and model-building time for predicting risk grow rapidly. This suggests a need to use methods for reducing the number of predictors without losing predictive performance. We explored and described three such methods and demonstrated their use by applying them to a real-world dataset consisting of 57 variables from health data of 1210 patients from one hospital system. We compared all models generated from predictor reduction methods against the full, 57-predictor model for predicting risk of 30-day readmissions for patients with heart failure. Our predictive performance, measured by the C-statistic, ranged from 0.630 to 0.840, while model-building time ranged from 10 minutes to 10 hours. Our final model achieved a C-statistic (0.832) comparable to the full model (0.840) in the validation cohort while using only 16 predictors and providing a 66-fold improvement in model-building time.

An argument for reporting data standardization procedures in multi-site predictive modeling: case study on the impact of LOINC standardization on model performance

Objectives

We aimed to gain a better understanding of how standardization of laboratory data can impact predictive model performance in multi-site datasets. We hypothesized that standardizing local laboratory codes to logical observation identifiers names and codes (LOINC) would produce predictive models that significantly outperform those learned utilizing local laboratory codes.

Materials and Methods

We predicted 30-day hospital readmission for a set of heart failure-specific visits to 13 hospitals from 2008 to 2012. Laboratory test results were extracted and then manually cleaned and mapped to LOINC. We extracted features to summarize laboratory data for each patient and used a training dataset (2008–2011) to learn models using a variety of feature selection techniques and classifiers. We evaluated our hypothesis by comparing model performance on an independent test dataset (2012).

Results

Models that utilized LOINC performed significantly better than models that utilized local laboratory test codes, regardless of the feature selection technique and classifier approach used.

Discussion and Conclusion

We quantitatively demonstrated the positive impact of standardizing multi-site laboratory data to LOINC prior to use in predictive models. We used our findings to argue for the need for detailed reporting of data standardization procedures in predictive modeling, especially in studies leveraging multi-site datasets extracted from electronic health records.

Loop diuretics for chronic heart failure: a foe in disguise of a friend?

Loop diuretics are recommended for relieving symptoms and signs of congestion in patients with chronic heart failure and are administered to more than 80% of them. However, several of their effects have not systematically been studied. Numerous cohort and four interventional studies have addressed the effect of diuretics on renal function; apart from one prospective study, which showed that diuretics withdrawal is accompanied by increase in some markers of early-detected renal injury, all others converge to the conclusion that diuretics receipt, especially in high doses is associated with increased rates of renal dysfunction. Although a long standing perception has attributed a beneficial effect to diuretics in the setting of chronic heart failure, many cohort studies support that their use, especially in high doses is associated with adverse outcome. Several studies have used propensity scores in order to match diuretic and non-diuretic receiving patients; their results reinforce the notion that diuretics use and high diuretics dose are true risk factors and not disease severity markers, as some have suggested. One small, randomized study has demonstrated that diuretics decrease is feasible and safe and accompanied by a better prognosis. In conclusion, until elegantly designed, randomized trials, powered for clinical endpoints answer the unsettled issues in the field, the use of diuretics in chronic heart failure will remain subject to physicians' preferences and biases and not evidence based.

Predictive models for identifying risk of readmission after index hospitalization for heart failure: A systematic review

Aims:

Readmission rates for patients with heart failure have consistently remained high over the past two decades. As more electronic data, computing power, and newer statistical techniques become available, data-driven care could be achieved by creating predictive models for adverse outcomes such as readmissions. We therefore aimed to review models for predicting risk of readmission for patients admitted for heart failure. We also aimed to analyze and possibly group the predictors used across the models.

Methods:

Major electronic databases were searched to identify studies that examined correlation between readmission for heart failure and risk factors using multivariate models. We rigorously followed the review process using PRISMA methodology and other established criteria for quality assessment of the studies.

Results:

We did a detailed review of 334 papers and found 25 multivariate predictive models built using data from either health system or trials. A majority of models was built using multiple logistic regression followed by Cox proportional hazards regression. Some newer studies ventured into non-parametric and machine learning methods. Overall predictive accuracy with C-statistics ranged from 0.59 to 0.84. We examined significant predictors across the studies using clinical, administrative, and psychosocial groups.

Conclusions:

Complex disease management and correspondingly increasing costs for heart failure are driving innovations in building risk prediction models for readmission. Large volumes of diverse electronic data and new statistical methods have improved the predictive power of the models over the past two decades. More work is needed for calibration, external validation, and deployment of such models for clinical use.

Vitamin D deficiency is an independent predictor of mortality in patients with chronic heart failure

Purpose

Low 25-hydroxyvitamin D (25[OH]D) concentrations have been associated with adverse outcomes in selected populations with established chronic heart failure (CHF). However, it remains unclear whether 25[OH]D deficiency is associated with mortality and hospitalisation in unselected patients receiving contemporary medical and device therapy for CHF.

Methods

We prospectively examined the prevalence and correlates of 25[OH]D deficiency in 1802 ambulatory patients with CHF due to left ventricular systolic dysfunction (left ventricular ejection fraction ≤ 45%) attending heart failure clinics in the north of England.

Results

73% of patients were deficient in 25[OH]D (< 50 nmol/L). 25[OH]D deficiency was associated with male sex, diabetes, lower serum sodium, higher heart rate, and greater diuretic requirement. During a mean follow-up period of 4 years, each 2.72-fold increment in 25[OH]D concentration (for example from 32 to 87 nmol/L) is associated with 14% lower all-cause mortality (95% confidence interval (CI) 1, 26%; p = 0.04), after accounting for potential confounding factors.

Conclusions

Low 25-hydroxyvitamin D deficiency is associated with increased mortality in patients with chronic heart failure due to left ventricular systolic dysfunction. Whether vitamin D supplementation will improve outcomes is, as yet, unproven.

Electronic supplementary material

The online version of this article (10.1007/s00394-018-1806-y) contains supplementary material, which is available to authorized users.

Observation of Patients Transitioned to an Oral Loop Diuretic Before Discharge and Risk of Readmission for Acute Decompensated Heart Failure

BACKGROUND

Heart failure (HF) is associated with high 30-day readmission rates and places significant financial burden on the health care system. The aim of this study was to determine if the duration of observation on an oral loop diuretic before discharge is associated with a reduction in 30-day HF readmission in patients with acute decompensated HF (ADHF).

METHODS AND RESULTS

This was a retrospective study of adult patients admitted for ADHF at a large academic medical center. A total of 123 patients were included. Baseline characteristics were similar between groups. The primary outcome of 30-day HF readmission occurred in 11 of 61 patients (18%) observed on an oral loop diuretic for <24 hours and in 2 of 62 patients (3.2%) observed on an oral loop diuretic for ≥24 hours (P = .023). Readmissions for 60- and 90-day HF were also significantly lower in patients observed for ≥24 hours (P = .014 and P = .049, respectively). Associations became stronger after multivariate analysis (P < .001). Observation for <24 hours and previous admission within 30 days were independent predictors of 30-day HF readmission (P = .03).

CONCLUSIONS

Observation of patients on an oral loop diuretic for <24 hours was associated with significantly higher 30-day HF readmission. Therefore, observation on an oral loop diuretic for ≥24 hours before discharge in patients presenting with ADHF should be strongly considered.

Multistate Model to Predict Heart Failure Hospitalizations and All-Cause Mortality in Outpatients With Heart Failure With Reduced Ejection Fraction: Model Derivation and External Validation

BACKGROUND

Outpatients with heart failure (HF) who are at high risk for HF hospitalization and death may benefit from early identification. We sought to develop and externally validate a model to predict both HF hospitalization and mortality that accounts for the semicompeting nature of the 2 outcomes and captures the risk associated with the transition from the stable outpatient state to the post-HF hospitalization state.

METHODS AND RESULTS

A multistate model to predict HF hospitalization and all-cause mortality was derived using data (n=3834) from the HEAAL study (Heart Failure Endpoint evaluation of Angiotensin II Antagonist Losartan), a multinational randomized trial in symptomatic patients with reduced left ventricular ejection fraction. Twelve easily and reliably obtainable demographic and clinical predictors were prespecified for model inclusion. Model performance was assessed in the SCD-HeFT cohort (Sudden Cardiac Death in Heart Failure Trial; n=2521). At 1 year, the probability of being alive without HF hospitalization was 94% for a typical patient in the lowest risk quintile and 77% for a typical patient in the highest risk quintile and this variability in risk continued through 7 years of follow-up. The model c-index was 0.72 in the derivation cohort, 0.66 in the validation cohort, and 0.69 in the implantable cardiac defibrillator arm of the validation cohort. There was excellent calibration across quintiles of predicted risk.

CONCLUSIONS

Our findings illustrate the advantages of a multistate modeling approach, providing estimates of HF hospitalization and death in the same model, comparison of predictors for the different outcomes and demonstrating the different trajectories of patients based on baseline characteristics and intermediary events.

CLINICAL TRIAL REGISTRATION

URL: http://www.clinicaltrials.gov. Unique identifiers: NCT00000609 and NCT00090259.

Patient and clinical characteristics that heighten risk for heart failure readmission

BACKGROUND

Within 30 days of hospital discharge, heart failure (HF) readmission rates nationally accumulate to more than 20%. Due to this high rate of unplanned re-hospitalization, predictive models are needed to identify patients who pose the highest readmission risk.

OBJECTIVE

To evaluate the diagnosis and timing and to identify patient and clinical characteristics associated with 30 day readmissions among HF patients.

METHODS

A retrospective analysis of electronic health records was conducted to study HF admissions during the period October 2008 to November 2014. Patients with a primary discharge diagnosis consistent with HF were included. Descriptive statistics were used to compare the readmitted and non-readmitted cohorts. Logistic regression was used to develop a predictive model to determine patient and clinical variables associated with 30 day readmission.

RESULTS

Characteristics of the study cohort (n = 2420) are: a mean age of 72, predominantly male (55%), white (55%), currently not employed (91%), and utilizing Medicare as a payer (68%). Overall, 42% were married. Over the study time period there were 394 (16.3%) 30 day readmissions after 2420 hospitalizations. The 3 most common reasons for readmission were HF (36.0%), renal disorders (8.4%), and other cardiac diseases (6.9%). Analysis showed that 11.9% of patients readmitted during days 0-3, 15.2% during days 4-7, 31.5% during days 8-15, and 41.4% during days 16-30. The final multivariate predictive model included 5 variables that were associated with an increased risk for 30-day readmission: employment status as retired or disabled, > 1 emergency department visit in the past 90 days, length of stay >5 days during index visit, and a BUN value > 45 mg/dL.

CONCLUSION

This study provides a deeper understanding of patient and clinical characteristics that are associated with readmission in HF. Evaluation of these characteristics will provide additional information to guide strategies meant to reduce HF readmission rates.

Mitochondrial dysfunction and its impact on diabetic heart

Mitochondrial dysfunction and associated oxidative stress are strongly linked to cardiovascular, neurodegenerative, and age associated disorders. More specifically cardiovascular diseases are common in patients with diabetes and significant contributor to the high mortality rates associated with diabetes. Studies have shown that the heart failure risk is increased in diabetic patients even after adjusting for coronary artery disease and hypertension. Although the actual basis of the increased heart failure risk is multifactorial, increasing evidences suggest that imbalances in mitochondrial function and associated oxidative stress play an important role in this process. This review summarizes these abnormalities in mitochondrial function and discusses potential underlying mechanisms. This article is part of a Special Issue entitled: Oxidative Stress and Mitochondrial Quality in Diabetes/Obesity and Critical Illness Spectrum of Diseases - edited by P. Hemachandra Reddy.

Diabetes mellitus is associated with adverse structural and functional cardiac remodelling in chronic heart failure with reduced ejection fraction

BACKGROUND

Diabetes mellitus is associated with an increased risk of death and hospitalisation in patients with chronic heart failure. Better understanding of potential underlying mechanisms may aid the development of diabetes mellitus-specific chronic heart failure therapeutic strategies.

METHODS

Prospective observational cohort study of 628 patients with chronic heart failure associated with left ventricular systolic dysfunction receiving contemporary evidence-based therapy. Indices of cardiac structure and function, along with symptoms and biochemical parameters, were compared in patients with and without diabetes mellitus at study recruitment and 1 year later.

RESULTS

Patients with diabetes mellitus (24.2%) experienced higher rates of all-cause [hazard ratio, 2.3 (95% confidence interval, 1.8-3.0)] and chronic heart failure-specific mortality and hospitalisation despite comparable pharmacological and device-based therapies. At study recruitment, patients with diabetes mellitus were more symptomatic, required greater diuretic doses and more frequently had radiologic evidence of pulmonary oedema, despite higher left ventricular ejection fraction. They also exhibited echocardiographic evidence of increased left ventricular wall thickness and pulmonary arterial pressure. Diabetes mellitus was associated with reduced indices of heart rate variability and increased heart rate turbulence. During follow-up, patients with diabetes mellitus experienced less beneficial left ventricular remodelling and greater deterioration in renal function.

CONCLUSION

Diabetes mellitus is associated with features of adverse structural and functional cardiac remodelling in patients with chronic heart failure.

Patient, Caregiver, and Physician Work in Heart Failure Disease Management: A Qualitative Study of Issues That Undermine Wellness

OBJECTIVE

To identify factors underlying heart failure hospitalization.

METHODS

Between January 1, 2012, and May 31, 2012, we combined medical record reviews and cross-sectional qualitative interviews of multiple patients with heart failure, their clinicians, and their caregivers from a large academic medical center in the Midwestern United States. The interview data were analyzed using a 3-step grounded theory-informed process and constant comparative methods. Qualitative data were compared and contrasted with results from the medical record review.

RESULTS

Patient nonadherence to the care plan was the most important contributor to hospital admission; however, reasons for nonadherence were complex and multifactorial. The data highlight the importance of patient education for the purposes of condition management, timeliness of care, and effective communication between providers and patients.

CONCLUSION

To improve the consistency and quality of care for patients with heart failure, more effective relationships among patients, providers, and caregivers are needed. Providers must be pragmatic when educating patients and their caregivers about heart failure, its treatment, and its prognosis.

Diabetes for Cardiologists: Practical Issues in Diagnosis and Management

Diabetes mellitus (DM), a chronic metabolic disease characterized by hyperglycemia, is a profound cardiovascular (CV) risk factor. It compounds the effects of all other risk factors, leads to premature micro- and macrovascular disease, facilitates development of heart failure, worsens the clinical course of all CV diseases, and shortens life expectancy. Established DM, unrecognized DM, and dysglycemia that may progress to DM are all commonly present at the time of presentation of overt CV disease. Thus, CV specialists and trainees frequently treat patients with dysglycemia. The traditional and proven role of cardiologists in reducing the risk of macrovascular events in this population is through aggressive lipid and blood pressure treatment. However, a more proactive role in the detection and management of DM is likely to become increasingly important as the prevalence continues to increase and therapies continue to improve. The latter include antihyperglycemic therapies with proven cardiovascular safety profiles and CV event reduction properties not yet fully elucidated and not necessarily related to glycemic control. Accordingly, the purpose of this article is to (1) expand the interest of cardiologists in earlier stages of the natural history of DM, when prevention or early detection might help achieve greatest benefit; (2) highlight principles of optimal glycemic management, with an emphasis on add-on choices showing promising reduction of CV events and lacking CV adverse effects; and (3) encourage cardiologists to become proactive partners in the multidisciplinary care needed to ensure optimal lifelong vascular health in patients with, or who are at risk of, DM.

Ambulatory heart rate range predicts mode-specific mortality and hospitalisation in chronic heart failure

Objective

We aimed to define the prognostic value of the heart rate range during a 24 h period in patients with chronic heart failure (CHF).

Methods

Prospective observational cohort study of 791 patients with CHF associated with left ventricular systolic dysfunction. Mode-specific mortality and hospitalisation were linked with ambulatory heart rate range (AHRR; calculated as maximum minus minimum heart rate using 24 h Holter monitor data, including paced and non-sinus complexes) in univariate and multivariate analyses. Findings were then corroborated in a validation cohort of 408 patients with CHF with preserved or reduced left ventricular ejection fraction.

Results

After a mean 4.1 years of follow-up, increasing AHRR was associated with reduced risk of all-cause, sudden, non-cardiovascular and progressive heart failure death in univariate analyses. After accounting for characteristics that differed between groups above and below median AHRR using multivariate analysis, AHRR remained strongly associated with all-cause mortality (HR 0.991/bpm increase in AHRR (95% CI 0.999 to 0.982); p=0.046). AHRR was not associated with the risk of any non-elective hospitalisation, but was associated with heart-failure-related hospitalisation. AHRR was modestly associated with the SD of normal-to-normal beats (R²=0.2; p<0.001) and with peak exercise-test heart rate (R²=0.33; p<0.001). Analysis of the validation cohort revealed AHRR to be associated with all-cause and mode-specific death as described in the derivation cohort.

Conclusions

AHRR is a novel and readily available prognosticator in patients with CHF, which may reflect autonomic tone and exercise capacity.