Heart failure re-admission: measuring the ever shortening gap between repeat heart failure hospitalizations

Initiation and continuation of pharmacological therapies in patients hospitalized for heart failure in Japan

Currently, the utilization patterns of medications for heart failure (HF) after worsening HF events remain unelucidated in Japan. Here, we conducted a retrospective cohort study evaluating the changes in HF drug utilization patterns in 6 months before and after hospitalizations for HF. The adherence to newly initiated HF medications was evaluated based on the proportion of days covered (PDC) and persistence as continuous treatment episodes among new users. The study included 9091 patients hospitalized for HF between January 2016 and September 2019, including 2735 (30.1%) patients who were newly prescribed at least one HF medication after hospitalization. Despite increases in the use of foundational HF therapy (beta-blockers, angiotensin-converting-enzyme inhibitors/angiotensin receptor blockers, or mineralocorticoid receptor antagonists), 35.6% and 7.6% of patients were treated with the HF foundational monotherapy or diuretics alone after hospitalization, respectively. The mean PDC of newly initiated HF medications ranged from 0.57 for thiazide diuretics to 0.77 for sodium-glucose cotransporter-2 inhibitors. Continuous use of HF medications during the first year after initiation was observed in 30-60% of patients. The mean PDC and one-year continuous HF medication use were consistently lower in patients aged ≥ 75 years and in patients with a history of HF hospitalization for all HF medication classes except for tolvaptan and digoxin. Despite the guideline recommendations of HF pharmacotherapy, both treatment and adherence were suboptimal after HF hospitalization, especially in vulnerable populations such as older patients and those with prior HF hospitalizations.

Time to Triple Therapy in Patients With de Novo Heart Failure With Reduced Ejection Fraction: a Population-Based Study

BACKGROUND

Quadruple therapy is recommended for the management of patients with heart failure (HF) and reduced ejection fraction (HFrEF). In order to provide background and identify barriers to quadruple therapy, in this study, the aim was to explore the time to initiation of triple therapy in a population-based cohort of patients with de novo HF.

METHODS

Adult patients with de novo hospital or emergency department (ED) diagnosis of HF between April 1, 2008, and March 31, 2018, in Alberta, Canada, were included and were linked to echocardiography data to identify patients with HFrEF (EF ≤ 40%). Any treatment with angiotensin-converting enzyme inhibitors/ angiotensin receptor blockers/ angiotensin receptor neprilysin inhibitors, beta-blockers, and mineralocorticoid receptor antagonists was captured if prescribed for ≥ 28 days and filled at least once during the 12 months after the index episode.

RESULTS

Among 14,092 patients with de novo HF and available echocardiography data, 54.9% had HFrEF. By 1 year after diagnosis, of those in the HFrEF cohort, 9.5% had received no therapy, 27.5% monotherapy, 41.6% dual therapy, and 21.4% triple therapy. The median (interquartile range) of time to mono-, dual- and triple therapy in patients with HFrEF were 1 (0, 26), 8 (0, 44), and 14 (0, 52) days, respectively. Patients who received triple therapy were younger, more likely to be male and to have higher frequencies of coronary artery disease, higher glomerular filtration rates and lower left ventricular ejection fraction levels compared to their counterparts. Patients with triple therapy had lower rates of clinical outcomes compared to those on no, mono or dual therapy (adjusted hazard ratio 0.15, 95% confidence interval 0.13, 0.17 for the composite outcome of death, hospitalization due to HF, or ED visit due to HF).

CONCLUSION

Despite guideline recommendations, triple therapy is underused and is slowly deployed in patients with HFrEF, even after hospitalization and ED presentation.

Multidisciplinary heart failure care program: an experience from Colombia

The prevalence of Heart Failure is growing alarmingly; its treatment consumes health resources and affects the quality of life of patients.

OBJECTIVE

to describe the changes in NYHA functional Class, ejection fraction, hospitalizations and mortality after 8 years of follow up in a multidisciplinary heart failure program in Colombia as a model for lower and middle income countries.

METHODS

An observational study was performed with the retrospective analysis of the information RESULTS: 1757 patients were included, The NYHA functional class at the beginning of the program was: NYHA I 23.5%, NYHA II 50.3%, NYHA class Improvement was observed at the end of the follow-up with an increase in the percentage of patients in Functional Class NYHA I and II. The reduction in hospitalizations were 35% less (mean: 0.68 ± 0.95, p < 0.0001), a reduction in the length of stay in the hospital was 13.2% (before: 4.46 ± 7.16, after 3.87 ± 8.1 days, p < 0.001). The total mortality after eight years of follow-up was 6.6 % (n = 116).

CONCLUSION

Multidisciplinary follow-up in HF programs improves Functional Class and EF, decreases hospital admissions as well as hospitalization and the length of stay. This is a very simple and successful model of care for this disease that can be implemented for countries of lower- and middle-income countries.

Epidemiology of worsening heart failure in a population-based cohort from Alberta, Canada: Evaluating eligibility for treatment with vericiguat

BACKGROUND

Patients with heart failure (HF) and a reduced ejection fraction (HFrEF) who experience worsening heart failure (WHF) events are at increased risk of adverse outcomes and experience significant morbidity and mortality. We herein describe the epidemiology of these patients and identify those potentially eligible for vericiguat therapy in this population-based study.

METHODS

This retrospective cohort study included hospitalized or emergency department (ED) patients with a primary diagnosis of HF and left ventricular ejection fraction (LVEF) <45% diagnosed between April 1^st, 2009 and March 31^st, 2019 in Alberta, Canada, with follow-up to March 31^st 2020. Inclusion criteria from the VICTORIA trial were applied to explore eligibility for vericiguat.

RESULTS

Among 25,629 patients with HF and LVEF data, 9,948 (38.8%) had HFrEF, of which 5,259 (52.8%) experienced WHF at some point during a median 5.8 years of follow-up, and 38.3% of those met the vericiguat trial eligibility criteria. Compared to HFrEF patients without WHF, those with WHF were older, with more comorbidities, worse renal function, similar LVEF status, but more use of HF medications, at baseline. At the time of WHF, 27% of those with HFrEF and WHF were on triple therapy, 50.6% were on dual therapy, and 15.4% were on monotherapy. All-cause mortality and the composite outcome of all-cause mortality or cardiovascular hospitalization at 1-year of follow-up were higher in the HFrEF with WHF cohort compared to HFrEF without WHF (adjusted hazard ratios of 1.92 and 1.51, respectively, both p<.0001).

CONCLUSION

Approximately, one-half of patients with HFrEF experienced WHF over long-term follow-up. Most were not on triple therapy, highlighting the underutilization of the existing standard-of-care treatments and opportunities for application of newer therapies; more than one-third of patients with HFrEF may be eligible for vericiguat.

LAY SUMMARY

Among patients with heart failure (HF), those who experience worsening HF are at increased risk of adverse outcomes. A few new therapies, including vericiguat, have emerged recently for patients with HF and reduced ejection fraction. However, the epidemiology, treatment patterns, and outcomes of patients with worsening HF in large representative populations is unclear. In current study, roughly, half of the patients with HF and reduced ejection fraction experienced worsening HF and 38.3% were potentially eligible for vericiguat therapy. The guideline-recommended therapies were under-utilized among patients with worsening HF, which highlights the need for initiatives to address this care gap.

Deep learning-based prediction of heart failure rehospitalization during 6, 12, 24-month follow-ups in patients with acute myocardial infarction

Heart failure is a clinical syndrome that occurs when the heart is too weak or stiff and cannot pump enough blood that our body needs. It is one of the most expensive diseases due to frequent hospitalizations and emergency room visits. Reducing unnecessary rehospitalizations is also an important and challenging task that has the potential of saving healthcare costs, enabling discharge planning, and identifying patients at high risk. Therefore, this paper proposes a deep learning-based prediction model of heart failure rehospitalization during 6, 12, 24-month follow-ups after hospital discharge in patients with acute myocardial infarction (AMI). We used the Korea Acute Myocardial Infarction-National Institutes of Health (KAMIR-NIH) registry which included 13,104 patient records and 551 features. The proposed deep learning-based rehospitalization prediction model outperformed traditional machine learning algorithms such as logistic regression, support vector machine, AdaBoost, gradient boosting machine, and random forest. The performance of the proposed model was accuracy, the area under the curve, precision, recall, specificity, and F1 score of 99.37%, 99.90%, 96.86%, 98.61%, 99.49%, and 97.73%, respectively. This study showed the potential of a deep learning-based model for cardiology, which can be used for decision-making and medical diagnosis tool of heart failure rehospitalization in patients with AMI.

Variability in Coronary Artery Disease Testing for Patients With New-Onset Heart Failure

BACKGROUND

Coronary artery disease (CAD) is the most common cause of new-onset heart failure (HF). Although guidelines recommend ischemic evaluation in this population, testing has historically been underutilized.

OBJECTIVES

This study aimed to identify contemporary trends in CAD testing for patients with new-onset HF, particularly after publication of the STICHES (Surgical Treatment for Ischemic Heart Failure Extension Study), and to characterize geographic and clinician-level variability in testing patterns.

METHODS

We determined the proportion of patients with incident HF who received CAD testing from 2004 to 2019 using an administrative claims database covering commercial insurance and Medicare. We identified demographic and clinical predictors of CAD testing during the 90 days before and after initial diagnosis. Patients were grouped by their county of residence to assess national variation. Patients were then linked to their primary care physician and/or cardiologist to evaluate variation across clinicians.

RESULTS

Among 558,322 patients with new-onset HF, 34.8% underwent CAD testing and 9.3% underwent revascularization. After multivariable adjustment, patients who underwent CAD testing were more likely to be younger, male, diagnosed in an acute care setting, and have systolic dysfunction or recent cardiogenic shock. Incidence of CAD testing remained flat without significant change post-STICHES. Covariate-adjusted testing rates varied from 20% to 45% across counties. The likelihood of testing was higher among patients co-managed by a cardiologist (adjusted OR: 5.12; 95% CI: 4.98-5.27) but varied substantially across cardiologists (IQR: 50.9%-62.4%).

CONCLUSIONS

Most patients with new-onset HF across inpatient and outpatient settings did not receive timely testing for CAD. Substantial variability in testing persists across regions and clinicians.

Emergency department consultations for respiratory symptoms revisited: exploratory investigation of longitudinal trends in patients' perspective on care, health care utilization, and general and mental health, from a multicenter study in Berlin, Germany

BACKGROUND

Only few studies of emergency department (ED) consulters include a longitudinal investigation. The EMACROSS study had surveyed 472 respiratory patients in eight inner-city EDs in Berlin in 2017/2018 for demographic, medical and consultation-related characteristics. This paper presents the results of a follow-up survey at a median of 95 days post-discharge. We aimed to explore the post hoc assessment of ED care and identify potential longitudinal trends.

METHODS

The follow-up survey included items on satisfaction with care received, benefit from the ED visit, potential alternative care, health care utilization, mental and general health, and general life satisfaction. Univariable between-subject and within-subject statistical comparisons were conducted. Logistic regression was performed for multivariable investigations of determinants of dropout and of retrospectively rating the ED visit as beneficial.

RESULTS

Follow-up data was available for 329 patients. Participants of lower education status, migrants, and tourists were more likely to drop out. Having a general practitioner (GP), multimorbidity, and higher general life satisfaction were determinants of response. Retrospective satisfaction ratings were high with no marked longitudinal changes and waiting times as the most frequent reason for dissatisfaction. Retrospective assessment of the visit as beneficial was positively associated with male sex, diagnoses of pneumonia and respiratory failure, and self-referral. Concerning primary care as a viable alternative, judgment at the time of the ED visit and at follow-up did not differ significantly. Health care utilization post-discharge increased for GPs and pulmonologists. Self-reported general health and PHQ-4 anxiety scores were significantly improved at follow-up, while general life satisfaction for the overall sample was unchanged.

CONCLUSIONS

Most patients retrospectively assess the ED visit as satisfactory and beneficial. Possible sex differences in perception of care and its outcomes should be further investigated. Conceivable efforts at diversion of ED utilizers to primary care should consider patients' views regarding acceptable alternatives, which appear relatively independent of situational factors. Representativeness of results is restricted by the study focus on respiratory symptoms, the limited sample size, and the attrition rate.

TRIAL REGISTRATION

German Clinical Trials Register ( DRKS00011930 ); date: 2017/04/25.

Low muscle mass assessed by psoas muscle area is associated with clinical adverse events in elderly patients with heart failure

Background

Acute decompensated heart failure (ADHF) is a growing healthcare burden with increasing prevalence and comorbidities due to progressive aging society. Accumulating evidence suggest that low skeletal muscle mass has a negative impact on clinical outcome in elderly adult population. We sought to determine the significance of psoas muscle area as a novel index of low skeletal muscle mass in elderly patients with ADHF.

Methods

In this single-center retrospective observational study, we reviewed consecutive 865 elderly participants (65 years or older) who were hospitalized for ADHF and 392 were available for analysis (79 years [74–85], 56% male). Cross-sectional areas of psoas muscle at the level of fourth lumbar vertebra were measured by computed tomography and normalized by the square of height to calculate psoas muscle index (PMI, cm²/m²).

Results

Dividing the patients by the gender-specific quartile value (2.47 cm²/m² for male and 1.68 cm²/m² for female), we defined low PMI as the lowest gender-based quartile of PMI. Multiple linear regression analysis revealed female sex, body mass index (BMI), and E/e’, but not left ventricular ejection fraction, were independently associated with PMI. Kaplan-Meier analysis showed low PMI was associated with higher rate of composite endpoint of all-cause death and ADHF re-hospitalization (P = 0.033). Cox proportional hazard model analysis identified low PMI, but not BMI, was an independent predictor of the composite endpoint (Hazard ratio: 1.52 [1.06–2.16], P = 0.024).

Conclusions

PMI predicted future clinical adverse events in elderly patients with ADHF. Further studies are needed to assess whether low skeletal muscle mass can be a potential therapeutic target to improve the outcome of ADHF.

Evaluating the effect of healthcare providers on the clinical path of heart failure patients through a semi-Markov, multi-state model

Background

Investigating similarities and differences among healthcare providers, on the basis of patient healthcare experience, is of interest for policy making. Availability of high quality, routine health databases allows a more detailed analysis of performance across multiple outcomes, but requires appropriate statistical methodology.

Methods

Motivated by analysis of a clinical administrative database of 42,871 Heart Failure patients, we develop a semi-Markov, illness-death, multi-state model of repeated admissions to hospital, subsequent discharge and death. Transition times between these health states each have a flexible baseline hazard, with proportional hazards for patient characteristics (case-mix adjustment) and a discrete distribution for frailty terms representing clusters of providers. Models were estimated using an Expectation-Maximization algorithm and the number of clusters was based on the Bayesian Information Criterion.

Results

We are able to identify clusters of providers for each transition, via the inclusion of a nonparametric discrete frailty. Specifically, we detect 5 latent populations (clusters of providers) for the discharge transition, 3 for the in-hospital to death transition and 4 for the readmission transition. Out of hospital death rates are similar across all providers in this dataset. Adjusting for case-mix, we could detect those providers that show extreme behaviour patterns across different transitions (readmission, discharge and death).

Conclusions

The proposed statistical method incorporates both multiple time-to-event outcomes and identification of clusters of providers with extreme behaviour simultaneously. In this way, the whole patient pathway can be considered, which should help healthcare managers to make a more comprehensive assessment of performance.

Physical Therapist Clinical Practice Guideline for the Management of Individuals With Heart Failure

The American Physical Therapy Association (APTA), in conjunction with the Cardiovascular and Pulmonary Section of APTA, have commissioned the development of this clinical practice guideline to assist physical therapists in their clinical decision making when managing patients with heart failure. Physical therapists treat patients with varying degrees of impairments and limitations in activity and participation associated with heart failure pathology across the continuum of care. This document will guide physical therapist practice in the examination and treatment of patients with a known diagnosis of heart failure. The development of this clinical practice guideline followed a structured process and resulted in 9 key action statements to guide physical therapist practice. The level and quality of available evidence were graded based on specific criteria to determine the strength of each action statement. Clinical algorithms were developed to guide the physical therapist in appropriate clinical decision making. Physical therapists are encouraged to work collaboratively with other members of the health care team in implementing these action statements to improve the activity, participation, and quality of life in individuals with heart failure and reduce the incidence of heart failure-related re-admissions.

Improvement in VO2peak predicts readmissions for cardiovascular disease and mortality in patients undergoing cardiac rehabilitation

Background

Improvement in exercise capacity is a main goal of cardiac rehabilitation but the effects are often lost at long-term follow-up and thus also the benefits on prognosis. We assessed whether improvement in VO2peak during a cardiac rehabilitation programme predicts long-term prognosis.

Methods and results

We performed a retrospective analysis of 1561 cardiac patients completing cardiac rehabilitation in 2011–2017 in Copenhagen. Mean age was 63.6 (11) years, 74% were male and 84% had coronary artery disease, 6% chronic heart failure and 10% heart valve replacement. The association between baseline VO2peak and improvement after cardiac rehabilitation and being readmitted for cardiovascular disease and/or all-cause mortality was assessed with three different analyses: Cox regression for the combined outcome, for all-cause mortality and a multi-state model. During a median follow-up of 2.3 years, 167 readmissions for cardiovascular disease and 77 deaths occurred. In adjusted Cox regression there was a non-linear decreasing risk of the combined outcome with higher baseline VO2peak and with improvement of VO2peak after cardiac rehabilitation. A similar linear association was seen for all-cause mortality. Applying the multi-state model, baseline VO2peak and change in VO2peak were associated with risk of a cardiovascular disease readmission and with all-cause mortality but not with mortality in those having an intermediate readmission for cardiovascular disease.

Conclusion

VO2peak as well as change in VO2peak were highly predictive of future risk of readmissions for cardiovascular disease and all-cause mortality. The predictive value did not extend beyond the next admission for a cardiovascular event.

Heart Failure and Cognitive Impairment: Clinical Relevance and Therapeutic Considerations

Heart failure (HF) is a devastating condition characterized by poor quality of life, numerous complications, high rate of readmission and increased mortality. HF is the most common cause of hospitalization in the United States especially among people over the age of 64 years. The number of people grappling with the ill effects of HF is on the rise as the number of people living to an old age is also on the increase.

Several factors have been attributed to these high readmission and mortality rates among which are; poor adherence with therapy, inability to keep up with clinic appointments and even failure to recognize early symptoms of HF deterioration which may be a result of cognitive impairment.

Therefore, this review seeks to compile the most recent information about the links between HF and dementia or cognitive impairment. We also assessed the prognostic consequences of cognitive impairment complicating HF, therapeutic strategies among patients with HF and focus on future areas of research that would reduce the prevalence of cognitive impairment, reduce its severity and also ameliorate the effect of cognitive impairment coexisting with HF.

External Validation and Refinement of Emergency Heart Failure Mortality Risk Grade Risk Model in Patients With Heart Failure in the Emergency Department

Background

Emergency Heart Failure Mortality Risk Grade (EHMRG) assesses the risk of death within 7 days of emergency department (ED) presentation for patients with acute heart failure (AHF). We aimed to externally validate and refine the EHMRG model in patients who presented to the ED with AHF.

Methods

We performed a cohort study using administrative data for all ambulance-transported patients from Alberta (2012-2016) presenting to the ED with a primary diagnosis of AHF.

Results

Among 6708 patients with AHF, the 7-day mortality was 0.0%, 0.8%, 1.6%, 4.0%, 4.2%, and 12.0% across EHMRG risk categories (1-4, 5A and 5B). The EHMRG score had a c-index of 0.73 (95% confidence interval [CI], 0.71-0.76) for 7-day mortality and 0.71 (95% CI, 0.70-0.73) for 30-day mortality, but lower c-statistics for other outcomes (0.61-0.67). The inclusion of natriuretic peptides to the EHMRG model improved prediction (Net Reclassification Improvement, 0.268; 95% CI, 0.173-0.363; P < 0.01) for 7-day mortality, as did the addition of the Canadian Triage and Acuity Scale (Net Reclassification Improvement, 0.111; 95% CI, 0.005-0.218; P = 0.04).

Conclusion

The EHMRG model exhibited moderate discriminative ability in a large population-based cohort of patients with AHF in the ED. Revision of the EHMRG score through factor inclusion and exclusion could improve the model’s performance.

Recurrent events analysis for examination of hospitalizations in heart failure: insights from the Enhanced Feedback for Effective Cardiac Treatment (EFFECT) trial

Aims

Hospitalizations often occur multiple times during the disease course of a heart failure (HF) patient. However, repeated hospitalizations have not been explored in a fulsome way in this setting. We investigated the association between patient factors and the risk of hospitalization among patients with HF using an extension of the Cox model for the analysis of recurrent events.

Methods and results

We examined hospitalizations and predictors of readmission among newly discharged patients with HF in the Enhanced Feedback For Effective Cardiac Treatment phase 1 (April 1999-March 2001) study with the Prentice-Williams-Peterson model with total time. Of 8948 individuals discharged alive from hospital, 7562 (84.5%) were hospitalized at least once during 15-year follow-up. More than 31 000 hospitalizations were observed. There was a progressive shortening of the interval length between hospitalization episodes. An increasing number of comorbidities (average 2.3 per patient) was associated to an increasing hazard of being readmitted to hospital. Most patient factors associated with the risk of hospitalization have been previously described in the literature. However, the estimates were smaller in comparison to a traditional analysis based on the Cox model.

Conclusion

The importance of patient factors for the risk of being admitted to hospital was variable over the course of the disease. Conditions such as diabetes and chronic pulmonary obstructive disease had a sustained association with the rate of hospitalization across all episodes examined. The analysis of recurrent events can explore the longitudinal aspect of HF and the critical issue of hospitalizations in this population.

The Relationship Between Heart-Failure Hospitalization and Mortality in Patients Receiving Transcatheter Aortic Valve Replacement

BACKGROUND

Patients who have had transcatheter aortic valve replacement (TAVR) are at risk of hospitalization during the first year postprocedure. Few studies have examined the incidence of heart- failure hospitalizations (HFH) post-TAVR and the impact this has on subsequent hospitalizations and mortality. Our aim was to determine the incidence, predictors, and mortality associated with HFH post-TAVR.

METHODS

We used prospectively collected data for all patients who underwent TAVR between August 1, 2010, and March 31, 2015; 742 consecutive patients who underwent TAVR during the study period were included. Patients were followed for a minimum of 1 year post-TAVR.

RESULTS

Mean age was 80.9 ± 8.1, and 58.2% were men. Hospitalizations post-TAVR occurred in 20% of patients at 30 days and 59.7% at 1 year. Of patients hospitalized, HFH was the primary cause of hospitalization in 25.8% and 21.4% of patients at 30 days and 1 year post-TAVR, respectively. Patients with HFH at either 30 days or 1 year had higher subsequent rates of rehospitalization compared with patients who had non-HFH. Patients with HFH or non-HFH at 30 days had 1-year mortality rates of 23.1% and 21.4%, respectively, whereas those with HFH by 1 year had a higher 1-year rate of mortality compared with patients who had non-HFHs (25% vs 10.9%, P < 0.001).

CONCLUSIONS

HF accounts for a quarter of all hospitalizations post-TAVR and is associated with higher rates of subsequent rehospitalization and death compared with those who had non-HFH. Understanding predictors of readmissions post-TAVR will allow for better risk stratification and improve outcomes in patients receiving TAVR.

Frailty syndrome and rehospitalizations in elderly heart failure patients

Background

Heart failure (HF) patients with frailty syndrome (FS) are at higher risk of falling, decreased mobility, ability to perform the basic activities of daily living, frequent hospitalizations, and death.

Aims

The purpose of this study was to evaluate the correlations between FS and hospital readmissions, and to assess which factors are associated with rehospitalizations.

Methods

The study included 330 patients with a mean age of 72.1 ± 7.9 years, diagnosed with HF. Frailty was measured using the Polish version of the Tilburg Frailty Indicator (TFI). Demographic, sociodemographic, and clinical data, such as the New York Heart Association (NYHA) functional class, ejection fraction (EF), number of rehospitalizations, and the medications taken, were obtained.

Results

Positive correlation was observed between the number of hospitalizations and FS. In the single-factor correlation analysis, treatment with diuretics, a higher NYHA class, and a lower left ventricular EF were predictors of a higher number of hospitalizations. Additionally, the physical and psychological components of the TFI, as well as the total TFI score, predisposed HF patients to more frequent hospitalizations.

Discussion

It seems that a deterioration of functional capabilities and an increase in symptom severity naturally lead to increased hospitalization frequency in HF. In the own study, regression analysis indicates that high NYHA classes and TFI social component scores are significant predictors of the number of hospitalizations in the studied group.

Conclusions

FS is highly prevalent among elderly HF patients. Higher frailty levels in elderly patients are a determinant of more frequent rehospitalizations in HF.

Time-to-first-event versus recurrent-event analysis: points to consider for selecting a meaningful analysis strategy in clinical trials with composite endpoints

BACKGROUND

Composite endpoints combining several event types of clinical interest often define the primary efficacy outcome in cardiologic trials. They are commonly evaluated as time-to-first-event, thereby following the recommendations of regulatory agencies. However, to assess the patient's full disease burden and to identify preventive factors or interventions, subsequent events following the first one should be considered as well. This is especially important in cohort studies and RCTs with a long follow-up leading to a higher number of observed events per patients. So far, there exist no recommendations which approach should be preferred.

DESIGN

Recently, the Cardiovascular Round Table of the European Society of Cardiology indicated the need to investigate "how to interpret results if recurrent-event analysis results differ […] from time-to-first-event analysis" (Anker et al., Eur J Heart Fail 18:482-489, 2016). This work addresses this topic by means of a systematic simulation study.

METHODS

This paper compares two common analysis strategies for composite endpoints differing with respect to the incorporation of recurrent events for typical data scenarios motivated by a clinical trial.

RESULTS

We show that the treatment effects estimated from a time-to-first-event analysis (Cox model) and a recurrent-event analysis (Andersen-Gill model) can systematically differ, particularly in cardiovascular trials. Moreover, we provide guidance on how to interpret these results and recommend points to consider for the choice of a meaningful analysis strategy.

CONCLUSIONS

When planning trials with a composite endpoint, researchers, and regulatory agencies should be aware that the model choice affects the estimated treatment effect and its interpretation.

Cost-Effectiveness of Multidisciplinary Management Program and Exercise Training Program in Heart Failure

Heart failure causes significant health and financial burdens for patients and society. Multidisciplinary management program (MMP) and exercise training program (ETP) have been reported as cost-effective in improving health outcomes, yet no study has compared the 2 programs. We constructed a Markov model to simulate life year (LY) gained and total costs in usual care (UC), MMP, and ETP. The probability of transitions between states and healthcare costs were extracted from previous literature. We calculated the incremental cost-effectiveness ratio (ICER) over a 10-year horizon. Model robustness was assessed through 1-way and probabilistic sensitivity analyses. The expected LY for patients treated with UC, MMP, and ETP was 7.6, 8.2, and 8.4 years, respectively. From a societal perspective, the expected cost of MMP was $20,695, slightly higher than the cost of UC ($20,092). The cost of ETP was much higher ($48,378) because of its high implementation expense and the wage loss it incurred. The ICER of MMP versus UC was $976 per LY gained, and the ICER of ETP versus MMP was $165,702 per LY gained. The results indicated that, under current cost-effectiveness threshold, MMP is cost-effective compared with UC, and ETP is not cost-effective compared with MMP. However, ETP is cost-effective compared with MMP from a healthcare payer's perspective.

Multi-state modelling of heart failure care path: A population-based investigation from Italy

Background

How different risk profiles of heart failure (HF) patients can influence multiple readmissions and outpatient management is largely unknown. We propose the application of two multi-state models in real world setting to jointly evaluate the impact of different risk factors on multiple hospital admissions, Integrated Home Care (IHC) activations, Intermediate Care Unit (ICU) admissions and death.

Methods and findings

The first model (model 1) concerns only hospitalizations as possible events and aims at detecting the determinants of repeated hospitalizations. The second model (model 2) considers both hospitalizations and ICU/IHC events and aims at evaluating which profiles are associated with transitions in intermediate care with respect to repeated hospitalizations or death. Both are characterized by transition specific covariates, adjusting for risk factors. We identified 4,904 patients (4,129 de novo and 775 worsening heart failure, WHF) hospitalized for HF from 2009 to 2014. 2,714 (55%) patients died. Advanced age and higher morbidity load increased the rate of dying and of being rehospitalized (model 1), decreased the rate of being discharged from hospital (models 1 and 2) and increased the rate of inactivation of IHC (model 2). WHF was an important risk factor associated with hospital readmission.

Conclusion

Multi-state models enable a better identification of two patterns of HF patients. Once adjusted for age and comorbidity load, the WHF condition identifies patients who are more likely to be readmitted to hospital, but does not represent an increasing risk factor for activating ICU/IHC. This highlights different ways to manage specific patients’ patterns of care. These results provide useful healthcare support to patients’ management in real world context. Our study suggests that the epidemiology of the considered clinical characteristics is more nuanced than traditionally presented through a single event.

Real world heart failure epidemiology and outcome: A population-based analysis of 88,195 patients

BACKGROUND

Heart failure (HF) is frequent and its prevalence is increasing. We aimed to evaluate the epidemiologic features of HF patients, the 1-year follow-up outcomes and the independent predictors of those outcomes at a population level.

METHODS AND RESULTS

Population-based longitudinal study including all prevalent HF cases in Catalonia (Spain) on December 31st, 2012. Patients were divided in 3 groups: patients without a previous HF hospitalization, patients with a remote (>1 year) HF hospitalization and patients with a recent (<1 year) HF admission. We analyzed 1year all-cause and HF hospitalizations, and all-cause mortality. Logistic regression was used to identify the independent predictors of each of those outcomes. A total of 88,195 patients were included. Mean age was 77 years, 55% were women. Comorbidities were frequent. Fourteen percent of patients had never been hospitalized, 71% had a remote HF hospitalization and 15% a recent hospitalization. At 1-year follow-up, all-cause and HF hospitalization were 53% and 8.8%, respectively. One-year all-cause mortality rate was 14%, and was higher in patients with a recent HF hospitalization (24%). The presence of diabetes mellitus, atrial fibrillation or chronic kidney disease was independently associated with all-cause and HF hospitalization and all-cause mortality. Hospital admissions and emergency department visits the previous year were also found to be independently associated with the three study outcomes.

CONCLUSIONS

Outcomes are different depending on the HF population studied. Some comorbidity, an all-cause hospitalization or emergency department visit the previous year were associated with a worse outcome.

Examining Characteristics of Hospitalizations in Heart Failure Patients: Results from the 2009 All-payer Data

Heart failure (HF) is one of the most common chronic and disabling illnesses, resulting in high morbidity and mortality. Readmission rate, one key indicator of healthcare quality and healthcare utilization, is prevalent in HF patients. Inconsistent evidences exist about the impact of rural health disparities on HF patients' readmissions. The purpose of this explorative study was to examine the characteristics of hospitalized HF patients and factors related to readmissions in 2009. The results showed all-cause readmission rates were 13.6%, 23.6%, and 31.6% at 30-, 90- and 180-days respectively. The factors related readmissions included age, income, discharge/transfer status from index hospitalization, and comorbidity. Findings from this analysis suggested additional studies using multiple data sources are needed to have a comprehensive understanding of risk factors related HF patients' healthcare utilization.

Continuous-Time Semi-Markov Models in Health Economic Decision Making

Continuous-time state transition models may end up having large unwieldy structures when trying to represent all relevant stages of clinical disease processes by means of a standard Markov model. In such situations, a more parsimonious, and therefore easier-to-grasp, model of a patient’s disease progression can often be obtained by assuming that the future state transitions do not depend only on the present state (Markov assumption) but also on the past through time since entry in the present state. Despite that these so-called semi-Markov models are still relatively straightforward to specify and implement, they are not yet routinely applied in health economic evaluation to assess the cost-effectiveness of alternative interventions. To facilitate a better understanding of this type of model among applied health economic analysts, the first part of this article provides a detailed discussion of what the semi-Markov model entails and how such models can be specified in an intuitive way by adopting an approach called vertical modeling. In the second part of the article, we use this approach to construct a semi-Markov model for assessing the long-term cost-effectiveness of 3 disease management programs for heart failure. Compared with a standard Markov model with the same disease states, our proposed semi-Markov model fitted the observed data much better. When subsequently extrapolating beyond the clinical trial period, these relatively large differences in goodness-of-fit translated into almost a doubling in mean total cost and a 60-d decrease in mean survival time when using the Markov model instead of the semi-Markov model. For the disease process considered in our case study, the semi-Markov model thus provided a sensible balance between model parsimoniousness and computational complexity.