Effect of a transitional care model following hospitalization for heart failure: 3-year outcomes of the Patient-Centered Care Transitions in Heart Failure (PACT-HF) randomized controlled trial.

AIMS: Patients are at high risk of death or readmission following hospitalization for heart failure (HF). We tested the effect of a transitional care model that included month-long nurse-led home visits and long-term heart function clinic visits - with services titrated to estimated risk of clinical events - on 3-year outcomes following hospitalization. METHODS AND RESULTS: In a pragmatic, stepped-wedge cluster randomized trial, 10 hospitals were randomized to the intervention versus usual care. The primary outcome was a composite of all-cause death, readmission, or emergency department (ED) visit. Secondary outcomes included components of the primary composite outcomes, HF readmissions and healthcare resource utilization. There were 2494 patients (50.4% female) with mean age of 77.7 years. The primary outcome was reached in 1040 (94.2%) patients in the intervention and 1314 (94.5%) in the usual care group at 3 years. The intervention did not reduce the risk of the primary composite outcome (hazard ratio [HR] 0.92, 95% confidence interval [CI] 0.81-1.05) nor the component outcomes overall, although numerically reduced the risk of ED visits in women but not men (HR 0.79, 95% CI 0.63-1.00 vs. HR 0.98, 95% CI 0.80-1.19; sex-treatment interaction p = 0.23). The uptake of guideline-directed medical therapy was no different with the intervention than with usual care, with the exception of sacubitril/valsartan, which increased with the intervention (3.3% vs 1.5%; relative risk 6.2, 95% CI 1.92-20.06). CONCLUSIONS: More than 9 of 10 patients hospitalized for HF experienced all-cause death, readmission, or ED visit at 3 years. A transitional care model with services titrated to risk did not improve the composite of these endpoints, likely because there were no major differences in uptake of medical therapies between the groups. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov Identifier NCT02112227.

Bridging Treatment Implementation Gaps in Patients With Heart Failure: JACC Focus Seminar 2/3.

Heart failure (HF) is a leading cause of death and disability in older adults. Despite decades of high-quality evidence to support their use, guideline-directed medical therapies (GDMTs) that reduce death and disease burden in HF have been suboptimally implemented. Approaches to closing care gaps have focused largely on strategies proven to be ineffective, whilst effective interventions shown to improve GDMT uptake have not been instituted. This review synthesizes implementation interventions that increase the uptake of GDMT, discusses barriers and facilitators of implementation, summarizes conceptual frameworks in implementation science that could improve knowledge uptake, and offers suggestions for trial design that could better facilitate end-of-trial implementation. We propose an evidence-to-care conceptual model that could foster the simultaneous generation of evidence and long-term implementation. By adopting principles of implementation science, policymakers, researchers, and clinicians can help reduce the burden of HF on patients and health care systems worldwide.

Pharmaco-disparities in heart failure: a survey of the affordability of guideline recommended therapy in 10 countries.

AIMS: Heart failure with reduced ejection fraction (HFrEF) is treatable but guideline-directed medical therapy (GDMT) may not be affordable or accessible to people living with the disease. METHODS AND RESULTS: In this cross-sectional survey, we investigated the price, affordability, and accessibility of four pivotal classes of HFrEF GDMT: angiotensin-converting enzyme inhibitors (ACEi), angiotensin receptor blockers (ARB) or angiotensin-neprilysin inhibitors (ARNI); beta-blockers; mineralocorticoid receptor antagonists (MRA); and sodium glucose co-transporter 2 inhibitors (SGLT2i). We sampled online or community pharmacies in 10 countries across a range of World Bank income groups, assessing mean 30 day retail prescription prices, affordability relative to gross national income per capita per month, and accessibility. We reported median price ratios relative to the International Reference Standard. We performed a literature review to evaluate accessibility to GDMT classes through publicly funded drug programmes in each country. HFrEF GDMT prices, both absolute and relative to the international reference, were highest in the United States and lowest in Pakistan and Bangladesh. The most expensive drug was the ARNI, sacubitril/valsartan, with a mean (standard deviation, SD) 30 day price ranging from $11.06 (0.81) in Pakistan to $611.50 (3.54) in United States. The least expensive drug was the MRA, spironolactone, with a mean (SD) 30 day price ranging from $0.18 (0.00) in Pakistan to $12.32 (0.00) in England. Affordability (SD) of quadruple therapy-ARNI, beta-blockers, MRA, and SGLT2i-was best in high-income and worst in low-income countries, ranging from 1.49 (0.00)% of gross national income per capita per month in England to 232.47 (31.47)% in Uganda. Publicly funded drug programmes offset costs for eligible patients, but ARNI and SGLT2i were inaccessible through these programmes in low- and middle-income countries. Price, affordability, and access were substantially improved in all countries by substituting ARNI for ACEi/ARB. CONCLUSIONS: There was marked variation between countries in the retail price of HFrEF GDMT. Despite higher prices in high-income countries, GDMT was more accessible and affordable than in low- and middle-income countries. Publicly funded drug programmes in lower income countries increased affordability but limited access to newer HFrEF GDMT classes. Pharmaco-disparities must be addressed to improve HFrEF outcomes globally.

Anderson-Fabry disease cardiomyopathy: an update on epidemiology, diagnostic approach, management and monitoring strategies.

Anderson-Fabry disease (AFD) is an X-linked lysosomal storage disorder caused by deficient activity of the enzyme alpha-galactosidase. While AFD is recognized as a progressive multi-system disorder, infiltrative cardiomyopathy causing a number of cardiovascular manifestations is recognized as an important complication of this disease. AFD affects both men and women, although the clinical presentation typically varies by sex, with men presenting at a younger age with more neurologic and renal phenotype and women developing a later onset variant with more cardiovascular manifestations. AFD is an important cause of increased myocardial wall thickness, and advances in imaging, in particular cardiac magnetic resonance imaging and T1 mapping techniques, have improved the ability to identify this disease non-invasively. Diagnosis is confirmed by the presence of low alpha-galactosidase activity and identification of a mutation in the GLA gene. Enzyme replacement therapy remains the mainstay of disease modifying therapy, with two formulations currently approved. In addition, newer treatments such as oral chaperone therapy are now available for select patients, with a number of other investigational therapies in development. The availability of these therapies has significantly improved outcomes for AFD patients. Improved survival and the availability of multiple agents has presented new clinical dilemmas regarding disease monitoring and surveillance using clinical, imaging and laboratory biomarkers, in addition to improved approaches to managing cardiovascular risk factors and AFD complications. This review will provide an update on clinical recognition and diagnostic approaches including differentiation from other causes of increased ventricular wall thickness, in addition to modern strategies for management and follow-up.

Trials using composite outcomes neglect the presence of competing risks: a methodological survey of cardiovascular studies.

OBJECTIVE: To determine how frequently competing risks were accounted for in recently published cardiovascular disease (CVD) trials with composite end points. STUDY DESIGN AND SETTING: We conducted a methodological survey of CVD trials that used composite end points and published from January 1 to September 27, 2021. The following databases were searched: PubMed, Medline, Embase, CINAHL, and Web of Science. Eligible studies were categorized according to whether they mentioned a competing risk analysis plan. If yes, whether a competing risk analysis was proposed as the primary or sensitivity analysis. RESULTS: Among the 136 included studies, only 14 (10.3%) conducted a competing risk analysis and reported the corresponding results. Seven (50%) of them conducted a competing risk analysis as their primary analysis, whereas the other seven (50%) as a sensitivity analysis to assess the robustness of their findings. The most commonly used competing risk analysis methods were the subdistribution hazard model (nine studies), followed by the cause-specific hazard model (four studies) and restricted mean time lost method (one study). None of the studies accounted for competing risks in their sample size calculations. CONCLUSION: Our findings underscore the pressing need for and importance of applying appropriate competing risk analysis in this field to disseminate clinically meaningful and unbiased results.

Applications of artificial intelligence and machine learning in heart failure.

Machine learning (ML) is a sub-field of artificial intelligence that uses computer algorithms to extract patterns from raw data, acquire knowledge without human input, and apply this knowledge for various tasks. Traditional statistical methods that classify or regress data have limited capacity to handle large datasets that have a low signal-to-noise ratio. In contrast to traditional models, ML relies on fewer assumptions, can handle larger and more complex datasets, and does not require predictors or interactions to be pre-specified, allowing for novel relationships to be detected. In this review, we discuss the rationale for the use and applications of ML in heart failure, including disease classification, early diagnosis, early detection of decompensation, risk stratification, optimal titration of medical therapy, effective patient selection for devices, and clinical trial recruitment. We discuss how ML can be used to expedite implementation and close healthcare gaps in learning healthcare systems. We review the limitations of ML, including opaque logic and unreliable model performance in the setting of data errors or data shift. Whilst ML has great potential to improve clinical care and research in HF, the applications must be externally validated in prospective studies for broad uptake to occur.

Temporal Trends and Factors Associated With the Inclusion of Patient-Reported Outcomes in Heart Failure Randomized Controlled Trials: A Systematic Review.

Background Patient-reported outcomes (PROs) are important measures of treatment response in heart failure. We assessed temporal trends in and factors associated with inclusion of PROs in heart failure randomized controlled trials (RCTs). Methods and Results We searched MEDLINE, Embase, and CINAHL for studies published between January 2000 and July 2020 in journals with an impact factor ≥10. We assessed temporal trends using the Jonckheere-Terpstra test and conducted multivariable logistic regression to explore trial characteristics associated with PRO inclusion. We assessed the quality of PRO reporting using the Consolidated Standards of Reporting Trials (CONSORT) PRO extension. Of 417 RCTs included, PROs were reported in 226 (54.2%; 95% CI, 49.3%-59.1%), with increased reporting between 2000 and 2020 (P<0.001). The odds of PRO inclusion were greater in RCTs that were published in recent years (adjusted odds ratio [aOR] per year, 1.08; 95% CI, 1.04-1.12; P<0.001), multicenter (aOR, 1.89; 95% CI, 1.03-3.46; P=0.040), medium-sized (aOR, 2.35; 95% CI, 1.26-4.40; P=0.008), coordinated in Central and South America (aOR, 5.93; 95% CI, 1.14-30.97; P=0.035), and tested health service (aOR, 3.12; 95% CI, 1.49-6.55; P=0.003), device/surgical (aOR, 6.66; 95% CI, 3.15-14.05; P<0.001), or exercise (aOR, 4.66; 95% CI, 1.81-12.00; P=0.001) interventions. RCTs reported a median of 4 (interquartile interval , 3-6) of a possible of 11 CONSORT PRO items. Conclusions Just over half of all heart failure RCTs published in high impact factor journals between 2000 and 2020 included PROs, with increased inclusion of PROs over time. Trials that were large, tested pharmaceutical interventions, and coordinated in North America / Europe had lower adjusted odds of reporting PROs relative to other trials. The quality of PRO reporting was modest.

Systematic review of academic bullying in medical settings: dynamics and consequences.

PURPOSE: To characterise the dynamics and consequences of bullying in academic medical settings, report factors that promote academic bullying and describe potential interventions. DESIGN: Systematic review. DATA SOURCES: We searched EMBASE and PsycINFO for articles published between 1 January 1999 and 7 February 2021. STUDY SELECTION: We included studies conducted in academic medical settings in which victims were consultants or trainees. Studies had to describe bullying behaviours; the perpetrators or victims; barriers or facilitators; impact or interventions. Data were assessed independently by two reviewers. RESULTS: We included 68 studies representing 82 349 respondents. Studies described academic bullying as the abuse of authority that impeded the education or career of the victim through punishing behaviours that included overwork, destabilisation and isolation in academic settings. Among 35 779 individuals who responded about bullying patterns in 28 studies, the most commonly described (38.2% respondents) was overwork. Among 24 894 individuals in 33 studies who reported the impact, the most common was psychological distress (39.1% respondents). Consultants were the most common bullies identified (53.6% of 15 868 respondents in 31 studies). Among demographic groups, men were identified as the most common perpetrators (67.2% of 4722 respondents in 5 studies) and women the most common victims (56.2% of 15 246 respondents in 27 studies). Only a minority of victims (28.9% of 9410 victims in 25 studies) reported the bullying, and most (57.5%) did not perceive a positive outcome. Facilitators of bullying included lack of enforcement of institutional policies (reported in 13 studies), hierarchical power structures (7 studies) and normalisation of bullying (10 studies). Studies testing the effectiveness of anti-bullying interventions had a high risk of bias. CONCLUSIONS: Academic bullying commonly involved overwork, had a negative impact on well-being and was not typically reported. Perpetrators were most commonly consultants and men across career stages, and victims were commonly women. Methodologically robust trials of anti-bullying interventions are needed. LIMITATIONS: Most studies (40 of 68) had at least a moderate risk of bias. All interventions were tested in uncontrolled before-after studies.

Derivation and validation of a two-variable index to predict 30-day outcomes following heart failure hospitalization.

BACKGROUND: The LACE index-length of stay (L), acuity (A), Charlson co-morbidities (C), and emergent visits (E)-predicts 30-day outcomes following heart failure (HF) hospitalization but is complex to score. A simpler LE index (length of stay and emergent visits) could offer a practical advantage in point-of-care risk prediction. METHODS AND RESULTS: This was a sub-study of the patient-centred care transitions in HF (PACT-HF) multicentre trial. The derivation cohort comprised patients hospitalized for HF, enrolled in the trial, and followed prospectively. External validation was performed retrospectively in a cohort of patients hospitalized for HF. We used log-binomial regression models with LACE or LE as the predictor and either 30-day composite all-cause readmission or death or 30-day all-cause readmission as the outcomes, adjusting only for post-discharge services. There were 1985 patients (mean [SD] age 78.1 [12.1] years) in the derivation cohort and 378 (mean [SD] age 73.1 [13.2] years) in the validation cohort. Increments in the LACE and LE indices were associated with 17% (RR 1.17; 95% CI 1.12, 1.21; C-statistic 0.64) and 21% (RR 1.21; 95% CI 1.15, 1.26; C-statistic 0.63) increases, respectively, in 30-day composite all-cause readmission or death; and 16% (RR 1.16; 95% CI 1.11, 1.20; C-statistic 0.64) and 18% (RR 1.18; 95% CI 1.13, 1.24; C-statistic 0.62) increases, respectively, in 30-day all-cause readmission. The LE index provided better risk discrimination for the 30-day outcomes than did the LACE index in the external validation cohort. CONCLUSIONS: The LE index predicts 30-day outcomes following HF hospitalization with similar or better performance than the more complex LACE index.

The LENT index predicts 30 day outcomes following hospitalization for heart failure.

AIMS: The LE index (Length of hospitalization plus number of Emergent visits ≤6 months) predicts 30 day all-cause readmission or death following hospitalization for heart failure (HF). We combined N-terminal pro-B type natriuretic peptide (NT-proBNP) levels with the LE index to derive and validate the LENT index for risk prediction at the point of care on the day of hospital discharge. METHODS AND RESULTS: In this prospective cohort sub-study of the Patient-centred Care Transitions in HF clinical trial, we used log-binomial regression models with LE index and either admission or discharge NT-proBNP as the predictors and 30 day composite all-cause readmission or death as the primary outcome. No other variables were added to the model. We used regression coefficients to derive the LENT index and bootstrapping analysis for internal validation. There were 772 patients (mean [SD] age 77.0 [12.4] years, 49.9% female). Each increment in the LE index was associated with a 25% increased risk of the primary outcome (RR 1.25, 95% CI 1.16-1.35; C-statistic 0.63). Adjusted for the LE index, every 10-fold increase in admission and discharge NT-proBNP was associated with a 48% (RR 1.48; 95% CI 1.10, 1.99; C-statistic 0.64; net reclassification index [NRI] 0.19) and 56% (RR 1.56; 95% CI 1.08, 2.25; C-statistic 0.64; NRI 0.21) increased risk of the primary outcome, respectively. The predicted probability of the primary outcome increased to a similar extent with incremental LENT, regardless of whether admission or discharge NT-proBNP level was used. CONCLUSIONS: The point-of-care LENT index predicts 30 day composite all-cause readmission or death among patients hospitalized with HF, with improved risk reclassification compared with the LE index. The performance of this simple, 3-variable index - without adjustment for comorbidities - is comparable to complex risk prediction models in HF.

Vericiguat reduced a composite of CV death or HF hospitalization in patients with HF and reduced LVEF.

SOURCE CITATION: Armstrong PW, Pieske B, Anstrom KJ, et al. Vericiguat in patients with heart failure and reduced ejection fraction. N Engl J Med. 2020;382:1883-93. 32222134.