Heart Failure in Low-Income and Middle-Income Countries: Rising Burden, Diverse Etiology, and High Mortality

Feasibility of Cardiac Rehabilitation Models in Kenya

Background:

Heart failure (HF), is a leading cause of cardiovascular morbidity and mortality in Sub-Saharan Africa. Cardiac rehabilitation (CR) is known to improve functional capacity and reduce morbidity associated with HF. Although CR is a low-cost intervention, global access and adherence rates to CR remain poor. In regions such as Western Kenya, CR programs do not exist. We sought to establish the feasibility CR for HF in this region by testing adherence to institution and home-based models of CR.

Methods:

One hundred participants with New York Heart Association (NYHA) class II and III HF symptoms were prospectively enrolled from a tertiary health facility in Western Kenya. Participants were non-randomly assigned to participate in one of two CR models based on their preference. Institution based cardiac rehabilitation (IBCR) comprised 36 facility-based exercise sessions over a period of 12 weeks. Home based cardiac rehabilitation (HBCR) comprised weekly pedometer guided exercise targets over a period of 12 weeks. An observational arm (OA) receiving usual care was also enrolled. The primary endpoint of CR feasibility was assessed based on study participants to adherence to at least 25% of exercise sessions. Secondary outcomes of change in NYHA symptom class, and six-minute walk time distance (6MWTD) were also evaluated. Data were summarized and analyzed as means (SD) and frequencies. Paired t-tests, Chi Square, Fisher’s, and ANOVA tests were used for comparisons.

Findings:

Mean protocol adherence was greater than 25% in both CR models; 46% ± 18 and 29% ± 11 (P < 0.05) among IBCR and HBCR participants respectively. Improvements by at least one NYHA class were observed among 71%, 41%, and 54%, of IBCR, HBCR and OA participants respectively. 6MWTD increased significantly by a mean of 31 ± 65 m, 40 ± 55 m and 38 ± 71 m in the IBCR, HBCR and OA respectively (P < 0.05).

Conclusions:

IBCR and HBCR, are feasible rehabilitation models for HF in Western Kenya. Whereas improvement in functional capacity was observed, effectiveness of CR in this population remains unknown. Future randomized studies evaluating effect size, long term efficacy, and safety of cardiac rehabilitation in low resource settings such as Kenya are recommended.

Birth weight and young adult body mass index for predicting the risk of developing adult heart failure in men

AIMS

Hospitalizations for heart failure among young adults and middle-aged individuals have increased. The aims of the present study were to evaluate the association between birth weight and risk of adult heart failure and the importance of change from low birth weight to overweight/obesity at young adulthood.

METHODS AND RESULTS

We used the population-based body mass index (BMI) Epidemiology Study cohort Gothenburg (n = 35 659) with birth weight and young adult BMI (20 years) available from child healthcare records, school health records, and military conscription register for men born 1945-1961. The cohort includes all children who finished school, which was mandatory, in Gothenburg, Sweden. Information on heart failure diagnosis was retrieved from the National Patient Register and the Cause of Death Register (n = 415). In cox regression analyses, there was an inverse association between birth weight and risk of heart failure [hazard ratio (HR) 0.83 per standard deviation (SD), 95% confidence interval (CI) 0.76-0.90], and a direct association for young adult BMI (HR 1.48 per SD, 95% CI 1.36-1.61). Of note, individuals with birth weight in the lowest tertile, who were overweight/obese in young adulthood had a five-fold risk of heart failure (HR 4.95, 95% CI 3.36-7.31) compared with individuals in the middle birth weight tertile who were normal weight at 20 years.

CONCLUSIONS

Birth weight was inversely associated with the risk of hospitalization due to heart failure. The combination of low birth weight and overweight/obesity in young adulthood results in excess risk of heart failure beyond that of low birth weight or young adult overweight/obesity separately. These findings indicate the need of a life course perspective in heart failure prevention and risk assessment.

Income level and outcomes in patients with heart failure with universal health coverage

Objective

We aimed to investigate the influence of income level on guideline-directed medical therapy (GDMT) prescription rates and prognosis of patients with heart failure (HF) following implementation of a nationwide health insurance programme.

Methods

A total of 633 098 hospitalised patients with HF from 1996 to 2013 were identified from Taiwan National Health Insurance Research Database. Participants were classified into low-income, median-income and high-income groups. GDMT utilisation, in-hospital mortality and postdischarge HF readmission, and mortality rates were compared.

Results

The low-income group had a higher comorbidity burden and was less likely to receive GDMT than the other two groups. The in-hospital mortality rate in the low-income group (5.07%) was higher than in the median-income (2.47%) and high-income (2.51%) groups. Compared with the high-income group, the low-income group had a significantly higher risk of postdischarge HF readmission (adjusted HR (aHR): 1.29, 95% CI 1.27 to 1.31), all-cause mortality (aHR: 1.98, 95% CI 1.95 to 2.02) and composite HF readmission/all-cause mortality (aHR: 1.54, 95% CI 1.52 to 1.56). These results were generally consistent among the population after propensity matching (low vs high: HR=2.08 for mortality and 1.36 for HF readmission; median vs high: HR=1.23 for mortality and 1.12 for HF readmission; all p<0.001) and after inverse probability of treatment weighting (low-income vs high-income group: HR: 2.19 for mortality and 1.16 for HF readmission; median-income vs high-income group: HR: 1.53 for mortality and 1.09 for HF readmission; all p<0.001). Lower utilisation of GDMT and poorer prognosis in lower-income hospitalised patients with HF appeared to mitigate over time.

Conclusions

Low-income patients with HF had nearly a twofold increase in the risk of in-hospital mortality and postdischarge events compared with the high-income group, partly due to lower GDMT utilisation. The differences between postdischarge HF outcomes among various income groups appeared to mitigate over time following the implementation of nationwide universal health coverage.

Artificial Intelligence (AI) and Cardiovascular Diseases: An Unexpected Alliance

Cardiovascular disease (CVD), despite the significant advances in the diagnosis and treatments, still represents the leading cause of morbidity and mortality worldwide. In order to improve and optimize CVD outcomes, artificial intelligence techniques have the potential to radically change the way we practice cardiology, especially in imaging, offering us novel tools to interpret data and make clinical decisions. AI techniques such as machine learning and deep learning can also improve medical knowledge due to the increase of the volume and complexity of the data, unlocking clinically relevant information. Likewise, the use of emerging communication and information technologies is becoming pivotal to create a pervasive healthcare service through which elderly and chronic disease patients can receive medical care at their home, reducing hospitalizations and improving quality of life. The aim of this review is to describe the contemporary state of artificial intelligence and digital health applied to cardiovascular medicine as well as to provide physicians with their potential not only in cardiac imaging but most of all in clinical practice.