Journal of Vascular Medicine & Surgery

Burden of Disease: Heart Failure in an Emerging Country

Clímaco Pérez Molina^1,2,3*, Carlos Castañeda Orjuela⁴, Pedro Valbuena Hernandez⁵, Rafael I Perez Arias⁶, María A Perez Arias⁷ and Ana María Arias Copete^{8 1}Department of Cardiology, Clinic of the Universidad de la Sabana, Bogotá, Colombia
²Department of Cardiology and Electrophysiology Service, Clínica Colombia de Sanitas, Bogotá, Colombia
³Department of Cardiology, Avidanti Clinic, Ibagué, Colombia
⁴Department of Cardiology, National Health Observatory, Bogotá, Colombia
⁵Department of Cardiology, Center for Economic Research Universidad del Bosque, Bogotá, Colombia
⁶Department of Cardiology, Medical student del Rosario University, Bogotá, Colombia
⁷Department of Cardiology, Medical student de la Sabana University, Bogotá, Colombia
⁸Department of Cardiology, Nogales Clinic, Bogotá, Colombia
^*Correspondence: Clímaco Pérez Molina, Department of Cardiology, Clinic of the Universidad de la Sabana, Bogotá, Colombia, Email:

Received: 18-Jul-2023, Manuscript No. JVMS-23-22226; Editor assigned: 21-Jul-2023, Pre QC No. JVMS-23-22226 (PQ); Reviewed: 11-Aug-2023, QC No. JVMS-23-22226; Revised: 18-Aug-2023, Manuscript No. JVMS-23-22226 (R); Published: 25-Aug-2023, DOI: 10.35248/2329-6925.23.11.533

Introduction

Heart failure (HF) is an important and growing medical problem with significant economic impacts for the health system, with high prevalence rates (around 2%) and incidence worldwide [1,2]. HF especially affects patients 65 years of age or older, accounting for 80% of hospitalizations and 90% of related deaths [3]. Being able to reach in countries like the United States, in people older than 75 years, up to 10% [4,5]. This increase in prevalence is related to the aging of the population (secondary to a longer life expectancy and a decrease in the birth rate in industrialized countries) and to the comorbidities that this brings, such as the increase in cases of high blood pressure, diabetes, etc. [6,7].

This increase in the prevalence in older adults, for the period 2000-2020, has constituted an enormous economic burden for the health systems of all countries, with an estimated global annual expenditure of US$ 108 billion, with $65 billion attributed to direct costs and $43 billion to indirect costs [8,9]. Especially for industrialized countries, for example, in Europe and the USA between 1% and 2% of the annual health budget is spent on HF [10]. The USA and Europe contribute with 28.4% and 6.83%, respectively, of the total world expenditure for this cause [9].

At the same time, HF has been defined as a pathophysiological state in which an abnormality in the function of the heart is responsible for its inability to pump blood at an adequate rate to meet the needs of the metabolizing tissues [11,12]. Currently, the diagnosis of HF is made based on the triad: clinical signs and symptoms, BNP levels, and echocardiographic findings [13]. Although advances in medical therapy, device assistance, and surgery have significantly improved HF outcomes, the implications remain dramatic. In a UK cohort study, age-adjusted all-cause mortality rates for the first year of diagnosis were estimated to be 23.0 (95% CI: 22.0-24.1) per 100 person-years between 2012-2015 [2,14].

On the other hand, decompensation and rehospitalizations of this disease can occur, up to 66% of cases, in the first year of diagnosis and up to 40% from the second year onwards [15]. Given its syndromic characteristics and the fact that it is not a definitive cause, but a potential cause of death, it has become difficult to conduct adequate studies of the burden of disease. The mortality rate of patients with HF is high, as shown in the Meta‐Analysis Global Group in Chronic (MAGGIC) meta-analysis that included individual data from 39,372 patients with 40.2% deceased during a median follow-up of 2.5 years, a recently published study showed that readmission rates at 30 days for HF are higher than for pneumonia or acute myocardial disease, infarction [9,16]. A first approach in this sense in Latin America was the systematic review and meta-analysis of Ciapponi, et al., conducted between January 1994 and June 2014, in 143 retrieved references. Most of the baseline studies were conducted in South America (92%), in Brazil (64%). The mean age was 60 ± 9 years and the mean ejection fraction was 36 ± 9%. The incidence of 199/100,000 person-years; prevalence, 1% (95% Confidence Interval (95% CI), 0.1-2.7%); rehospitalization rates, 33%, 28%, 31%, and 35% at 3, 6, 12, and 24-60 months of follow-up, respectively; and median hospital stay, 7.0 days. The one-year mortality rate was 24.5% (95% CI, 19.4- 30.0%). In-hospital mortality was 11.7% (95% CI, 10.4-13.0%), and the latter was increased in patients with reduced ejection fraction, ischemic heart disease, and Chagas disease.

For all of the above, it is the responsibility of public policy managers in public health to produce research that moves the frontier of knowledge, to generate solutions or policies that help mitigate the health and economic burden generated by HF. Based on this, the objective of this study is to calculate, based on the available information, the estimate of the global burden of disease due to HF in Colombia.

Materials and Methods

In order to have a synthetic indicator that allows decision-making and the orientation of investment in health, the Global Burden of Disease (GBD) was calculated for HF. This was clinically diagnosed using structured criteria such as the Framingham Criteria and those of the European Society of Cardiology [13,14,16]. For this, it was necessary to calculate frequency measures such as incidence, prevalence, and mortality and, on the other hand, the assessment of their fatal consequences (loss of years of life). An analytical model was then elaborated from the data obtained from the different sources, to determine the prevalence and incidence, the SISPRO records in Colombia ( Comprehensive Social Protection Information System) were explored, based on the related codes in the International Statistical Classification of Diseases and Related Problems with health, version 10 (ICD-10), for HF and its causes (Table 1) [17,18].

Table 1: ICD-10 code of main causes of HF.

Sources

SISPRO (Integrated Social Protection Information System) is a health information center that, since 2013, has been registering hospital morbidity events and medications in Colombia. It is made up of databases and information systems. Sector information on supply and demand for health services, quality of services, insurance, financing, social promotion. For its part, the GBD 2020, conducted by the Institute of Health Metrics and Evaluation (IHME), is the most complete and systematic effort to date, to estimate the burden of diseases, injuries, and risk factors worldwide [19,20]. To assess mortality, the vital statistics records of the National Administrative Department of Statistics of Colombia (DANE) were consulted, for the codes related to mortality for HF and its causes, from the ICD-10, (data corrected by age groups and sex, according to the magnitude of the estimated underreporting and the misclassification of the basic cause of death) [17,18,21,22]. The population estimates of the last census in Colombia in 2018 and intercensal projections and the GBD 2020 were also considered [19-22]. Finally, specific contributions from the scientific literature on the subject under study, at a regional and global level, were also used. Incidences were expressed as incidence density using the number of cases/100,000 person-years (Figures 1 and 2) [23].

Figure 1: Result of HF data modeling at the population level by DISMOD. Note: Incidence (i), Prevalence (i), Mortality (i).

Figure 2: Result of HF data modeling at the population level by DISMOD. Note: () Incidence (i), () Prevalence (i), () Mortality (i), () Incidence (o), () Prevalence (o), () Remission (o), () Case fatality (o), () Duration (o), () Mortality (o), () RR mortality (o).

Process

The annual risk of death from HF was calculated as the ratio between the number of deaths for each cause taken from DANE, for the period 2015-2021, and the number of inhabitants for Colombia according to the 2018 population census [21]. Case fatality was calculated as the ratio between the specific number of deaths from HF and the total number of morbid cases discharged from hospital in Colombia for the study period. The annual risk of suffering a fatal HF event was calculated as the ratio between the risk of having a fatal HF event and its lethality. The number of non-fatal events due to HF was calculated as the difference between registered fatal events and the estimated total number of events (fatal and nonfatal). From the data obtained from these sources, the necessary epidemiological indicators were identified: Incidence, prevalence, case fatality rate, general mortality rates, severity, and disability, for HF and its risk of sudden death. To reconcile the origin of the data obtained from the sources, and in order to validate the internal consistency, the statistical program Dismod II© developed by the WHO was used; tool that allowed modeling HF data at the population level [24]. The use of this software is common in burden of disease studies. Finally, in the objective of quantifying the loss of health, which occurs as a consequence of premature cardiovascular deaths. The degree of disability and Disability-Adjusted Life Years (DALYs) were measured [25,26].

Analysis phase

Years of Life Lost (YLL) due to premature death were calculated by multiplying the number of deaths at each age by life expectancy in years. It was used for the study as standard life expectancy at age 80 years for men and 82.5 years for women, from international life tables [26]. For Years of Life Lost Due to Disability (YLD), the severity or weight of disability, which is calculated for each disabling sequela (assessed between 0 without disability, and 1 death, for cardiovascular disease and HF, divided according to severity into four levels: controlled, medically managed, mild, moderate, and severe HF [27]. Each severity level of HF was assigned a disability weight, which represents the magnitude of health loss associated with the severity level [27]. The descriptions and weights of disability for different levels of severity of HF, multiplied by the duration and number of incident cases of each disease In the end, the sum of PYLL and PYLL determines the DALYs or in English Disability Adjusted Life Years (DALY), particular variant of Quality Adjusted Life Years (QALYs) Unlike QALYs, DALYs are measured by means of scales, which give a severity score between 0 to 1, where 0 represents perfect health and 1 death. it means a year of v lost healthy life. The DALY scale deducts 3% from the value of each year of future life (Rodríguez-García) [26]. These values were validated, with those obtained from the global study of CGE of the WHO [19,20].

Epidemiological simulation model

Then, a matrix-type simulation model was developed, with a kernel programmed in Microsoft Excel^® in which the data was stored, and the central estimation calculations were performed in a deterministic manner. Only data from all persons aged 0 to 100 years were used in the model. For the analysis, the STATA version 14.0 software was used.

Results

Regarding the prevalence of HF, in Colombia in the period from 2013 to 2021, there were 2,892,700 (2,863,967.8-2,921,432.2) events for outpatient consultations, procedures, emergencies (86.1%) and hospitalization (13.9%), (Table 2). Bearing in mind that approximately 53% of these are re-consultations and readmissions (1,533,131) and the deaths for this period, according to the DANE registry, there are 162,881 deaths: for an estimated 1,196,688 (1,183,184-1,210,192) cases. For a current population of 51,807,375 inhabitants, which allows calculating a prevalence of 2.31% (2.28-2.33), and for those over 60 years of age, on an estimated 659,371 patients (12.3%), in a population according to the 2018 Census of 6,372,307 inhabitants, 10.35% (10.24-10.37). For its part, the incidence density for the 2013-2021 period was 298.8 cases/100,000 person-years (Supplementary Figure 1). With a cumulative incidence for the 2015-2021 period of 18.26 cases/10,000 people. Observing an increase in prevalence, over the decades, reaching in those over 60 years, up to 6 times the value for the general population, explained by the fact that at older ages, the presence of this disease is more frequent.

Table 2: SISPRO reported events for CI 2013-2015.

According to data from DANE, in the period 2013-2021, 162,881 people died from HF as a potential cause of death in Colombia. The final causes of death were HF (100%), Ischemic heart diseases (26.5%), Hypertensive diseases (26.2%), Chronic diseases of the lower respiratory tract (23.4%), Cardiopulmonary diseases and Pulmonary circulation diseases (19.7%), All other forms of heart diseases (2.4%) and Acute rheumatic fever and chronic rheumatic heart diseases (1.8%), (Table 3). The mortality rate Annual HF (for the 2012-2021 period) was calculated at 34.93 deaths per 100,000 inhabitants, the average HF lethality for the 2013-2021 period was 13.6%, (in men 7.17% and in women 6.43%). The annual risk of suffering an event due to fatal HF, for this same period, in Colombia, was 0.26% (annual), the number of non-fatal cases due to annual HF, for the period, was 132,965 cases/year and the number of annual non-fatal clinical events (consultation, procedure, emergency and/or hospitalization) occurring due to HF in Colombia was 318,219 events/year.

Table 3: Mortality of patients with HF in Colombia, 2013-2021.

Based on morbidity data from SISPRO, mortality from DANE, and the 2018 population census, years of life lost, years lost due to disability, and DALYs were estimated for the total population with HF, for the period (2013-2021), an average value of 309,771.90 DALYs/year and 597.93 × 100,000 (266.06-604.25), (Table 4).

Table 4: Estimated DALYs for the population with HF in Colombia, 2013-2021.

On the other hand, based on the statistical data of the GBD 2020 for cardiovascular diseases, the indicators of burden of disease, prevalence, incidence, mortality, years lost due to premature death, years lost due to disability and DALY for HF were estimated for the period 2016-2019. For which the records were considered, by causes, as in the study by Bragazzi et al. Ischemic heart disease (26.5%), hypertensive heart disease (26.2%), Chronic obstructive pulmonary disease (23.4%), cardiomyopathies (6.5%), mitral valve (2.7%), alcoholic cardiomyopathy (2 .4%), aortic valve (2.4%), other cardiovascular (2.4%), rheumatic disease (1.8%) and myocarditis (1.8%). Below, they are described per 100,000 (Table 5).

Table 5: Disease burden indicators for HF, data from the GBD 2020, period 2016-2019.

Discussion

In the present study, we have evaluated the global burden of HF from 2013 to 2021, making comparisons between different sources, by age groups and sex. The results suggest that the global burden of HF in Colombia is significantly high, the number of cases is 1 in every 50 inhabitants in general, with a growing increase in prevalence by age. Aging and population growth explain the absolute increase in the number of HF cases, the latter driven by the increase in risk factors such as hypertension, diabetes mellitus, obesity, smoking, unhealthy lifestyles, and Alzheimer's disease [29-31] (Supplementary Table 1).

Ischemic and hypertensive heart disease and COPD are the three main causes of HF, representing in adults and globally, almost three quarters of the prevalence standardized by age. However, in children and adolescents, congenital heart disease, myocarditis, and other cardiomyopathies were the main underlying causes, although overall, the incidence of HF in these age groups is low. Despite this, complications and mortality from pediatric HF remain substantial. Children whose hospitalizations are complicated by HF have a more than 20-fold increased risk of death compared with children without HF [32] (Supplementary Table 2).

From a gender perspective, a similar prevalence rate was observed between men and women in all age groups, while women had a significantly higher number of HF cases than men in age groups ≥ 70 years, due to increased life expectancy. Regarding other risk factors, air pollution is a critical problem, related to Chronic Obstructive Pulmonary Disease (COPD) which was not evaluated in this study, but could be the subject of causal evaluation in other investigations [33-35]. The relationship with alcohol, is described, among cardiomyopathies, since alcohol causes dilatation and HF and in European countries, alcohol contributed to 10.5% of all deaths from cardiovascular diseases [36,37].

These data could be useful to visualize the impact of HF at the population level, inform and lay the foundations for the implementation of policies, to smooth out barriers to access, inequities, and inequalities, based on the local availability of medicines and medical devices, clinical practice patterns, and geographically specific public health strategies for HF management (Supplementary Table 3A).

Recognizing the disease burden of chronic diseases, as is the case of HF, is a key input to measure the impact of the disease on the population, public health intervention must be on the way to creating public policies to address this problem, close the gaps resulting from barriers, inequalities, and inequities, in the most vulnerable individuals. To achieve the ultimate goal, the equitable distribution of economic resources, allocated in the national budgets for health, in such a way that this distribution is as fair as possible (Supplementary Table 3B).

Conclusion

HF is a public health problem in Colombia due to its high burden of disease, which is ratified in this study, finding in its findings, 1-prevalence of 2%, 1 of every 50 inhabitants, 2-high incidence, 3-mortality, at least one third of those who die from ischemic cardiomyopathy, 4-number of years lost per year due to premature death 173,371.75 (334.65 years × 100,000 inhabitants), 5-years with annual disability of 136,400.16 years (263.28 years × 100,000 inhabitants) and 5-number of Disability Adjusted Life Years of 309,771.90 (597.93 years × 100,000 inhabitants).

This warns of the need to lay the foundations for the formulation of public policies, which lead to reducing the burden of disease, premature deaths secondary to the health impact of HF, and help health professionals and leaders of the health sector in Colombia, to design and implement promotion and prevention strategies that allow reducing the current and future burden of disease of this condition.

Limitations

Two limitations affect the present investigation. First, data comparability is, at least in part, hampered by different collection methods, sources, and reporting standards. This heterogeneity is enriching, but in the same way it detracts from the robustness of the analysis that emerges from the data, in this sense, the search for homogenization is indicated, in this context the Dismod program is a valuable tool in reconciling the origin of the data obtained from the sources.

Second, direct HF data are scarce, particularly for mortality. This can be attributed to the fact that this disease has been identified in the context of the final outcomes of cardiovascular diseases, unlike other chronic diseases, which are recognized as main or direct causes of death.

The results of this study open the panorama for carrying out economic evaluations on the direct and indirect costs of HF and its therapeutic and diagnostic interventions, as well as comparative studies on the burden of disease for different zones or regions, as well as evaluation studies and/or formulation of public policies, which allow to impact access barriers, inequalities and inequities, in the care and provision of services for the care of people suffering from this disease.

Declarations

Thanks to the governmental and international institutions and entities that allowed the development of this study, based on the national patient registry, to Adriana Fajardo, for her contributions in the transcription.

Author contributions

CP designed the study, interpreted the results, and edited the final draft, PV and CC contributed to text editing, RP, MAP, and AA assisted in data and information collection, All authors read, contributed to, and approved the final manuscript.

Funding

This work was conducted with the main author's own resources, hence its strength, as it does not depend on pressure or bias resulting from support.

Availability of data and materials

The datasets analyzed in this study are available for the corresponding. Institutions, Authors, upon reasonable request.

Ethical approval

This study only involved parts of databases, the necessary ethical procedures were followed, for this purpose. Ethical approval was obtained from the ethical review committee of Universidad del Bosque, and from the respective health care institutions, for studies involving medical records.

Consent to publication

Does not apply.

Conflict of interests

None declare.

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