Journal of Clinical Sciences

ORIGINAL RESEARCH REPORT
Year
: 2021  |  Volume : 18  |  Issue : 3  |  Page : 133--141

Risk factors for new-onset heart failure with reduced or preserved ejection fraction in patients with ischemic heart disease: A cohort study


Senbeta Guteta Abdissa 
 Department of Internal Medicine, Division of Cardiology, School of Medicine, College of Health Sciences, Addis Ababa University, Addis Ababa, Ethiopia

Correspondence Address:
Dr. Senbeta Guteta Abdissa
P. O. Box 28287/1000, Addis Ababa
Ethiopia

Abstract

Background: Risk factors for heart failure (HF) with reduced ejection fraction (HFrEF) or HF with preserved ejection fraction (HFpEF) in Ethiopian and Sub-Saharan African patients with ischemic heart disease (IHD) is not well-known. Methods: This is a cohort study where 228 patients with IHD were recruited and followed retrospectively over 24 months period. Exclusion criteria were known HF at baseline and absence of echocardiography data. From baseline clinical and echocardiographic patient characteristics, risk factors for incident HFpEF and incident HFrEF were analyzed. Results: New-onset HF was diagnosed in 67.1% (153/228) of the patients. Median time to HF diagnosis was 12.02 (3.42–13.31) months in HFrEF and 12.06 (2.66–15.28) months in HFpEF. There was no significant difference between HFrEF and HFpEF in time to incident HF. On univariate regression analysis risk factors for incident total HF were age, diabetes, and left atrium (LA) size. Diabetes, systolic blood pressure (SBP), diastolic blood pressure, LA and diastolic left ventricular dimension (LVD) had significant association with HFrEF. Age, sex, hypertension, SBP, and diastolic LVD were significantly associated with HFpEF. On cox regression analysis diabetes and LA dimension were associated with total HF while diastolic LVD was associated with incident HFpEF and HFrEF. Age, diabetes, and dimension of LA were also associated with HFrEF. Conclusion: These data suggest a major role for age, sex, diabetes, bigger LA size, and diastolic LVD as predictors of HFrEF and HFpEF in patients with IHD. Strategies directed to prevention and treatment of diabetes, dilatation of left ventricle and LA may prevent a considerable proportion of HFrEF or HFpEF.



How to cite this article:
Abdissa SG. Risk factors for new-onset heart failure with reduced or preserved ejection fraction in patients with ischemic heart disease: A cohort study.J Clin Sci 2021;18:133-141


How to cite this URL:
Abdissa SG. Risk factors for new-onset heart failure with reduced or preserved ejection fraction in patients with ischemic heart disease: A cohort study. J Clin Sci [serial online] 2021 [cited 2021 Dec 8 ];18:133-141
Available from: https://www.jcsjournal.org/text.asp?2021/18/3/133/324407


Full Text



 Introduction



Heart failure (HF) is one of the main causes of premature morbidity and mortality despite recent improvements of its treatment.[1],[2] It has a lifetime risk of 20%–46%,[3] and preventive strategies focused on pathogenic mechanisms are necessary. It is a complex clinical syndrome that results from any structural or functional impairment of ventricular filling or ejection of blood that may result from disorders of the pericardium, myocardium, endocardium, heart valves, great vessels, or metabolic abnormalities, but most patients with HF have symptoms due to impaired left ventricular (LV) structure or function.[4]

Preventing new-onset HF is increasingly important and requires knowledge of its risk factors.[5],[6] Several studies have established risk factors for new-onset HF, including higher age, hypertension (HTN), and the presence of ischemic heart disease (IHD).[7],[8] Initially, studies aimed at identifying risk factors were based on an HF diagnosis on signs and symptoms only.[9],[10] Recently, echocardiography is used in the diagnosis and classification of HF based on LV ejection fraction (LVEF). Based on clinical and echocardiographic characteristics, HF is usually categorized as HF with LVEF ≥50% referred to as HF with preserved ejection fraction (HFpEF) and HF with LVEF <50% referred to as HF with reduced ejection fraction (HFrEF).[11]

HFpEF accounts for approximately half of HF in the community,[12] and the lack of therapies that improve the prognosis of this condition reflects an incomplete understanding of its pathogenesis. In addition, data on the incidence of new-onset HFpEF or HFrEF and their risk factors in Ethiopian and Sub-Saharan setting are scarce. Moreover, only limited information is available regarding the risk factors for incident HFpEF and HFrEF.[13],[14],[15],[16],[17]

The aim of this study was to examine the different risk factors of HFpEF and HFrEF in patients with IHD. The hypothesis of this study was that the risk factor profiles of HFpEF, and HFrEF may suggest distinct pathophysiological mechanisms. Using available clinical and echocardiographic baseline characteristics, risk factors for new-onset HFpEF and HFrEF were identified in a cohort of IHD patients without HF at baseline.

 Methods



Study design and clinical setting

This is a retrospective cohort study in Ethiopian patients with IHD that was planned to identify individuals with cardiac dysfunction (as assessed by echocardiography) and increased risk of HF. The study reports the follow-up of the cohort to detect incident HF.

The flow chart for participant recruitment and follow-up is shown in [Figure 1]. In summary, there were a total of 7390 patients in follow-up at the Hospital. Inclusion criteria were diagnosis of IHD in follow-up until the study exit date, development of HF, or death. The exclusion criteria were diagnosis of HF before the date of enrolment, incomplete data, absence of echocardiographic data, and loss to follow up before the study exit date.{Figure 1}

Patients with IHD fulfilling the recruitment criteria were enrolled in the study starting from November 30, 2015. A total of 228 individual (age of 18 years and above) IHD patients who had echocardiography at baseline were included in the cohort and they were followed to measure the outcome. Each study participant was followed up for 24 months or until the diagnosis of HF was made. Patients with IHD or HF were identified based on the treating Physician's final diagnosis that was made based on symptoms suggestive of IHD or HF respectively. The study was approved by the institutional review board of the College and permission to use de-identified personal healthcare information for all included subjects was obtained.

Definition of variables

Patients with preceding IHD were those who had a clinical diagnosis of myocardial infarction (MI), and/or a history of angina or angina-driven coronary revascularization. IHD was defined based on information from patient records where the attending physician (Cardiologist) made the diagnosis. Previous HF was identified if patients had physician documented diagnosis of HF or if they had typical signs and symptoms consistent with HF syndrome and/or used furosemide as part of their treatment. If a patient was diagnosed with HF or used furosemide during the 24 months follow-up, then they were categorized in a group with incident HF. If no HF diagnosis was made during the follow-up period, they were categorized into the group with no incident HF.

Based on echocardiographic LVEF data, patients were categorized into groups depending on the diagnosis of HF and LVEF classification as either HFpEF (LVEF ≥50%) or HFrEF (LVEF <50%).

Outcome measures

The primary outcome of interest was incident HF.

Data collection

Data on baseline characteristics, risk factors, comorbidities, diagnosis, and date of diagnosis of IHD and HF, functional classification of HF based on New York Heart Association, complementary laboratory tests were collected from the medical records by trained medical staff. Resting 12-lead electrocardiographs, transthoracic echocardiography findings, medications, and hospital admission were collected from the patient's medical records.

Statistical analysis

Baseline characteristics by incident HF and ejection fraction were presented as numbers (percentages) for categorical variables. Continuous parametric variables were expressed as means (± standard deviation) or medians (interquartile range [IQR]) depending on their distribution. Comparisons between categorical data were performed with the use of Pearson's Chi-square test while comparisons of continuous data were done with the use of Student's t-test.

Factors predicting the risk of incident HF were explored in a univariate and multivariate logistic and Cox-regression model with incident HF as the outcome (dependent) variable and all covariates described below as predictor (independent) variables. In the multivariate model, all variables associated with the evaluated endpoint at the 0.10 level in the univariate analysis were entered in the model and removed using a backward stepwise likely-hood ratio selection process for the determination of predictors of new-onset HF. For each covariate, hazard ratio (HR), 95% confidence interval (CI), and P value are reported. Covariates included in the multivariable analysis were age, gender, comorbidities including diabetes mellitus, HTN, LVEF, diastolic LV dimension (LVD), and left atrium (LA) dimension.

The cumulative probability of incident HF and time to incident HF was illustrated with Kaplan-Meier time to event curve estimates. Cox regression analysis was used to calculate the HRs for predictors of HF. A two-sided P < 0.05 was considered to indicate statistical significance. Data were analyzed with SPSS software V.23 Statistical Package for the Social Sciences (SPSS) Windows, Version 23 (IBM Corp, Armonk, NY, USA).

 Results



Baseline clinical variables and heart failure diagnosis

Baseline data for participants who developed HF during follow-up and those who did not are shown in [Table 1]. The follow-up duration of the 228 study participants was 24 months. All study participants had echocardiography at baseline. LVEF determination at baseline was performed by echocardiography.{Table 1}

During the follow-up period, new-onset HF was diagnosed in 67.1% (153/228). There were significant differences in HF incidence rate between the age groups, but no difference in incident HF was found between men and women. In comparison to participants who did not develop HF during follow-up, participants who developed HF were older, with a higher prevalence of diabetes, and larger left atrium size. Participants who developed HF also were more likely to be taking beta-blockers, Renin angiotensin system inhibitor, loop diuretic, aldosterone antagonist, digoxin, and antidiabetic medications.

As shown in [Table 2], 57.0% (130/228) of the patients had reduced LVEF at baseline. During the follow-up period, new-onset HF developed in 70.1% (92/130) of patients with reduced LVEF and in 62.2% (61/98) of patients with preserved LVEF. There were differences in baseline variables between participants with preserved LVEF and reduced LVEF. In comparison with participants with reduced LVEF, participants with preserved LVEF were more likely to have higher systolic blood pressure (SBP), higher diastolic blood pressure (DBP), and higher prevalence of HTN and less likely to develop advanced HF symptoms. Patients with preserved LVEF at baseline also had smaller LV size and smaller LA size. They were less likely to have dilated LA and less likely to be taking aldosterone antagonists.{Table 2}

Risk factors for incident heart failure, heart failure with reduced ejection fraction, heart failure with preserved ejection fraction

Baseline variables with incident total HF, HFrEF, and HFpEF on univariate logistic regression analysis are shown in [Table 3], [Table 4], [Table 5]. Predictors for incident total HF on univariate analysis, as shown in [Table 3] were age (crude odds ratio [COR] 1.04 [95% CI 1.01–1.07], P = 0.003), diabetes (COR 1.88 [95% CI 1.01–3.51], P = 0.045) and left atrium size (COR 1.07 [95% CI1.02–1.12], P = 0.006).{Table 3}{Table 4}{Table 5}

As shown in [Table 4], predictors identified for HFrEF were diabetes (COR 1.89 [95% CI 1.02–3.51], P = 0.04), SBP (COR 0.97 [95% CI 0.95–0.99], P = 0.001), DBP (COR 0.95 [95% CI 0.91–0.98], P = 0.002), LA size (COR 1.08 [95% CI 1.03–1.14], P = 0.002) and increasing diastolic LVD (COR 1.13 [95% CI 1.09–1.18], P < 0.0001).

Moreover, risk factors for HFpEF were age (COR 1.03 [95% CI 1.003–1.06], P = 0.03), sex (COR 2.37 [95% CI 1.29–4.37], P = 0.006), HTN (COR 2.40 [95% CI 1.31–4.39], P = 0.005), SBP (COR 1.02 [95% CI 1.01–1.04], P = 0.006) and increasing diastolic LVD (COR 0.89 [95% CI 0.86–0.93], P < 0.0001) [Table 5].

[Table 6] shows Cox regression with multivariable sub-distribution of HRs. From the 153 patients with new onset HF, 60.1% (92/153) where those with HFrEF while 39.9% (61/153) where those with HFpEF. Diabetes (HR 2.07 [95% CI 1.33–3.22], P = 0.001) and left atrium dimension (HR 1.03 [95% CI 1.001–1.065], P = 0.04) were associated with total HF. Age 46–55 (HR 0.4 [95% CI 0.17–0.94], P = 0.036), Age 66 and above (HR 0.36 [95% CI 0.13–0.98], P = 0.047), diabetes (HR 2.80 [95% CI 1.55–5.07], P = 0.001); left atrium dimension (HR 1.07 [95% CI 1.13–1.12], P = 0.002) and increasing diastolic LVD (HR 1.06 [95% CI 1.03–1.09], P < 0.0001) were associated with HFrEF. Diastolic LVD was also associated with HFpEF (HR 0.93 [95% CI 0.90–0.97], P < 0.0001).{Table 6}

As shown in [Figure 2], there was no significant difference between HFrEF and HFpEF in the time to incident HF (HR 1.01 [95% CI 0.78–1.56], P = 0.58). The median time to HF diagnosis after enrollment was 12.02 (IQR 3.39–14.00) months for all 153 patients with HF, 12.02 (3.42–13.31) months for participants who developed HFrEF, and 12.06 (2.66–15.28) months for those who developed HFpEF.{Figure 2}

 Discussion



This study revealed a range of risk factors for incident total HF, HFpEF, and HFrEF in the cohort of patients with IHD. The median time to HF after enrollment was about 12 months. There was no significant difference between HFrEF and HFpEF in the time to incident HF. Risk factors for incident HF in the overall groups of IHD patients were age, sex, diabetes, LA dimension, and diastolic LVD. Increasing diastolic LVD was found to be a risk factor for both incidents HFpEF and incident HFrEF. Age, diabetes, and LA dimension were also found to be risk factors for incident HFrEF.

Older age and diabetes as risk factors for incident total HF in this study are consistent with previous studies findings that reported established risk factors for incident HF. However, female sex as risk factor in this study is not consistent with the study by Yang et al. that reported male gender as an established risk factor. In addition, we found that LA dimension is one of the predictors of incident HF.[18],[19]

This study also showed that risk factors for HFrEF were diabetes, SBP, DBP, bigger LA, and bigger diastolic LVD. Risk factors identified for HFpEF were age, female sex, HTN, SBP, and diastolic LVD. On cox regression analysis diabetes and LA dimension remained to be associated with total HF. Moreover, age, diabetes, bigger LA dimension, and bigger diastolic LVD remained to be significantly associated with HFrEF while diastolic LVD was associated with HFpEF. When compared to patients with reduced LVEF, those with preserved LVEF were more likely to have higher SBP, higher DBP, higher prevalence of HTN, smaller LVD, smaller LA size and were less likely to develop advanced HF symptoms.

Few studies have examined the risk factors for incident HFpEF and HFrEF separately.[13],[14],[15],[16],[17] A pooled analysis of HFpEF (LVEF >45%) and HFrEF (LVEF ≤45%) cohorts found that age, SBP, body mass index (BMI), antihypertensive treatment, diabetes, alcohol use, and previous MI were risk factors for HFpEF; the same risk factors were associated with HFrEF, in addition to the male gender, DBP, heart rate, smoking, previous stroke, LV hypertrophy and left bundle branch block.[17] In contrast to previous studies of risk factors for incident HFpEF and HFrEF, we provide information about LA and LVD[13],[16] as risk factors for HFpEF and HFrEF. The association of age and diabetes with incident HFrEF in this cohort was in agreement with previous studies.[15],[16],[17] Risk factor that was common to both HFrEF and HFpEF was age.

Age 56–65, diabetes, bigger LA, and bigger diastolic LVD were risk factors for HFrEF; this association was maintained in multivariable analysis after adjusting for gender.

Key findings of this study suggested diabetes, size of LA, and size of diastolic LVD play a major role as predictors of total HF, HFpEF, and HFrEF. Previous studies also found LA diameter to be an independent predictor for HF.[20],[21] Atrial stretch leads to neurohormonal activation and secretion of atrial natriuretic peptide, which may have a role in the development of atrial dysrhythmias and HF.[20],[22]

Increased LV internal dimensions were also found to be positively associated with incident HF, similar to previous studies from Framingham investigators and the Cardiovascular Health Study cohort.[21],[23],[24] Increased LV size is an indicator of LV remodeling that eventually leads to HF.

Data from the echocardiographic studies of the Studies of Ventricular Enlargement trial and Valsartan HF Trial demonstrated that baseline end-diastolic LVD and changes over time were independent predictors of HF and other outcomes.[25],[26]

Although we currently have no therapies that improve prognosis in HFpEF, several strategies have been shown to improve diastolic function and may therefore prevent or postpone HFpEF. Blood pressure-lowering therapies prevent HF,[27],[28],[29] and it is likely that this is due in part to the prevention of HFpEF by reducing myocardial fibrosis and LV mass, and improving diastolic function.[30],[31],[32],[33] Vigorous physical activity is associated with reduced HF incidence independently of BMI[34] and caloric restriction improves diastolic function in individuals who are not obese with evidence of diastolic dysfunction and ameliorates the age-associated decline in diastolic function.[35],[36]

Strengths and limitations

The strengths of this study include the diagnosis of HF in a predominantly ambulant setting, the optimal duration of follow-up such that risk factor information was collected well before HF diagnosis was made, and the identification of many risk factors for incident HFpEF and HFrEF. The baseline echocardiographic parameters also provided additional risk factor information.

The limitations of this study included its retrospective cohort design and its intrinsic biases. This study cohort was from the Ethiopian population, and the generalizability of the findings to other geographic regions could not be determined. In addition, the study population was referral-based, and thus, whether the findings can be generalized to nonreferral-based populations is unknown. Despite attempts to capture all incident cases of HF some cases of early HF may have been missed, and cases may also have been missed because of the reliance on retrospective review to pick up HF. Furthermore, outcome ascertainment based on chart review may have underestimated the number of events. However, given the referral of the majority of IHD patients to Black Lion Hospital, it is relatively unlikely that such underestimation would be significant.

 Conclusion



Risk factors for incident total HF, HFpEF, and HFrEF that preceded HF development by many months were identified, and this suggests that the mechanisms of HF pathogenesis were operating years before HF diagnosis. Each risk factor identified is hypothesis generating with respect to pathophysiological mechanisms of HF and potential therapeutic approaches. In particular, the data suggest a major role for age, sex, diabetes, bigger LA size, and diastolic LVD as predictors in HFrEF and HFpEF. Regular determination of LA and LVD at baseline is recommended for directing appropriate treatment. Strategies directed to prevention and treatment of diabetes, dilatation of the left ventricle and left atrium may prevent a considerable proportion of HFrEF or HFpEF in patients with IHD.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.

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