|Year : 2019 | Volume
| Issue : 4 | Page : 166-172
Impact of comorbidities in heart failure – prevalence, effect on functional status, and outcome in indian population: A single-center experience
Saurabh Mehrotra MBBS, MD, DM 1, Tejinder M Sharma MBBS, MD 2, Ajay Bahl MBBS, DRM, MD 1
1 Department of Cardiology, Advanced Cardiac Centre, Post Graduate Institute of Medical Education and Research, Chandigarh, India
2 Department of Medicine, Post Graduate Institute of Medical Education and Research, Chandigarh, India
|Date of Web Publication||6-Jan-2020|
Dr. Saurabh Mehrotra
Department of Cardiology, Post Graduate Institute of Medical Education and Research, Sector.12, Chandigarh - 160 012
Source of Support: None, Conflict of Interest: None
Background: We sought to estimate the prevalence of comorbidities in heart failure (HF) patients and their impact on functional status and clinical outcomes in Indian population. Patients and Methods: This prospective study was carried out at a tertiary care institute in North India. Patients were followed up prospectively for readmission and mortality for a median of 18 months. Results: A total of 113 HF patients were included in the study – 59 being HF with preserved ejection fraction (HFpEF) and 54 being HF with reduced ejection fraction (HFrEF). Patients with HFpEF were older (P = 0.03) with an equal proportion of males and females. Patients with HFpEF were less intensively treated with HF medications, particularly, spironolactone and other diuretics (P = 0.001). A total of 17 comorbidities were identified, and patients with HFpEF exhibited a higher burden of total and noncardiac comorbidities. After 18 months of follow-up, the all-cause readmissions and all-cause mortality were higher (P = 0.01) in patients with HFrEF as compared to HFpEF. The high New York Heart Association (NYHA) class, low ejection fraction, and high proBNP were associated with an increased risk of all-cause mortality. The mean Geriatric Nutritional Risk Index (GNRI) was significantly low in the HFrEF group (96.4 ± 10.8 vs. 102.3 ± 12.9, P = 0.009). Quality of life was poor in patients with HFrEF as compared with the HFpEF group, and 36-item Short-Form Health Survey score decreased proportionately with a decrease in EF. Multivariate analysis showed EF, GNRI, albumin (mg/dl), urea (mg/dl), sodium, and all-cause mortality to be associated with HF-related readmissions. Furthermore, NYHA class, urea (mg/dl), all-cause readmission, and HF-related readmission were seen to be associated with HF-related mortality. Conclusion: Despite differential prevalence, comorbidities exert substantial impact on the functional status in HFrEF as well as HFpEF patients. An individualized treatment approach based on comorbidities could provide a way forward, especially in low-resource countries.
Keywords: Comorbidities in heart failure, Geriatric Nutritional Risk Index, heart failure with preserved ejection fraction, heart failure with reduced ejection fraction, malnutrition index
|How to cite this article:|
Mehrotra S, Sharma TM, Bahl A. Impact of comorbidities in heart failure – prevalence, effect on functional status, and outcome in indian population: A single-center experience. J Clin Prev Cardiol 2019;8:166-72
|How to cite this URL:|
Mehrotra S, Sharma TM, Bahl A. Impact of comorbidities in heart failure – prevalence, effect on functional status, and outcome in indian population: A single-center experience. J Clin Prev Cardiol [serial online] 2019 [cited 2022 Jan 29];8:166-72. Available from: https://www.jcpconline.org/text.asp?2019/8/4/166/275164
| Introduction|| |
<Heart failure (HF) is a complex clinical syndrome characterized by structural and functional impairment of ventricular filling or ejection of blood. An increase in cardiac and noncardiac comorbidities with the advancement of age contributes significantly to the poor prognosis and alters the response to treatment in HF., More than 50% of patients with the clinical syndrome of HF has a normal left ventricular ejection fraction (LVEF) termed as HF with preserved ejection fraction (HFpEF) as compared to HF with reduced ejection fraction (HFrEF). Although substantial data are available from Western countries on the differential impact of comorbidities in these HF subtypes, the evidence from India is very scarce. Moreover, as compared to other developing countries, India exhibits a greater burden of mortality from HF that might be attributed to the difference in demographic, clinical, and genetic profile of Indian population., The present study aimed to evaluate the prevalence of comorbidities in HF subtypes along with its impact on functional status and clinical outcomes in Indian population. The study also aimed to evaluate the nutritional status and quality of life (QoL) of HF patients.
| Patients and Methods|| |
This prospective study was carried out at the Postgraduate Institute of Medical Education and Research, Chandigarh, a tertiary care institute, in North India. Consecutive hospitalized patients with or without HF-related reasons were included in the study and divided into two groups (HFpEF and HFrEF). HF was defined as per the modified Framingham criteria. Details of medical history, general physical examination, and laboratory data were recorded from the patient's medical records. LVEF was measured by two-dimensional echo using Simpson method. LV systolic dysfunction was graded as mild (EF: 41%–45%), moderate (EF: 36%–40%), or severe (EF: 35% or lower). QoL was evaluated with 36-item Short-Form Health Survey (SF-36) score and New York Heart Association (NYHA) class. Nutritional status was assessed by the Geriatric Nutritional Risk Index (GNRI). Type 2 diabetes mellitus (T2DM) was defined as fasting blood sugar >126 or random blood sugar >200 mg/dl or glycosylated hemoglobin (HbA1c) .5%. Hypertension was defined as per the Eighth Joint National Committee criteria. Obesity was defined as body mass index (BMI) >27.5 kg/m2 or waist circumference (WC) >90 and 80 cm in males and females, respectively. Renal dysfunction was defined as estimated glomerular filtration rate <60 ml/min/m2 by the Modification of Diet in Renal Disease formula. Anemia was defined as Hb <13 and 12 g/dl in men and women, respectively. Diagnosis of atrial fibrillation (AF) was based on baseline electrocardiogram. Dyslipidemia was defined as low-density lipoproteins (LDLs) >100 mg/dl, high-density lipoproteins (HDLs) <40 mg/dl in males and <50 mg/dl in females, triglycerides >150 mg/dl, or total cholesterol >200 mg/dl. Peripheral arterial disease was defined as a history of claudication or ankle–brachial index of <0.8. Chronic obstructive pulmonary disease (COPD) was defined as the presence of dyspnea, chronic cough with sputum production, and history of exposure to risk factor for disease (smoking, smoke from home cooking, and occupational dust) along with the presence of postbronchodilator forced expiratory volume in 1 s/forced vital capacity ratio of <70% as measured by spirometer. The study was conducted according to the ethical principles stated in the latest version of Helsinki Declaration and the applicable guidelines for good clinical practice. Ethics approval was obtained from the institutional ethics committee, and written informed consent was obtained from individual patient.
The sample size was calculated as 100, based on the effect size and alpha error consideration. All quantitative variables are presented as mean or median with measures of dispersion (standard deviation and standard error) and analyzed by independent t-test and Mann–Whitney U-test. Categorical variables are described as frequencies or proportions and analyzed by Chi-square test. Univariate and multivariate analyses were carried out to find significant predictors for the outcome of interest in both the groups. All tests were performed at two-tailed, and P < 0.05 was considered as statistically significant. Multivariable Cox proportional hazards model was used to calculate the hazard ratio (HR) for mortality. Ordinal and linear regressions were used to assess the impact of different comorbidities on the NYHA class and SF-36 score.
| Results|| |
A total of 113 HF patients were included in the study. Of the 113 patients, HFrEF and HFpEF were present in 59 (53.3%) and 54 (47.7%) patients, respectively. Among the patients with HFrEF, 11.9% had mild systolic dysfunction, 11.9% had moderate systolic dysfunction, and 76.3% had severe systolic dysfunction. The demography, clinical symptoms, and clinical findings are presented in [Table 1]. The mean age of the patients in the HFrEF group was 57.9 ± 13.4 years, and most were male (61.1%). Patients in the HFpEF group were older (62.9 ± 11 vs. 57.9 ± 13.4, P = 0.03) with an equal proportion of males and females. As compared to patients with HFrEF, patients with HFpEF were less symptomatic and had fewer clinical findings, P < 0.05 for all symptoms except dyspnea, edema, and family history of coronary artery disease (CAD). Patients with HFpEF were less intensively treated with HF medications, particularly, spironolactone and other diuretics (P = 0.001).
Prevalence of comorbidities
The prevalence of comorbidities in the study population is presented in [Table 2]. A total of 17 comorbidities were identified among 113 HF patients, with a mean of 5.5 ± 1.9 comorbidities. Of the 17 comorbidities, CAD and AF were cardiac comorbidities, whereas diabetes, hypertension, hypothyroidism, dyslipidemia, cerebrovascular accident (CVA), peripheral vascular disease (PVD), anemia, Vitamin D deficiency, chronic kidney disease, obstructive sleep apnea (OSA), COPD, obesity, malnutrition (GNRI), iron deficiency, and hypoalbuminemia were noncardiac comorbidities.
Patients with HFpEF exhibited a higher burden of total (5.9 ± 1.9 vs. 5.2 ± 1.9) and noncardiac comorbidities (5.0 ± 1.9 vs. 4.2 ± 1.9). Dyslipidemia (P = 0.09), CVA (P = 0.4), anemia (P = 0.1), iron deficiency (P = 0.1), and hypoalbuminemia (P = 0.009) were more prevalent in patients with HFpEF, whereas T2DM (P = 0.09), hypothyroidism (P = 0.9), hypertension (P = 0.01), renal dysfunction (P = 0.3), AF (P = 0.2), COPD (P = 0.5), CAD (P = 0.6), and obesity (P = 0.9) were more frequent in patients with HFrEF. Patients were followed up for 18 months. Of the 24 all-cause readmissions, 15 and 9, respectively, were found to be HF- and non-HF-related readmissions. HF-related readmission was statistically more frequent in the HFrEF group (P = 0.04).
Functional status and clinical outcomes
Significantly more proportion of patients with HFrEF had a higher grade of NYHA functional class than those with HFpEF [Figure 1] (P = 0.001). Univariate analysis revealed that more patients in NYHA functional Class 4 had orthopnea, palpitation, edema, hypotension, tachycardia, hypoxia, raised jugular venous pressure (JVP), S3/S4, murmur, crepitation, and OSA. Univariate analysis also revealed that low HDL, EF, GNRI, hypoalbuminemia while higher HbA1c, urea, creatinine, and high proBNP were associated with higher NYHA class. Patients with NYHA functional Class 4 were younger with low mean SF-36 score [Table 3].
|Figure 1: New York Heart Association class distribution among study groups. *P = 0.001 versus heart failure with reduced ejection fraction|
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|Table 3: Univariate analysis and Spearman correlation of New York Heart Association class with various parameters|
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Univariate analysis demonstrated that dyslipidemia, hypoalbuminemia, renal dysfunction, PVD, low GNRI, and low SF-36 scores were significantly associated with all-cause readmission [Table 4]. Patients presenting with orthopnea, crepitation, raised JVP, family history of CAD, hypoalbuminemia, renal dysfunction, hyponatremia, low SF-36 score, and higher NYHA class had an increased risk of HF-related readmission. Of the 19 all-cause mortality, 16 and 3, respectively, were HF and non-HF-related mortalities. HF-related mortality was statistically more frequent in patients with HFrEF (P = 0.01). High NYHA class, low EF, and high proBNP were associated with an increased risk of all-cause mortality. Patients with a history of all-cause and HF-related readmission had a significantly increased risk of all-cause mortality.
|Table 4: Univariate analysis and Spearman correlation of all.cause and heart failure readmission and mortality with various parameters|
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Quality of life and nutritional status
QoL was poor in patients with HFrEF as compared with the HFpEF group, and SF-36 score decreased proportionately with a decrease in EF. The mean malnutrition index GNRI was significantly low in the HFrEF group (96.4 ± 10.8 vs. 102.3 ± 12.9, P = 0.009) [Table 2]. More number of patients with HFrEF were at high malnutrition risk. Patients at high risk of malnutrition exhibited low EF, BMI, waist-to-hip ratio, WC, LDL, total protein, triglyceride, albumin levels, and SF-36 score, while they had high blood urea nitrogen levels and higher NYHA class.
Results of Cox HR analysis of various parameters for HF-related readmission and mortality are presented in [Table 5] and [Table 6]. While EF , GNRI, albumin (mg/dl), urea (mg/dl), Na, and all-cause mortality were associated with HF-related readmissions, NYHA class, urea (mg/dl), all-cause readmission, and HF-related readmission were associated with HF-related mortality.
|Table 5: Cox hazard ratio analysis of various parameter for heart failure-related readmission|
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|Table 6: Cox hazard ratio analysis of various parameter for heart failure-related mortality|
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| Discussion|| |
The present study evaluated total 17 comorbidities in patients with HFpEF and HFrEF. Patients with HFpEF were significantly less symptomatic compared to those with HFrEF. Patients with HFpEF exhibited a higher burden of total and noncardiac comorbidities. Significantly more proportion of patients with HFrEF had a higher grade of NYHA functional class and poor QoL and nutritional status. HF-related readmissions and mortality were statistically more frequent in HFrEF patients.
Patients with HFpEF exhibited a higher burden of total and noncardiac comorbidities in the present study; however, these findings are in contrast with those reported by Edelmann et al. 2011. Nevertheless, the prevalence of T2DM was similar and that of AF was slightly higher in patients with HFpEF in previous studies., When compared to HFrEF, patients with HFpEF have been older, majorly female and exert high prevalence of hypertension and anemia.,,,,,,, Patients in our study had a similar presentation but had an equal proportion of males and females. The prevalence of all other comorbidities was equal in both the groups. The optimal treatment of anemia in HF patients requires further studies.
Majority of the patients with HFrEF had NYHA Class 3 (37%) and Class 4 (30.5%), which was significantly different from that of HFpEF, who majorly had Class 2 (66.7%) and Class 3 (18.5%) HF. These results are in agreement with those reported by Edelmann et al. who also showed lower mean NYHA in patients with HFpEF. In our study, older patients had lower QoL with a higher mean NYHA score; similar observations were also reported in previous studies that show a decrease in QOL with worsening of NYHA functional class.,
All-cause mortality was similar in both HF types; however, HF-related readmissions and mortality were statistically more frequent in the HFrEF group. Prognosis in patients with HFpEF has remained similar to that in patients with HFrEF in several studies., Nonetheless, some recent multicenter studies and a meta-analysis show better prognosis in patients with HFpEF., In an international multi-ethnic cohort study, patients with HFpEF had a lower risk of death compared with those with HFrEF (HR: 0.62, 95% confidence interval: 0.46–0.85). Further, a meta-analysis revealed that the patients with HFpEF have a lower risk of death than patients with HFrEF irrespective of age, gender, and etiology of HF.
In a study that enrolled 40,239 patients, the risk of cardiovascular and HF readmissions was higher in HFrEF compared with HFpEF. The presence of higher NYHA class, low EF, and high proBNP was associated with an increased risk of all-cause mortality in our study which is in line with previously published reports where renal failure, previous history of hospitalization for HF, impaired functional status (NYHA Classes III–IV), and elevated Brain natriuretic peptide (BNP) were found to be the significant predictors of mortality.,,
When compared with HFpEF, patients with HFrEF had poor QoL in our study, and there was a proportional decrease in SF-36 score with a decrease in EF. Conversely, a CHARM study demonstrated a similar QoL in HF subtypes, and the study also showed that the extent of QoL worsening was independent of LVEF.
To our knowledge, the present study is the first in North India to analyze the role of GNRI in a patient with HF. The mean malnutrition index GNRI was significantly low in the HFrEF group, and more number of patients with HFrEF were at high malnutrition risk.
| Conclusion|| |
Our findings suggest that HFpEF is more common in older population and exhibits a greater burden of comorbidities as compared to HFrEF. Further, patients with HFrEF have poor QoL in term of higher NYHA class and SF-36 score along with poor nutritional status. Although a patient has similar all-cause readmission and all-cause mortality in both the groups, HF-related readmission and mortality are more frequent in patients with HFrEF. Regardless of EF, these patients experience substantial mortality and readmission indicating the need for new therapeutic strategies.
In summary, there are marked differences in the prevalence and prognostic outcomes of comorbidities in HFrEF as compared to HFpEF. However, comorbidities do exert a substantial impact on functional status in HFrEF as well as in HFpEF patients. Hence, focusing treatment on comorbidities may be more beneficial in order to reduce the burden on public health services in low-resource countries such as India.
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Conflicts of interest
There are no conflicts of interest.
| References|| |
Jhund PS, Tavazzi L. Has the 'epidemic' of heart failure been replaced by a tsunami of co-morbidities? Eur J Heart Fail 2016;18:500-2.
Schmidt M, Ulrichsen SP, Pedersen L, Bøtker HE, Sørensen HT. Thirty-year trends in heart failure hospitalization and mortality rates and the prognostic impact of co-morbidity: A Danish nationwide cohort study. Eur J Heart Fail 2016;18:490-9.
Dokainish H, Teo K, Zhu J, Roy A, AlHabib KF, ElSayed A, et al.
Global mortality variations in patients with heart failure: Results from the international congestive heart failure (INTER-CHF) prospective cohort study. Lancet Glob Health 2017;5:e665-72.
Jayashree S, Arindam M, Vijay KV. Genetic epidemiology of coronary artery disease: An Asian Indian perspective. J Genet 2015;94:539-49.
McKee PA, Castelli WP, McNamara PM, Kannel WB. The natural history of congestive heart failure: The Framingham study. N Engl J Med 1971;285:1441-6.
James PA, Oparil S, Carter BL, Cushman WC, Dennison-Himmelfarb C, Handler J, et al
.2014 evidence-based guideline for the management of high blood pressure in adults: Report from the panel members appointed to the eighth joint national committee (JNC 8). JAMA 2014;311:507-20.
Bhatia RS, Tu JV, Lee DS, Austin PC, Fang J, Haouzi A, et al.
Outcome of heart failure with preserved ejection fraction in a population-based study. N Engl J Med 2006;355:260-9.
Fonarow GC, Stough WG, Abraham WT, Albert NM, Gheorghiade M, Greenberg BH, et al.
Characteristics, treatments, and outcomes of patients with preserved systolic function hospitalized for heart failure: A report from the OPTIMIZE-HF registry. J Am Coll Cardiol 2007;50:768-77.
Owan TE, Hodge DO, Herges RM, Jacobsen SJ, Roger VL, Redfield MM, et al.
Trends in prevalence and outcome of heart failure with preserved ejection fraction. N Engl J Med 2006;355:251-9.
Hogg K, Swedberg K, McMurray J. Heart failure with preserved left ventricular systolic function; epidemiology, clinical characteristics, and prognosis. J Am Coll Cardiol 2004;43:317-27.
Tribouilloy C, Rusinaru D, Mahjoub H, Soulière V, Lévy F, Peltier M, et al.
Prognosis of heart failure with preserved ejection fraction: A 5 year prospective population-based study. Eur Heart J 2008;29:339-47.
Lam CS, Donal E, Kraigher-Krainer E, Vasan RS. Epidemiology and clinical course of heart failure with preserved ejection fraction. Eur J Heart Fail 2011;13:18-28.
Yancy CW, Lopatin M, Stevenson LW, De Marco T, Fonarow GC, ADHERE Scientific Advisory Committee and Investigators. et al.
Clinical presentation, management, and in-hospital outcomes of patients admitted with acute decompensated heart failure with preserved systolic function: A report from the acute decompensated heart failure national registry (ADHERE) database. J Am Coll Cardiol 2006;47:76-84.
Lenzen MJ, Scholte op Reimer WJ, Boersma E, Vantrimpont PJ, Follath F, Swedberg K, et al.
Differences between patients with a preserved and a depressed left ventricular function: A report from the euroheart failure survey. Eur Heart J 2004;25:1214-20.
Juenger J, Schellberg D, Kraemer S, Haunstetter A, Zugck C, Herzog W, et al.
Health related quality of life in patients with congestive heart failure: Comparison with other chronic diseases and relation to functional variables. Heart 2002;87:235-41.
Erceg P, Despotovic N, Milosevic DP, Soldatovic I, Zdravkovic S, Tomic S, et al.
Health-related quality of life in elderly patients hospitalized with chronic heart failure. Clin Interv Aging 2013;8:1539-46.
Lam CS, Gamble GD, Ling LH, Sim D, Leong KT, Yeo PS, et al.
Mortality associated with heart failure with preserved vs. reduced ejection fraction in a prospective international multi-ethnic cohort study. Eur Heart J 2018;39:1770-80.
Meta-analysis Global Group in Chronic Heart Failure (MAGGIC). The survival of patients with heart failure with preserved or reduced left ventricular ejection fraction: An individual patient data meta-analysis. Eur Heart J 2012;33:1750-7.
Cheng RK, Cox M, Neely ML, Heidenreich PA, Bhatt DL, Eapen ZJ, et al.
Outcomes in patients with heart failure with preserved, borderline, and reduced ejection fraction in the medicare population. Am Heart J 2014;168:721-30.
Arora S, Lahewala S, Virk HU, Setareh-Shenas S, Patel P, Kumar V, et al.
Etiologies, trends, and predictors of 30-day readmissions in patients with diastolic heart failure. Am J Cardiol 2017;120:616-24.
Dalos D, Mascherbauer J, Zotter-Tufaro C, Duca F, Kammerlander AA, Aschauer S, et al.
Functional status, pulmonary artery pressure, and clinical outcomes in heart failure with preserved ejection fraction. J Am Coll Cardiol 2016;68:189-99.
Kristensen SL, Jhund PS, Køber L, McKelvie RS, Zile MR, Anand IS, et al.
Relative importance of history of heart failure hospitalization and N-terminal pro-B-type natriuretic peptide level as predictors of outcomes in patients with heart failure and preserved ejection fraction. JACC Heart Fail 2015;3:478-86.
Lewis EF, Lamas GA, O'Meara E, Granger CB, Dunlap ME, McKelvie RS, et al.
Characterization of health-related quality of life in heart failure patients with preserved versus low ejection fraction in CHARM. Eur J Heart Fail 2007;9:83-91.
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6]