|Year : 2023 | Volume
| Issue : 1 | Page : 46-52
Comparative analysis of different prognostic markers in predicting outcome in advanced heart failure
Parth Godhiwala, Sunil Kumar, Sourya Acharya, Mansi Patel
Department of Medicine, Jawaharlal Nehru Medical College, Datta Meghe Institute of Higher Education and Research (Deemed to be University), Wardha, Maharashtra, India
|Date of Submission||25-Feb-2023|
|Date of Decision||03-Mar-2023|
|Date of Acceptance||24-Mar-2023|
|Date of Web Publication||04-May-2023|
Department of Medicine, Jawaharlal Nehru Medical College, Datta Meghe Institute of Higher Education and Research (Deemed to be University), Sawangi, Meghe, Wardha, Maharashtra
Source of Support: None, Conflict of Interest: None
Introduction: Heart failure (HF) is a debilitating condition with an adverse outcome, especially during the advanced stage having higher morbidity and mortality rates. Various parameters have been used as prognostic markers in advanced HF. This study highlights about the comparative analysis of different prognostic markers in predicting mortality in advanced HF. Methods: This prospective observational study was conducted in patients of advanced HF admitted to the department of medicine intensive care unit in a rural tertiary care hospital from 2018 to 2020. Advanced HF was diagnosed using the updated HF Association-European Society of Cardiology criteria. The serum N-terminal pro-B-type natriuretic peptide (NT-proBNP), six-minute walk test (6MWT), left ventricular ejection fraction (LVEF), estimated glomerular filtration rate, and glycosylated hemoglobin type A1c levels were measured on admission. Receiver operating characteristic (ROC) curve was also studied for the above-mentioned variables, and the area under ROC curve (AUROC) was also determined. Results: Seventy-five patients with an average age of 60.55 ± 14.04 years were evaluated. Out of 75, 48 (64%) were male and 27 (36%) were female. There was inhospital mortality in 20 (26.67%) patients. The mean NT-proBNP levels among the mortality group was 9826.95 ± 3485.10 pg/mL, while in nonmortality group, it was 6135.40 ± 2342.77 pg/mL (P = 0.001). The cutoff range in this study for on-admission serum NT-proBNP levels was 8990 pg/mL, with AUROC of 0.81, the sensitivity of 70.0%, and specificity of 90.9%. In multiple regression analysis keeping mortality as the dependent variable, it was seen that variables NT-proBNP, 6MWT (<300 m), and LVEF were significantly associated with mortality. Conclusion: Serum NT-proBNP and 6MWT (<300 m) were important predictors of mortality in advanced HF.
Keywords: Advanced heart failure, left ventricular ejection fraction, N-terminal pro-B-type natriuretic peptide, six-minute walk test
|How to cite this article:|
Godhiwala P, Kumar S, Acharya S, Patel M. Comparative analysis of different prognostic markers in predicting outcome in advanced heart failure. J Pract Cardiovasc Sci 2023;9:46-52
|How to cite this URL:|
Godhiwala P, Kumar S, Acharya S, Patel M. Comparative analysis of different prognostic markers in predicting outcome in advanced heart failure. J Pract Cardiovasc Sci [serial online] 2023 [cited 2023 Jun 8];9:46-52. Available from: https://www.j-pcs.org/text.asp?2023/9/1/46/375805
| Introduction|| |
Advanced heart failure (HF), also known as “refractory,” “end-stage,” or “American College of Cardiology/American Heart Association stage D” HF, is defined by the HF Society of America as the presence of progressive and/or persistent severe signs and symptoms of HF, despite optimized medical, surgical, and device therapy. It is generally accompanied by frequent hospitalization, severely limited exertional tolerance, and poor quality of life, and is associated with high morbidity and mortality. Importantly, the progressive decline should be primarily driven by the HF syndrome., HF is a debilitating condition with an adverse outcome, especially during the advanced stage. Higher rates of morbidity and mortality have been reported, reaching as high as 50% approximately during the 1-year follow-up. Early detection of factors responsible for progression and intervening is crucial to change the natural course of their disease. Early intervention can help possibly reduce mortality in advanced HF.
Conventionally, clinical manifestations have been used to diagnose HF and have been used as prognostic markers and as a marker of risk stratification.,, Many studies which were done in the past support the fact that lesser functional class (NYHA I and II) has a better outcome than those who are NYHA III and IV. Mortality rates are higher in patients with NYHA FC III and IV., Even if the symptoms help define the prognosis, they cannot be relied on in patients with advanced HF as there is hardly any change in clinical status., These patients usually have a history of repeated admissions due to decompensation and form a population with a grave prognosis. A good prognostic test in such a scenario can identify early mortality.
Recently, many variables such as the serum N-terminal pro-B-type natriuretic peptide (NT-proBNP), six-minute walk test (6MWT), left ventricular ejection fraction (LVEF), estimated glomerular filtration rate (eGFR), and glycosylated hemoglobin type A1c (HbA1c) levels have been used for defining prognosis in patients with advanced HF. This manuscript highlights about the comparison between these variables and to find out the best predictor of mortality in advanced HF patients.
| Methods|| |
This prospective observational study was conducted in patients of advanced HF admitted to the department of medicine intensive care unit in a rural tertiary care hospital over 1.5 years, i.e., November 2018 to April 2020 after approval by the Institutional Ethics Committee (IEC) with number: DMIMS (DU)/IEC/2018-19/7550.
A total of 75 patients with advanced HF were enrolled in this study, who had undergone 6MWT and laboratory investigations that included NT-proBNP, eGFR, fasting lipid profile, cardiac markers (Creatine Kinase-Myocardial Band (CKMB), and TROPONIN I), HbA1c, two-dimensional (2D) echo, and coronary angiography. Details of the study method have been highlighted in the flow chart [Figure 1]. All the patients fulfilled the updated HF Association - European Society of Cardiology (ESC) criteria. The ESC definition includes four criteria: (1) hospitalizations or emergency department visits for HF or ventricular arrhythmias, (2) left ventricular EF ≤30%, isolated right ventricular (RV) failure or nonoperable severe valvular or congenital abnormalities or significant structural abnormalities or diastolic dysfunction and preserved or mildly reduced EF, (3) severe and persistent symptoms of HF, and (4) severely impaired exercise capacity. Other medical histories included were age, sex, risk factors such as alcohol intake and tobacco use, and comorbid conditions such as obesity (after calculating body mass index [BMI]), diabetes mellitus, and hypertension. Patients with <18 years of age, anemia, patients with HF with LVEF <30%, having prosthetic valve implantation, shock, and patients not giving consent were excluded from the study. All the patients had undergone 2D echocardiographic assessment and were categorized as reduced (HF reduced EF [HFrEF], <40%) or preserved (HF preserved EF [HFpEF], ≥50%). Other echocardiographic characteristics such as qualitative assessment of RV function, left atrial size, diastolic function grade, E/e′, and estimated RV systolic pressure were also assessed. The primary outcome of the study was inhospital mortality after admission and its predictors like different prognostic markers.
|Figure 1: Flow chart of the study method. ICU: Intensive care unit, HFA-ESC: Heart Failure Association-European Society of Cardiology, LVEF: Left ventricular ejection fraction|
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Continuous variables in this study were presented as mean ± standard deviation, while rates and percentages were used for categorical variables. The Student's t-test was used while comparing the continuous variables. A “receiver operating characteristic” (ROC) curve was used to determine the cutoff point for the serum NT-proBNP level as a predictor of mortality. P < 0.05 value was considered statistically significant.
| Results|| |
Out of 75 patients enrolled in this study, the mean age was 60.55 ± 14.04 years; 48 (64%) being males and 27 (36%) females. The mean age among males was 61.25 ± 14.76 years, while in females, it was 59.25 ± 12.86 years. Alcohol consumption was present in 28 (37.3%) patients. Tobacco use was present in 30 (40.0%) patients. The mean BMI in this study was 24.80 ± 2.14 kg/m2. All other baseline characteristics of the patients are shown in [Table 1].
In this study, hypertension was present in 34 (45.3%), diabetes mellitus was present in 25 (33.3%), and ischemic heart disease was present in 29 (38.7%). A combination of more than one comorbidity was present in 34 (45.3%) patients. Coronary artery disease (CAD) was the most common etiology of advanced HF, 43 (57.33%). Dyslipidemia was present in 34 (45.3%) patients of the total sample size. HbA1c of >6.5% was present in 24 (32%) patients. eGFR was <60 mL/kg/1.73 m2 in 40 (53.33%) patients with a mean eGFR of 59.24 ± 24.37 mL/kg/1.73 m2 in the present study. The mean eGFR among the mortality group was 54.25 ± 26.19 mL/kg/1.73 m2.
The mean serum NT-proBNP levels in this study were 7119.81 ± 3134.43. The mean NT-proBNP levels among the mortality group were 9826.95 ± 3485.10, while in the nonmortality group, it was 6135.40 ± 2342.77. ROC curve analysis was done to measure the diagnostic performance of NT-proBNP (pg/mL) in predicting mortality in patients with refractory HF. The cutoff range in this study for on-admission serum NT proBNP levels was 8990 pg/mL, with area under ROC (AUROC) of 0.81, the sensitivity of 70.0%, and specificity of 90.9%. 6MWT was performed on 39 patients on admission. The mean distance covered was 268.97 ± 63.24 m. Out of 75 study participants, 38 (50.7%) patients had LVEF <20%, while 37 (49.3%) patients had LVEF between 21% and 30%. The mean LVEF in this study was 22.73 ± 4.89. 20 (26.67%) patients in this study had inhospital mortality, while 55 (73.33%) were discharged after successful treatment.
[Table 2] shows the clinical profile in both mortality and nonmortality groups. The mean age in the mortality group was 58.00 ± 15.09 years, while in the nonmortality group, it was 61.47 ± 13.69 years. The mean NT-proBNP levels among the mortality group were 9826.95 ± 3485.10, while in the nonmortality group, it was 6135.40 ± 2342.77. ROC curve analysis was done to measure the diagnostic performance of NT-proBNP (pg/mL) in predicting mortality in patients with advanced HF. The cutoff range in this study for on-admission serum NT-proBNP levels was 8990 pg/mL, with AUROC of 0.81, the sensitivity of 70.0%, and specificity of 90.9% as shown in [Figure 2].A multiple regression analysis studying the effect of variables such as CAD, LVEF, HbA1c, 6MWT, NT.proBNP, and eGFR were done to observe its significance in advanced heart failure. NT-proBNP (P = 0.005), 6MWT (P = 0.005), and LVEF (P = 0.025) were statistically significant in this study indicating their prognostic importance in patients of advanced HF as shown in [Table 3]. AUC for different markers such as LVEF 0.706, HbA1C 0.376, 6-MWT 0.824, NT-pro BNP 0.812, and eGFR 0.584 is shown in [Figure 3]a, [Figure 3]b, [Figure 3]c, [Figure 3]d, [Figure 3]e.
|Figure 2: ROC curve analysis showing diagnostic performance of NT-proBNP in predicting mortality (cutoff point). ROC: Receiver operating characteristic, NT-proBNP: N-terminal pro-B-type natriuretic peptide|
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|Figure 3: Receiver operating characteristic (ROC) curve for different variables in association with mortality. (a) ROC for LVEF (Left ventricular ejection fraction); (b) ROC for HbA1C( Glycosylated hemoglobin type A1c); (c) ROC for 6MWT (Six minute walk test); (d) ROC for NT proBNP (N.terminal pro.B.type natriuretic peptide); (e) ROC for eGFR ( estimated Glomerular Filtration Rate)|
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| Discussion|| |
The world needs a good prognostic marker for advanced HF, and the search is on! Cardiac impairment was identified by an LVEF of <25% and oxygen requirement <12 mL/kg/min, or the presence of symptoms represents the criteria used by HF units to define the need for heart transplantation.
NT-proBNP is a test recently to the above-mentioned variables. Many studies have already done regarding its use as a prognostic marker., High levels of NT-proBNP on admission help in the diagnosis of HF and failure in reduction of these levels after treatment indicates poor prognosis and higher mortality rates.
The mean serum NT-proBNP levels in this study were 7119.81 ± 3134.43; 9826.95 ± 3485.10 in mortality group, while in the nonmortality group, it was 6135.40 ± 2342.77. The cutoff range in this study for on-admission serum NT-proBNP levels was 8990 pg/mL, with the sensitivity of 70.0% and specificity of 90.9%. Velibey et al. performed a study to determine a predictive cutoff value for NT-proBNP on admission that could predict 4-year survival in acute HF patients. The cutoff point was identified as 9152.4 pg/mL at 95% confidence interval, which had a sensitivity of 71.4% and specificity of 81.3% in predicting 30-day survival. Scrutinio et al. evaluated the relation of the updated ADHF/NT-proBNP risk score with inhospital and 90-day mortality in advanced ADHF patients. The mean NT-proBNP levels in their study were 5418, and value >5180 pg/mL was found in 51.4%, which had higher mortality rates. Luers et al. studied the NT-proBNP levels of 85 patients with decompensated HF, out of which 31% of patients died within the first 30 days. NT-proBNP on admission among survivors was 4227 (1220–8079) and among nonsurvivors was 7939 (1879–12,499). Salah et al. performed a study on 1228 patients with HF, of which 776 patients had EF <40% (HFrEF group), having mean serum NT-proBNP levels of 7173 (4039–13,264).
The 6MWT is a very simple test to measure the functional capacity of an individual. A distance of 300 m or less is consistent with advanced HF and a high risk of mortality. In this study, the mean distance covered was 268.97 ± 63.24 m. On discharge, it was performed on 55 patients with a mean of 318.55 ± 67.18 m. Shah et al. had performed a study to determine the prognostic value of the 6-min walk in patients of advanced HF. The study was performed on 440 patients divided into two groups, one being able to walk and another unable to walk. 6MWT in able to walk group was 218 m (range: 128–297).
In our study, out of 75 study participants, 38 (50.7%) patients had LVEF <20%, while 37 (49.3%) patients had LVEF between 21% and 30%, mean being 22.73 ± 4.89. Gu et al. had enrolled 902 patients for their study. Of which, 290 (32.2%) had HFpEF, 131 (14.5%) HFbEF, and 481 (53.3%) HFrEF. They had also studied LVEF in these patients. The mean LVEF for HFrEF (n = 481) was 34.4 ± 2.6, which was very high compared to this study. The study group HFrEF was defined as EF < 40%. Hence, the mean was on the higher side.
In an analytical study by Costanzo et al., 1433 patients of “Stage D” HF in ADHERE LM registry were evaluated having a mean LVEF of 29.5 ± 14.1. These results were high when compared to this study. Lam et al. studied the regional and ethnic differences among patients with HF in Asia. The overall mean LVEF was 28 (range: 22–33) in a total of 5276 patients. These results were on the higher side compared to the current study. Dewan et al. had studied the mean LVEF in 13,174 patients of HFrEF. They found out that the mean LVEF was 28.9 ± 6.0 in Western Europe (n = 3521), 30.8 ± 5.4 in Central/Eastern Europe (n = 4758), 26.7 ± 7.0 in North America (n = 613), 27.9 ± 5.6 in India (n = 1390), and 29.5 ± 4.9 in China (n = 833). These results were on the higher side compared to the present study.
Cheng et al. had conducted a study on a total of 40,239 patients. The mean LVEF in their study was 25 ± 5. These results were similar to the present study.
In this study, the mean eGFR (mL/kg/1.73 m2) was 59.24 ± 24.37. Only 7 (9.3%) participants had eGFR 15–29 mL/kg/1.73 m2; 15 (20.0%) had eGFR 30–44 mL/kg/1.73 m2, 18 (24%) had eGFR 45–59 mL/kg/1.73 m2, 25 (33.3%) had eGFR 60–89 mL/kg/1.73 m2, and 10 (13.3%) had eGFR ≥90 mL/kg/1.73 m2. As in this study, patients were from rural setup, and compliance to medications and treatment was not proper. This was probably the reason patients had a mean eGFR on the lower side in this study.
Chopra et al. had conducted a study on 5590 patients having a mean eGFR of 76.1 ± 27.7 mL/kg/1.73 m2. The mean eGFR in the mortality group was 68.5 ± 30.2 mL/kg/1.73 m2 and in the nonmortality group was 77.7 ± 26.9 mL/kg/1.73 m2. There was a statistically significant difference between the groups, which was similar to the present study. Lam et al. studied the regional and ethnic variations among HF patients in Asia. The mean eGFR was 66.8 ± 28.2, 72.0 ± 32.4, and 59.7 ± 26.2 in Northeast Asia (n = 1658), South Asia (n = 1436), and Southeast Asia (n = 2182), respectively. The overall mean eGFR was 64.9 ± 28.8 of a total of 5276 patients. These results were similar to the present study. Dewan et al. had studied the mean eGFR in 13174 patients of HFrEF. They found out that the mean eGFR was 65.8 ± 19.1 in Western Europe (n = 3521), 70.0 ± 19.5 in Central/Eastern Europe (n = 4758), 61.7 ± 17.7 in North America (n = 613), 77.5 ± 29.5 in India (n = 1390), and 80.4 ± 21.0 in China (n = 833). The mean eGFR had a varied distribution all over the world. As the study was done in HFrEF, the time at which the patient presents plays a crucial role. Early presentation and regular follow-up have a better prognosis and quality of life. According to the IN-HF Outcome Registry, almost 55% showed an eGFR <60 mL/min/1.73 m2. These results were similar to the present study.
The mean HbA1c in this study was 5.98 ± 1.25, in which 37 (49.3%) patients had HbA1c <5.6, 14 (18.7%) had 5.7–6.4, and 24 (32%) had HbA1c >6.5. U-shaped distribution was seen in this study.
Elder et al. performed a cohort study to correlate HbA1c and death in diabetic individuals with HF. They had divided the cohort into five groups: HbA1c <6.0%, HbA1c 6.1%–7.0%, HbA1c 7.1%–8.0%, HbA1c 8.1%–9.0%, and HbA1c >9.0%. After adjusting all other significant predictors, a Cox regression model showed a U-shaped relationship between the two variables with the middle HbA1c category (7.1%–8.0%). This reference was similar to our study. Aguilar et al. performed a study to determine the association between HbA1C and poor outcomes in diabetics with established HF. Mortality was seen in 25% of patients in Q1 (HbA1C ≤6.4), 23% in Q2 (6.4 < HbA1c ≤ 7.1), 17.7% in Q3 (7.1 < HbA1c ≤ 7.8), 22.5% in Q4 (7.8 < HbA1c ≤ 9.0), and 23.2% in Q5 (HbA1c >9.0) after 2 years of follow-up. It was found that the middle quintile (Q3) had the lowest deaths when compared with the other quintile after adjusting significant variables. The relation between two variables in diabetic patients with HF appeared to be U-shaped. Cavero-Redondo et al. performed an analytical study to determine the association between HbA1c levels and outcomes in the form of morbidity, mortality due to cardiac cause, and all-cause mortality. There was an increased risk of all-cause mortality when HbA1c was over 8.0% and 6.0% in diabetic and nondiabetic populations, respectively. They concluded HbA1c as a dependable prognostic marker in both diabetics and nondiabetics either cardiovascular or noncardiovascular cause. The range in this study was from 6.0% to 8.0% in people with diabetes and from 5.0% to 6.0% in those without diabetes forming a U-shaped relation.
There was a stronger relation between outcome and eGFR in HFrEF making it a good prognostic marker in advanced HF, probably due to fact that reduced LVEF leads to reduced cardiac output hence reduced eGFR. It was also observed that lower eGFR at the time of admission was a better predictor of long-term mortality from HF. Based on studies that have compared NT-proBNP with other variables such as an evaluation of symptoms, ejection fractions, and even oxygen uptake, it was observed that NT-proBNP was superior to other variables in predicting the outcome. The knowledge of NT-proBNP level, eGFR, 6MWT, LVEF, and HbA1c permits us to predict the worst outcome. NT-proBNP and 6MWT are easily performed tests that proved to be an excellent prognosis marker for advanced HF patients.
Being a single-center study with a relatively small number of patients, limits the generalization of these results. We were not able to follow up the patients.
| Conclusion|| |
HF is a new emerging epidemic and needs special attention. Advanced HF is challenging to treat, and hence, early diagnosis and treatment can prevent morbidity and mortality in these patients. With the advent of newer treatment modalities, there has been a reduction in mortality rates. Prognosis is most commonly judged by clinical presentation. Hence, there is a need to develop a better prognostic marker for advanced HF. From this study, we conclude that 6MWT and NT-proBNP are efficacious in predicting mortality in advanced HF.
This research study was approved by the Institutional Ethics Committee (IEC) with registration number: DMIMS (DU)/IEC/2018-19/7550.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Crespo-Leiro MG, Metra M, Lund LH, Milicic D, Costanzo MR, Filippatos G, et al.
Advanced heart failure: A position statement of the Heart Failure Association of the European Society of Cardiology. Eur J Heart Fail 2018;20:1505-35.
Pocock SJ, Ariti CA, McMurray JJ, Maggioni A, Køber L, Squire IB, et al.
Predicting survival in heart failure: A risk score based on 39 372 patients from 30 studies. Eur Heart J 2013;34:1404-13.
Pereira-Barretto AC, de Oliveira MT Jr., Strunz CC, Del Carlo CH, Scipioni AR, Ramires JA. Serum NT-proBNP levels are a prognostic predictor in patients with advanced heart failure. Arq Bras Cardiol 2006;87:174-7.
Fonarow GC, Adams KF Jr., Abraham WT, Yancy CW, Boscardin WJ, ADHERE Scientific Advisory Committee, Study Group, and Investigators. Risk stratification for in-hospital mortality in acutely decompensated heart failure: Classification and regression tree analysis. JAMA 2005;293:572-80.
Subramaniam AV, Weston SA, Killian JM, Schulte PJ, Roger VL, Redfield MM, et al.
Development of advanced heart failure: A population-based study. Circ Heart Fail 2022;15:e009218.
Kearney MT, Fox KA, Lee AJ, Prescott RJ, Shah AM, Batin PD, et al.
Predicting death due to progressive heart failure in patients with mild-to-moderate chronic heart failure. J Am Coll Cardiol 2002;40:1801-8.
Bettencourt P, Azevedo A, Pimenta J, Friões F, Ferreira S, Ferreira A. N-terminal-pro-brain natriuretic peptide predicts outcome after hospital discharge in heart failure patients. Circulation 2004;110:2168-74.
Brophy JM, Dagenais GR, McSherry F, Williford W, Yusuf S. A multivariate model for predicting mortality in patients with heart failure and systolic dysfunction. Am J Med 2004;116:300-4.
Metra M, Dinatolo E, Dasseni N. The new heart failure association definition of advanced heart failure. Card Fail Rev 2019;5:5-8.
Gardner RS, Ozalp F, Murday AJ, Robb SD, McDonagh TA. N-terminal pro-brain natriuretic peptide. A new gold standard in predicting mortality in patients with advanced heart failure. Eur Heart J 2003;24:1735-43.
Velibey Y, Golcuk Y, Golcuk B, Oray D, Atilla OD, Colak A, et al.
Determination of a predictive cutoff value of NT-proBNP testing for long-term survival in ED patients with acute heart failure. Am J Emerg Med 2013;31:1634-7.
Scrutinio D, Ammirati E, Passantino A, Guida P, D'Angelo L, Oliva F, et al.
Predicting short-term mortality in advanced decompensated heart failure – Role of the updated acute decompensated heart failure/N-terminal pro-B-type natriuretic Peptide risk score. Circ J 2015;79:1076-83.
Luers C, Sutcliffe A, Binder L, Irle S, Pieske B. NT-proANP and NT-proBNP as prognostic markers in patients with acute decompensated heart failure of different etiologies. Clin Biochem 2013;46:1013-9.
Salah K, Stienen S, Pinto YM, Eurlings LW, Metra M, Bayes-Genis A, et al.
Prognosis and NT-proBNP in heart failure patients with preserved versus reduced ejection fraction. Heart 2019;105:1182-9.
Hartmann F, Packer M, Coats AJ, Fowler MB, Krum H, Mohacsi P, et al.
Prognostic impact of plasma N-terminal pro-brain natriuretic peptide in severe chronic congestive heart failure: A substudy of the Carvedilol Prospective Randomized Cumulative Survival (COPERNICUS) trial. Circulation 2004;110:1780-6.
Shah MR, Hasselblad V, Gheorghiade M, Adams KF Jr., Swedberg K, Califf RM, et al.
Prognostic usefulness of the six-minute walk in patients with advanced congestive heart failure secondary to ischemic or nonischemic cardiomyopathy. Am J Cardiol 2001;88:987-93.
Gu J, Pan JA, Fan YQ, Zhang HL, Zhang JF, Wang CQ. Prognostic impact of HbA1c variability on long-term outcomes in patients with heart failure and type 2 diabetes mellitus. Cardiovasc Diabetol 2018;17:96.
Costanzo MR, Mills RM, Wynne J. Characteristics of “Stage D” heart failure: Insights from the Acute Decompensated Heart Failure National Registry Longitudinal Module (ADHERE LM). Am Heart J 2008;155:339-47.
Lam CS, Teng TK, Tay WT, Anand I, Zhang S, Shimizu W, et al.
Regional and ethnic differences among patients with heart failure in Asia: The Asian sudden cardiac death in heart failure registry. Eur Heart J 2016;37:3141-53.
Dewan P, Jhund PS, Shen L, Petrie MC, Abraham WT, Atif Ali M, et al.
Heart failure with reduced ejection fraction: Comparison of patient characteristics and clinical outcomes within Asia and between Asia, Europe and the Americas. Eur J Heart Fail 2019;21:577-87.
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.
Chopra VK, Mittal S, Bansal M, Singh B, Trehan N. Clinical profile and one-year survival of patients with heart failure with reduced ejection fraction: The largest report from India. Indian Heart J 2019;71:242-8.
Tavazzi L, Senni M, Metra M, Gorini M, Cacciatore G, Chinaglia A, et al.
Multicenter prospective observational study on acute and chronic heart failure: One-year follow-up results of IN-HF (Italian Network on Heart Failure) outcome registry. Circ Heart Fail 2013;6:473-81.
Elder DH, Singh JS, Levin D, Donnelly LA, Choy AM, George J, et al.
Mean HbA1c and mortality in diabetic individuals with heart failure: A population cohort study. Eur J Heart Fail 2016;18:94-102.
Aguilar D, Bozkurt B, Ramasubbu K, Deswal A. Relationship of hemoglobin A1C and mortality in heart failure patients with diabetes. J Am Coll Cardiol 2009;54:422-8.
Cavero-Redondo I, Peleteiro B, Álvarez-Bueno C, Rodriguez-Artalejo F, Martínez-Vizcaíno V. Glycated haemoglobin A1c as a risk factor of cardiovascular outcomes and all-cause mortality in diabetic and non-diabetic populations: A systematic review and meta-analysis. BMJ Open 2017;7:e015949.
[Figure 1], [Figure 2], [Figure 3]
[Table 1], [Table 2], [Table 3]