Abstract
Background and Objectives
Although an inverse correlation between the level of amino (N)-terminal pro-brain natriuretic peptide (NT-proBNP) and body mass index (BMI) has been reported, the impact of BMI on the prognostic value of NT-proBNP has not been well addressed.
Methods
A total of 1,877 patients (67-year-old and 49.9% females) hospitalized for acute heart failure (HF) with documented NT-proBNP levels at baseline were included. Patients were classified into 2 groups by BMI (nonobese: BMI<23 kg/m2 and overweight or obese: BMI≥23 kg/m2). Clinical events during the follow-up including all-cause mortality and HF readmission were assessed.
Results
During the median follow-up of 828 days (interquartile range, 111–1,514 days), there were 595 cases of total mortality (31.7%), 600 cases of HF readmission (32.0%), and 934 cases of composite events (49.8%). In unadjusted analyses, higher NT-proBNP level was associated with all-cause mortality and composite events (all-cause mortality and HF readmission) in both patients with BMI<23 kg/m2 and those with BMI≥23 kg/m2. In adjusted analyses controlling for potential confounders, however, a higher NT-proBNP level was associated with all-cause mortality and composite events in patients with BMI<23 kg/m2, but not in those with BMI≥23 kg/m2.
Conclusions
The prognostic value of NT-proBNP was more significant in nonobese patients than in overweight and obese patients in this HF population. BMI should be considered when NT-proBNP is used for risk estimation in HF patients.
Keywords: Body mass index, Heart failure, NT-proBNP, Prognosis, Obesity
INTRODUCTION
Although methods for the prevention and management of heart failure (HF) have been much improved during recent several decades, HF is highly prevalent and HF outcome is still poor.1) Obesity is one of the risk factors for cardiovascular disease and HF.2) The prevalence of obesity is constantly increasing, and it becomes a major public health concern globally.3) As a cardiac biomarker, the diagnostic and prognostic value of amino (N)-terminal pro-brain natriuretic peptide (NT-proBNP) is well established.4),5),6) Recently, inverse relationship between NT-proBNP and body mass index (BMI) has been reported.7),8) Decreased production and increased clearance of natriuretic peptide in obese patients has been suggested as possible mechanisms.9),10),11) On this background, it can be postulated that the prognostic utility of NT-proBNP may differ between obese and nonobese patients, which have also raised concerns about the prognostic value of NT-proBNP in obese patients with HF. However, it is not well-determined whether the prognostic power of NT-proBNP is modified by BMI. Although there are several observational studies on this issue, most studies are performed in Western countries, and their results are still conflicting.12),13),14) Therefore, this study was performed to investigate the effect of BMI on the predictive value of NT-proBNP in Korean patients with HF.
METHODS
Study population
Study data was derived from the Korean Heart Failure (KorHF) Registry, which included participation of 24 well-qualified cardiac centers in Korea. Information regarding the KorHF Registry has previously been described.15) Briefly, patients hospitalized for HF between June 2004 and April 2009 were enrolled in the registry. HF on admission was diagnosed according to the Framingham criteria,16) and the diagnosis was confirmed at the time of hospital discharge. Patients' data was entered into the KorHF Registry database via a web-based electronic data capture system that included an electronic case report form.15) Data collection and audition were performed by the KorHF Registry Steering Committee at the Korean Society of HF. Among 3,427 patients with HF initially screened, both BMI and NT-proBNP were available in 2,280 (66.5%), who were analyzed in this study. This study complies with the Declaration of Helsinki, and the Institutional Review Board (IRB) at each participating hospital approved the study protocol (IRB number of Boramae Medical Center was 07-2019-39). Written informed consent was obtained from each study patient.
BMI criteria
Patient's height and body weight were measured at the time of admission. BMI was calculated by dividing weight in kilograms by height squared in meters. For Korean population, there is an increase in morbidity from the BMI of 23 kg/m2 and an increase in mortality from the BMI of 25 kg/m2. According to the Korean guideline, overweight is defined as a BMI of 23 to 24.9 kg/m2, and obesity as a BMI≥25 kg/m2.17) As only 28.9% of the patients had a BMI≥25 kg/m2, we used a BMI of 23 kg/m2 for the stratification in this study. About half of patients (48.4%) had BMI of≥23 kg/m2 in this study.
Data collection
Systolic and diastolic blood pressures and heart rate were measured by a trained nurse using an oscillometric device. Information on previous medical history or concomitant medical problems including HF, myocardial infarction, chronic kidney disease, hypertension and diabetes mellitus was obtained. HF was classified etiologically as ischemic or non-ischemic. Major laboratory parameters suggested as prognostic markers in HF were measured using venous blood sample. These parameters included hemoglobin, blood urea nitrogen, creatinine and sodium. Transthoracic echocardiography was performed, and left ventricular (LV) dimensions, LV ejection fraction and left atrial size were measured according to the current guidelines.18) Medications at the time of discharge were also reviewed, and information on the use of beta-blocker, renin-angiotensin system-blockers including angiotensin-converting enzyme inhibitor and angiotensin II receptor blocker was collected.
NT-proBNP testing
NT-proBNP was measured at the time of admission with the electro-chemiluminescence immunoassay method using an Elecsys 2010 analyzer (Roche Diagnostics, Basel, Switzerland) or NT-proBNP assay for Dimension platform, Siemens Medical Solutions Diagnostics.19)
Clinical events
Two types of clinical events were focused in this study, which included all-cause mortality and composite events including all-cause mortality and HF readmission during the follow-up. Clinical events were assessed by research coordinators through reviewing medical records and telephone contact was performed if needed, using the standardized report form. HF readmission was defined as hospitalization for clinical manifestations of worsening HF resulting in the new administration of intravenous drugs, mechanical or surgical intervention, or hemodialysis for the management of HF.
Statistical analysis
Continuous variables are presented as mean±standard deviation, and categorical variables are expressed as percentages. Univariate comparisons between patients with BMI≥23 kg/m2 and those with BMI<23 kg/m2 were performed using Student's t-test for continuous variables and the χ2 test for dichotomous variables. The mean values of NT-proBNP were compared among patients according to the BMI criteria using analysis of variance. Scatter plots were used to demonstrate correlation between log-transformed NT-proBNP and BMI. Correlation coefficients were obtained using Pearson's correlation. Cox proportional hazard analysis was performed to determine independent associations of NT-proBNP with mortality and composite events after discharge. The following variables were considered potential confounders and adjusted during the multivariable analyses: age, systolic blood pressure, heart rate, hypertension, ischemic etiology of HF, blood levels of hemoglobin, sodium, and creatinine, LV ejection fraction, and medications including beta-blocker and renin-angiotensin system blocker. Kaplan-Meier survival curves with log-rank comparison were plotted to demonstrate different event rates according to NT-proBNP values in patients with BMI≥23 kg/m2 and those with BMI<23 kg/m2. For adjustment for confounding factors, Cox regression survival plots were generated. NT-proBNP was categorized into 3 groups based on tertiles during multivariable analysis and Kaplan-Meier survival analysis. A p value of <0.05 was considered statistically significant. All statistical analyses were conducted using SPSS version 18.0 (IBM Corp., Armonk, NY, USA).
RESULTS
Baseline clinical characteristics of the study patients
The baseline clinical characteristics of the study patients according to BMI are shown in Table 1. Patients with BMI≥23 kg/m2 were older, male dominant and had worse cardiovascular risk profiles including higher blood pressure, and higher prevalence of hypertension and diabetes mellitus than those with BMI<23 kg/m2. Beta-blocker and RAS blocker were more frequently prescribed to patients with BMI≥23 kg/m2 than to those with BMI < 23 kg/m2. The NT-proBNP levels were significantly higher in patients with BMI≥23 kg/m2 than in those with BMI<23 kg/m2 (6,259±8,086 vs. 9,690±10,238 pg/mL, p<0.001). There was an inverse relationship between the NT-proBNP level and BMI (p<0.001) (Figure 1).
Table 1. Baseline characteristics of study patients.
| Characteristic | BMI<23 kg/m2 (n=968) | BMI≥23 kg/m2 (n=909) | p value | |
|---|---|---|---|---|
| Age (years) | 70.1±13.4 | 64.3±14.5 | <0.001 | |
| Female (sex) | 54.9 | 44.7 | <0.001 | |
| Systolic blood pressure (mmHg) | 129±29 | 133±29 | <0.001 | |
| Diastolic blood pressure (mmHg) | 76.7±16.8 | 79.8±19.0 | <0.001 | |
| Heart rate (beat/min) | 91.6±25.4 | 88.7±25.5 | 0.016 | |
| Combined medical conditions | ||||
| Hypertension | 43.2 | 53.4 | <0.001 | |
| Diabetes mellitus | 27.9 | 34.3 | 0.003 | |
| Previous heart failure | 32.2 | 29.5 | 0.238 | |
| Previous myocardial infarction | 16.1 | 15.2 | 0.578 | |
| Underlying conditions | 0.041 | |||
| Ischemic | 39.5 | 35.2 | ||
| Non-ischemic | 48.7 | 49.5 | ||
| Unknown | 11.9 | 15.3 | ||
| Laboratory findings | ||||
| Hemoglobin (g/dL) | 12.0±2.2 | 12.9±2.3 | <0.001 | |
| Blood urea nitrogen (mg/dL) | 24.8±15.1 | 23.4±14.5 | 0.049 | |
| Creatinine (mg/dL) | 1.47±1.33 | 1.47±1.30 | 0.964 | |
| Sodium (mEq/L) | 138±5 | 139±4 | 0.060 | |
| NT-proBNP (pg/mL) | 9,690±10,238 | 6,259±8,086 | <0.001 | |
| Echocardiographic findings | ||||
| LV end-diastolic dimension (mm) | 57.2±10.3 | 57.8±10.1 | 0.001 | |
| LV end-systolic dimension (mm) | 44.3±12.1 | 43.9±12.2 | 0.354 | |
| LV ejection fraction (%) | 38.8±15.5 | 40.2±16.2 | 0.063 | |
| Left atrial size (mm) | 56.6±28.9 | 56.8±30.1 | 0.001 | |
| Medications at discharge | ||||
| Beta-blocker | 38.5 | 45.1 | 0.010 | |
| Renin-angiotensin system blocker | 45.8 | 51.9 | 0.008 | |
Data are expressed as the mean±standard deviation or number (%).
BMI = body mass index; NT-proBNP = N-terminal pro-B-type natriuretic peptide; LV = left ventricular.
Figure 1. Association between BMI and NT-proBNP. (A) The mean value of NT-proBNP according to the category of BMI, (B) scatter plot showing the negative correlation between BMI and log (NT-proBNP) concentration.
NT-proBNP = amino (N)-terminal pro-brain natriuretic peptide; BMI = body mass index; ANOVA = analysis of variance.
Prognostic value of NT-proBNP according to BMI
During the median follow-up of 828 days (interquartile range, 111–1,514 days), there were 595 cases of all-cause mortality (31.7%), 600 cases of HF readmission (32.0%), and 934 cases of composite events (49.8%). Unadjusted and adjusted risks of NT-proBNP for mortality are demonstrated in Table 2. In unadjusted analyses, a higher NT-proBNP level was associated with increased mortality risk in the total population, and in both patients with BMI<23 kg/m2 and BMI≥23 kg/m2. In adjusted analyses controlling for potential confounders, a higher NT-proBNP level was associated with increased mortality risk in the total population (highest vs. lowest tertile; hazard ratio [HR], 1.76; 95% confidence interval [CI], 1.34–2.31; p<0.001) and in patients with BMI<23 kg/m2 (highest vs. lowest tertile; HR, 2.24; 95% CI, 1.54–3.25; p<0.001) but not in those with BMI≥23 kg/m2 (p>0.05). Unadjusted and adjusted risks of NT-proBNP for composite events is shown in Table 3. In unadjusted analyses, a higher NT-proBNP level was associated with increased composite event risk in the total population, and in both patients with BMI<23 kg/m2 and BMI≥23 kg/m2. In adjusted analyses controlling for potential confounders, a higher NT-proBNP level was associated with increased composite event risk in the total population (highest vs. lowest tertile; HR, 1.39; 95% CI, 1.12–1.72; p=0.002) and in patients with BMI<23 kg/m2 (highest vs. lowest tertile; HR, 1.50; 95% CI, 1.12–2.00; p=0.006) but not in those with BMI≥23 kg/m2 (p>0.05). Kaplan-Meier curves demonstrates different prognostic value of NT-proBNP in mortality and composite events (Figure 2) according to BMI. Differences in survival and event-free survival rates according to NT-proBNP tertiles were more obvious in patients with BMI<23 kg/m2 than in those with BMI≥23 kg/m2. Even after controlling for the effects of potential confounders, prognostic value of NT-proBNP in the prediction of survival was greater in in patients with BMI<23 kg/m2 than in those with BMI≥23 kg/m2 (Figure 3).
Table 2. Unadjusted and adjusted risk of NT-proBNP for mortality.
| Subgroup | Unadjusted | Adjusted* | |||
|---|---|---|---|---|---|
| HR (95% CI) | p value | HR (95% CI) | p value | ||
| Total population | |||||
| Lowest tertile (2–2,467 pg/mL) | 1 | 1 | |||
| Middle tertile (2,470–7,295 pg/mL) | 1.28 (1.08–1.53) | 0.004 | 1.19 (0.91–1.56) | 0.185 | |
| Highest tertile (7,309–35,000 pg/mL) | 1.80 (1.52–2.14) | <0.001 | 1.76 (1.34–2.31) | <0.001 | |
| BMI<23 kg/m2 | |||||
| Lowest tertile (13–3,165 pg/mL) | 1 | 1 | |||
| Middle tertile (3,166–9,800 pg/mL) | 1.30 (1.03–1.64) | 0.023 | 1.46 (1.02–2.07) | 0.035 | |
| Highest tertile (9,838–35,000 pg/mL) | 1.98 (1.58–2.48) | <0.001 | 2.24 (1.54–3.25) | <0.001 | |
| BMI≥23 kg/m2 | |||||
| Lowest tertile (2–1,947 pg/mL) | 1 | 1 | |||
| Middle tertile (1,957–5,596 pg/mL) | 1.38 (1.06–1.80) | 0.016 | 1.19 (0.77–1.82) | 0.417 | |
| Highest tertile (5,609–35,000 pg/mL) | 1.57 (1.21–2.05) | 0.001 | 1.27 (0.82–1.98) | 0.278 | |
HR = hazard ratio; CI = confidence interval; BMI = body mass index; NT-proBNP = N-terminal pro-B-type natriuretic peptide.
*Adjusted for age, sex, systolic blood pressure, heart rate, hypertension, ischemic etiology of heart failure, blood level of hemoglobin, sodium, and creatinine, left ventricular ejection fraction, and medications including beta-blocker and renin-angiotensin system blocker.
Table 3. Unadjusted and adjusted risk of NT-proBNP for composite events.
| Subgroup | Unadjusted | Adjusted* | |||
|---|---|---|---|---|---|
| HR (95% CI) | p value | HR (95% CI) | p value | ||
| Total population | |||||
| Lowest tertile (2–2,467 pg/mL) | 1 | 1 | |||
| Middle tertile (2,470–7,295 pg/mL) | 1.41 (1.11–1.78) | 0.004 | 1.19 (0.97–1.45) | 0.087 | |
| Highest tertile (7,309–35,000 pg/mL) | 2.21 (1.76–2.77) | <0.001 | 1.39 (1.12–1.72) | 0.002 | |
| BMI<23 kg/m2 | |||||
| Lowest tertile (13–3,165 pg/mL) | 1 | 1 | |||
| Middle tertile (3,166–9,800 pg/mL) | 1.70 (1.26–2.29) | <0.001 | 1.11 (0.84–1.45) | 0.452 | |
| Highest tertile (9,838–35,000 pg/mL) | 2.81 (2.11–3.75) | <0.001 | 1.50 (1.12–2.00) | 0.006 | |
| BMI≥23 kg/m2 | |||||
| Lowest tertile (2–1,947 pg/mL) | 1 | 1 | |||
| Middle tertile (1,957–5,596 pg/mL) | 1.21 (0.82–1.77) | 0.324 | 1.30 (0.96–1.77) | 0.082 | |
| Highest tertile (5,609–35,000 pg/mL) | 1.86 (1.29–2.68) | 0.001 | 1.16 (0.83–1.63) | 0.360 | |
HR = hazard ratio; CI = confidence interval; BMI = body mass index; NT-proBNP = N-terminal pro-B-type natriuretic peptide.
*Adjusted for age, sex, systolic blood pressure, heart rate, hypertension, ischemic etiology of heart failure, blood level of hemoglobin, sodium, and creatinine, left ventricular ejection fraction, and medications including beta-blocker and renin-angiotensin system blocker.
Figure 2. Kaplan-Meier survival curves showing survival and event-free survival rates according to NT-proBNP tertiles. Survival rates in patients with BMI<23 kg/m2 (A) and those with BMI≥23 kg/m2 (B), and event-free survival rates in patients with BMI<23 kg/m2 (C) and those with BMI≥23 kg/m2 (D).
NT-proBNP = amino (N)-terminal pro-brain natriuretic peptide; BMI = body mass index.
Figure 3. Cox plots showing survival rates according to NT-proBNP tertiles in patients with BMI<23 kg/m2 (A) and those with BMI≥23 kg/m2 (B) after adjustment for confounding clinical covariates. Clinical covariates adjusted were age, sex, systolic blood pressure, heart rate, hypertension, ischemic etiology of heart failure, blood level of hemoglobin, sodium, and creatinine, left ventricular ejection fraction, and medications including beta-blocker and renin-angiotensin system blocker.
NT-proBNP = amino (N)-terminal pro-brain natriuretic peptide; BMI = body mass index.
DISCUSSION
Considering the increasing prevalence of both obesity and HF, understanding the relationship between BMI and the prognostic value of NT-proBNP is essential. Using the nation-wide HF registry, present study showed that there was an inverse relationship between BMI and NT-proBNP. More importantly, our data demonstrated that the prognostic value of NT-proBNP was greater in HF patients with BMI<23 kg/m2 than in those with BMI≥23 kg/m2. This result provides additional evidence regarding an influence of BMI on the utility of the NT-proBNP assay for the prognosis of patients with HF.
Previous studies indicated that the NT-proBNP level is lower in patients with higher BMI than in those with normal or lower BMI.7),8) Our data also confirmed that the NT-proBNP level decreased in relation to increase in BMI. Underlying pathophysiology for the association between obesity and lower NT-proBNP level is not fully defined. As possible mechanisms, it has been suggested that release of natriuretic peptide decreased from the heart,9),10) while clearance of this biomarker increased in obese patients.11) Additional studies are needed to identify clear mechanisms why the NT-proBNP level is low in obese individuals.
It has been clearly demonstrated that NT-proBNP is a strong prognostic marker for worse cardiovascular outcomes in HF patients.4),5),6) However, most of these studies did not consider the BMI effect. Similar findings were also obtained from our study in the total HF patients without stratification by BMI; NT-proBNP concentrations were well able to identify those at high risk for worse cardiovascular outcome. However, when we stratified study patients into 2 groups according to BMI (<23 kg/m2 vs. ≥23 kg/m2), prognostic value of NT-proBNP was different between the 2 groups. Similar finding was reported in the other study. In 8,217 patients with chronic HF, Nadruz et al.12) showed that the ability of NT-proBNP to predict prognosis was attenuated in moderately or severe obese patients. In contrast, Bayes-Genis et al.13) showed that the prognostic value of NT-proBNP remained irrespective of BMI categories. In that study, however, they included patients who presented with dyspnea in the emergency department rather than those with confirmed HF, the number of enrolled patients was smaller (n=1,103) than in ours (n=2,280), and multivariate analysis differed from ours in that only age and sex were corrected. Another study including patients with decompensated HF found that the prognostic value of NT-proBNP was not modified by BMI.14) However, it should be cautious to interpret the results because our study also involved a relatively small number of patients (n=686), and the duration of follow-up of clinical events was also short (=180 days).
Considering high prevalence and poor prognosis of HF, risk stratification using reliable biomarkers is very important for individualized therapy. For this, it is first necessary to know in what circumstances the utility of NT-proBNP is maximized, and in what circumstances the effectiveness of the biomarker is reduced. Because HF and obesity continue to increase globally, HF is highly prevalent in obese patients,20) and the use of NT-proBNP is widely spread, it is very important for clinicians to understand the possible confounding impact of obesity on the validity of NT-proBNP for the adequate application of this biomarker. Finding the underlying mechanisms explaining lower level and prognostic value of NT-proBNP in overweight and obese patients may provide an important step in understanding the cardiovascular risk of obesity. Because the NT-proBNP level is low in patients with greater BMI, diagnosis of HF in obese individuals with NT-proBNP alone will increase false negative rate. In addition, the finding of lower prognostic value of NT-proBNP in overweight and obese patients has raised question whether NT-proBNP could work as a prognostic marker in patients with high BMI. For the physician using NT-proBNP to estimate the risk of HF patients, it would be better to avoid making an important decision only with NT-proBNP concentration especially in overweight and obese patients. Other prognostic biomarkers such as troponin or ST2, and echocardiographic parameters, such as LV ejection fraction or E/e′ should be combined to ascertain the correct estimation of long-term cardiovascular outcomes.
There are several limitations in this study. There might be some selection bias because only HF patients who were hospitalized were included in this study. In addition, only 66.5% of patients with available data on BMI and NT-proBNP were selected in our study. The lack of information on central obesity and BMI change during hospitalization is another limitation to this study. Also, mechanisms explaining the less prognostic value of NT-proBNP in patients with higher BMI could not be suggested. Finally, patients in our study are all Koreans, and thus, our results may be difficult to apply to other ethnic groups.
The prognostic value of NT-proBNP was greater in nonobese than in overweight and obese Korean patients with HF. BMI should be considered NT-proBNP is used for risk estimation in this population. Further studies are needed to confirm our findings.
Footnotes
Conflict of Interest: The authors have no financial conflicts of interest.
- Conceptualization: Kim HL, Kim MA.
- Data curation: Oh S, Choi DJ, Han S, Jeon ES, Cho MC, Kim JJ, Yoo BS, Shin MS, Kang SM, Chae SC, Ryu KH.
- Formal analysis: Kim HL, Oh S.
- Resources: Choi DJ, Jeon ES, Cho MC, Ryu KH.
- Supervision: Kim MA.
- Validation: Kim MA.
- Writing - original draft: Kim HL.
- Writing - review & editing: Han S, Kim JJ, Yoo BS, Shin MS, Kang SM, Chae SC.
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