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 Table of Contents  
ORIGINAL ARTICLE
Year : 2019  |  Volume : 7  |  Issue : 2  |  Page : 49-54

Role of B-type natriuretic peptide level in predicting future cardiac events in patients presenting with dyspnea (a hospital-based study)


Department of General Medicine, Institute of Medical Sciences, Banaras Hindu University, Varanasi, Uttar Pradesh, India

Date of Web Publication28-Jun-2019

Correspondence Address:
Dr. Lalit Prashant Meena
Department of General Medicine, Institute of Medical Sciences, Banaras Hindu University, Varanasi - 221 005, Uttar Pradesh
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/heartindia.heartindia_17_19

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  Abstract 


Introduction: Acute dyspnea is one of the most common reasons for admission to emergency rooms. Differentiation of heart failure (HF) from other causes of shortness of breath is often difficult but compulsory. Natriuretic peptides are present in higher concentration in patients with HF and have a potential diagnostic role. The decline in B type natriuretic peptide (BNP) levels subsequent to the treatment of acute HF could predict the future risk of HF and/or cardiac event.
Materials and Methods: This was an in-hospital longitudinal study conducted on adult patients presenting with acute dyspnea to the Department of General Medicine in our institution from January 1, 2016, to December 31, 2016. Eligible patients were followed up over a period of the next 6 months from their day of the first visit. Patients presenting with acute dyspnea were selected. Patients were evaluated using predetermined pro forma including history, physical examination, blood investigations, electrocardiography, chest X-ray, BNP analysis, and two-dimensional echo. BNP levels of the patients with BNP >500 pg/ml at the time of admission were again measured at the time of discharge, and these patients were followed up for 6 months for any endpoint.
Results: This study of 100 participants gives insight about common etiologies among the patients presenting with acute dyspnea in which HF is a competing diagnosis. In the study, a BNP cutoff of 413 pg/ml determines cardiogenic dyspnea. Out of 60 patients with BNP >500 pg/ml at admission, 22 patients had at least 1 endpoint by the end of 6 months. Cutoff for determination of an endpoint for BNP at admission and BNP at discharge was 1298 and 367.5 pg/ml, respectively.
Conclusion: The study showed that BNP at admission and BNP at discharge determines prognosis in patients presenting with dyspnea. The study shows BNP as a better predictor of prognosis than ejection fraction or past history of any cardiac event.

Keywords: B-type natriuretic peptide, cardiac events, dyspnea


How to cite this article:
Saha S, Meena LP, Chakravarty J, Rai M. Role of B-type natriuretic peptide level in predicting future cardiac events in patients presenting with dyspnea (a hospital-based study). Heart India 2019;7:49-54

How to cite this URL:
Saha S, Meena LP, Chakravarty J, Rai M. Role of B-type natriuretic peptide level in predicting future cardiac events in patients presenting with dyspnea (a hospital-based study). Heart India [serial online] 2019 [cited 2019 Aug 22];7:49-54. Available from: http://www.heartindia.net/text.asp?2019/7/2/49/261832




  Introduction Top


Acute dyspnea is one of the most common reasons for admission to emergency rooms. Numerous disorders cause dyspnea, including acute heart failure syndrome (AHFS), acute exacerbation of chronic obstructive pulmonary disease (COPD), asthma, pulmonary embolism, pneumonia, metabolic acidosis, neuromuscular weakness, and others. Differentiation of HF from other causes of shortness of breath is often difficult but compulsory. In the condition of HF, where there is a clinical need for early and appropriate treatment, but no objective method for a rapid and accurate diagnosis exists, the potential benefits for any biomarker that can reliably rule in or rule out this syndrome may be enormous. Natriuretic peptides are known to be present in higher concentration in patients with HF and therefore have a potential diagnostic role. The cardiac natriuretic peptides consist of atrial natriuretic peptide, brain natriuretic peptide, and their associated metabolites. BNP is initially formed as a 134-amino acid precursor known as pre-pro-BNP and subsequently converted to the active 32-amino acid BNP which corresponds to the C-terminal sequence and a 76-amino acid N-terminal fragment, N-terminal prohormone BNP. Several well-designed studies have demonstrated the usefulness of circulating natriuretic peptide assays in the assessment of dyspnea. Among them, B type natriuretic peptide (BNP) qualifies all criteria for ideal biomarker.[1],[2] Despite the fact that the gold standard for diagnostic testing for congestive HF (CHF) is two-dimensional (2D) echocardiography with color Doppler, this test is rarely available in acute care settings such as emergency departments (EDs) and urgent care centers, especially in our resource-poor country. Due to the limitations in access to Doppler echocardiography, BNP testing is a cost-effective and suitable alternative in acute care settings. One study concluded that “plasma BNP levels are found to be significantly correlated with conventional echocardiographic parameters.”[3] Harrison et al. evaluated whether B-type natriuretic peptide predicts future cardiac events in patients presenting to the ED with dyspnea.[4] A multicenter Italian (8 centers) observational study with 287 patients which showed a reduction of BNP >46% at hospital discharge compared to the admission levels coupled with a BNP absolute value <300 pg/mL seems to be a very powerful negative prognostic value for future cardiovascular outcomes in patients hospitalized with acute decompensated HF (ADHF).[5]

The decline in BNP levels subsequent to the treatment of AHF could predict the future risk of HF and/or cardiac event. However, no such study has been done in our setting. There is also a lack of any universal cutoff value of BNP which can predict future risk of cardiac events in patients presenting with dyspnea.


  Materials and Methods Top


This was an in-hospital longitudinal study conducted on adult patients presenting with acute dyspnea to the Department of General Medicine, Sir Sunder Lal Hospital, Institute of Medical Sciences, BHU, Varanasi, between January 1, 2016, and December 31, 2016. Eligible patients were followed up over a period of the next 6 months from their day of the first visit. The study included males and females >18 years of age presenting with dyspnea as a prominent complaint willing to participate in the study. Patients whose dyspnea is clearly as a result of trauma (e.g., knife wounds, cardiac tamponade, and pneumothorax) with unstable angina or acute myocardial infarction (determined by electrocardiography [ECG] changes and cardiac enzymes), unless their predominant presentation is that of dyspnea; with chronic kidney disease; with other comorbidities (e.g., malignancy) that may affect 6 months survival of the patient; and not willing to participate in the study were excluded from the study. Patients presenting with acute dyspnea were selected. Patients were evaluated using predetermined pro forma. A brief history with special emphasis on the duration of dyspnea, presence or absence of orthopnea and paroxysmal nocturnal dyspnea, palpitation, chest pain, and pedal edema was taken. Any past history of CHF, hypertension, coronary artery disease (CAD), and coronary artery bypass graft was revealed. A history suggestive of risk factors for COPD such as smoking, cooking on smoky chulha, and any occupational exposure was taken along with drug history. History taking was followed by thorough general and systemic examination with special emphasis on examination of the chest and cardiovascular system. All these patients were subjected to routine blood investigations, digital chest X-ray, and 12-lead ECG. Patients presenting to ED with the obvious known pulmonary cause of dyspnea such as bronchial asthma and COPD with acute exacerbations, pleural effusion, and pneumonia were excluded from the study. Rest of the patients in which the possibility of HF cannot be ruled out were taken into the study, and BNP estimation of the patients was done at this point.

At the same time point of care, B type natriuretic peptide (BNP) was done in each patient after taking informed written consent from the patient. If a patient was not able to give written consent, then it was taken from a legal guardian. All patients with HF underwent 2D echocardiography (ECHO) with color Doppler. The cardiologist doing ECHO was blinded of the BNP result but had access to the chest X-ray along with other investigations. All the willing patients were admitted and treated as per the diagnosis of the case made by the physician based on clinical details (present and past history along with physical examination) and other relevant investigations. A physician was be blinded to the initial BNP level. BNP levels of the patients with BNP >500 at the time of admission were again measured at the time of discharge, and these patients were followed up for 6 months from the time of presentation. Follow-up was either by clinic visit or telephone call if no contact had occurred within the 6-month period.

Endpoints were defined as death (any cardiac, noncardiac, and CHF), hospital admissions (any cardiac and CHF), and repeat ED visits for CHF. A CHF endpoint was defined as CHF death, admission, or repeat ED visit. A cardiac endpoint was defined as a cardiac (including CHF) death or admission. CHF admissions were determined by a cardiologist (blinded to BNP values). The same was done for cardiac admissions such as CHF, acute myocardial infarction, arrhythmias, angina, and CAD. The cause of death was determined by autopsy report if present, clinical scenario leading up to death (reviewed by a cardiologist blinded to BNP values), and death certificate if the previous data are not available.

Statistical analysis

Statistical analysis was done using SPSS version 16.0 (SPSS Inc., Chicago, IL, USA). Evaluation of patients with acute dyspnea in ED was done. The data were captured to evaluate the utility of BNP measurements as a prognostic indicator of future cardiac events. For this purpose, receiver operating characteristic (ROC) curves were used to determine the sensitivity, specificity, and accuracy of these BNP levels for risk stratification.


  Results Top


This study of 100 participants gives useful insight about the common etiologies among the patients presenting with acute dyspnea in which HF is a competing diagnosis. Among these patients, myocardial dysfunction (25%) resulting in reduced ejection fraction (EF) was the most common cause of dyspnea, followed by valvular heart disease (18%) and anemia (16%), respectively [Figure 1]. Mean age of the patients was 42.09 years, with a standard deviation (SD) of 16.003 years. Most of the patients were male (53) as compared to female (47). In the study, a BNP cutoff of 413 (confidence interval [CI]: 95% and P < 0.001, the area under the curve was 0.997) has a sensitivity 95.3% and a specificity 100% to determine a cardiogenic cause of dyspnea [Figure 2]. Patients with BNP >500 had higher mean EF as compared to patients with BNP level <500 (46.07% versus 54.10% EF). Out of 60 patients, most of the patients were male, with a percentage of 56.7% (n = 34) [Table 1]. Out of 60 patients, 22 patients had at least 1 endpoint by the end of 6 months. Rest of the patients had an uneventful follow-up. Most commonly noticed endpoint was CHF observed in 11 patients (50% of patients with endpoint) [Table 2]. Most of the patients with endpoint had valvular heart disease as the primary etiology (59%) leading to dyspnea [Table 3]. Cutoff for determination of an endpoint for BNP at admission and BNP at discharge was 1298 (sensitivity 95.5%, specificity 94.7%) and 367.5 (sensitivity 95.5%, specificity 94.7%), respectively, with CI 95% and P < 0.001. Cutoff for determination of death for BNP at admission and BNP at discharge was 1697 (sensitivity: 80%, specificity: 74.5%) and 664 (sensitivity: 80%, specificity: 80%), respectively, with CI 95% and P < 0.001. All the patients having CHF endpoint had a BNP >1298 at the time of admission and a BNP >367 at discharge. Only 1 patient with BNP <1298 at the time of admission and BNP <367 had endpoint in the form of noncardiac death representing that all cardiac endpoints occurred in patients with BNP at admission >1298 and BNP at discharge >367 [Figure 3]. ROC curve for EF in relation to endpoint with CI 95%, the area under the curve being 0.549 at P = 0.529. Optimum value of EF is 44% (sensitivity: 68.2%, specificity: 42.1%) [Figure 4].
Figure 1: Etiology of patients presenting with dyspnea

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Figure 2: Receiver operating characteristic curve for BNP at admission in relation to cardiac dyspnea

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Table 1: Mean and standard deviation values of important variables (brain natriuretic peptide >500)

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Table 2: Frequencies of various endpoints

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Table 3: Etiology of patients having an endpoint

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Figure 3: Receiver operating characteristic curve for BNP at admission and BNP at discharge in relation to endpoint

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Figure 4: Receiver operating characteristic curve for ejection fraction in relation to endpoint

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  Discussion Top


One of the most common reasons for in-hospital admissions, especially to ED and acute care units, is acute dyspnea. This study gives us useful insight into the prognostic role of BNP in acute care settings and in the follow-up period and manages accordingly. According to previous studies, the prevalence of common diseases which cause dyspnea in the general population was 2%, 5%–10%, and 5% for CHF, COPD, and asthma, respectively.[6],[7] Depending on the hospital setting, AHFSs account for 30%–70% of acute dyspnea in the ED.[8] This study showed myocardial dysfunction (25%) resulting in reduced EF as the most common cause of dyspnea, followed by valvular heart disease (18%). Other common etiologies were anemia (16%), sepsis (10%), acute respiratory distress syndrome (9%), hypertensive HF, myocarditis, congenital heart disease, cor pulmonale, thyrotoxicosis with atrial fibrillation, and pulmonary embolism. There were no obvious pulmonary causes of dyspnea as these patients were excluded from the study. According to previous studies, most were male (95%), with an average age of 65 years.[4] In Italian RED study, 118 patients out of 247 were male and rest 129 were female, and the mean age was 76 years.[5] In our study, most of the patients were male, with a percentage of 53% (n = 53). Mean age of the patients was 42.09 years and SD was 16.003 years. In this study, the cutoff point for detection of cardiogenic dyspnea was at 413 pg/ml with a sensitivity of 95.3% and specificity of 100%, almost similar to the previous study. Out of total 100 patients, 60 patients had BNP >500 pg/ml at the time of admission. These patients were followed up for 6 months to look for endpoints. Among these patients, 25 patients (41.7%) had myocardial dysfunction leading to reduced EF as the primary etiology of dyspnea, followed by valvular heart disease (30%). Only 1 patient each had congenital heart disease and severe anemia as a cause of dyspnea.

In our study, among the patients with BNP at admission >500 pg/ml, mean EF was 46.07% and SD was 10.243%. Mean BNP at admission was 1383.70 pg/ml and mean BNP at discharge was 574.47 pg/ml. In Italian RED study, BNP median (interquartile range [IQR]) value at admission was 822 (412–1390) pg/mL and at discharge was 325 (160–725).[5] In our study, median values for BNP at admission and BNP at discharge were 949 (IQR = 849.50–1829) pg/ml and 273 (IQR = 221.25–679) pg/ml, respectively. Thirty-five patients (58.3%) in the study had no associated comorbidity. Twelve patients suffered from hypertension (20%). In the study by Harrison et al., an equal number of patients had histories of pulmonary disease (40%) and CHF (41%), and 18% of patients had histories of both pulmonary disease and CHF.[4] In a study by Boldanova et al., history allowed the identification of 64 patients (14%) with and 388 patients (86%) without a history of HF.[2] We mainly followed the patients with BNP >500 pg/ml, i.e., with HF. In our population, 68.3% had no significant past history, 16.7% had a past history of HF and only 5% of patients had a previous history of pulmonary disease. The study also revealed no significant difference in the occurrence of endpoints between the groups with or without any significant past history, P = 0.081. In Italian RED study, there were 78 events (27.1%) out of 287 patients.[5] We had 22 events (36.67%) out of 60 patients. 63.3% of patients recovered without an endpoint (n = 38). The most common endpoint was CHF occurring in 11 patients (18.3%). Total deaths were 7 (11.6%) including CHF death, cardiac death, and noncardiac death. In the study by Harrison et al., the area under the ROC curve using BNP to detect a CHF endpoint – a CHF death, hospital admission, or repeat ED visit – was 0.870 (95% CI: 0.826–0.915). A BNP value of 480 pg/mL had a sensitivity of 68%, a specificity of 88%, and an accuracy of 85% for predicting a subsequent CHF endpoint.[4] The area under the ROC curve for BNP at admission was 0.955. Optimum cutoff for determination of an endpoint for BNP at admission was 1298 pg/ml (sensitivity: 95.5%, specificity: 94.7%). It differed from the previous study as we selected only patients who had a baseline BNP at admission >500 pg/ml. In Italian RED study, out of 78 events through follow-up, 58 patients had BNP level at discharge >300 pg/mL. The conclusion of the study was that a reduction of BNP >46% at hospital discharge compared to the admission levels coupled with a BNP absolute value <300 pg/mL seems to be a very powerful negative prognostic value for future cardiovascular outcomes in patients hospitalized with ADHF.[5] In our study, cutoff for determination of an endpoint for BNP at discharge was 367.5 pg/ml (sensitivity: 95.5%, specificity: 94.7%). The area under the ROC curve was 0.981. The ability of BNP to predict 6-month mortality was also assessed with ROC analysis. The area under the ROC curve using BNP to detect death from CHF was 0.881 (95% CI: 0.807–0.954). The area under the ROC curve using BNP to detect any cardiac death was 0.877 (95% CI: 0.822–0.933).[4] In our study, we used ROC to predict a 6-month mortality from any cardiac cause. The area under the curve for BNP at admission and BNP at discharge was 0.815 and 0.905, respectively. Optimum cutoff for determination of cardiac death for BNP at admission and BNP at discharge was 1697 pg/ml (sensitivity: 80%, specificity: 74.5%) and 664 pg/ml (sensitivity: 80%, specificity: 80%), respectively. The area under the ROC curve for BNP at admission and BNP at discharge for any death with CI 95% with P < 0.05 was 0.736 and 0.865, respectively. Optimum cutoff for determination of death for BNP at admission and BNP at discharge was 1593 pg/ml (sensitivity: 85.7%, specificity: 75.5%) and 563 pg/ml (sensitivity: 85.7%, specificity: 77.4%), respectively. Most of the endpoints occurred in patients who had BNP at discharge >500 pg/ml. All CHF events occurred in patients who had BNP at discharge >500 pg/ml. Chi-square test for detection of an endpoint with respect to various EF groups revealed no significant difference among the groups, and the P value was found to be 0.569.


  Conclusion Top


The study showed that BNP taken at the time of admission and at discharge can easily and accurately predict future cardiac events in patients presenting with dyspnea. The study also shows BNP as a better predictor of prognosis than EF or past history of any cardiac event. Measurement of BNP is an easy and quick bedside method which does not require any specialized skill. Thus, this study is especially important for common hospital setting in our country to determine the early prognosis of patients.

Limitations of the study

The sample size of the study was small and included only 100 patients, and patients with the known pulmonary cause of dyspnea were excluded from the study. Only 60 patients had BNP >500 pg/ml at the time of admission and were followed up for any endpoint till the next 6 months. Hence, in order to validate these cutoffs, the study could be extended to large number of patients.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
  References Top

1.
Collinson PO, Barnes SC, Gaze DC, Galasko G, Lahiri A, Senior R. Analytical performance of the N terminal pro B type natriuretic peptide (NT-proBNP) assay on the elecsys 1010 and 2010 analysers. Eur J Heart Fail 2004;6:365-8.  Back to cited text no. 1
    
2.
Boldanova T, Noveanu M, Breidthardt T, Potocki M, Reichlin T, Taegtmeyer A, et al. Impact of history of heart failure on diagnostic and prognostic value of BNP: Results from the B-type natriuretic peptide for acute shortness of breath evaluation (BASEL) study. Int J Cardiol 2010;142:265-72.  Back to cited text no. 2
    
3.
Karakiliç E, Kepez A, Abali G, Coşkun F, Kunt M, Tokgözoǧlu L, et al. The relationship between B-type natriuretic peptide levels and echocardiographic parameters in patients with heart failure admitted to the emergency department. Anadolu Kardiyol Derg 2010;10:143-9.  Back to cited text no. 3
    
4.
Harrison A, Morrison LK, Krishnaswamy P, Kazanegra R, Clopton P, Dao Q, et al. B-type natriuretic peptide predicts future cardiac events in patients presenting to the emergency department with dyspnea. Ann Emerg Med 2002;39:131-8.  Back to cited text no. 4
    
5.
Di Somma S, Magrini L, Pittoni V, Marino R, Mastrantuono A, Ferri E, et al. In-hospital percentage BNP reduction is highly predictive for adverse events in patients admitted for acute heart failure: The Italian RED study. Crit Care 2010;14:R116.  Back to cited text no. 5
    
6.
Pauwels RA, Rabe KF. Burden and clinical features of chronic obstructive pulmonary disease (COPD). Lancet 2004;364:613-20.  Back to cited text no. 6
    
7.
Rees J. ABC of asthma. Prevalence. BMJ 2005;331:443-5.  Back to cited text no. 7
    
8.
Wang CS, FitzGerald JM, Schulzer M, Mak E, Ayas NT. Does this dyspneic patient in the emergency department have congestive heart failure? JAMA 2005;294:1944-56.  Back to cited text no. 8
    


    Figures

  [Figure 1], [Figure 2], [Figure 3], [Figure 4]
 
 
    Tables

  [Table 1], [Table 2], [Table 3]



 

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