NT-proBNP as a Prognostic Indicator for Decompensated Heart Failure in Elderly Population

Eranda L Ranasinghe Arachchi; Koumavi Agboyibor; Gunawardan Yalamanchilli

doi:https://doi.org/10.47739/2573-1297/

NT-proBNP as a Prognostic Indicator for Decompensated Heart Failure in Elderly Population

Case Report | Open Access | Volume 6 | Issue 1

Article DOI : https://doi.org/10.47739/2573-1297/

Eranda L Ranasinghe Arachchi^1* Koumavi Agboyibor² Gunawardan Yalamanchilli²

^1*. Northern Ireland Medical and Dental Training Agency, United Kingdom
^2. University of Buckingham, United Kingdom
^2. University of Buckingham, United Kingdom

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Corresponding Authors

Eranda L Ranasinghe Arachchi, Northern Ireland Medical and Dental Training Agency, United Kingdom

ABSTRACT

Background: As per the updated NICE guidelines, brain (B-type) natriuretic peptide (BNP) is used in the diagnostic criteria and management of heart failure. In this study, we aimed to evaluate the prognostic value of the inactive N-terminal fragment NT-proBNP in an elderly population with decompensated heart failure.

Materials and Methods: We conducted a retrospective observational cohort study of 88 elderly patients who were admitted with decompensated heart failure between September 2023 to April 2024, covering the South Eastern Trust in Northern Ireland. Suspected heart failure admissions were randomly selected to obtain snapshots of each month. Among these admissions, 88 heart failure cases were identified based on echocardiogram findings and NT-proBNP levels obtained at initial admission. The same cohort was followed up for 12 weeks to monitor two specific end points: re-admission with heart failure or death. Heart failure follow-ups were also assessed post-discharge. All cases were categorized into two main cohorts: a heart failure with reduced ejection fraction (HFrEF/EF > 60%) cohort and a heart failure with preserved ejection fraction (HFpEF/EF > 40%) cohort. Prognostic values and all-cause mortality after discharge were assessed for each cohorts via multivariable adjusted Cox regression analysis. Each cohort was further divided into three sub-cohorts based on NT-proBNP value.

Results: The data analysis showed that patients with NT-proBNP values of >2000 exhibited a mortality rate of 29.1% and a heart failure re-admission rate of 45.6%. Those with rising NT-proBNP values during heart failure follow-up exhibited a re-admission rate of 66.6%, which was much lower than that (33.3%) seen in those with declining NT-proBNP values.

Conclusions: Our results indicated that higher NT-proBNP levels on admission were predictive of higher mortality and re-admission rates among the elderly population. Furthermore, rising NT-proBNP levels during heart failure follow up were associated with higher mortality and morbidity rates. Therefore, NT-proBNP levels can be used as a prognostic biomarker for elderly patients with heart failure, irrespective of their ejection fraction status.

KEYWORDS

Heart Failure; NT-proBNP; Elderly; Prognostic Indicator; Mortality Predictor.

INTRODUCTION

Brain (B-type) natriuretic peptide (BNP) is a peptide hormone released primarily from the cardiac ventricles in response to myocyte stretch. It is synthesized as an inactive prohormone that is split into the active hormone BNP and the inactive N-terminal fragment NT-proBNP. BNP has several systemic effects, including vasodilation, increased urinary volume and sodium output, and inhibition of the sympathetic nervous and renin–angiotensin–aldosterone systems [1]. The prognostic importance of BNP and NT-pro-BNP has been extensively studied in patients with heart failure and acute coronary syndromes, and both markers have been shown to be strong predictors of morbidity and mortality [2]. However, neither BNP nor NT-proBNP has been studied as a prognostic indicator among the elderly population. Evaluating BNP as a prognostic indicator of heart failure among the elderly population would enable care providers to plan their treatment and follow-up effectively. Therefore, in this study, we aimed to evaluate the prognostic value of BNP as a predictor of overall outcome in elderly patients with heart failure.

MATERIALS AND METHODS

Study Population

We conducted a retrospective observational cohort study of 98 elderly patients who were admitted with decompensated heart failure between September 2023 to April 2024 in Lagan Valley Hospital, and Lisburn and Ulster Hospital (Dundonald, Northern Ireland). These two major tertiary care and secondary care hospitals, respectively, cover the entire southeastern trust of Norther Ireland, which represents most of the elderly population in the country. Both hospitals have focused protocols for elderly care with onsite availability of cardiac services. We assessed 120 patients with suspected heart failure over eight months. The cases were randomly selected as snapshots covering each month. Among these 120 patients, 88 were confirmed to have heart failure based on clinical symptoms, echocardiography findings, and NT-proBNP findings on admission. Verbal informed consent was obtained from each patient for echocardiography, blood testing, and clinical history and follow-up, as well as for anonymized patient information sharing.

Baseline Measurements

In all patients, a thorough medical history was recorded, including details of any previous myocardial infarction or revascularization, angina pectoris, arterial hypertension, suspected congestive heart failure (defined by symptoms of shortness of breath or leg edema), previous stroke or transient ischemic attacks, diabetes, atrial fibrillation, and any malignancy. This information was obtained from medical records, directly from the patients, or both. Clinical frailty was evaluated for each patient using the Rockwood Clinical Frailty Scale. Echocardiography findings were evaluated for all the identified cases. Ejection fraction and presence of any regional wall motion abnormalities, valve pathologies, and LV thrombus was documented. The majority of patients received NT-proBNP during the admission. The inclusion criteria were as follows: > 65 years of age or a Rockwood Clinical Frailty Scale score of > 4, established acute hospital admission with heart failure, and an NT-proBNP value of > 400 ng/L.

Follow Up

Heart failure medications upon discharge were documented and categorized as beta blockers, diuretics, dapagliflozin, digoxin, antiplatelets, or anticoagulants. All 98 patients were followed up for 12 weeks after initial hospital discharge. Follow-up pathways were traced through electronic data records, including follow up with any cardiologist, heart failure nurse, or community-based heart failure care provider. Any medication changes or additions during follow up were recorded. Patients who received repeat NT-proBNP were also recorded with values. Follow up was monitored in terms of two major end points: heart failure–related death and re-admission due to heart failure.

Data Analysis

All patients were sorted into two main cohorts: a heart failure with reduced ejection fraction (HFrEF/EF > 60%) cohort and a heart failure with preserved ejection fraction (HFpEF/EF > 40%) cohort. Each cohort was again categorized into three main sub-cohorts according to NT-proBNP value on admission: < 400, 400-2000, and >2000. In total, six sub-cohorts were established, and data were analyzed for each sub-cohort. Average age, gender distribution, clinical frailty score, presenting symptoms, and past medical history were listed under demographic distribution cohort. Follow-up details, heart failure admissions, and deaths were listed under morbidity and mortality section.

Nt-Probnp Values and End Points

The same cohorts were further followed up for 12-15 weeks to monitor the two above-mentioned end points. In addition, whether patients received outpatient heart failure follow-up (e.g., with heart failure nurse, cardiac hub, or cardiology specialist) was also monitored. Repeat BNP values during follow-ups were compared with each patient’s initial BNP value and documented as either a “reduction” or “increase.” These parameters were again correlated with the aforementioned end points.

RESULTS

Demographic Characteristics

HFpEF Cohort: Patients in the HFpEF cohort were categorized into three sub-cohorts according to BNP values. In all three sub-cohorts of the HFpEF cohort, the majority of patients were male, and most had a Rockwood Clinical Frailty Scale score of 6. The majority of patients presented with shortness of breath, and a minority had evidence of fluid overload. Those with moderately and highly elevated BNP had other associated vascular risk factors, including coronary artery disease, hypertension, CKD, CVA, and AF, as seen in (Table 1).

Table 1: Demographic characteristics of HFpEF cohort.

NT-proBNP	< 400 ng/L n = 111	400-2000 ng/L n = 151	> 2000 ng/L n = 27
Age in years, average (SD)	66.2 (13.7)	80.7 (6.3)	83.3 (8.5)
Sex
Female	5 (17.2%)	9 (31.0%)	15 (51.7%)
Male	6 (25.0%)	6 (25.0%)	12 (50.0%)
Clinical Frailty Score
2	2 (100.0%)	0 (0.0%)	0 (0.0%)
3	2 (50.0%)	1 (25.0%)	1 (25.0%)
4	3 (42.9%)	2 (28.6%)	2 (28.6%)
5	3 (23.1%)	5 (38.5%)	5 (38.5%)
6	0 (0.0%)	7 (38.9%)	11 (61.1%)
7	1 (11.1%)	0 (0.0%)	8 (88.9%)
NYHA II SOB	10 (22.2%)	11(24.4%)	24 (53.3%)
Fluid Overload	2 (14.3%)	4 (28.6%)	8 (57.1%)
Hypertension	2 (8.3%)	8 (33.3%)	14(58.3%)
Diabetes Mellitus	2 (15.4%)	3 (23.1%)	8 (61.5%)
Chronic Kidney Disease	0 (0.0%)	2 (16.7%)	10 (83.3%)
Dyslipidemia	2 (40.0%)	2 (40.0%)	1 (20.0%)
Coronary Artery Disease	6 (33.3%)	5 (27.8%)	7 (38.9%)
Cerebrovascular Accident	2 (33.3%)	2 (33.3%)	2 (33.3%)
Atrial Fibrillation	0 (0.0%)	6 (33.3%)	12 (66.7%)
Respiratory Diseases	5 (29.4%)	5 (29.4%)	7 (41.2%)
Malignancy	0 (0.0%)	3 (25.0%)	9 (75.0%)

Data are presented as frequencies (percentages) unless otherwise stated. NYHA II SOB: xxx. SD: standard deviation.

HFrEF Cohort: The HFrEF cohort was categorized into sub-cohorts according to BNP values. Similar to the HFpEF cohort, the majority of patients were male, the majority of patients presented with shortness of breath and were diagnosed with heart failure, and the minority of patients presented with evidence of fluid overload. The average Rockwood Clinical Frailty Scale score of the HFrEF cohort was 5. As seen in the HFpEF cohort, patients with moderately and highly elevated Surevalues had other cardiovascular risk factors, as seen in (Table 2-4).

Table 2: Demographic characteristics of HFrEF cohort.

BNP	< 400 ng/L n = 41	400-2000 ng/L n = 71	> 2000 ng/L n = 24
Age in years, average (SD)	71.3 (10.7)	60.3 (14.1)	77.3 (13.4)
Sex
Female	1 (8.3%)	3 (25.0%)	8 (66.7%)
Male	3 (13.0%)	4 (17.4%)	16 (69.6%)
Clinical Frailty Score
3	1 (100.0%)	0 (0.0%)	0 (0.0%)
4	1 (16.7%)	3 (50.0%)	2 (33.3%)
5	1 (20.0%)	1 (20.0%)	3 (60%)
6	0 (0.0%)	0 (0.0%)	12 (100%)
7	1 (16.7%)	1 (16.7%)	4 (66.7%)
Missing observations	0	2	3
Presenting symptoms
NYHA II SOB	2 (8.3%)	4 (16.7%)	18 (75.0%)
Fluid Overload	0 (0.0%)	0 (0.0%)	6 (100%)
Past Medical History
Hypetension	0 (0.0%)	2 (20.0%)	8 (80.0%)
Diabetes Mellitus	0 (0.0%)	1 (16.7%)	5 (83.3%)
Chronic Kidney Disease	0 (0.0%)	0 (0.0%)	6 (100.0%)
Dyslipidemia	0 (0.0%)	0 (0.0%)	3 (100%)
Coronary Artery Disease	0 (0.0%)	1 (16.7%)	5 (83.3%)
Cerebrovascular Accident	0 (0.0%)	0 (0.0%)	1 (100%)
Atrial Fibrillation	2 (20.0%)	2 (20.0%)	6 (60.0%)
Respiratory Diseases	1 (20.0%)	1 (20.0%)	3 (60%)
Malignancy	0 (0.0%)	0 (0.0%)	3 (100%)

Data are presented as frequencies (percentages) unless otherwise stated. NYHA II SOB: xxx, SD: standard deviation.

Table 3: Data analysis of end points for HFrEF cohort.

	NT Pro BNP 0-400	NT Pro BNP 400 - 2000	NT Pro BNP > 2000
Mortality
Alive	3 (75%)	7 (100%)	22 (91.6%)
Deceased	1 (25%)	0%	3 (12.5%)
Readmissions
Yes ( including terminal event admission )	1 (25%)	0%	3 (12.5%)
No admission	3 (75%)	7 (100%)	21 (87.5%)
Heart Failure follow up
Received	4 (100%)	7 (100%)	12 (54.5%)
Not Received	0 (0%)	0 (0%)	6 (27.2%)
Not Warranted	0 (0%)	0 (0%)	4 (18.1%)
NT Pro BNP measured?
Yes	0 (0%)	3 (42.8%)	10 (41.6%)
No	4 (100%)	2 (57.1%)	6 (29.1%)

Table 4: Data analysis of end points for HFpEF cohort.

	NT Pro BNP 0-400	NT Pro BNP 400 - 2000	NT Pro BNP >2000
Mortality
Alive	10 (91%)	13 (86.6%)	15 (55.6%)
Deceased	01 (9%)	02 (13.3%)	12 (44.4%)
Readmissions
Yes (including terminal event admission)	02 (18.1%)	03 (33.3%)	19 (74.0%)
No admission	09 (81.8%)	12 (66.6%)	08 (26%)
Heart failure Follow up
Received	05 (45.4%)	08 (61.5%)	05 (35.7%)
Not Received	04 (36.3%)	04 (38.5%)	10 (64.2%)
Not Warranted	02 (18.1%)	0 (0%)	0 (0%)
OP NT Pro BNP monitored?
Yes	1 (11.1%)	03 (38.4%)	02 (35.7%)
No	4 (88.8%)	05 (61.6%)	03 (64.2%)

Nt-Probnp and Mortality: The association between NT-proBNP value and mortality was evaluated for both cohorts. In the HFpEF cohort, the sub-cohort with an initial NT-proBNP value of > 2000 on admission demonstrated a high mortality rate of 44% from admission through follow up. In contrast, the same sub-cohort of the HFrEF cohort exhibited a mortality rate of 8.3%. The mortality rates of all sub-cohorts were standardized and plotted against NT-proBNP levels. The total cohort demonstrated higher mortality. The two sub-cohorts with NT-proBNP values of >2000 demonstrated a mortality rate of 29.1% (Figure 1).

Nt-Probnp and Heart Failure Re-Admission

All data from the six sub-cohorts were analyzed in terms of the heart failure re-admission end point. In the HFpEF cohort, the sub-cohort with initial NT-proBNP values of > 2000 on admission demonstrated a high readmission rate of 74% during follow up. In contrast, in the HFrEF cohort, the same sub-cohort exhibited a lower readmission rate of 12.5%, similar to the results of the mortality end point analysis between groups. The data were then statistically standardized for the whole population and plotted against NT-proBNP values, which showed higher incidence with readmissions (Figure 2).

Heart Failure Follow-Up: 65.7% (n = 23) of the HFrEF cohort received heart failure follow up from a specialist or heart failure nurse–led clinic, whereas only 33.7% (n =18) of the HFpEF cohort received follow up (Figure 3,4). Of the patients who received follow up, 46.3% (n =19) % received a repeat NT-proBNP evaluation either during the follow up or during a readmission. More than 35% of patients with moderately high NT-proBNP (400–2000)-38.4% (n = 3) for the HFpEF cohort and 42.8% (n =3) for the HFrEF cohort-received repeat NT-proBNP evaluation during follow up. Sub-cohorts with NT-proBNP values of > 2000 demonstrated similar repeat BT-proBNP evaluation rates during follow up: 37.5% (n = 6) for the HFpEF cohort and 41.6 %( n = 10) for the HFrEF cohort.

The data analysis was further extended to determine whether patients exhibited declining or rising NT-proBNP values during heart failure follow up, compared the BNP reduction rate with the re-admissions. During follow up, nine patients exhibited rising NT-proBNP values, of which six were re-admitted due to heart failure exacerbation, representing a 66.6% re-admission rate for patients with rising NT-proBNP values. Of the 12 patients who exhibited declining NT-proBNP values during follow up, only four were re-admitted with heart failure exacerbation, representing a 33.3% re-admission rate for patients with declining NT-proBNP values, as seen in (Figure 5).

Figure 1: NT-proBNP values and mortality rates for both HFrEF and HFpEF cohorts.

Figure 2: NT-proBNP values and heart failure readmission rates for HFrEF and HFpEF cohorts.

Figure 3: Follow-up rates for HFrEF and HFpEF cohorts.

Figure 4: Follow-up NT-proBNP evaluation rates for total study sample and sub-cohorts.

Figure 5: Association between changes in NT-proBNP value and re-admission rate

Statistical Power: Categorical variables are reported as frequencies and percentages. Normally distributed continuous variables are presented as means ± standard deviations, whereas non-normally distributed continuous variables are presented medians and interquartile ranges. Student’s t-test or the Mann–Whitney U test for continuous variables, and the chi?squared or Fisher’s exact test for categorical variables were used comparison between groups, as appropriate. When needed, the variables were transformed for further analysis. We re-categorized all the data according to NT-proBNP values. Area under the receiver operating curve (AUROC) was calculated for each cohort to measure the natriuretic peptide’s performance in predicting heart failure mortality at first admission screening. Multiple logistic regression was then performed for the total study sample to determine whether NT-proBNP was predictive of mortality in heart failure, as seen in (Figure 6). AUROC was 0.478 for the total study sample, indicating that NT-proBNP values can be used as a prognostic biomarker for predicting mortality in elderly heart failure patients.

Kaplan-Meier curves and log?rank analysis were used to compare the cumulative incidence of the primary end point between groups, as seen in (Figures 7,8). The Kaplan–Meier curves for both cohorts demonstrated that survival probability decreased as NT-proBNP levels increased (p-values of 0.29 and 0.018 for the HFpEF and HFrEF cohorts, respectively). In this study, the null hypothesis is that NT-proBNP cannot be used as a prognostic indicator for elderly patients with heart failure. As the significance level for this study was set at 1, and the p-values for both cohorts were less than this significance level, the null hypothesis was rejected (Figure 9).

Figure 6: Receiver operating characteristic curve for the total study sample, indicating NT-proBNP as a mortality and readmission predictor for heart failure exacerbation.

Figure 7: Kaplan–Meier curve for HFpEF cohort.

Figure 8: Kaplan–Meier curve for HFrEF cohort.

Figure 9: Kaplan–Meier Curve for different NT-proBNP levels.

DISCUSSION

The Summery of Main Findings F

In this cohort study, two major heart failure cohorts were analyzed for specific end points under six main sub-cohorts. Our data analysis showed that whose with NT-proBNP values of > 2000 exhibited a mortality rate of 29.1% and a heart failure re-admission rate of 45.6%. Those with rising NT-proBNP values during heart failure follow-up exhibited a re-admission rate of 66.6%, which was much lower than that (33.3%) among those with declining NT-proBNP values. Based on the statistical power of the study, NT-proBNP can be used as a prognostic marker for mortality in elderly patients with heart failure irrespective of their ejection fraction.

Strengths and Limitations of the Study

The case selection for this study was done after a thorough analysis of more than 200 patients, considering clinical presentation, echocardiography findings and NT-pro BNP values. The case selection represents a correct picture of a clinical case of an elderly patient who has chronic heart failure with recurrent exacerbations. The scope of this study was to evaluate how impactful monitoring NT-proBNP levels in such a case to reduce the recurrence of exacerbations and improve the overall morbidity and mortality. The monitoring time for the endpoint is powerful in this study as we managed to monitor each case for more than 8 months. Assessing the follow up details across longer duration with follow up NT-proBNP levels were powerful as the existing literature on this fact is still limited. Echocardiographic Heart of England Screening (ECHOES) study [5] is one of the major studies that is carried out to date, to evaluate the long-term prognosis of patients with chronic heart failure patients. Even though, the results of ECHOES study shows that the survival rate in severe left ventricular dysfunction is poor, there was no measurement and correlation with NT-pro BNP levels in the study population. Furthermore, there were no classifications of heart failure as HFrEF or HFpEF at the time of ECHOES study happened. Hence, our pilot study can be considered as a stepping stone for a comprehensive mass study of analyzing all types of heart failure with NT-Pro BNP assessment.

This study did have some limitations. The data collection was done randomly to obtain snapshots of each month of the study period. The initial approach used for data collection included screening patients who had inpatient echocardiography for heart failure, with the assumption that all heart failure admissions received inpatient echocardiography. However, this selection process may have missed some patients. Other factors that can cause high NT-proBNP values were not evaluated in this study. However, the documented demographic characteristics included most of these factors, and the results were standardized. 14 of 16 Data on body mass index, serum creatinine levels, and sepsis were not collected, as it was challenging to access these data sets.

In the future, we hope to carry out a separate study to extensively analyze these factors. The mortality and re-admission record we obtained were analyzed to determine the causes for mortality and re-admissions. Some patients had other associated causes of mortality beyond heart failure, such as sepsis, Acute Kidney Injury (AKI) on Chronic Kidney Disease (CKD) and cardiorenal syndrome. Most of the re-admissions were actual heart failure re-admissions, but a minority of patients presented with respiratory conditions that could have exacerbated existing heart failure, such as pneumonia or infective exacerbation of chronic obstructive pulmonary disease. The presence of other associated conditions in addition to heart failure that contributed to mortality and re-admission was an unavoidable limitation in this study.

Comparison with Existing Literature

Taylor C.J did a study [1] by analyzing 594 participants of the ECHOES study who took part in the NT-proBNP sub-study. As per the analysis, the proportion of patients surviving 10 years was significantly lower in the group with an NT-proBNP level ≥150 pg/mL compared to an NT-proBNP level <150pg/mL (61% vs 89%respectively in the general population). An NT-proBNP level ≥150 pg/mL was strongly predictive of a diagnosis of HF at screening and of death in the next 10 years. Our study further confirms similar findings of above study in further comprehensive manner by assessing the population based on different Ejection fraction levels (HFrEF and HFpEF) and different NT- proBNP levels. Clare J did a study [5] which was similar to our study by assessing the mortality my correlating NT-pro BNP values with HFrEF and HFpEF cohorts. This study highlights that NT-proBNP levels confer the same relative risk information in HFpEF cohort similar to the HFrEF cohort. The study further confirms that NT-pro BNP still can be used as a prognostic indicator for patients who have other comorbidities along with HFpEF. Similarly, our study results also proved that NT-Pro BNP still can predict the morbidity and mortality, irrespective of the ejection fraction status of the patients.

Additionally, we were able to prove in our study that rising NT-proBNP values during the follow up, tend to result in more re-admissions whereas the opposite for declining NT-pro BNP values. This fact was not evaluated much in the study [5] done by Clare J. Hobbs FDR did another study [3] by assessing 591 patients in the community level to evaluate the reliability of both NT-pro BNP and BNP in diagnosing heart failure. This study confirmed that both NT-proBNP and BNP have value in diagnosing left ventricular systolic dysfunction in a community setting, with similar sensitivities and specificities. Our study further proves that monitoring NT-pro BNP at the community is reliable in diagnosing heart failure exacerbations in the community.

Charlotte K, did another study [6] by assessing 288 patients with stable coronary artery disease. The results showed median NT-pro-BNP level was significantly lower among patients who survived than among those who died from cardiovascular diseases. This study was done in a cohort with stable coronary artery disease where they have included patients with non-occlusive coronary arteries as the inclusion criteria. This study further proves that NT-proBNP is an excellent independent prognostic indicator for mortality in patients with left ventricular systolic dysfunction irrespective of associated ischemic origin. We believe that this fact (inclusion criteria of patients with non-occlusive coronaries) was something deficient in our study that we might have been considered in the study design. Zhang. B did a similar type of a study [7] to assess the prognostic value of NT-proBNP in patients with valvular heart disease. The results were similar to the rest of the study results confirming that NT-pro BNP levels can be used as a prognostic indicator in patients with valvular heart diseases. In our study, we were able to collect echocardiographic data on valvular abnormalities but could not correlate with the NT-pro BNP values and the end points. This is again something deficient on our study compared to the study by Bin Zhang MD [7].

Implications on Future Practice

Current National Institute of Health and Care Excellence ( NICE) , United Kingdom guidelines [4] only consider measuring NT-proBNP as a part of treatment optimization protocol only in a specialized care setting for people under 75 who have heart failure with reduced ejection fraction and estimated Glomerular Filtration Rate ( eGFR) more than 60 ml/min/1.73 m2. The results of our study, along with existing literature proves that NT-proBNP is a very reliable prognostic indicator for mortality and morbidity, irrespective of the ejection fraction status and presence of coronary artery disease. Furthermore, the study proves that routine monitoring of NT-pro BNP and assessing the trend would accurately predict future readmissions and then mortality of the patients with chronic heart failure.

These results would enable to re-evaluate NICE guidelines [4] on chronic heart failure follow up, by expanding the criteria by enabling the elderly population to have NT-proBNP as a part of follow up irrespective of their age and the follow up care provider. Monitoring NT-pro BNP tends on the follow up, would enable the health care providers to identify future re-admissions early and make the treatment plans accordingly to prevent exacerbations. This would be a potential guideline update in the future if this pilot study gets expanded.

CONCLUSION

Our results provided satisfactory statistical evidence that higher NT-proBNP values on admission were a good predictor of mortality and re-admission among the elderly population. Furthermore, rising NT-proBNP levels during heart failure follow up were associated with higher mortality and morbidity rates. Therefore, NT-proBNP level can be used as a prognostic biomarker for elderly patients with heart failure, irrespective of their ejection fraction status. Monitoring NT-proBNP levels in all heart failure cases could be beneficial to prevent mortality and morbidity, as heart failure medications can then be optimized prior to episodes of heart failure decompensation.

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