European Journal of Cardiovascular Medicine

Ambulatory blood pressure monitoring (ABPM) provides a nuanced understanding of blood pressure patterns over a 24-hour period and is invaluable in managing various cardiovascular conditions, including acute heart failure (AHF). AHF is a rapid onset or exacerbation of the symptoms and signs of heart failure, often resulting in hospital admission. ABPM in AHF settings reveals crucial information regarding fluctuating blood pressure that could influence patient management and outcomes.1

The variability in blood pressure, including nocturnal dipping and morning surge, has been linked to cardiovascular outcomes in heart failure patients. ABPM has proven to be superior to office BP measurements in predicting cardiovascular events and adjusting treatment strategies in chronic heart failure. Studies like those by Hauspurg A et al. (2024) highlight the prognostic importance of understanding the patterns of blood pressure variation in patients with cardiovascular disease.2,3

Acute heart failure management often overlooks the importance of blood pressure variability, which can play a significant role in patient outcomes. This study seeks to  harness the diagnostic capabilities of ABPM to fill this gap by providing detailed insights into blood pressure patterns during acute episodes of heart failure. These insights could lead to more personalized and effective treatment strategies.4

This observational study at a tertiary care center aimed to explore the role of ABPM in patients admitted with AHF. It focused on the correlation of circadian blood pressure patterns with the severity and symptoms of heart failure, along with associated cardiac risk factors. Furthermore, it investigated the relationship between baseline ambulatory blood pressure values and cardiac structural parameters such as left ventricular ejection fraction (LVEF) and left ventricular end-diastolic dimension (LVEDD).5

The study was conducted after approval by the Institutional Ethics Committee, SMS Medical College and Hospital, Jaipur.

Source of Data

Data was collected from patients admitted with AHF to the department of cardiology at SMS Medical College and Hospital, Jaipur.

Study Design

This was a prospective cross- sectional observational study designed to analyze blood pressure patterns using ambulatory blood pressure monitoring in patients admitted with AHF.

Study Location

The study was conducted in department of cardiology at SMS Medical College and Hospital, Jaipur, India.

Study Duration

Data collection occurred over one year, from April 2023 to March 2024.

Sample Size

The minimum required sample size with 10% margin of error and 5% level of significance is 94 patients. To reduce the margin of error, the total sample size taken was 100.

Formula used for sample size determination:

 N ≥ (Zα/2)2 (pq)

            (d)2

where Zα/2 = 1.96 at α=0.05(95% CI)

            p     = Non dipper pattern

            q     = 1-p

            d     = Allowable error (Absolute)

Calculations:

           n ≥ 3.84 X 42 X 58 = 93.54 = 94(approx.)

                      10X10

Therefore, the study comprised of 100 patients, selected based on predefined inclusion and exclusion criteria.

Inclusion Criteria

1. Patients presenting with AHF classified according to ACC/AHA guidelines, and on medical therapy were included. An exclusion criterion is applied before selection of patients for study.
2. Age >/= 18 years.
3. Giving informed consent.

Exclusion Criteria

Exclusion criteria comprised of patients with:

1. Acute myocardial infarction
2. Acute HF with acute pulmonary embolism
3. Hemodynamically unstable terminally ill patients
4. Irregular heart rhythm
5. Congenital heart disease
6. Revascularization within past six months
7. Endocarditis
8. Pericarditis
9. Myocarditis
10. Peripheral arterial disease and
11. Patients on cardiac re-synchronization therapy

Methodology

• For each patient, complete medical history was taken, and thorough physical examination was done.
• ABPM devices were fitted to patients 24 hours prior to discharge post-initial clinical stabilization.
• The device recorded systolic blood pressure (SBP) and diastolic BP (DBP) (by the oscillometric method), and pulse rate every 30 min during daytime (7 a.m. to 10:59 p.m.) and every 60 min during night-time (11 p.m. to 6.59 a.m.). Clinical assessments and symptom evaluations were recorded concurrently.
• BP measurement was performed on the side opposite the dominant arm in this study.
• Transthoracic echocardiography (TTE) was done.
• ABPM data was correlated with echo parameters and clinical characteristics of heart failure patients.

Statistical Methods

Continuous variables were expressed as mean ± standard deviation or median (interquartile range), and inter-group differences were compared using Student’s t-test. Categorical variables were summarized as percentages and analysed using the x2 test. Data were analyzed using the Statistical Package for the Social Sciences (SPSS) version 26. Descriptive statistics described patient demographics and blood pressure measurements. p values <0.05 were considered statistically significant.

Data Collection

Data was meticulously collected on patient demographics, clinical symptoms, ambulatory blood pressure measurements, and echocardiographic data. For each patient, baseline data collected included age, sex, body mass index (BMI), HF etiology, medical history, vital signs, laboratory and echocardiographic data, and medications on admission and at discharge (Table 2). All data was securely stored and analyzed to ensure patient confidentiality and data integrity.

RESULTS

Table 1: Baseline characteristics in the riser and non-riser groups.

ACEi: angiotensin-converting enzyme inhibitor; ARB: angiotensin receptor blocker; beta-blocker: beta-adrenergic receptor blocker; BMI: body mass index; BNP, B-type natriuretic peptide; Ca, calcium; SGLT2, sodium glucose co-transporter-2; EDD, end-diastolic diameter; EF, ejection fraction; eGFR, estimated glomerular filtration rate; HF, heart failure; HFmrEF, heart failure with mildy reduced ejection fraction; HFpEF, heart failure with preserved ejection fraction; HFrEF, heart failure reduced with ejection fraction; LV, left ventricular; MRA, mineralocorticoid receptor antagonist; NYHA, New York Heart Association.

We classified patients with HF into HFpEF (Heart Failure with preserved Ejection Fraction), HFmrEF (Heart Failure with mildly reduced Ejection Fraction), and HFrEF (Heart Failure with reduced Ejection Fraction) groups based on their LVEF and compared their baseline clinical characteristics (Table 1). We further divided the HF types into two subgroups, namely, riser and non- riser groups based on ABPM measurements obtained.

Table 1 shows that no significant differences were found in age between risers and non-risers across all HF types. Females are more prevalent in HFpEF (56.3% non-risers, 52.8% risers), while males dominate in HFrEF (27.5% non-risers, 32.1% risers). No significant gender differences between riser and non-riser pattern. BMI was slightly higher in riser pattern across all groups, but no significant differences (p-values > 0.05). Ischemic heart disease was more prevalent in HFmrEF riser (53.1%) compared to non-riser pattern (37.2%), but not statistically significant (p = 0.26). Dilated Cardiomyopathy was more common in HFrEF riser (37.6%) compared to non-riser pattern (33.4%), but not significant (p = 0.56). Hypertension was highly prevalent across all groups, with no significant differences between riser and non-riser pattern. Diabetes Mellitus was higher in HFrEF risers (46.5%) compared to non-riser pattern (39.3%), but not significant (p = 0.62). NYHA Class III or IV at admission was significantly higher in HFmrEF risers (96.2%) compared to non-risers (88.9%) (p = 0.02). No significant differences in HFpEF or HFrEF.

LVEF (Left Ventricular Ejection Fraction) showed no significant differences between riser and non-riser pattern across all HF types. LVEDD (Left Ventricular End-Diastolic Diameter) was slightly higher in riser pattern, but not statistically significant. Smoking was more prevalent in HFmrEF non-riser (41.2%) compared to riser pattern (28.4%), but not significant (p = 0.23). Haemoglobin, eGFR, Sodium, NT-proBNP showed no significant differences between risers and non-riser patter across all HF types.

ACEi/ARBs/ARNI, beta-blockers, diuretics were highly used across all groups, with no significant differences between risers and non-risers. SGLT2 inhibitors were more commonly used in HFrEF (72.4% non-risers, 76.9% risers), but no significant differences between risers and non-risers.

 Table 2: Vital Signs and Circadian Blood Pressure Patterns by Heart Failure Type

ABPM: ambulatory blood pressure monitoring; SBP: systolic blood pressure; DBP: diastolic blood pressure; HFpEF: Heart failure with preserved ejection fraction; HFmrEF: Heart failure with mildly reduced ejection fraction HFrEF: Heart failure with reduced ejection fraction.

Vital signs at admission and discharge as well as ABPM data broken down by heart failure type (HFpEF, HFmrEF, and HFrEF) are shown in Table 2. On admission, HFpEF patients had the highest SBP (129.4 ± 16.8 mmHg), followed by HFmrEF (118.3 ± 16.6 mmHg), and HFrEF (100.3 ± 18.3 mmHg). The differences were statistically significant (p=0.01). DBP showed no significant differences were observed among the groups. HFmrEF patients had the highest pulse rate (106.2 ± 25.3 b.p.m.), followed by HFrEF (103.2 ± 26.1 b.p.m.) and HFpEF (95.8 ± 28.3 b.p.m.). The differences were significant (p=0.01).

At discharge, HFpEF patients still had the highest SBP (121.9 ± 18.6 mmHg), followed by HFmrEF (111.4 ± 16.8 mmHg) and HFrEF (104.2 ± 14.1 mmHg). The differences were highly significant (p=0.001). DBP and pulse rate showed no significant differences.

ABPM measurements showed that HFpEF patients had the highest average 24-hour SBP (124.9 ± 17.8 mmHg), followed by HFmrEF (112.4 ± 15.2 mmHg) and HFrEF (102.8 ± 13.9 mmHg). The differences were significant (p=0.01). Similar trends were observed in awake and sleep-time SBP, with HFpEF patients having the highest SBP during both awake and sleep periods (p=0.01 for both). No significant differences were observed in 24-hour, awake, or sleep-time pulse rates (p>0.05). Pattern of circadian rhythm for riser, non-dipper, and dipper patterns showed no significant differences were observed among the groups (p>0.05).

HFpEF patients had the highest prevalence of nocturnal hypertension (52.7%), followed by HFmrEF (34.1%) and HFrEF (27.4%). The differences were significant (p=0.01).

Table 3: Heart Failure Severity by Type

Table 3 delineates NYHA class and LVEF by heart failure type. The differences in LVEF between the groups are statistically significant, with HFpEF showing the best heart function and HFrEF showing the worst.

Hypertension is a common comorbidity in patients with heart failure, contributing to disease development and prognosis. Hypertension is closely associated with the development of left ventricular hypertrophy, which is an important precursor of heart failure. In particular, nocturnal blood pressure appears to be an important, modifiable risk factor. There is a growing body of evidence that nocturnal BP and a non-dipper or riser pattern of blood pressure are important predictors of mortality and cardiovascular events and provide better prognostic information than office blood pressure. ⁶

Ambulatory blood pressure monitoring (ABPM) is

an important out-of-office blood pressure (BP) measurement tool which has been in clinical use for over 50 years.  The use of ABPM is particularly important in AHF due to its specific features, including disrupted BP variability with marked morning BP surge, and nocturnal hypertension seen in heart failure.⁷

The present study was done to explore the role of ABPM in patients admitted with AHF.  It focused on the correlation of circadian blood pressure patterns with the severity and symptoms of heart failure, along with associated cardiac risk factors. Furthermore, it investigated the relationship between baseline ambulatory blood pressure values and cardiac structural parameters such as left ventricular ejection fraction (LVEF) and left ventricular end-diastolic dimension (LVEDD).

Patients presenting with AHF classified according to ACC/AHA guidelines were fitted with ABPM device 24 hours prior to discharge post-initial clinical stabilization. The device recorded SBP and DBP, and pulse rate every 30 min during daytime (7 a.m. to 10:59 p.m.) and every 60 min during night-time (11 p.m. to 6.59 a.m.). Night-time BP dipping patterns were classified into three groups: dipper, nondipper, and riser patterns.

Based on echocardiographic findings, the patients were  divided into HFpEF (n=32), HFmrEF (n=26), HFrEF (n=42).⁷ Table 1 provides a detailed comparison of patient characteristics, medical history, and treatment patterns across three types of heart failure HFpEF, HFmrEF, and HFrEF. The data is further divided into riser and non-riser groups, with statistical comparisons (p-values) provided for each category.

In HFpEF and HFrEF group no significant differences between risers and non-riser patterns in demographics, etiology, medical history, or treatment patterns were found. Slightly higher BMI and hypertension prevalence was seen in HFpEF riser pattern group, but not statistically significant.

In HFmrEF group, NYHA Class III/IV was significantly higher in risers (96.2%) compared to non-risers (88.9%) (p = 0.02). This signifies that riser pattern in HFmrEF group showed more severity of symptoms when compared to non-riser pattern.

Table 2 shows that HFpEF patients consistently had higher systolic blood pressure (SBP) compared to HFmrEF and HFrEF, both on admission and at discharge. This aligns with the pathophysiology of HFpEF, which is often associated with hypertension. HFrEF patients had the lowest SBP, reflecting the more severe systolic dysfunction in this group. HFmrEF and HFrEF patients had higher pulse rates on admission compared to HFpEF, possibly indicating a more pronounced sympathetic activation in these groups. At discharge, pulse rates normalized across all groups, with no significant differences.⁷

HFpEF patients had the highest prevalence of nocturnal hypertension (52.7%), which may contribute to their higher risk of cardiovascular events and poorer outcomes. HFrEF patients had the lowest prevalence of nocturnal hypertension, possibly due to their lower overall blood pressure levels. It has been well-established that nocturnal BP during sleep is closely associated with cardiovascular events and sub-clinical organ damage. Nocturnal BP surges triggered by obstructive sleep apnoea (OSA) episodes, arousal, rapid-eye-movement sleep, and nocturnal activities, such as nocturia—modulates the circadian rhythm of BP, leading to the different individual circadian variation of 24-hour ambulatory BP. Riser patterns were more prevalent in HFpEF group of patients; however, circadian rhythm patterns showed no significant differences in riser, non-dipper, or dipper patterns among the groups.⁶

The findings show lower SBP at admission and discharge in HFrEF patients compared to HFpEF and HFmrEF align with study by Malha L and White WB in 2024 suggesting that HFrEF patients often present with worse hemodynamic stability.  The lack of significant differences in DBP at discharge across the groups is consistent with the findings of another study by Sierra A et al in 2024 indicating that DBP differences are minimal after standardized heart failure treatment. ^8,9

Table 3 demonstrated that HFpEF patients in our study had the lowest NYHA class, indicating milder symptoms compared to HFmrEF and HFrEF. HFpEF patients had the highest LVEF (56.6%), indicating better heart function compared to HFmrEF (44.9%) and HFrEF (35.2%). This is statistically significant. The variance in NYHA class, although subtle, reflects symptom severity correlating with ejection fraction, which is supported by literature stating that lower LVEF often correlates with higher NYHA classes.^10,11

In our study, HFrEF group had overall higher prevalence of NYHA Class III/IV on admission and HFmrEF riser pattern showed a significantly higher proportion of patients in NYHA Class III/IV on admission when compared to, suggesting more severe symptoms at presentation compared to HFmrEF non-riser pattern. Echo- cardiographic findings showed that LVEF % was lowest in HFrEF and intermediate in HFmrEF and LVEDD was highest in HFrEF and intermediate in HFmrEF which probably led to increased severity of symptoms.^10,11

HFpEF had more incidence of nocturnal hypertension than the other types of HF which was statistically significant. This warrants a need for more frequent use of ABPM devices in AHF patients to detect the presence of nocturnal hypertension and titrate medication accordingly. In patients with HFpEF, a nondipper (less night-time BP dipping)/riser pattern is an independent risk factor for future cardiovascular events, including recurrence of hospitalized heart failure,16 and cognitive dysfunction.¹²

Therefore, ABPM should be an imperative part of antihypertensive strategies designed to control nocturnal BP and contribute to the goal of achieving perfect 24-hour BP management. Nevertheless, additional research is needed to determine the effects of reducing nocturnal BP and improving the circadian BP profile on the rate of HF, other cardiovascular events, and mortality.^12,13

This observational study on ambulatory blood pressure monitoring (ABPM) for patients admitted with acute heart failure at a tertiary care center has provided significant insights into the blood pressure patterns and their clinical implications. Compared to the HFmrEF non-riser pattern, the HFmrEF riser pattern revealed a considerably larger percentage of patients in NYHA Class III/IV upon admission, indicating more severe symptoms at presentation. HFpEF is characterized by higher systolic blood pressure, both on admission and at discharge, and a higher prevalence of nocturnal hypertension. This reflects the association of HFpEF with hypertension and diastolic dysfunction. HFrEF is associated with lower systolic blood pressure and a lower prevalence of nocturnal hypertension. These findings highlight the importance of blood pressure management in AHF and the need for tailored treatment strategies based on HF subtype.

Therefore, optimizing strategies to detect and manage hypertension is of utmost importance.  ABPM can be used for detecting ambulatory cardiovascular risk (isolated daytime hypertension, isolated nocturnal hypertension) in heart failure that cannot be detected using clinic BP measurements.

ABPM is also useful for evaluating the 24-h BP-lowering effect of antihypertensive treatments, and for detecting masked uncontrolled hypertension, and white coat hypertension. ABPM would be useful for detecting ambulatory hypotensive episodes as well (antihypertensive medication-related).

We propose the use of ABPM in all patients admitted with AHF to properly assess circadian rhythm of BP which will help clinicians in tailoring treatment approaches, such as timing of medication administration to optimize blood pressure control and potentially improve clinical outcomes. Future studies should focus on longitudinal outcomes related to these ABPM patterns to further refine treatment protocols and improve patient outcomes in acute heart failure management.

Limitations of Study:

1.            Single-Center Scope: Conducted at a single tertiary care center, the findings may not be generalizable to other settings or populations. The specific patient demographic and healthcare practices at this center might influence the results, limiting their applicability to broader populations.

2.            Lack of Control Group: Without a control group of heart failure patients not undergoing ABPM, it is challenging to directly attribute observed outcomes solely to the patterns identified through ABPM. This limitation restricts the ability to definitively conclude the impact of ABPM compared to standard blood pressure monitoring methods.

3.            Sample Size: Although 100 patients provide a reasonable sample for statistical analysis, this number might still be too small to capture the full spectrum of variability in blood pressure patterns and their clinical implications in acute heart failure. Larger studies could provide more robust data and stronger conclusions.

4.            Confounding Factors: The study might not account adequately for all potential confounding factors that could influence blood pressure patterns, such as medication use, other underlying chronic conditions, or lifestyle factors that were not uniformly controlled across the study population.

5.            Temporal Limitations: ABPM was only conducted over a 24-hour period prior to discharge after initial stabilization, which might not fully capture the longitudinal blood pressure variability and its implications over the entire course of hospitalization or post-discharge outcomes.

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