Association of proportional pulse pressure with cardiac function and complications in patients hospitalized with acute exacerbation of chronic heart failure

Abstract

Background

Proportional pulse pressure (PPP), calculated as pulse pressure divided by systolic blood pressure, is a simple, non-invasive hemodynamic index. Previous studies suggest its potential role in assessing cardiac function and prognosis in heart failure (HF) patients, particularly in identifying low cardiac output. This study aimed to investigate the relationship between PPP and key cardiac functional indices (Cardiac Index [CI] and Cardiac Output [CO]) in patients with hospitalized with acute exacerbation of chronic heart failure (CHF).

Methods

This cross-sectional study included 80 hospitalized patients with acute exacerbation of CHF at Baqiyatallah Hospital in Tehran (2024). Patients with arrhythmias (including atrial fibrillation, atrial flutter, or ventricular tachycardia), valvular disease, or thyroid disorders were excluded. Brachial blood pressure was measured multiple times, and average PPP was calculated. CI and CO were determined via transthoracic echocardiography. Correlation and multiple regression analyses were performed to assess the relationship between PPP and CI/CO, controlling for confounders like age and gender. Patients were also divided into quartiles based on PPP for comparative analysis.

Results

The mean age was 64.8 ± 10.7 years, and 70% were male. A modest but statistically significant positive correlation was found between PPP and both CI (r = 0.258, p = 0.021) and CO (r = 0.187, p = 0.04). Multivariate regression identified PPP as the strongest independent predictor for both CO (Beta = 0.324, p = 0.009) and CI (Beta = 0.324, p = 0.007). Patients in the lowest PPP quartile had significantly lower CO (2.6 vs. 7.0 L/min, p < 0.0001), lower LVOT-VTI (10.6 vs. 21.2 cm), higher heart rate in the highest PPP quartile (89.6 vs. 74.3 bpm in Q2, p = 0.04), and a similar prevalence of pleural effusion (55% vs. 55%, p = 0.9) compared to the highest quartile. Trends towards lower ejection fraction and inverse correlations with BNP and QT interval were not statistically significant.

Conclusion

This study found that proportional pulse pressure is associated with key haemodynamic parameters in patients hospitalised for an acute exacerbation of chronic heart failure. A modest positive correlation was observed between PPP and both cardiac index and cardiac output, and PPP emerged as an independent predictor in the multivariate regression analysis. However, larger prospective multicentre studies are needed to validate these findings.

Introduction

Chronic heart failure (CHF) has become a major problem in developing countries, with coronary artery disease being its most common underlying cause. If not treated properly and in a timely manner, coronary artery disease leads to severe cardiac complications, the most important of which is heart failure [1]. It is associated with a significant increase in complications, mortality, poor quality of life, and a substantial economic burden on national healthcare systems [2]. Despite advances in heart failure treatment, complication and mortality rates remain very high. The American Heart Association/American College of Cardiology guidelines define heart failure as a complex clinical syndrome resulting from any structural or functional cardiac disorder that impairs the ventricle’s ability to fill with or eject blood. This condition is primarily a clinical diagnosis based on a detailed history and physical examination.

Accurate diagnosis in patients suspected of having acute heart failure based solely on history and physical examination is challenging and is confirmed in only 40 to 50% of cases when natriuretic peptide testing or echocardiography is used as the reference standard [3]. Studies have shown that adding plasma natriuretic peptide measurement to the usual history, clinical examination, and conventional investigations (e.g., chest radiography) improves diagnostic accuracy. This has led to the recommendation of these markers in international diagnostic guidelines [3, 4]. Natriuretic peptides are well-established in the diagnostic process for heart failure. Low levels are particularly useful for ruling out heart failure [5]. Numerous studies, mainly in patients presenting with acute symptoms suggestive of heart failure, have convincingly demonstrated the value of natriuretic peptides in this regard [6, 7]. A review indicated that elevated B-type natriuretic peptide levels signify a worse prognosis in patients with heart failure [8]. In individuals with normal blood pressure, hypertension, and those with vascular disease and diabetes, decreased pulse pressure is associated with an increased risk of myocardial infarction, stroke, coronary artery disease, left ventricular hypertrophy, microcirculatory damage, heart failure, and death [9]. Among clinically relevant physical signs in patients with heart failure, pulse pressure and proportional pulse pressure have been identified as independently and significantly associated with low cardiac output in patients with advanced heart failure [10]. Pulse pressure, defined as the difference between systolic and diastolic blood pressure, is a marker of increased large artery stiffness and is a major independent predictor of cardiovascular mortality and new-onset atrial fibrillation [11]. Recent cohort studies have shown that increased systolic pressure is associated with an elevated risk of cardiovascular disease and predicts future cardiovascular events in patients with heart failure [12].

Proportional pulse pressure is an important risk indicator in heart failure. It is a simple, inexpensive, and easily measurable clinical index. This non-invasive test provides useful prognostic information for patients with heart failure with reduced ejection fraction, especially in those with an EF less than 30%, where a lower proportional pulse pressure independently predicts mortality [13]. Proportional pulse pressure, defined as the ratio of pulse pressure to systolic pressure, is associated with functional capacity and identifies a low cardiac index [14]. Among clinically relevant physical signs in CHF, pulse pressure and proportional pulse pressure have been found to be independently and significantly associated with low cardiac output in patients with advanced failure [10]. Measuring proportional pulse pressure is a non-invasive tool for diagnosing and predicting chronic heart failure, and studies have shown it to be associated with certain cardiac indices. Evidence suggests that proportional pulse pressure may help identify heart failure patients presenting with low cardiac output, low ejection fraction, and a worse prognosis. Since this method is non-invasive and the relationship between this index and cardiac index has been somewhat established, if a correlation exists between this index and other heart failure-related indices, it can be used as a predictive factor for complications and for monitoring patients with heart failure. Therefore, this study aims to investigate the relationship between proportional pulse pressure and other cardiac functional indices in patients hospitalized with acute exacerbation of chronic heart failure.

Materials and methods

Study design and population

This prospective cross-sectional study was conducted at Baqiyatallah Medical Specialty Hospital in Tehran. In this cross-sectional design, blood pressure measurements were repeated over the hospitalization period to obtain a stable average PPP value; however, all outcome measurements (echocardiography, laboratory tests, and chest radiography) were performed during the same admission, with predictor and outcome assessed contemporaneously. Patients with chronic heart failure who were hospitalized due to acute exacerbation from January to December 2024 were selected. Sample size was calculated based on the expected correlation between PPP and CI observed in previous studies (r ≈ 0.30) (Petrie et al., 2018). With a power of 80%, alpha of 0.05, and allowing for a 20% dropout rate, a minimum of 74 patients was required. Accordingly, we enrolled 80 patients. Written informed consent was obtained from all participants prior to enrollment. The study protocol was approved by the Institutional Review Board of Baqiyatallah University (approval code IR.BMSU.BAQ.REC.1403.065).

Eligibility criteria

The study included adults over 18 years of age with chronic heart failure who presented with signs and symptoms of heart failure exacerbation. Patients with a history of or documented cardiac arrhythmia including atrial fibrillation, atrial flutter, ventricular tachycardia, or any significant arrhythmia affecting hemodynamic stability, hyperthyroidism, severe iron deficiency anemia, valvular heart disease, and hypothyroidism were excluded.

Clinical assessments and procedures

A detailed medical history was taken for all patients, followed by a complete physical examination, and the findings were recorded. Proportional pulse pressure was measured. Patients underwent tests including a complete blood cell count and Brain Natriuretic Peptide measurement. A 12-lead ECG was obtained to measure the QT interval. A chest radiograph (posteroanterior and lateral views) was obtained for all patients and interpreted by a board-certified radiologist blinded to clinical data to evaluate for Kerley B lines and pleural effusion. Transthoracic echocardiography (Philips EPIQ 7, USA) was performed to assess cardiac functional parameters. Brachial systolic and diastolic blood pressure and pulse rate were measured. Systolic and diastolic blood pressure were measured for each patient once upon admission, once at discharge, and eight times during the study. The average of these ten readings was calculated. Based on this, Pulse Pressure was calculated for each patient using the formula:

Then, for each patient, Proportional Pulse Pressure was calculated using the formula:

Next, Cardiac Output was calculated using the formula:

Subsequently, Cardiac Index was calculated using the formula:

In the above formula, Body Surface Area was calculated separately for men and women using the Schlich formula:

For Men:  

For Women:

Statistical analysis

After data collection and entry, SPSS version 22 was used. Normality of continuous variables was assessed using the Shapiro-Wilk test. Variables with normal distribution are presented as mean ± standard deviation, while non-normally distributed variables (e.g., BNP) are presented as median with interquartile range where appropriate. Descriptive statistics (mean ± standard deviation) were employed for quantitative data, while frequency and percentage were used for qualitative data. Appropriate statistical tests, such as correlation analysis, chi-square, and regression, were performed to examine relationships between parameters. A p-value < 0.05 was considered statistically significant. Multiple regression analysis, while simultaneously controlling for confounding variables, allowed for the examination of the effect of several independent variables (such as age, gender, EF, PPP) on the dependent variables (CI and CO). By including variables like age and gender in the model, the net effect of PPP on cardiac function was isolated, preventing distortion from other factors. Furthermore, standardized coefficients (Beta) indicate which variables have the greatest impact on CI and CO.

Coefficient of Determination (R²): An R²=0.552 for the CO model and R²=0.451 for the CI model indicate the extent to which the model explains the variance in the data.

Quartile analysis (Comparison of quartiles)

Patients were divided into 4 quartiles based on their PPP to enable a systematic comparison of cardiac parameters (such as CO, EF, HR) across different PPP levels. Furthermore, using statistical tests (like ANOVA or Kruskal-Wallis) to compare quantitative variables between quartiles, associations were assessed. This method is suitable for non-normal data and investigates non-linear relationships between variables.

Results

The present study was conducted on 80 patients. Of the total participants, 70% were men and the rest were women. The mean age was 64.8 ± 10.7 years. The youngest and oldest patients were 30 and 88 years old, respectively. Table 1 shows the frequency distribution of variables related to medical history at the time of admission. The mean height was 169.9 ± 10.0 cm, and the mean weight was 79.4 ± 15.2 kg. Diabetes was observed in 41.3% of patients, hypertension in 45%, and ischemic heart disease in 92.5%. 20% of patients had a history of smoking. Edema of extremities was reported in 31.2%, ascites in 10%, and chronic kidney disease in 8.7%. 23.7% of patients had an implanted cardiac device (Table 1).

Table 1.

Frequency distribution of variables related to medical history at admission in the studied patients

Variable	n	% or Value
Male	56	70%
Female	24	30%
Age	80	64.8 ± 10.7 years
Height	80	169.9 ± 10.0 cm
Weight	80	79.4 ± 15.2 kg
Body Mass Index (BMI)	80	27.5 ± 4.6 kg/m²
Diabetes	33	41.3%
Hypertension	36	45%
Ischemic Heart Disease (IHD)	74	92.5%
Smoking	16	20%
Edema of Extremities	25	31.2%
Ascites	8	10%
Chronic Kidney Disease (CKD)	7	8.7%
Implantable Cardioverter-Defibrillator (ICD)	19	23.7%
Percutaneous Coronary Intervention (PCI)	9	11.2%
Coronary Artery Bypass Graft (CABG)	19	23.7%
Orthopnea	28	35%

Table 2 shows the frequency distribution of echocardiographic variables. The mean Left ventricular outflow tract velocity time integral (LVOT-VTI) was 16.0 cm (SD 5.7 cm). The mean LVOT diameter was 2.1 ± 0.19 cm. The mean heart rate (HR) was 79.9 ± 18.4 bpm. The mean ejection fraction (EF) was 26.3 ± 9.7% and the mean pulmonary artery pressure (PAP) was 40.4 ± 13.3 mmHg. The mean QT interval was 419.1 ± 29.9 ms. Mild pleural effusion was observed in 31 patients (38.7%) and moderate in 13 patients (16.2%). Kerley lines were observed in 11 patients (13.8%) (Table 2).

Table 2.

Frequency distribution of echocardiographic variables in the studied patients

Variable	Mean ± SD or n (%)
LVOT-VTI (cm)	16.0 ± 5.7
LVOT Diameter (cm)	2.1 ± 0.19
Heart Rate (bpm)	79.9 ± 18.4
EF (%)	26.3 ± 9.7
PAP (mmHg)	40.4 ± 13.3
QT interval (ms)	419.1 ± 29.9
Pericardial Effusion	23 (28.7%)
Mild	21
Trivial	2
Pleural Effusion	44 (55%)
Mild	31
Moderate	13
Kerley Lines	11 (13.8%)

Table 3 shows the frequency distribution of laboratory variables. Key findings include a mean BNP of 877.8 ± 983.4 pg/mL, with 75% of patients having levels > 125 pg/mL. The mean creatinine was 1.52 ± 0.88 mg/dL, with 52.5% having levels > 1.3 mg/dL. All patients had normal TSH levels, and the majority had normal thyroid hormone levels. Mean hemoglobin was 13.2 ± 1.9 g/dL, and mean HbA1c was 7.9 ± 2.3%.

Table 3.

Frequency distribution of laboratory variables in the studied patients

Variable	Mean ± SD	Unit	Frequency (%)
BNP	877.8 ± 983.4	pg/mL
BNP > 125		pg/mL	60 (75.0)
Creatinine	1.5 ± 0.88	mg/dL
Cr > 1.3		mg/dL	42 (52.5)
Hemoglobin (Hb)	13.2 ± 1.9	g/dL
TSH	2.5 ± 2.1	mIU/L
TSH (0.4–8.9)		mIU/L	80 (100)
T3	1.3 ± 0.6	ng/mL
T3 (0.5–2.2)		ng/mL	63 (78.7)
T4	77.0 ± 22.2	nmol/L
T4 (45–126)		nmol/L	68 (85.0)
Iron (Fe)	35.2 ± 32.8	µg/dL
Vitamin D	29.1 ± 15.6	ng/mL
Vit D > = 10		ng/mL	57 (67.5)
TIBC	327.4 ± 41.4	µg/dL
Ferritin	171.6 ± 150.8	ng/mL
ALT	34.5 ± 30.4	U/L
ALT > = 34		U/L	21 (26.2)
AST	36.0 ± 23.8	U/L
AST > = 31		U/L	31 (38.7)
HbA1c	7.9 ± 2.3	%
Platelet (PLT)	233.0 ± 97.2	x10³/µL
D-dimer Negative			74 (92.5)
Troponin Negative			70 (87.5)

Table 4 shows the correlation coefficients between PPP and CI, CO, BNP, and QT. A significant correlation was found between CI and PPP (r = 0.258; P = 0.021) (Table 4 and Fig. 1). A significant correlation was also observed between CO and PPP (r = 0.187; P = 0.04) (Table 4 and Fig. 2). Correlations between PPP and both QT interval (r=-0.149, p = 0.188) and BNP (r=-0.164, p = 0.145) were not statistically significant (Table 4, Fig. 3 and 4).

Table 4.

Correlation Coefficients between PPP and CI, CO, BNP, and QT

Variable	Correlation Coefficient (r)	P-value
CI	0.258*	0.021
CO	0.187	0.04
BNP	-0.164	0.145
QT	-0.149	0.188

The asterisk (*) next to the correlation coefficient for CI is preserved, typically indicating statistical significance (its P-value is less than 0.05)

Fig. 1.

Scatter plot of CI values against PPP

Fig. 2.

Scatter plot of CO values against PPP

Fig. 3.

Scatter plot of QT interval values against PPP

Fig. 4.

Scatter plot of BNP values against PPP

Table 5 compares clinical and echocardiographic variables across PPP quartiles. Patients were divided into 4 quartiles (20 patients each). Quartile 1: lowest PPP (≤ 0.33); Quartile 4: highest PPP (≥ 0.42). The percentage of males in quartile 1 (75%) was higher than in quartile 4 (63%). The prevalence of pleural effusion was 55% in quartile 1 compared to 55% in quartile 4 (p = 0.9). Regarding hemodynamic parameters, LVOT-VTI showed a significant decrease from 21.2 cm in quartile 4 to 10.6 cm in quartile 1. A significant increase (p = 0.04) in heart rate was observed across quartiles, with the highest rate (89.6 bpm) in Q4 and the lowest (74.3 bpm) in Q2. No significant difference in the frequency of Kerley B lines was observed among the PPP quartiles (p = 0.5). Corrected QTc values were 421 ± 31 ms in Q1, 418 ± 28 ms in Q2, 420 ± 30 ms in Q3, and 417 ± 29 ms in Q4 (p = 0.07).

Table 5.

Statistics for the comparison of CI and CO predictor variables across PPP quartiles

Variable	Total Patients (n = 80)	Q1 (PPP ≤ 0.33) (n = 20)	Q2 (PPP 0.34–0.38) (n = 20)	Q3 (PPP 0.38–0.42) (n = 20)	Q4 (PPP ≥ 0.42) (n = 20)	P-Trend
Number	80	20	20	20	20
Male Gender, n (%)	56 (70.0)	15 (75.0)	15 (75.0)	14 (66.7)	12 (63.2)	0.7
Pulmonary Edema, n (%)	23 (28.8)	8 (40.0)	7 (35.0)	3 (15.0)	5 (25.0)	0.04
Pleural Effusion, n (%)	44 (55.0)	11 (55.0)	12 (60.0)	10 (50.0)	11 (55.0)	0.9
Age, years	64.8 ± 10.7	65.0 ± 10.5	65.9 ± 8.6	65.9 ± 10.8	62.5 ± 13.3	0.7
LVOT-VTI, cm	16.0 ± 5.7	10.6 ± 2.6	15.4 ± 4.5	17.1 ± 4.6	21.2 ± 5.4	< 0.0001
LVOT Diameter, cm	2.1 ± 0.19	2.0 ± 0.18	2.1 ± 0.24	2.2 ± 0.11	2.2 ± 0.2	0.02
Heart Rate (HR), bpm	79.9 ± 18.4	80.0 ± 14.3	74.3 ± 17.2	82.0 ± 21.0	89.6 ± 17.2	0.04
PPP	0.38 ± 0.06	0.36 ± 0.05	0.37 ± 0.06	0.37 ± 0.07	0.41 ± 0.06	0.04
Cardiac Output (CO), L/min	4.6 ± 1.8	2.6 ± 0.5	3.8 ± 0.4	5.2 ± 0.9	7.0 ± 1.4	< 0.0001
Cardiac Index (CI), L/min/m²	2.5 ± 0.9	2.1 ± 0.7	2.5 ± 0.7	2.5 ± 0.9	3.0 ± 1.1	0.03
Ejection Fraction (EF), %	26.3 ± 9.7	23.0 ± 9.9	25.5 ± 7.9	26.4 ± 10.1	30.5 ± 9.8	0.1
Pulmonary Artery Pressure (PAP), mmHg	40.4 ± 13.3	42.9 ± 12.4	38.1 ± 13.0	44.3 ± 15.1	36.2 ± 11.5	0.18
QTc, ms	419.1 ± 29.9	421 ± 31	418 ± 28	420 ± 30	417 ± 29	0.07
BNP > 125 pg/mL, n (%)	60 (75.0)	17 (85.0)	15 (75.0)	16 (76.2)	12 (63.2)	0.4
Kerley B Lines, n (%)	11 (13.8)	3 (15.0)	4 (20.0)	1 (5.0)	3 (15.0)	0.5

Quartile Ranges:

• Q1: PPP ≤ 0.33

• Q2: PPP 0.34–0.38

• Q3: PPP 0.38–0.42

• Q4: PPP ≥ 0.42

A multivariate regression analysis was performed to determine the predictors of CI and CO. In the multivariate model, PPP was the strongest predictor of CO (P: 0.009; Table 6). PPP was also the strongest predictor of CI (P: 0.007; Table 7). The regression coefficients for significant predictors are shown in Tables 6 and 7.

Table 6.

Multiple Regression Analysis of CO Predictor Variables

, R-Square = 0.552.	Unstandardized Coefficients		Standardized Coefficients	t	P
	B	Std. Error	Beta
(Constant)	7.208	3.384		2.130	0.037
PPP	9.012	3.363	0.305	2.680	0.009
sex	0.267	0.459	0.067	0.582	0.562
age	− 0.069	0.020	− 0.403	-3.379	0.001
QT	− 0.006	0.007	− 0.091	− 0.832	0.408
EF (%)	0.032	0.024	0.166	1.342	0.184
PAP (mmHg)	0.006	0.016	0.047	0.408	0.684
BNP (pg/mL)	0.000	0.000	− 0.179	-1.477	0.144

Table 7.

Multiple Regression Analysis of CI Predictor Variables

, R-Square = 0.451.	Unstandardized Coefficients		Standardized Coefficients	t	P
	B	Std. Error	Beta
(Constant)	2.474	1.811		1.366	0.176
PPP	4.970	1.799	0.324	2.763	0.007
sex	− 0.118	0.245	− 0.057	− 0.483	0.631
age	− 0.024	0.011	− 0.270	-2.197	0.031
QT	− 0.001	0.004	− 0.037	− 0.325	0.746
EF (%)	0.018	0.013	0.181	1.419	0.160
PAP (mmHg)	0.000	0.009	0.005	0.038	0.969
BNP (pg/mL)	0.000	0.000	− 0.143	-1.145	0.256

Discussion

Proportional pulse pressure can serve as a simple and accessible marker for assessing patient status. Derived by dividing pulse pressure by systolic pressure, PPP has a significant correlation with left ventricular function. Various studies have shown that a reduced PPP is associated with impaired left ventricular systolic function, decreased cardiac output, and increased systemic vascular resistance. In patients with heart failure with reduced ejection fraction, a high PPP typically indicates elevated left ventricular filling pressure, while in patients with preserved ejection fraction, it may be a marker of increased vascular stiffness [15].

From a prognostic perspective, research has shown that a low PPP is an independent predictor of adverse cardiovascular outcomes, including mortality and hospitalization due to worsening heart failure. The mechanism of this association likely involves reduced vascular compliance, impaired endothelial function, and increased cardiac filling pressures. Studies have confirmed these relationships. In patients with heart failure, both abnormally low and abnormally high PPP have been associated with adverse outcomes, though through different mechanisms: low PPP typically reflects reduced stroke volume and low cardiac output, while high PPP (often defined as > 0.50–0.55) may indicate increased arterial stiffness and afterload [16]. Clinically, PPP can be useful for monitoring treatment response and guiding pharmacotherapy, as an increase in PPP following treatment initiation may indicate improved cardiac function. However, this index should be interpreted in conjunction with other hemodynamic parameters and imaging findings to provide a more comprehensive assessment. Overall, as a simple and non-invasive tool, PPP can be beneficial in the evaluation and management of patients with chronic heart failure [17].

Low PPP is more closely associated with ventricular dysfunction and reduced stroke volume, reflecting impaired left ventricular systolic performance [18]. Patients with low PPP are at a higher risk of hospitalization due to worsening heart failure. This association may be attributed to hemodynamic impairment and increased cardiac filling pressures. PPP may serve as a useful marker for assessing the response to pharmacological treatments (such as beta-blockers, ACE inhibitors, or afterload reducing agents) [17]. An increase in PPP after initiating treatment may indicate improved cardiac function.

Elevated PPP may reflect arterial stiffness, which is associated with an increased risk of cardiovascular events, while reduced PPP may be indicative of impaired vascular function and higher left ventricular filling pressures (e.g., pulmonary capillary wedge pressure).

Studies have suggested PPP as a simple and non-invasive marker for risk assessment in patients with heart failure [8].

In the present study, mean PPP serves as a predictor for CI and CO. Furthermore, age demonstrated a significant inverse relationship with cardiac function, such that each year of age increase was associated with a decrease of approximately 0.07 L/min in CO and 0.02 L/min/m² in CI. A decrease in PPP was accompanied by a decline in LVOT-VTI from 21.2 cm to 10.6 cm and an increase in heart rate from 74.3 bpm (Q2) to 89.6 bpm (Q4), consistent with a compensatory response to reduced stroke volume.

In a 2020 study evaluating pulse pressure and proportional pulse pressure as predictors of severity in patients with heart failure, Kothai et al. demonstrated that PPP may help identify heart failure patients presenting with low cardiac output and a worse prognosis [13]. Furthermore, in a 2016 study investigating the clinical significance of pulse pressure in patients with heart failure, Tokitsu et al. demonstrated that a pulse pressure of less than 45 mmHg and greater than 75 mmHg is closely associated with heart failure prognosis, highlighting its clinical importance for risk stratification [18]. In 2018, Petrie, Colin J et al. investigated the relationship between PPP and CI in patients with acute heart failure and reported a significant positive correlation, demonstrating that PPP is a useful non-invasive predictor of CI [19]. Abdallah M. Elshal and colleagues, in 2022, demonstrated that bedside blood pressure parameter measurements are associated with the functional capacity of patients and can predict functional limitation in patients with HFmrEF and HFpEF [20].

The results of the present study revealed a modest correlation between PPP and CO and CI. An inverse, yet statistically non-significant, correlation was also observed between QT and BNP values versus PPP. Recent work has identified several predictors of LVEF improvement in HFrEF patients, including younger age, absence of ischemic etiology, and lower baseline BNP; although PPP was not examined in that study, our findings suggest that baseline hemodynamic parameters such as PPP could potentially add to the prognostic toolkit [21]. Although EF is recognized as a key index for assessing systolic cardiac function, its role in predicting CI and CO was not statistically significant in this study. This observation is consistent with studies that emphasize the importance of integrating hemodynamic and clinical data in the management of heart failure, as EF alone may not fully capture the hemodynamic profile of patients with advanced disease [22].

Limitations

Several limitations of this study warrant consideration. First, the modest correlation coefficients (r = 0.258 for CI, r = 0.187 for CO) indicate that while PPP is statistically significantly associated with cardiac output indices, the strength of this association is weak to moderate, limiting its clinical utility as a standalone diagnostic tool. Second, it is important to acknowledge that PPP does not solely reflect cardiac output; it is also influenced by the vascular component. Therefore, PPP values may be affected by vascular characteristics independent of cardiac performance. In this context, the lack of data regarding antihypertensive treatment and other factors influencing vascular function should be recognized as a limitation of the study. Third, we used BNP rather than NT-proBNP; although both are clinically useful, NT-proBNP has a longer half-life and is less affected by exogenous BNP administration. Fourth, patients with cardiac arrhythmias (including atrial fibrillation) were excluded, which limits the applicability of our findings to a substantial proportion of the heart failure population. Finally, external validation in an independent cohort is needed before PPP can be recommended for routine clinical use. Future prospective multicenter studies with larger sample sizes and longitudinal follow-up are required to confirm these findings and establish clinically meaningful PPP thresholds.

Conclusion

This study found that proportional pulse pressure is associated with key haemodynamic parameters in patients hospitalised for an acute exacerbation of chronic heart failure. A modest positive correlation was observed between PPP and both cardiac index and cardiac output, and PPP emerged as an independent predictor in the multivariate regression analysis. However, larger prospective multicentre studies are needed to validate these findings.

Authors' contributions

MFM (Meysam Fallah Moghaddam): Conceptualization, methodology, data curation, investigation, and writing - original draft. MMF (Maryam Moshkani Farahani): Conceptualization, methodology, supervision, and writing - review and editing. AK (Arezoo Khosravi): Data curation, investigation, formal analysis, and writing - review and editing. MF (Manijeh Fallah): Data curation, investigation, and writing - review and editing. AN (Alireza Nasiri): Formal analysis, visualization, and writing - review and editing. MS (Mojtaba Sepandi): Formal analysis, validation, and writing - review and editing. SJD (Seyed Javad Davari-Sani): Conceptualization, methodology, supervision, project administration, and writing - review and editing (corresponding author).All authors read and approved the final manuscript.

Funding

not applicable.

Data availability

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Declarations

Ethics approval and consent to participate

The study protocol was approved by the Institutional Review Board of Baqiyatallah University (approval code IR.BMSU.BAQ.REC.1403.065). The study complied with the Helsinki Declaration. Written informed consent was obtained from all participants prior to enrollment. The participants were informed about the study objectives, procedures, potential risks, and benefits, and their right to withdraw at any time without affecting their medical care.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.