Abstract
Objective
This study aims to evaluate the clinical characteristics of postmenopausal women diagnosed with heart failure (HF) and to identify prognostic factors associated with mortality during the early post-discharge period—a critical phase marked by increased susceptibility to adverse clinical outcomes.
Methods
This analysis utilized data from the “Research on the Current Status and Trends of Cardiovascular Disease Treatment in Beijing” study, conducted between January 1, 2014, and December 31, 2015. Logistic regression models were applied to identify variables independently associated with short-term post-discharge mortality.
Results
Among the cohort of postmenopausal women with HF, 78.4% had heart failure with preserved ejection fraction (HFpEF). The prevalence of comorbid coronary artery disease, hypertension, and diabetes mellitus was 50.9%, 74.6%, and 36.1%, respectively. Diastolic blood pressure was negatively associated with 30-day mortality [odds ratio (OR) = 0.97; 95% confidence interval (CI): 0.95–1.00; p < 0.05]. Beta-blocker use was negatively associated with 30-day mortality following discharge [OR = 0.45; 95% CI: 0.28–0.67; p < 0.001]. Age was positively associated with 90-day mortality [OR = 1.05; 95% CI: 1.01–1.11; p < 0.05], while use of angiotensin-converting enzyme inhibitors (ACEIs) or angiotensin receptor blockers (ARBs) was negatively associated with 90-day mortality [OR = 0.26; 95% CI: 0.06–0.63; p < 0.05].
Conclusion
Postmenopausal women with HF exhibit distinct clinical characteristics, with a high prevalence of HFpEF and cardiovascular comorbidities. Diastolic blood pressure, age, and the use of beta-blockers and ACEIs/ARBs were identified as significant prognostic factors for short-term mortality during the early post-discharge period. Appropriate management during hospitalization may contribute to reduced mortality risk in this vulnerable timeframe.
Keywords: Early post-discharge period, Heart failure, Heart failure with preserved ejection fraction, Postmenopausal women, Prognostic factors, Vulnerable phase
Introduction
Cardiovascular disease (CVD) remains the leading cause of mortality worldwide, with approximately 51% of annual deaths among women in Europe attributed to CVD-related causes [1]. Heart failure (HF) is a major contributor to cardiovascular morbidity and mortality [2]. A multicenter epidemiological survey on cardiovascular health conducted in 2000 in China, involving 15,518 residents across 10 provinces and cities reported a significantly higher prevalence of HF among women compared to men (1.0% vs. 0.7%, p < 0.05). The prevalence of HF in women increases with advancing age and surpasses that observed in men across older age groups [3]. Data from the China-HF registry, which included 8,516 patients hospitalized with HF, indicated a 5.3% in-hospital mortality rate among female patients [4]. Furthermore, HF exerts a more substantial negative impact on health-related quality of life in women than in men [5].
Menstruation is considered to exert protective effects on the heart, whereas menopause increases cardiovascular risk in women [6]. The influence of female sex hormones on the pathophysiology of HF is consistent and persists throughout the course of the disease [7]. Postmenopausal women, in particular, exhibit significantly higher incidence and mortality rates of HF [8]. Estrogen levels are a major factor contributing to these differences, as confirmed in relevant studies. Estrogen can reduce cardiovascular risk in women and influence cardiac function by acting on myocardial contractile proteins. Female sex hormones are a known significant contributor. In premenopausal women, estrogen promotes the release of nitric oxide (NO), resulting in vasodilation and reduced vascular stiffness [9]. Furthermore, ovarian hormones reduce plasma renin and angiotensin-converting enzyme activity [10]. The onset of menopause, characterized by decreased estrogen levels, is associated with increased arterial stiffness due to collagen accumulation and elastin fragmentation. Estrogen levels play a crucial role in this process. Studies involving ovariectomized and non-ovariectomized rats show distinct regulation of nitric oxide synthase (NOS) expression and activity across different estrogen states. Notably, ovariectomized rats demonstrate reduced NOS activity, which may affect cardiac function.
However, the clinical characteristics and short-term prognosis of postmenopausal women with HF remain underreported [8]. Moreover, current HF management guidelines contain limited data on sex-specific clinical features and prognostic risk factors for female patients with HF [11]. This study aims to describe the clinical features of postmenopausal women with HF and analyze the factors associated with mortality during the early post-discharge period.
Materials and methods
Study participants and grouping
Data were obtained from the project titled Research on the Current Status and Trends of Cardiovascular Disease Treatment in Beijing, conducted between January 1, 2014, and December 31, 2015. The study included 1,231 hospitalized postmenopausal women with chronic HF from nine hospitals in Beijing. All participating hospitals were equipped to manage acute coronary syndrome, atrial fibrillation, and HF, comprising four secondary and five tertiary medical institutions.
Inclusion criteria were postmenopausal women with a primary discharge diagnosis of chronic HF. Menopausal status was determined retrospectively based on the absence of menstruation for 12 consecutive months in women over 40 years of age, excluding pregnancy and other causes of amenorrhea. The diagnosis of chronic HF was made by CVD specialists at the local hospitals based on clinical symptoms, physical signs, and relevant diagnostic evaluations.
Exclusion criteria were as follows:
1) Patients with other severe comorbidities associated with a life expectancy of less than 12 months.
2) Patients who died within 10 min of hospital arrival.
3) Patients who were discharged against medical advice.
4) Patients with chronic HF classified as less than New York Heart Association (NYHA) Class II, or with right HF due to other causes.
Observational indicators
General data
Data were collected by trained personnel through a review of medical records. Collected information included patient age and marital status. Medical history data encompassed a history of CVD, other comorbid conditions, and relevant personal history. The diagnosis of coronary artery disease (CAD) required either definitive imaging evidence or a documented history of related interventions, including percutaneous coronary intervention, coronary artery bypass grafting, coronary computed tomography angiography, or coronary angiography. Patients with a history of CAD did not include those with a diagnosis limited to acute coronary syndrome. Additional clinical indicators collected at admission included heart rate (HR), blood pressure, height, and weight.
Laboratory tests
Upon hospital admission, a 4 mL venous blood sample was obtained from the median cubital vein for biochemical testing. Laboratory measurements included low-density lipoprotein cholesterol (LDL-C) and glycated hemoglobin (HbA1c). In addition, levels of B-type natriuretic peptide (BNP) or N-terminal pro B-type natriuretic peptide (NT-proBNP) were assessed using a chemiluminescent immunoassay.
Echocardiography
All patients underwent transthoracic echocardiographic evaluation within three days of hospital admission. Examinations were performed by trained personnel in the cardiac ultrasound department using a color Doppler ultrasound diagnostic system. The parameters measured included left atrial diameter (LAD), left ventricular end-diastolic diameter (LVEDD), left ventricular end-systolic diameter (LVESD), interventricular septal thickness (IVS), and left ventricular ejection fraction (LVEF). The sonographers were blinded to the patients’ participation in the study.
Pharmacologic treatments during hospitalization
Pharmacologic treatments administered during hospitalization were documented in detail. Medications included aldosterone receptor antagonists, beta-blockers, angiotensin-converting enzyme inhibitors (ACEIs), and angiotensin receptor blockers (ARBs).
Mortality events at 30 and 90 days post-discharge
The study database was linked to the Beijing Death Surveillance System to facilitate continuous monitoring and verification of patient survival status. Patients not recorded in the death registry were presumed to be alive. Complete survival data were obtained for all hospitalized participants. The study was approved by the ethics committees of all participating institutions, and the requirement for informed consent was waived.
Statistical analysis
Statistical analyses were conducted using SAS software, version 9.4 (SAS Institute Inc., Cary, NC, USA). Continuous variables with a normal distribution are expressed as mean ± standard deviation, while non-normally distributed variables are reported as median and interquartile range (IQR). Categorical variables are presented as frequencies and percentages. Multivariate logistic regression analysis was performed to identify factors associated with 30-day and 90-day post-discharge mortality. All variables were initially assessed through univariate analysis. Variables that were statistically significant in the univariate analysis, along with age, were included in the multivariate models. A p-value < 0.05 was considered statistically significant.
Study results
Baseline data
A total of 1,231 postmenopausal women were included in the study, with a median age of 76.0 years (IQR: 69.0–81.0 years). Marital status distribution was as follows: 1,147 participants were married (93.2%), 67 widowed (5.4%), 6 divorced (0.5%), and 11 never married (0.9%). The median age at menopause was 50.0 years (IQR: 46.0–53.0 years).
Regarding comorbidities, 627 participants (50.9%) had CAD, 39 (3.2%) had cardiomyopathy, 294 (23.9%) had atrial flutter or fibrillation, and 150 (12.2%) had valvular heart disease. Hypertension was present in 918 participants (74.6%), diabetes mellitus in 444 (36.1%), hyperlipidemia in 317 (25.8%), ischemic stroke in 261 (21.2%), chronic kidney disease in 135 (11.0%), and anemia in 42 (3.4%). A history of smoking was reported by 42 participants (3.5%) and alcohol consumption by 181 (14.9%).
According to the NYHA classification, 15 patients (1.2%) were classified as Class II, 557 (46.0%) as Class III, and 636 (52.5%) as Class IV. The median body mass index (BMI) was 24.8 kg/m² (IQR: 22.0–27.9 kg/m²). Median HR at admission was 80 beats per minute (bpm) (IQR: 69.0–91.0 bpm). Median systolic blood pressure (SBP) was 130 mmHg (IQR: 120–149 mmHg) and diastolic blood pressure (DBP) was 80 mmHg (IQR: 70–85 mmHg).
Laboratory findings included a median LDL-C level of 2.4 mmol/L (IQR: 1.8–2.9 mmol/L) and median HbA1c of 6.3% (IQR: 5.8–7.3%). The median BNP level was 757 pg/mL (IQR: 249–1920 pg/mL), and NT-proBNP was 2,320 pg/mL (IQR: 856–6,798 pg/mL).
Echocardiographic measurements showed a median LAD of 40.8 mm (IQR: 36.0–45.8 mm), LVEDD of 50.6 mm (IQR: 46.0–57.5 mm), LVESD of 36.0 mm (IQR: 30.0–46.0 mm), and IVS of 10.0 mm (IQR: 8.9–10.8 mm). A total of 794 patients (78.4%) had an LVEF greater than 40%.
Regarding pharmacologic treatment during hospitalization, 746 patients (60.6%) received ACEIs or ARBs, 930 (75.5%) received spironolactone, and 767 (62.3%) were treated with beta-blockers (Table 1).
Table 1.
Baseline characteristics of the study population (Total number = 1231)
| Variable | Value |
|---|---|
| Age (years) | 76.0 [69.0–81.0] |
| Age of menopause (years) | 50.0 [46.0–53.0] |
| Marital Status (n (%)) | |
| Married | 1147 (93.2%) |
| Divorced | 6 (0.5%) |
| Widowed | 67 (5.4%) |
| Coronary artery disease (n (%)) | 627 (50.9%) |
| Cardiomyopathy (n (%)) | 39 (3.2%) |
| Atrial fibrillation/flutter (n (%)) | 294 (23.9%) |
| Valvular heart disease (n (%)) | 150 (12.2%) |
| Hypertension (n (%)) | 918 (74.6%) |
| Diabetes (n (%)) | 444 (36.1%) |
| Hyperlipidemia (n (%)) | 317 (25.8%) |
| Ischemic stroke (n (%)) | 261 (21.2%) |
| Chronic kidney disease (n (%)) | 135 (11.0%) |
| Anemia (n (%)) | 42 (3.4%) |
| Alcohol consumption history (n (%)) | 181 (14.9%) |
| Smoking history (n (%)) | 42 (3.4%) |
| NYHA classification (n (%)) | |
| Grade II | 15 (1.2%) |
| Grade III | 557 (45.2%) |
| Grade IV | 636 (52.5%) |
| BMI (m/kg2) | 24.8 [22.0- 27.9] |
| HR (beats per minute) | 80 [69–91] |
| SBP (mmHg) | 130 [120–149] |
| DBP (mmHg) | 80 [70–85] |
| LDL-C (mmol/L) | 2.4 [1.8–2.9] |
| HbA1c (%) | 6.3 [5.8–7.3] |
| BNP (pg/nL) | 757 [249–1920] |
| NT-proBNP (pg/nL) | 2320 [856–6798] |
| LVEDD (mm) | 50.6 [46.0–57.5.0.5] |
| LVESD (mm) | 36.0 [30.0–46.0] |
| LA (mm) | 40.8 [36.0–45.8.0.8] |
| IVS (mm) | 10 [8.9–10.8] |
| LVEF: >40% (n (%)) | 794 (78.4%) |
| Beta-blockers (n (%)) | 767 (62.3%) |
| ACEI/ARB (n (%)) | 746 (60.6%) |
| Spironolactone (n (%)) | 930 (75.5%) |
NYHA: New York Heart Association; BMI: Body Mass Index, calculated as weight (kg) divided by height (m) squared; HR: Heart Rate; SBP: Systolic Blood Pressure; DBP: Diastolic Blood Pressure; LDL-C: Low-Density Lipoprotein Cholesterol; HbA1c: Glycated Hemoglobin; BNP: B-type Natriuretic Peptide; NT-proBNP: N-terminal Pro-B-type Natriuretic Peptide; LVEDD: Left Ventricular End-Diastolic Diameter; LVESD: Left Ventricular End-Systolic Diameter; LA: Left Atrial Diameter; IVS: Interventricular Septal Thickness; LVEF: Left Ventricular Ejection Fraction; ACEI: Angiotensin-Converting Enzyme Inhibitors; ARB: Angiotensin II Receptor Blockers
Correlation analysis results
As shown in Tables 2 and 3, there were 54 deaths (4.4%) at 30 days and 108 deaths (8.7%) at 90 days following discharge.
Table 2.
Analysis of factors associated with 30-day mortality after discharge (Death number = 54, total number = 1231)
| Variable | Univariate Analysis | Multivariate Analysis | ||
|---|---|---|---|---|
| OR (95% CI) | P Value | OR (95% CI) | P Value | |
| Age (years) | 1.07 (1.03, 1.12) | < 0.001 | 1.01 (0.98, 1.05) | 0.52 |
| Marital Status (Unmarried (reference)) | ||||
| Married | 0.11 (0.01, 1.28) | 0.08 | ||
| Divorced | 0.40 (0.02, 10.02) | 0.58 | ||
| Widowed | 1.16 (0.01, 2.10) | 0.16 | ||
| Coronary artery disease | 0.91 (0.47, 1.75) | 0.78 | ||
| Cardiomyopathy | 0.85 (0.11, 6.33) | 0.87 | ||
| Atrial fibrillation/flutter | 0.88 (0.40, 1.94) | 0.74 | ||
| Valvular heart disease | 0.63 (0.19, 2.07) | 0.45 | ||
| Hypertension | 0.49 (0.25, 0.95) | 0.04 | 0.53 (0.46, 1.85) | 0.99 |
| Diabetes | 1.22 (0.62, 2.37) | 0.57 | ||
| Hyperlipidemia | 0.79 (0.36, 1.75) | 0.56 | ||
| Ischemic stroke | 0.71 (0.29, 1.73) | 0.45 | ||
| Chronic kidney disease | 1.94 (0.84, 4.51) | 0.12 | ||
| Anemia | 4.89 (1.80, 13.25) | 0.002 | 0.70 (0.40, 1.20) | 0.19 |
| Alcohol consumption history | 1.45 (0.62, 3.37) | 0.39 | ||
| Smoking history | 1.73 (0.40, 7.46) | 0.46 | ||
| BMI (m/kg2) | 0.96(0.85, 1.08) | 0.47 | ||
| HR (beats per minute)2) | 1.03 (1.01, 1.04) | < 0.001 | 1.01 (0.10, 1.03) | 0.16 |
| SBP (mmHg) | 0.99 (0.97, 1.00) | 0.06 | ||
| DBP (mmHg) | 0.96 (0.94, 0.99) | 0.006 | 0.97 (0.95, 1.00) | 0.04 |
| LDL-C (mmol/L) | 0.91 (0.60, 1.39) | 0.66 | ||
| BMI (m/kg2) | 0.96(0.85, 1.08) | 0.47 | ||
| HbA1c (%) | 1.02 (0.92, 1.14) | 0.73 | ||
| BNP (pg/nL) | 1.00 (1.00, 1.00) | 0.17 | ||
| NT-proBNP (pg/nL) | 1.00 (1.00, 1.00) | 0.49 | ||
| LVEDD (mm) | 0.98 (0.94, 1.02) | 0.26 | ||
| LVESD (mm) | 1.02 (0.97, 1.06) | 0.46 | ||
| LA (mm) | 0.99 (0.95, 1.04) | 0.77 | ||
| IVS (mm) | 0.95 (0.78, 1.16) | 0.62 | ||
| LVEF: ≤40% | 1.53 (0.63, 3.74) | 0.35 | ||
| Beta-blockers | 0.19 (0.09, 0.40) | < 0.001 | 0.45 (0.28, 0.67) | < 0.01 |
| ACEI /ARB | 0.26 (0.13, 0.54) | 0.003 | 0.95 (0.89, 1.29) | 0.10 |
| Spironolactone | 0.91 (0.47, 1.75) | 0.78 | ||
Note: BMI: Body Mass Index, calculated as weight (kg) divided by height (m) squared; HR: Heart Rate; SBP: Systolic Blood Pressure; DBP: Diastolic Blood Pressure; LDL-C: Low-Density Lipoprotein Cholesterol; HbA1c: Glycated Hemoglobin; BNP: B-type Natriuretic Peptide; NT-proBNP: N-terminal Pro-B-type Natriuretic Peptide; LVEDD: Left Ventricular End-Diastolic Diameter; LVESD: Left Ventricular End-Systolic Diameter; LA: Left Atrial Diameter; IVS: Interventricular Septal Thickness; LVEF: Left Ventricular Ejection Fraction; ACEI: Angiotensin-Converting Enzyme Inhibitors; ARB: Angiotensin II Receptor Blockers.
Table 3.
Analysis of factors associated with 90-day mortality after discharge (Death number = 108, total number = 1231)
| Variable | Univariate Analysis | Multivariate Analysis | ||
|---|---|---|---|---|
| OR (95% CI) | P Value | OR (95% CI) | P Value | |
| Age (years) | 1.06 (1.03, 1.09) | 0.0002 | 1.05 (1.01, 1.11) | 0.03 |
| Marital Status (Unmarried (reference)) | ||||
| Married | 0.18 (0.02, 2.03) | 0.17 | ||
| Divorced | 0.40 (0.02, 10.02) | 0.58 | ||
| Widowed | 0.35 (0.03, 4.24) | 0.41 | ||
| Coronary artery disease | 0.94 (0.60, 1.46) | 0.77 | ||
| Cardiomyopathy | 0.74 (0.18, 3.13) | 0.68 | ||
| Atrial fibrillation/flutter | 0.81 (0.47, 1.40) | 0.45 | ||
| Valvular heart disease | 0.87 (0.43, 1.77) | 0.70 | ||
| Hypertension | 0.65 (0.40, 1.04) | 0.07 | ||
| Diabetes | 0.85 (0.53, 1.36) | 0.49 | ||
| Hyperlipidemia | 0.67 (0.38, 1.18) | 0.17 | ||
| Ischemic stroke | 0.88 (0.50, 1.55) | 0.66 | ||
| Chronic kidney disease | 1.72 (0.94, 3.15) | 0.08 | ||
| Anemia | 2.41 (0.99, 5.89) | 0.05 | ||
| Alcohol consumption history | 1.23 (0.68, 2.24) | 0.50 | ||
| Smoking history | 1.98 (0.76, 5.19) | 0.16 | ||
| BMI (m/kg2) | 0.90 (0.84, 0.97) | 0.004 | 0.93 (0.85, 1.01) | 0.10 |
| HR (beats per minute) | 1.02 (1.01, 1.03) | 0.001 | 1.01 (0.10, 1.03) | 0.16 |
| SBP (mmHg) | 0.99 (0.98, 1.00) | 0.008 | 0.99 (0.97, 1.02) | 0.42 |
| DBP (mmHg) | 0.98 (0.97, 1.00) | 0.04 | 1.03 (0.99, 1.07) | 0.16 |
| LDL-C (mmol/L) | 0.93 (0.70, 1.23) | 0.61 | ||
| HbA1c (%) | 1.00 (0.90, 1.12) | 0.97 | ||
| BNP (pg/nL) | 1.00 (1.00, 1.00) | 0.05 | ||
| NT-proBNP (pg/nL) | 1.00 (1.00, 1.00) | 0.44 | ||
| LVEDD (mm) | 0.99 (0.97, 1.02) | 0.68 | ||
| LVESD (mm) | 1.02 (0.99, 1.05) | 0.14 | ||
| LA (mm) | 1.01 (0.98, 1.04) | 0.68 | ||
| IVS (mm) | 1.00 (0.95, 1.06) | 0.97 | ||
| LVEF: ≤40% | 1.18 (0.64, 2.20) | 0.60 | ||
| Beta-blockers | 0.32 (0.20, 0.50) | < 0.001 | 0.79 (0.69,1.62) | 0.18 |
| ACEI/ARB | 0.32 (0.20, 0.52) | < 0.001 | 0.26 (0.06,0.63) | 0.04 |
| Spironolactone | 1.02 (0.61, 1.72) | 0.94 | ||
BMI: Body Mass Index, calculated as weight (kg) divided by height (m) squared; HR: Heart Rate; SBP: Systolic Blood Pressure; DBP: Diastolic Blood Pressure; LDL-C: Low-Density Lipoprotein Cholesterol; HbA1c: Glycated Hemoglobin; BNP: B-type Natriuretic Peptide; NT-proBNP: N-terminal Pro-B-type Natriuretic Peptide; LVEDD: Left Ventricular End-Diastolic Diameter; LVESD: Left Ventricular End-Systolic Diameter; LA: Left Atrial Diameter; IVS: Interventricular Septal Thickness; LVEF: Left Ventricular Ejection Fraction; ACEI: Angiotensin-Converting Enzyme Inhibitors; ARB: Angiotensin II Receptor Blockers
For the analysis of 30-day mortality, univariate logistic regression identified the following variables as significantly associated with mortality: age, history of hypertension, history of anemia, HR, DBP, and the use of beta-blockers and ACEIs or ARBs (p < 0.05 for all). Variables with statistical significance in univariate analysis were included in the multivariate logistic regression model. The results indicated that DBP was negatively associated with 30-day mortality [odds ratio (OR) per 1 mmHg increase = 0.97; 95% confidence interval (CI): 0.95–1.00; p < 0.05], and the use of beta-blockers was also negatively associated with 30-day mortality [OR = 0.45; 95% CI: 0.28–0.67; p < 0.001].
For the analysis of 90-day mortality, univariate logistic regression showed that age, BMI, HR, SBP, DBP, and the use of beta-blockers and ACEIs/ARBs were significantly associated with mortality (p < 0.05 for all). These variables were included in the multivariate analysis. The results demonstrated that age was positively associated with 90-day mortality [OR = 1.05; 95% CI: 1.01–1.11; p < 0.05], while the use of ACEIs/ARBs was negatively associated with 90-day mortality [OR = 0.26; 95% CI: 0.06–0.63; p < 0.05]. Detailed data are presented in Table 3.
Discussion
Although women represent nearly half of the global population affected by HF, female-specific representation in randomized controlled trials remains limited. Existing data reveal inconsistencies in the clinical characteristics, prognosis, and treatment responses of HF in women [12]. The prevalence of HF increases with advancing age, particularly among women, who exhibit a higher prevalence than men of the same age group [13]. Estrogen levels are a significant factor contributing to these sex-related differences. Estrogen has been shown to reduce cardiovascular risk and influence myocardial function by modulating contractile proteins [14, 15]. In premenopausal women, estrogen promotes the release of NO, resulting in vasodilation and reduced vascular stiffness [16]. Following menopause, the decline in estrogen levels is associated with increased arterial stiffness, driven by collagen accumulation and elastin fragmentation, thereby contributing to elevated blood pressure in postmenopausal women.
Hypertension has a direct impact on cardiac function, including LVEF. In this study, 21.4% of postmenopausal women with HF had an LVEF below 40%, a finding consistent with international reports on female HF populations (Table 4) [2, 17–19]. Ovarian hormones also influence components of the renin–angiotensin–aldosterone system by reducing plasma renin activity and angiotensin-converting enzyme activity [20]. The clinical role of ACEIs and ARBs in improving short-term prognosis is well established. In the present analysis, both age and ACEI/ARB use were significantly associated with 90-day mortality.
Table 4.
Comparison of baseline characteristics between this study and other international female cohort studies
| Variable | This Study (n = 1,231) |
COACH Study (n = 216) |
ADHERE Study (n = 54,674) |
GWTG-HF Study (n = 49,225) |
OPTIMIZE-HF Study (n = 25,075) |
|---|---|---|---|---|---|
| Age (mean ± SD, years) | 74.8 ± 9 | 72.7 ± 11.4 | 74.5 ± 14 | 74 ± 14 | 75.4 ± 13.6 |
| LVEF > 40%(%) | 78.6 | 20.9 | 51 | 56 | 59.6 |
| SBP(mean ± SD, mmHg) | 133.7 ± 22.5 | 120.6 ± 21.9 | -- | 144 ± 31 | 146.3 ± 33.2 |
| BMI(mean ± SD, m/kg2) | 25.2 ± 5.8 | 27.9 ± 6.6 | - | - | - |
| Comorbidities | |||||
| Coronary artery disease | 49.1% | 29.6% | 51% | 44% | 44.4% |
| Hypertension | 74.6% | 48.6% | 76% | 77% | 74.2% |
| Diabetes | 36.1% | 35.7% | 44% | 42% | 41.5% |
| flutter | 23.9% | 22.2% | 30% | 30% | 30.8% |
| Chronic kidney disease | 11.0% | - | 27% | 18% | 16.8% |
| Ischemic stroke | 3.4% | 56.2% | 51% | 20% | 19.8% |
| Medication Use | |||||
| ACEI/ARB | 60.6% | - | - | 60% (EF ≦ 40%) 51% (EF > 40%) | - |
| ACEI | - | 44.9% | 51% | 37.6% | |
| ARB | - | 12.0% | 14% | 12.9% | |
| Beta-blockers | 62.3% | 41.2% | 52% | 41% (EF ≦ 40%) 37% (EF > 40%) | 51.6% |
| Aldosterone | 75.5% | 29.3% | - | 13% (EF ≦ 40%) 5% (EF > 40%) | 6.3% |
BMI: Body Mass Index, calculated as weight (kg) divided by height (m) squared; SBP: Systolic Blood Pressure; LVEF: Left Ventricular Ejection Fraction; ACEI: Angiotensin-Converting Enzyme Inhibitors; ARB: Angiotensin II Receptor Blockers
Findings from the STRONG-HF (Strengthening the Treatment of Heart Failure) study similarly demonstrated that a simplified treatment regimen consisting of ACEI/ARB, beta-blockers, and mineralocorticoid receptor antagonists significantly reduced rates of readmission and mortality during the early post-discharge period [21]. However, some studies have reported that the therapeutic benefit of ACEIs may be less pronounced in female patients compared to males, whereas ARBs offer comparable benefits across sexes [22]. In patients with HFpEF, women generally exhibit better treatment responses than men. Further investigation into sex-specific treatment responses in HFpEF remains essential. Contributing factors such as lower natriuretic peptide levels, NOS-dependent regulation, sex-based differences in microvascular inflammation, and variations in dose-response relationships warrant continued research [23].
In patients with HF, an increase in HR from baseline is associated with worse outcomes; specifically, each 1 bpm increase in HR is associated with a 3% increased risk of cardiovascular death or hospitalization due to worsening HF, while a 5 bpm increase corresponds to a 16% higher risk [24]. Initiating treatment with ivabradine and beta-blockers during hospitalization for acute HF has been shown to significantly reduce HR, improve hemodynamic parameters, and enhance short-term survival [25]. In the present study, correlation analysis demonstrated that DBP and the use of beta-blockers were significantly associated with 30-day mortality, further supporting the clinical importance of HR control and beta-blocker therapy in improving short-term outcomes in patients with HF.
The global prevalence of obesity is higher in women, and each standard deviation increase in BMI is associated with a 34% increased risk of developing HFpEF [26]. Central (abdominal) obesity, which is more common in postmenopausal women, has been significantly associated with worsening HF [27, 28]. The increased prevalence of both diabetes and obesity in female patients highlights a key pathological mechanism of HFpEF, which centers on systemic inflammation [29]. At the cellular level, endothelial microvascular inflammation affects NO signaling. NO is synthesized by NOS. In HFpEF, reduced NO bioavailability in cardiomyocytes may contribute to left ventricular diastolic dysfunction and myocardial fibrosis. Estrogen levels play a critical role in regulating this pathway. Animal studies involving ovariectomized and non-ovariectomized rats have demonstrated differential regulation of NOS expression and activity depending on estrogen status. Notably, ovariectomized rats exhibit reduced NOS activity, which may adversely affect cardiac function [23].
Previous studies have shown that, in 2006, approximately 10.8% of hospitalized patients with HF died within one month following discharge [30]. More recent data from the Diuretic Strategies in Acute Heart Failure study reported a 60–90-day readmission rate of up to 30% among patients with HF [31]. In the present study, the 30-day and 90-day mortality rates among postmenopausal women were 4.4% and 8.7%, respectively. These findings suggest an improvement in short-term survival compared to earlier reports; however, the overall survival rate remains suboptimal.
Limitations
This study is a retrospective observational analysis and is subject to several inherent limitations. First, patient histories were incomplete for some variables; for example, age at menopause was recorded for only 72.71% of participants, potentially limiting the depth of related analyses. Prior international studies have suggested that age at menopause is associated with HF risk and prognosis in women [32]. Additionally, the study did not capture the use of many newer HF therapies introduced in recent years, nor did it include data on the final treatment outcomes.
The retrospective design, based on registry data, carries an inherent risk of bias. Selection bias may have occurred, as the cohort included only hospitalized patients who met specific inclusion criteria, thereby limiting generalizability to postmenopausal women with HF in outpatient settings or with excluded conditions. Information bias is also a concern, as data were extracted from medical records, which may be incomplete or inconsistently documented. Medication data reflected inpatient prescriptions but did not include information on dosing, adherence, or changes after discharge. Additionally, data on disease severity, socioeconomic status, and lifestyle factors such as diet and physical activity were not available.
The diagnosis of HFpEF was based on LVEF > 40% and clinical signs and symptoms, as comprehensive diastolic function parameters were not systematically collected in the registry. This limits the precision of HFpEF classification according to current diagnostic standards.
Although standardized abstraction protocols were used, along with objective mortality data, blinded echocardiographic assessments, and multivariable adjustment for key confounders, residual confounding from unmeasured variables remains possible. The study design also precludes causal inference. Therefore, the observed associations between in-hospital treatments and post-discharge mortality should be interpreted as hypothesis-generating, suggesting potential targets for future interventional studies rather than establishing definitive causality.
Prospective cohort studies with active follow-up and detailed phenotyping, as well as randomized controlled trials specifically evaluating interventions during the early post-discharge period in this high-risk population, are essential to validate our findings and generate higher-level evidence for clinical practice. This study assessed mortality only at 30 and 90 days post-discharge. While these time points capture the critical early vulnerable period, they do not provide information on longer-term outcomes such as 6-month or 1-year mortality. Future studies should extend follow-up duration to assess the sustainability of interventions over time; apply Cox proportional hazards regression to analyze longer-term time-to-event data; and explore advanced machine learning approaches to enhance risk stratification, improve predictive accuracy, and identify novel high-risk subgroups.
Additionally, the study population was drawn exclusively from hospitals in Beijing, China. While this offers valuable insights into a specific metropolitan cohort, it limits the generalizability of the findings to other regions or ethnic populations. Cardiovascular risk profiles, healthcare infrastructure, access to care, and treatment practices may vary across geographic and cultural contexts, potentially influencing both patient characteristics and prognostic factors. Future multi-regional or international studies are needed to confirm the applicability of these results across diverse populations.
Conclusion
Postmenopausal women with HF predominantly present with HFpEF, with diabetes, hypertension, and obesity identified as key contributing comorbidities. Although the prognosis during the early post-discharge period remains poor, heart rate control and the use of beta-blockers and ACEIs or ARBs during hospitalization may improve short-term outcomes. Given the limited international evidence specific to postmenopausal women with HF, further prospective cohort studies and randomized controlled trials are necessary to better understand this population and to inform tailored treatment strategies.
Acknowledgements
Not applicable.
Author contributions
Conceptualization: Yu-qing Sun, Jian-zeng Dong, Chang-sheng MaData curation: Yu-qing Sun, Liu HeData analysis: Liu He, Xin DuStatistical analysis: Yu-qing Sun, Liu HeFunding acquisition: Roles/Writing - original draft: Yuqing Sun, Jian-zeng DongWriting - review & editing: Xin Du, Chang-sheng Ma. All authors approved the final manuscript as submitted and agree to be accountable for all aspects of the work.
Funding
No funding was received.
Data availability
The datasets generated and analysed during the current study are not publicly available but are available from the corresponding author (Jian-zeng Dong ) on reasonable request.
Declarations
Ethics approval and consent to participate
This study was conducted in accordance with the declaration of Helsinki.This study was conducted with approval from the Ethics Committee of Beijing Anzhen Hospital. As this is a retrospective study, the clinical data of the patients involved are all based on the patient’s past medical history and actual diagnosis and treatment data during hospitalisation. This study does not interfere with routine diagnosis and treatment, does not affect patients’ medical rights, and does not increase additional risks to patients. Therefore, after discussion with the Ethics Committee of Beijing Anzhen Hospital, Capital Medical University, it was decided to waive the requirement for informed consent from patients. In addition, patients’ clinical data will be used for scientific research and confidentiality will be ensured. The patient’s consent was informed and obtained during hospitalisation.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The datasets generated and analysed during the current study are not publicly available but are available from the corresponding author (Jian-zeng Dong ) on reasonable request.