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Prognostic role of minimum heart rate in elderly heart failure patients with hypertensive heart disease: an analysis of MIMIC-IV database

European Journal of Medical Research volume 30, Article number: 303 (2025) Cite this article

Abstract

Background

Heart rate has been documented as a predictive factor in heart failure. However, its prognostic role in specific heart failure patients is diverse and not comprehensively identified.

Methods

A retrospective cohort study was conducted based on the MIMIC-IV database. 2476 elderly (≥ 60 years old) patients with heart failure and hypertensive heart disease were recruited. The participants were divided into a low minimum heart rate (MHR) (< 60 bpm) group and a high MHR (≥ 60 bpm) group. Multivariable Cox proportional hazards regression analysis was implemented to evaluate the relationship between the two MHR groups and mortality. The association between prognosis and MHR as a continuous variable was elucidated via the restricted cubic spline model. The association in subgroups was assessed as well.

Results

Compared with high MHR, low MHR was significantly associated with higher 30-day all-cause mortalities (hazard ratio 1.289, 95% confidence interval 1.044 to 1.591, p = 0.018), 90-day all-cause mortality (hazard ratio 1.206, 95% confidence interval 1.007 to 1.444, p = 0.042), and 1-year all-cause mortality (hazard ratio 1.183, 95% confidence interval 1.016 to 1.377, p = 0.03) after adjustment for confounding variables. A U-shaped relationship between outcomes and MHR as a continuous variable was observed, with a nadir at MHR of approximately 50 to 60 bpm. The predictive value of low MHR was significant in women or without comorbidity, but not in men or with comorbidity.

Conclusions

We demonstrated that MHR plays a prognostic role in elderly patients with heart failure and hypertensive heart disease. Low MHR predicts higher all-cause mortality, and the association conforms to a U-shaped pattern. Our findings extend those of previous studies and suggest the potential predictive value of HR in specific heart failure patients.

Introduction

Heart rate (HR) is a routinely assessed, simple-to-measure, low-cost metric in clinical practice. For decades, an increasing number of studies have demonstrated that HR is closely associated with cardiovascular events, cardiovascular mortality, and all-cause mortality in both general and diseased populations [1,2,3,4]. Owing to the increasing prevalence and low control rate of hypertension, hypertensive heart disease (HHD) is the second most common cause of heart failure (HF) worldwide [5]. Nearly one-quarter of HF cases are attributed to hypertension [5]. In the aged population, the number increases to over 60% [6]. Despite the prior studies that have documented the close association between HR and outcomes in HF as well as in hypertension [7,8,9], to the best of our knowledge, no studies have been conducted in patients with HF and HHD to date, therefore whether and how HR predicts prognosis in these patients remains unclear.

The prognostic capability of HR is independent of other risk factors in a broad spectrum of disorders, including stable coronary artery disease (CAD), acute coronary syndrome (ACS), hypertension, and HF, as well as non-cardiovascular diseases, for instance, chronic obstructive pulmonary disease (COPD) [10,11,12,13,14]. While the role of HR in HF has been profoundly investigated, mixed or conflicting results have been reported in HF patients under different conditions. A large body of evidence has suggested that the relationship between HR and prognosis in HF patients is complex and may vary by etiology, comorbidity, acute heart failure (AHF), chronic heart failure (CHF), and even age and sex [15], thereby in-depth investigations focusing on specific heart failure patients are warranted.

Patients with HF and HHD, especially elderly patients, frequently have concomitant diseases, such as CAD, atrial fibrillation (AF), hypertension, COPD, and diabetes. Although more patients are prone to increased mortality, the prognosis is actually complex and with large variability. For this reason, approaches are required to identify the high-risk patients who need more intensive care and tailored treatments. Nevertheless, risk stratification in these patients is dramatically challenging because of the complicated clinical conditions. There are few predictive markers in clinical practice with both efficacy and efficiency currently. HR is a promising candidate, but the demonstration of its prognostic value in specific patients with HF and HHD is needed.

To explore the prognostic value of HR in patients with HF and HHD, we conducted a retrospective cohort study based on the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. We extracted data from elderly patients with HF and HHD who were hospitalized in the intensive care unit (ICU). The relationship between minimum heart rate (MHR) on admission and all-cause mortalities at the 30-day, 90-day, and 1-year follow-ups was analyzed to examine the predictive value of MHR for short-term and long-term prognosis in those patients.

Methods

Data source and population

For this retrospective cohort study, patient data were extracted from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. The MIMIC-IV is a large contemporary electronic health record database with free public access. The MIMIC-IV contains deidentified critical care records from approximately 300,000 patients who were admitted to the ICU at Beth Israel Deaconess Medical Center in Boston, MA, in the U.S. during the decade between 2008 and 2019. In total, 2476 elderly (≥ 60 years old) patients with HF and HHD admitted to the ICU were enrolled in the study. The diagnosis of HHD and HF was made according to the recorded diagnosis in the MIMIC-IV database complying with the standards of the International Classification of Diseases, either ninth (ICD-9) or tenth revision (ICD-10). Specifically, we ruled in the patients with chronic hypertension and heart failure irrespective of with or without cardiac ischemia or AF. The exclusion criteria included: age < 60 years; lack of HR data; the patients with obvious identified causes, such as advanced valvular heart disease, toxic cardiomyopathy, infiltrative cardiomyopathy, and so on; the patients with the diagnosis of dilated cardiomyopathy, ischemic cardiomyopathy or hypertrophic cardiomyopathy; the patients with de novo acute HF due to acute MI, acute valvular regurgitation, or fulminant myocarditis.

MHR and outcomes

Each patient’s HR was measured, validated, and recorded hourly while they stayed in the ICU. MHR was defined as the minimum recorded HR within the first 24 h after the patient’s admission to the ICU. The enrolled patients were divided into two groups according to their MHR: a high MHR group (MHR ≥ 60 bpm) and a low MHR group (MHR < 60 bpm). The outcomes in this study were defined as 30-day all-cause mortality, 90-day all-cause mortality, and 1-year all-cause mortality from the patient’s admission date to the ICU.

Data collection

The patients’ data were extracted using PostgreSQL software (version 15.6.21, PostgreSQL Global Development Group). To avoid selection bias caused by an absence of data, the variables that did not apply to more than 30% of the participants were excluded from the study. For those variables with missing data in less than 30% of the participants, we implemented multiple imputation with the MICE package in the R program (version 4.3.2, R Foundation). The information we collected consisted of general characteristics, including age, sex, race, and health insurance; laboratory blood tests, including albumin, serum creatinine, hemoglobin, platelet, and NT-proBNP; prescribed medications, including angiotensin-converting enzyme (ACE) inhibitors, angiotensin receptor blockers (ARBs), calcium channel blockers (CCBs), loop diuretics (furosemide and torsemide), β-blockers, carvedilol, morphine and spironolactone; and comorbidities, including AF, COPD, ischemic heart disease (IHD) and renal failure. All the data originated from the records upon the patient’s admission, and the values of laboratory blood tests were decided as per the first measures taken after the patients were admitted to the ICU.

Statistical analysis

The categorical variables were presented as numbers or percentages and were compared with the Chi-squared test. For continuous variables, we initially performed a normality check using the Shapiro–Wilk test, which showed that all the continuous variables in the study had a skewed distribution. Hence, they were presented as medians with an interquartile range (IQR), and the Mann–Whitney U test was applied for statistical assessment.

The participants were partitioned into two groups according to MHR level: a low MHR group (MHR < 60 bpm) and a high MHR group (MHR ≥ 60 bpm). The Cox proportional hazards regression analysis was conducted to determine the relationship between the MHR groups and all-cause mortalities at the 30-day, 90-day, and 1-year follow-ups. We confirmed that the Cox regression model met the proportional hazards (PH) assumption by the Schoenfeld residuals test (p = 0.0743) and the analysis of the K-M curves of the two groups which showed the same trend without crossover. A hazard ratio with a 95% confidence interval (CI) was used to determine the statistically significant difference between the low MHR group and the high MHR group. A multivariable model was applied to ascertain whether MHR was associated with all-cause mortality independent of potential confounders. Model 1 denoted univariable Cox regression analysis. Model 2 adjusted for Model 1 plus age, sex, race, and health insurance. Model 3 adjusted for Model 2 plus laboratory blood tests, including albumin, serum creatinine, hemoglobin, platelet, and NT-proBNP. Model 4 adjusted for Model 3 plus prescribed medications and comorbidities, including ACE inhibitors, ARBs, CCBs, loop diuretics, β-blockers, carvedilol, morphine, spironolactone, AF, COPD, IHD, and renal failure. Kaplan–Meier survival curves were plotted, and the difference between outcomes in the low MHR group and the high MHR group was detected by the log-rank test at 30 days, 90 days, and 1 year. In addition, the restricted cubic spline (RCS) function was used to uncover the relationship between MHR as a continuous variable and outcomes. Given the sample size, we selected 5 knots. The location of the knots was prespecified based on the quartiles of MHR at 0.05, 0.275, 0.5, 0.725, and 0.95. Subgroups were further generated according to sex or coexisting disorders. Cox proportional hazards regression analysis with adjustment for potential confounders was performed to detect the association between low MHR and high MHR in the subgroups.

All the statistical analyses were implemented using the R program (version 4.3.2, R Foundation) or Prism GraphPad (version 8.0.1, GraphPad software). p < 0.05 indicates statistical significance.

Results

Baseline characteristics

In this study, we recruited 2476 elderly patients with HF and HHD who were admitted to the ICU. A total of 1419 patients were allocated to the high MHR group, while the other 1057 patients were in the low MHR group. The average age was 74 (IQR 68 to 82) years. Females accounted for 1268 (51.2%) of the total patients. There was no significant difference between the high and low MHR groups in terms of age (p = 0.28) or sex (p = 0.733) (Table 1). All the laboratory blood test results were not significantly different between the groups. Notably, CCBs and carvedilol were more commonly prescribed in the low MHR group than in the high MHR group (CCBs: 28.6% vs. 18.2%, p < 0.001; carvedilol: 16% vs. 11.6%, p = 0.02), which may have contributed to the greater HR reduction in the low MHR group. As to comorbidity, AF and renal failure occurred more frequently in the low MHR group than in the high MHR group (AF: 65% vs. 60%, p = 0.013; renal failure: 62.7% vs. 53.9%, p < 0.001).

Table 1 Baseline characteristics by MHR
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Association between MHR and outcomes

Multivariable Cox proportional hazards regression model analysis

We applied the Cox proportional hazards regression model to evaluate the association between the MHR groups and 30-day, 90-day, and 1-year all-cause mortalities. Compared with high MHR, low MHR was significantly associated with higher 30-day all-cause mortality (hazard ratio 1.377, 95% CI 1.121 to 1.692, p = 0.02), 90-day all-cause mortality (hazard ratio 1.262, 95% CI 1.057 to 1.505, p = 0.01), and showed a borderline significance in 1-year all-cause mortality (hazard ratio 1.239, 95% CI 1.068 to 1.438, p = 0.05) (Table 2). We further implemented multivariable analysis to preclude confounding effects from variables. After a series of adjustments, low MHR still exhibited a statistically significant association with higher all-cause mortality compared with high MHR at 30 days (hazard ratio 1.289, 95% CI 1.044 to 1.591, p = 0.018), 90 days (hazard ratio 1.206, 95% CI 1.007 to 1.444, p = 0.042) and 1 year (hazard ratio 1.183, 95% CI 1.016 to 1.377, p = 0.03).

Table 2 MHR predicted all-cause mortality in the multivariable model
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Kaplan–Meier survival analysis

Kaplan–Meier survival curves for the low MHR group and the high MHR group were plotted. All-cause mortality in the low MHR group significantly increased compared with that in the high MHR group at 30 days (p = 0.002), 90 days (p = 0.01), and 1 year (p = 0.005) (Fig. 1a–c). The results implied that low MHR predicts worse outcomes than high MHR does in both short-term and longer-term prognoses.

Fig. 1
figure 1

Kaplan–Meier survival curves for all-cause mortality at 30 days (a), 90 days (b), and 1 year (c) in the low minimum heart rate (MHR) group (dotted line) and the high MHR group (solid line). Log-rank test was used to compare the differences between the groups. p < 0.05 indicates statistical significance

Full size image

U-shaped relationship between MHR and outcomes

To further explore the precise relationship between MHR as a continuous variable and patient outcomes, we performed RCS analysis. By the five prespecified knots, MHR values were partitioned into six intervals from the lowest to the highest, i.e., 0–33 bpm, 34–54 bpm, 55–61 bpm, 62–69 bpm, 70–84 bpm, and 85–121 bpm. The number of patients within each MHR range was 126, 570, 596, 528, 532, and 124, respectively. The curves disclosed a nonlinear U-shaped relationship between MHR and all-cause mortality at all follow-up durations (30 days, 90 days, and 1 year) both with and without adjustment for possible confounders. The U-shaped pattern indicated that either higher or lower MHR from the value at the nadir was linked to increased mortality. Without adjustment, MHR at the nadir was 51 to 60 bpm for 30-day mortality and 55 to 60 bpm for both 90-day mortality and 1-year mortality (Fig. 2a–c). It was 47 to 61 bpm for 30-day mortality and 52 to 61 bpm for both 90-day mortality and 1-year mortality after adjusting for variables (Fig. 2d–f). MHR predicted the best outcomes, as it met the value at the nadir.

Fig. 2
figure 2

Relationship between MHR and all-cause mortality in restricted cubic spline (RCS) plots. The left panels represent hazard ratio and 95% CI for MHR in 30-day mortality (a), 90-day mortality (b), and 1-year mortality (c) without adjustment. The right panels represent hazard ratio and 95% CI for MHR in 30-day mortality (d), 90-day mortality (e), and 1-year mortality (f) after adjusting for variables. The reference: horizontal dotted line denotes hazard ratio = 1; vertical dotted line denotes MHR of 60 bpm. p < 0.05 indicates statistical significance. Adjustment for the variables including age, sex, race, health insurance, albumin, serum creatinine, hemoglobin, platelet, NT-proBNP, ACE inhibitors, ARBs, CCBs, diuretics, β-blockers, carvedilol, morphine, spironolactone, AF, COPD, IHD and renal failure. ACE angiotensin-converting enzyme, AF atrial fibrillation, ARBs angiotensin receptor blockers, CCBs calcium channel blockers, CI confidence interval, COPD chronic obstructive pulmonary disease, HR hazard ratio, IHD ischemic heart disease, MHR minimum heart rate

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Subgroup analysis

For a more comprehensive understanding of the association between MHR and outcomes in specified patients, we separated the participants by sex or by the presence of AF, COPD, IHD, or renal failure. Compared with the high MHR group, the low MHR group was associated with significantly higher all-cause mortality in women at 30 days (hazard ratio 1.422, 95% CI 1.063 to 1.901, p = 0.018), 90 days (hazard ratio 1.362, 95% CI 1.060 to 1.750, p = 0.016) and 1 year (hazard ratio 1.274, 95% CI 1.030 to 1.577, p = 0.026), but not significantly different in men in all terms (Table 3). The association was likewise significant in patients without AF (for 90-day mortality, p = 0.013, and for 1-year mortality, marginal p = 0.052), COPD, IHD (for 30-day mortality, p = 0.019, and for 1-year mortality, p = 0.038) or renal failure, whereas it was not significant in patients with AF, COPD, IHD or renal failure.

Table 3 MHR and outcomes in subgroups
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Discussion

Although how HR is linked to outcomes in HF patients has been explored for decades, to the best of our knowledge, this is the first study to investigate the prognostic value of HR in patients with HF and HHD. In this study, we focused on patients who were older than 60 years, were diagnosed with HF as well as HHD, and were admitted to critical care. We demonstrated that MHR is associated with the prognosis in these patients. Low MHR (< 60 bpm) upon patient admission predicted higher all-cause mortalities than high MHR (≥ 60 bpm). This finding suggested that low HR might be more detrimental than high HR in patients with HF and HHD. In addition to a simple comparison between the low and high MHR groups, we assessed the precise relationship between outcomes and MHR as a continuous variable. MHR and all-cause mortality followed a U-shaped relationship rather than a linear relationship. The MHR for best prognosis was approximately 50 to 60 bpm. Either a higher or lower MHR forecasted increased death in both the short and longer terms. Combining all the above findings, we may speculate that despite implying a worse prognosis by a lower MHR of less than 60 bpm in general, MHR located within a specific range of slightly lower than 60 bpm, presumably predicts a better outcome. As such, identifying favorable HR values in more precise ranges deserves more focus and in-depth investigation in the future.

Our results uncovered that low MHR predicted worse outcomes compared with high MHR, which contrasts with the early findings in HF patients. It has been reported that high baseline HR was related to more cardiovascular events and deaths than low baseline HR in patients with CHF according to the SHIFT and CHARM trials [16, 17]. A subgroup analysis from the BEAUTIFUL trial showed similar results in patients with LVSD and CAD [18]. For patients who have baseline HR ≥ 75 bpm, β-blockers or ivabradine could improve the prognosis by reducing to lower HR [19, 20]. In the above studies, participants were usually divided into the low HR and high HR groups according to defined cut-off values, which were around 70 bpm to 80 bpm [18, 19, 21]. Despite a lower HR cut-off value, 60 bpm, in our study, which may weaken the adverse influence of high HR on prognosis, there might be more important explanations on top of that.

Low HR is more harmful to prognosis than high MHR in our study may be due to a couple of underlying causes as below. Firstly, we already know that in a failing heart, elevated HR leads to reduced contractility and negative inotropism caused by an impaired force–frequency relationship [22], augmenting energy demand and worsening oxygen supply in the myocardium. Moreover, subjects with high HR are more susceptible to ventricular tachycardia, and sudden cardiac death. However, on the other hand, bradycardia is also related to sudden cardiac death in the general population or patients with advanced HF [23,24,25]. Bradycardia, such as sick sinus syndrome and AV block, becomes more common with increasing age because of fibrosis and sclerosis of the conduction system [6]. In this context, more life-threatening bradycardia in the elderly patients in the low MHR group may contribute to higher mortalities in our study.

Secondly, low HR likely raises central aortic pressure by increasing pressure wave reflection as a result of prolonged systolic ejection time [26]. In turn, raised central aortic pressure could lead to poor outcomes [27]. This theory is supported by a meta-analysis which found that a reduction in HR was linked to increased cardiovascular events and death in hypertensive patients caused by elevated central aortic pressure [28]. These detrimental effects were presumably exaggerated in elderly patients with HHD because of advanced age and coexisting hypertension, thereby contributing to more deaths in the low MHR group in this study.

Thirdly, according to the CIBIS II trial, elevated HR was significantly correlated with increased mortality in patients with HF in sinus rhythm but not in those with AF [29]. Conversely, low HR predicted higher mortality in patients with AHF and AF, or patients with advanced CHF and AF [30, 31]. An adopted hypothesis is that appropriately increased HR is a compensatory mechanism, as atrial pump function is lost in AF. In this circumstance, high HR is beneficial, whereas failure to raise might be harmful in AF patients. This makes the relationship between HR and prognosis complex in patients with concomitant AF. AF represents the most common type of arrhythmia in HF patients, and its prevalence is estimated to be nearly 50% in NYHA class IV patients [32]. The burden of AF even doubles in the population > 65 years old [33]. In our study, given that the enrolled patients were aged, with advanced HF, and had HHD, which is also a major risk factor for AF, the prevalence of coexisting AF was more than 60% in the total participants and even higher in the low MHR group. In this context, AF seemed to account for the correlation between low MHR and worse outcomes to a certain extent. However, in the subgroup analysis, low MHR failed to predict a worse prognosis in the patients with AF, which suggested that the effect might be in a more sophisticated manner. Considering the limitation of a subgroup analysis, more in-depth explorations are warranted in the future.

Fourthly, the main post hoc analysis concluded that high HR predicted adverse outcomes from CHF patients, but not AHF patients [16, 17, 34]. Nevertheless, increased HR is an important compensatory mechanism in AHF, so the failure to increase HR might reflect incompetence due to underlying severe abnormalities in the cardiac conduction system. This is supported by the studies reporting that low admission HR was linked to worsening outcomes in hospitalized AHF patients [30, 35]. In our present study, the median of blood NT-proBNP concentration in the total participants was about 2000 pg/ml (IQR: 672.25 to 4936.75 pg/ml), and there was no difference between the groups (p = 0.882). Despite the rising level of NT-proBNP on average, it’s not able to ensure that most patients in the study were presented with acute HF because NT-proBNP level is considerably affected by multiple clinical factors, such as old age, obesity, AF, and renal dysfunction. Hence, whether admission with acute HF contributed to our results, at least in part, remains uncertain and needs a careful scrutiny.

We further examined how MHR is related to prognosis as a continuous variable and found that they followed a U-shaped correlation. Indeed, a U-shaped (or J-shaped) relationship is not uncommon in HF and other diseases. Increasing evidence has shown that HR is related to outcomes in a U-shaped pattern in both CHF and AHF, irrespective of in sinus rhythm or AF [35,36,37]. In addition to HF, a U-shaped relationship has been reported in other cardiovascular diseases including hypertension. An analysis based on the INVEST trial found a linear relationship for baseline resting HR but a J-shaped relationship for follow-up resting HR in hypertensive patients with CAD [38]. A similar J-shaped relationship was observed in a cohort study in patients with resistant hypertension [9]. Besides, the J-shaped relationship seems also more likely to exist in high-risk patients, such as those with diabetes or ACS [39, 40]. Our findings are in agreement with those of the above studies by confirming a U-shaped relationship in patients with HF and HHD in an acute setting.

The SHIFT study concluded that ivabradine or β-blockers had the best effect on outcomes in HF patients with HR reduction > 10 bpm or who achieved HR < 60 bpm [41]. In a U-shaped pattern, resting HR in the range of 55 to 65 bpm was associated with the best prognosis in patients with CHF according to Cullington et al.’s observation and analysis from the CIBIS-ELD trial [36, 37]. By comparison, Bui et al. reported the best HR range of 70 to 75 bpm in patients hospitalized with AHF [35]. Our results revealed that MHR between around 50 and 60 bpm favored outcomes to the best extent after adjusting for potential confounders. This value was slightly lower than the range reported in previous findings, which may be attributed to differences in age, sex, cardiac rhythm, disease severity, or comorbidity. It is worthwhile to identify the HR range for the best prognosis in specific patients. From this aspect, our findings provide a clue in clinical practice for HR titration in patients with HF and HHD.

In our subgroup analysis, the association between MHR and all-cause mortality was significant in women but not in men. This is the opposite of the findings in the majority of earlier studies, in which the association was stronger in men but weaker or even absent in women [42, 43]. The mechanism remains unclear. The greater viability of HR in women and more risk factors for atherosclerosis in men may account for this difference [44]. However, there are still exceptions. One study based on the National Health and Nutrition Examination Survey showed a strong association between HR and cardiovascular mortality in African American women [45]. This indicated that the relationship may vary by sex in different races. It’s already known that gene expression plays a key role in the development and diversity of heart failure and hypertension [46,47,48]. In particular, genetic polymorphism likely accounts for the racial discrepancy to some extent and hence warrants investigation [49]. Similarly, Okin et al. reported that the association between in-treatment HR and all-cause mortality in hypertensive patients with electrocardiographic left ventricular hypertrophy was significantly steeper in women than in men [50]. Our results were similar to the above observations. A possible explanation could be that after adjusting for age, HR in women is typically 2 to 7 bpm higher than that in men on average [51], therefore, lower MHR with the same value indicates a relatively greater HR decline in women than in men. The difference between women and men is deemed to be affected by many factors and warrants further in-depth exploration.

Additionally, we observed that the association between MHR and mortality was significant in patients without AF, COPD, IHD, or renal failure but not in those with any of these disorders. In aged patients, comorbidity commonly exists and is a key factor in determining the relationship between HR and outcomes. The prognostic role of HR may be entangled with comorbidity and thus render an erratic consequence. Previous studies have revealed the inconsistent effect of HR on the prognosis in patients with coexisting AF [29,30,31]. In patients with concomitant COPD or IHD, because elevated HR is a powerful prognostic marker for COPD and IHD as well [14, 52], combinations of disparate, even conflicting, relationships may lead to inconclusive or nonsignificant consequences. Our study supported this theory by showing no significant association between MHR and outcomes in patients with HF, HHD, and comorbidity. However, the results were from the subgroup analysis. Further investigation should be focused on a specific comorbidity and elaborate its effect on the prognostic role of HR.

There are several limitations in the present study. We utilized a multivariable model to preclude potential confounding effects, even so, there were unknown confounders we did not take into account due to the nature of a cohort study. Also, some biomarkers, for instance, C-reactive protein (CRP), were not available or lacked enough data in the MIMIC-IV database. In addition, specific subgroups, like the patients with AF, were not thoroughly explored herein but deserve close examination and in-depth discussion in our future studies. Another limitation is that we only assessed MHR within 24 h of patient admission. It has been reported that 24-h ambulatory HR as well as alterations in follow-up resting HR have more reliable predictive value in cardiovascular diseases [52, 53]. These parameters need to be considered in our further investigations. Moreover, we did not evaluate the exact contributions of cardiac rhythm or left ventricular ejection fraction in this study. In the future, the analysis focusing on these variables is warranted. Besides, whether the prognostic value of HR can be extrapolated to young, middle-aged, or stable patients with HF and HHD needs to be explored in further studies.

Conclusions

Convincing evidence has demonstrated the association between HR and outcomes in cardiovascular diseases, especially HF. We extended the investigation to elderly patients with HF and HHD. The results uncovered that low MHR predicts higher all-cause mortality in these patients. Furthermore, the relationship was displayed in a U-shaped pattern. Based on our findings, MHR may play a valuable prognostic role in clinical practice in specific heart failure patients.

Availability of data and materials

Publicly accessible datasets were analyzed in this study. The data are available at the website: https://mimic-iv.mit.edu/docs/access/.

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Authors and Affiliations

  1. Harbin Medical University, Harbin, 150001, Heilongjiang, China

    Xiaowei Li, Yanli Yang, Xiaolong Zhu, Hongyuan Xia & Zhen Tan

  2. Department of Cardiology, The Fourth Affiliated Hospital of Harbin Medical University, Harbin, 150001, Heilongjiang, China

    Xiaowei Li, Yanli Yang, Xiaolong Zhu, Hongyuan Xia & Zhen Tan

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XL designed the study; XL was responsible for the data extraction from the MIMIC-IV database; XL, YY, XZ, HX, and ZT analyzed the data; XL and ZT wrote the paper. All authors read and approved the final manuscript.

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Li, X., Yang, Y., Zhu, X. et al. Prognostic role of minimum heart rate in elderly heart failure patients with hypertensive heart disease: an analysis of MIMIC-IV database. Eur J Med Res 30, 303 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s40001-025-02574-8

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European Journal of Medical Research

ISSN: 2047-783X

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