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Body mass index modifies the major adverse cardiovascular and cerebral events risk of NT-proBNP in patients with acute coronary syndrome

Diabetology & Metabolic Syndrome volume 17, Article number: 88 (2025) Cite this article

Abstract

Background

Little is known about the relationship between body mass index (BMI) and the prognostic value of N-terminal pro-B-type natriuretic peptide (NT-proBNP) in patients with acute coronary syndrome (ACS). This study aimed to investigate how BMI modifies the association between NT-proBNP levels and clinical outcomes in ACS patients.

Methods

A total of 11,757 ACS patients from the Cardiovascular Centre Beijing Friendship Hospital were recruited. The association between NT-proBNP and major adverse cardiovascular and cerebral events (MACCEs) was assessed using multivariate Cox proportional hazards models. The multiplicative interaction between NT-proBNP and BMI was evaluated using the Wald χ2 test.

Results

During the median follow-up time of 3.04 (IQR: 1.07‒5.02) years (33,232 person-years), 1996 MACCEs were documented. A significant multiplicative interaction was observed between natural logarithm (Ln)-NT-proBNP and BMI (p for multiplicative interaction = 0.013). The categorical thresholds of NT-porBNP for the risk of MACCEs were 1559, 155, and 419 pg/ml for normoweight, overweight, and obese patients, respectively. When NT-proBNP levels were near-normal or mildly elevated (≤ 300 pg/ml), overweight and obese patients exhibited a higher event probability than normoweight patients at a given NT-proBNP level. However, an opposite trend was observed at significantly elevated NT-proBNP levels (> 300 pg/ml), with normoweight patients showing a higher event probability. When BMI and NT-proBNP were considered jointly, normoweight patients with elevated NT-proBNP had a significantly higher risk of MACCEs than overweight patients without elevated NT-proBNP (hazard ratio: 2.28; 95% confidence interval: 1.83‒2.84; p < 0.001).

Conclusion

The prognostic value of NT-proBNP in ACS patients varies with BMI, with the extent of NT-proBNP elevation playing a role in this relationship.

Introduction

The prevalence of obesity and acute coronary syndrome (ACS) is gradually increasing, leading to an increase in morbidity and mortality and posing a significant burden on global public health [1, 2]. Early identification of high-risk patients and prompt risk stratification has become crucial to optimize clinical outcomes in ACS populations. N-terminal pro-B-type natriuretic peptide (NT-proBNP) is a biomarker with established diagnostic and prognostic value in heart failure (HF) and ACS [3,4,5,6]. Elevated concentrations of NT-proBNP serve as a biomarker of cardiac stress and ventricular dysfunction, demonstrating significant correlation with poor clinical outcomes in ACS patients [7,8,9], as well as improving risk stratification when added to clinical risk models [10, 11]. However, multiple factors, such as age, sex [12], renal function [13], and body mass index (BMI) [14] influence NT-proBNP levels. Previous studies in both the general population and patients with HF found that BMI and NT-proBNP were negatively correlated within a certain range, which could potentially modulate the prognostic value of NT-proBNP [14,15,16]. However, the association between BMI and NT-proBNP in ACS patients remains elusive. Besides, whether NT-proBNP-associated adverse outcomes are modified by BMI in ACS patients is worthy of investigation.

The present study explored the modifying effect of BMI on the relationship between NT-proBNP levels and the risk of major adverse cardiovascular and cerebral events (MACCEs) in ACS patients. By examining the interplay between these two parameters, we seek to gain more insights into the complex relationship between BMI, NT-proBNP, and prognosis of patients with ACS, as well as identify subgroups of patients who may benefit from more intensive monitoring and targeted interventions. This may pave the way for the development of more personalized risk prediction models and treatment strategies for ACS patients.

Methods

Study population

This observational cohort study enrolled a consecutive sample of 15,330 patients with ACS admitted to Beijing Friendship Hospital between January 2013 and January 2021. The exclusion criteria were as follows: (1) lack of NT-proBNP or BMI data; (2) BMI < 18.5 kg/m2; (3) severe renal insufficiency with an estimated glomerular filtration rate (eGFR) < 30 ml/min/1.73 m2 or patients on kidney replacement therapy; (4) severe acute infection or malignancy; and (5) the presence of cardiogenic shock. ACS was defined as unstable angina pectoris (UAP), non-ST-segment elevation myocardial infarction (NSTEMI), or ST-segment elevation myocardial infarction (STEMI) [17]. Diabetes was defined as a previous diagnosis, current use of anti-diabetic drugs, fasting plasma glucose (FPG) ≥ 7.0 mmol/L, or glycated hemoglobin (HbA1c) ≥ 6.5% [18]. Cardiogenic shock was defined as systolic blood pressure (SBP) < 90 mmHg for at least 30 min or the need for catecholamines to maintain SBP above 90 mmHg, along with clinical evidence of pulmonary congestion and impaired end-organ perfusion (altered mental status, cold/clammy skin and extremities, urine output < 30 ml/hour, or lactate > 2.0 mmol/L), or a Killip class IV rating [19]. A total of 11,757 ACS patients were included in the final analysis (Supplemental Fig. 1). The study was approved by the Ethics Committee of Beijing Friendship Hospital affiliated with Capital Medical University and followed the principles of the Declaration of Helsinki.

Measurement of NT-proBNP

NT-proBNP levels were measured using the Chemiluminescent Enzyme Immuno Assay (PATHFAST™ Immunoanalyzer, PHC Europe B.V.), which exhibits a detection range of 15 pg/ml to 30,000 pg/ml, with a coefficient of variation ranging from 4.6 to 5.4%. The peak NT-proBNP value was utilized for further analyses. NT-proBNP values were stratified into quintiles: Q1 (< 64 pg/ml), Q2 (64‒154 pg/ml), Q3 (155‒418 pg/ml), Q4 (419‒1558 pg/ml), and Q5 (≥ 1559 pg/ml). The subgroups were further categorized into designated risk levels: low-risk (Q1 and Q2), intermediate-risk (Q3 and Q4), and high-risk (Q5).

Definition of BMI

BMI was determined by dividing the weight in kilograms by the square of the height in meters (kg/m2). Patients were categorized into three BMI groups based on the guidelines established by the Working Group on Obesity in China: normoweight (18.5–23.9 kg/m2), overweight (24.0–27.9 kg/m2), obese (≥ 28.0 kg/m2) [20]. For the current analysis, patients who were underweight (BMI < 18.5 kg/m²) were excluded for the following reasons: (1) underweight status is associated with unique metabolic derangements (e.g., cachexia, malnutrition, or sarcopenia) and frailty [21], which may exert independent influences on cardiovascular outcomes in ACS patients; (2) the relatively small sample size of underweight ACS patients in our cohort (n = 250) precludes meaningful subgroup analysis while introducing disproportionate variance.

Outcomes

Follow-up information was collected by telephonic interviews or outpatient clinic visits conducted at 1-, 3-, and 6-month intervals, and annually thereafter until either the participant reached their primary endpoint or the end of the follow-up (March 31, 2021), whichever came first. The primary endpoint of the study was MACCEs, which is the composite of all-cause death, non-fatal myocardial infarction, non-fatal stroke, and ischemia-induced revascularization. Non-fatal stroke, including ischemic and hemorrhagic stroke, was defined as neurological dysfunction resulting from cerebral vascular obstruction or sudden rupture, as diagnosed through computed tomography or magnetic resonance imaging. Revascularization was defined as either percutaneous coronary intervention (PCI) or coronary artery bypass grafting (CABG) of target or non-target vessels.

Covariates

Clinical data, encompassing demographic details, lifestyle factors, medical history, physical examination results, and inpatient treatments, were gathered from medical records. The medical history was obtained through patient self-reporting. Inpatient treatment encompassed antiplatelet therapy (aspirin, or clopidogrel/ticagrelor), β-blocker, angiotensin-converting enzyme inhibitor (ACEI) or angiotensin receptor blocker (ARB), statins, and PCI. Peripheral venous blood samples were obtained and examined for various biomarkers, including FPG, hemoglobin, high-sensitivity C-reactive protein (hs-CRP), total cholesterol, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), triglycerides, HbA1c, and serum creatinine. The eGFR was calculated using the Modification of Diet in Renal Disease (MDRD) formula: eGFR (ml/min/1.73 m2) = 175 × (Scr)−1.154 × (Age)−0.203 × (0.742 if female) × (1.212 if African American). Echocardiograms were performed by expert cardiologists or ultrasound specialists with the left ventricular ejection fraction (LVEF) measured using the Simpsons method. Coronary angiography and PCI procedures were carried out by experienced cardiologists according to established guidelines.

Statistical analysis

Baseline characteristics of the study population according to BMI categories or NT-proBNP were summarised using frequency and percentage (%) for categorical variables and mean ± standard deviation (SD) or median and interquartile range (IQR) for continuous variables as appropriate. Differences in baseline characteristics were compared using the Pearson’s χ2 test for categorical variables and one-way ANOVA or Kruskal-Wallis H test for continuous variables.

Natural logarithm (Ln)-transformed values of NT-proBNP were used when included as continuous variables in statistical models. NT-proBNP was also examined as a categorical variable by quintiles. The crude incidence rates of MACCEs per 1000 person-years were estimated by dividing the number of events by the total follow-up time. The relationship between NT-proBNP and MACCEs was assessed utilizing multivariate Cox proportional hazards models. Models were adjusted for age (continuous), sex, diagnosis of acute myocardial infarction (AMI), history of dyslipidemia, history of myocardial infarction, history of arrhythmia, SBP (quartiles), LVEF (quartiles), eGFR (quartiles), hs-CRP (quartiles), LDL-C (quartiles), smoking status, PCI, and in-hospital medication (antiplatelet therapy, β-blocker, ACEI or ARB, and statins). The formal multiplicative interaction test between NT-proBNP and BMI was conducted using the Wald χ2 test, by incorporating an multiplicative interaction term (i.e., Ln-NT-proBNP × BMI) into the multivariate models. The time-to-MACCEs across different NT-proBNP risk levels, stratified by BMI categories, was evaluated using adjusted cumulative incidence curves based on the Cox model [22], using the “stcurve” command in STATA software. We then calculated the overall P value using the “testparm” command, and computed pairwise comparison P value using the “lincom” command. For joint analyses, a new variable was created by combining NT-proBNP and BMI, resulting in nine categories that represented all possible (3 × 3) combinations of NT-proBNP risk levels (low-risk, intermediate-risk, and high-risk) and BMI categories (normoweight, overweight, and obese).

To further compare the absolute risk of MACCEs at five years across different NT-proBNP and BMI levels, regression analysis of censored data using pseudo-observations was employed [23]. We first utilized the “stpsurv” commend in Stata software to obtain the predicted risk of MACCEs at five years. Then, we conducted generalized linear models that included the Ln-NT-proBNP, BMI, their interaction term (Ln-NT-proBNP × BMI), and relevant covariates. Finally, to visualize the does-response relationship between NT-proBNP and five-year MACCEs, we used “margins” commend in Stata software to calculate standardized risks associated with various concentrations of NT-proBNP across different BMI levels. To assess the trend of NT-proBNP-associated five-year MACCEs risk across different BMI levels, we used an inverse-variance weighted least-squares model.

Given that median levels and distributions of NT-proBNP differ significantly between males and females, a subgroup analysis was performed to compare the relationship between NT-proBNP and BMI with MACCEs in males and females.

Statistical analysis was performed using STATA software version 17.0 (StataCorp LP, College Station, TX, USA). Two-tailed p < 0.05 was considered statistically significant.

Results

Overall, 11,757 patients with ACS were included in the study cohort, of whom 65.6% were males. The overall mean age was 65.1 ± 10.9 years. The overall mean BMI was 25.9 ± 3.4 kg/m2. About 29.6% (n = 3477) of the cases were normoweight, 45.8% were overweight (n = 5386), and 24.6% were obese (n = 2894). The baseline characteristics stratified by BMI are summarised in Table 1. Patients with higher levels of BMI tended to be younger; had a higher proportion of diabetes, hypertension, and dyslipidemia but less proportion of STEMI; had higher mean levels of SBP, FPG, hemoglobin, hs-CRP, LDL-C, and triglycerides; and were more likely to use aspirin, ACEI/ARB, β-blocker, and statins. The median NT-proBNP level in the overall population was 244.0 pg/ml (IQR: 82.0‒1087.0 pg/ml). Notably, the NT-proBNP level decreased significantly with an increase in the BMI. The baseline characteristics stratified by quintiles of NT-proBNP are presented in Supplemental Table 1. The comorbidity profile across various categories defined by the cross-classification of NT-proBNP risk levels and BMI are shown in Supplemental Table 2.

Table 1 Baseline and clinical characteristics by BMI categories
Full size table

During the median follow-up time of 3.04 (IQR: 1.07‒5.02) years (33,232 person-years), 1996 MACCEs were reported, averaging 60.1 events per 1000 person-years. The association between NT-proBNP and the risk of MACCEs by Ln-NT-proBNP or quintiles is depicted in Table 2. In the entire cohort, NT-proBNP exhibited a significant association with MACCEs, as evaluated by both the per unit increase in Ln-NT-proBNP (hazard ratio [HR]: 1.49; 95% confidence interval [CI]: 1.39‒1.60; p < 0.001) and the NT-proBNP quintiles (HRs compared with the Q1: Q2, 1.28; Q3, 1.41; Q4, 1.74; and Q5, 2.43 [p < 0.05 for all quintiles]).

Table 2 NT-proBNP-Associated MACCEs according to BMI threshold
Full size table

A significant multiplicative interaction was observed between Ln-NT-proBNP and BMI (p for multiplicative interaction = 0.013). No significant association was observed between the risk of MACCEs and NT-proBNP in the first four quintiles in normoweight patients; only the fifth quintile of NT-proBNP (≥ 1559 pg/ml) was associated with a higher risk of MACCEs (HR: 1.91; 95% CI: 1.25‒2.91; p = 0.003). Conversely, a significant association was found between elevated NT-proBNP levels and the risk of MACCEs in overweight and obese patients, whether considering an Ln-SD unit increase (overweight HR: 1.51, 95% CI: 1.36‒1.67, p < 0.001; obese HR: 1.51, 95% CI: 1.29‒1.75, p < 0.001) or using categorical thresholds of 155 pg/ml (Q3‒Q5) for overweight patients and 419 pg/ml for obese patients (Q4‒Q5). The adjusted cumulative incidence of MACCEs across the three distinct risk levels of NT-proBNP within each BMI category is displayed in Fig. 1. Similarly, the high-risk group exhibited a significantly increased cumulative incidence of MACCEs among normoweight patients compared with low-risk group. However, both the intermediate-risk and high-risk groups showed elevated incidence rates among overweight and obese patients.

Fig. 1
figure 1

Adjusted cumulative incidence of MACCEs across NT-proBNP groups within each BMI category

Full size image

The incidence rates of MACCEs (per 1000 person-years) across various categories defined by the cross-classification of NT-proBNP risk levels and BMI are displayed in Fig. 2(A). The event rates for MACCEs were the lowest among overweight patients in the low-risk NT-proBNP group and the highest among normoweight patients in the high-risk NT-proBNP group. Therefore, we calculated the HRs for the remaining eight groups, using the group with the lowest risk as the reference (Fig. 2[B]). Compared with the reference group, normoweight patients with NT-proBNP ≥ 1559 pg/ml had the highest relative risk, with an HR value of 2.28 (95% CI: 1.83‒2.84; p < 0.001).

Fig. 2
figure 2

Joint analyses by the combinations of NT-proBNP risk levels and BMI categories: (A) Incidence rate per 1000 person-years of MACCEs. (B) The joint association with incident MACCEs in the fully adjusted model

Full size image

Notably, the absolute risk of five-year MACCEs associated with specific NT-proBNP levels exhibited BMI-dependent variations (Fig. 3). At near-normal or mildly elevated NT-proBNP levels (within approximately 300 pg/ml), overweight and obese patients carried higher MACCEs risk compared to normoweight patients with equivalent NT-proBNP concentrations. In this lower range, each 10 pg/ml increase in NT-proBNP was associated with a 0.47%, 0.37%, and 0.28% increase in the risk of MACCEs for normoweight, overweight, and obese patients, respectively. This risk stratification pattern reversed substantially at significantly elevated NT-proBNP levels (above approximately 300 pg/ml), where normoweight patients demonstrated greater event probability than overweight and obese patients, revealing a paradoxical obesity-associated risk attenuation at higher biomarker concentrations. In this upper NT-proBNP range, each 10 pg/ml increase in NT-proBNP was associated with a 0.04%, 0.03%, and 0.02% for respective BMI categories.

Fig. 3
figure 3

Five-year event probabilities of MACCEs as a function of NT-proBNP stratified by BMI categories

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A subgroup analysis was conducted by categorizing the study population based on sex (Supplemental Table 3). The P values for multiplicative interaction for Ln-NT-proBNP and BMI were 0.007 and 0.740 in males and females, respectively. The sex differences of the MACCE probabilities across NT-proBNP as a function of BMI are presented in Fig. 4 and Supplemental Table 4. The differences in MACCE probabilities among various BMI categories were more pronounced in male patients at higher NT-proBNP levels.

Fig. 4
figure 4

Five-year event probabilities of MACCEs as a function of NT-proBNP stratified by BMI categories in men and women

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Discussion

The present study evaluated the impact of BMI on the prognostic value of NT-proBNP in 11,757 patients with ACS. Our analysis demonstrated a significant multiplicative interaction between NT-proBNP and BMI, with particularly pronounced observations in male subgroups. Specifically, under conditions of mild NT-proBNP elevation, overweight and obese patients showed increased absolute risk of five-year MACCEs with equivalent NT-proBNP levels. Conversely, this relationship reversed at markedly elevated NT-proBNP levels, where normoweight patients carried higher MACCEs risk compared to overweight/obese patients. Furthermore, the combined evaluation of BMI and NT-proBNP revealed that normoweight patients with elevated NT-proBNP levels faced substantially greater MACCE risks (HR: 2.28; 95% CI: 1.83‒2.84) compared to overweight individuals with normal NT-proBNP levels. These results underscore the critical need for considering BMI when employing NT-proBNP for clinical risk stratification in ACS management.

Studies examining the impact of BMI on the prognostic performance of NT-proBNP in ACS patients are limited. One study including 2217 patients with myocardial infarction found that the significance of the NT-proBNP was severely compromised in obese patients [24]. However, this finding may be limited by the small sample size. A previous study by our team also found that NT-proBNP was an independent prognostic factor, with its prognostic value varying with BMI. Specifically, the optimal NT-proBNP cut-off values for mortality risk prediction decreased with an increase in BMI. Nevertheless, the prognostic value was attenuated in underweight patients rather than obese patients [25]. To the best of our knowledge, this is the first study to investigate the multiplicative interaction and verify the result that BMI modifies the prognostic value of NT-proBNP. Our study found that the effect of BMI on the prognostic value of NT-proBNP in ACS patients was related to the extent of NT-proBNP elevation and was more pronounced in male than female patients, providing a profound understanding of the specific pattern of the relationship between BMI and the prognostic value of NT-proBNP in ACS patients.

Prior community-based studies demonstrated that NT-proBNP provides significant prognostic information on the risk of developing HF among obese individuals, despite its inverse relationship with BMI. One prospective cohort study involving 12,230 individuals in the general population revealed that higher BMI categories were associated with an increased absolute risk of HF at each NT-proBNP level. For instance, among patients with BMI ≥ 35 kg/m2, the average 10-year HF risk was 4.7% when NT-proBNP was < 50 pg/ml and 10% when NT-proBNP was in the range of 100 to < 200 pg/ml. The corresponding risks in the normoweight group were 1.5% and 4.4%, respectively [15]. Another cohort study involving over 15,000 obese individuals demonstrated that the risk of HF for a given NT-proBNP value was significantly higher among obese individuals with elevated NT-proBNP (≥ 125 pg/ml). Specifically, an NT-proBNP level of 169 pg/ml and 300 pg/ml indicated a two-year HF event probability of 2.5% and 5.0%, respectively, among individuals with a BMI ≥ 35 kg/m2, whereas those with a BMI < 35 kg/m2 had corresponding NT-proBNP levels of 319 pg/ml and 496 pg/ml for an equivalent two-year risk [26]. Kozhuharov et al. also indicated that utilizing lower cut-off values of NT-proBNP concentrations for individuals with a BMI of ≥ 30 kg/m2 may further enhance its clinical utility in the early diagnosis of acute HF in patients presenting to the emergency department with acute dyspnea [27]. Similarly, the present study found that overweight and obese patients exhibited a higher probability of MACCEs when NT-proBNP levels were mildly elevated (within 300 pg/ml). Therefore, we believe that the negative correlation between NT-proBNP and BMI does not diminish the prognostic value of NT-proBNP but rather it enhances the magnitude of absolute risk in NT-proBNP levels. These findings suggest that caution should be taken when interpreting low-level elevations in NT-proBNP in overweight and obese patients, as they may indicate a higher risk potential and a lower threshold for risk increase.

Contrary to the findings of community-based studies, the present study showed that normoweight patients gradually exhibited a higher risk for a given NT-proBNP level as NT-proBNP levels continued to rise (above 300 pg/ml). The phenomenon that normoweight patients exhibit higher risks can be termed the “obesity paradox”, which has been widely studied in ACS patients [28,29,30]. Notably, the obesity paradox was only observed in patients with significantly elevated NT-proBNP levels, with patients with low NT-proBNP levels showing no discernible obesity paradox. This finding suggests that the obesity paradox is more pronounced and evident in patients with more severe conditions. Consequently, further analysis was conducted by jointly considering BMI and NT-proBNP. It was found that normoweight patients with elevated NT-proBNP had the highest risk of MACCEs among ACS patients.

The mechanisms underlying the interplay between BMI and the prognostic value of NT-proBNP remain unclear. There is an intricate and bidirectional interrelationship between obesity and natriuretic peptides (NPs). Experimental studies demonstrate that BNP binds to its cognate receptor NPR-A (natriuretic peptide receptor-A), triggering metabolic improvements including suppression of inflammation, enhancement of insulin sensitivity, and optimization of mitochondrial function and is cleared from the circulation through internalization by their clearance receptor (NPR-C) [31]. While adipocytes have been shown to have high expression of NPR-C, which increased NP clearance and impair NP-mediated cardiovascular homeostasis [32]. Furthermore, adipose tissue expansion and metabolic dysregulation in obesity drive the activation of inflammatory pathways, including toll-like receptor (TLR) signaling, TNF-α/NF-κB cascades, and apoptosis-related mechanisms [33]. The elevated absolute cardiovascular risk observed in obese patients with lower NT-proBNP concentrations aligns with the hypothesis that obesity may reduce NPs levels and stimulate inflammatory, thereby exacerbating cardiovascular risk and contributing to poor clinical outcomes. However, when NT-proBNP is markedly elevated in ACS patients, it signifies a more severe impairment of cardiac dysfunction and indicates a more critical condition [34, 35]. The pathological elevation of NT-proBNP secondary to myocardial impairment and increased left ventricular wall stress may significantly surpass the obesity-related acceleration of NT-proBNP clearance mechanisms. In such cases, contrary to the expected biological effect of obesity, overweight or obese patients tend to have a better prognosis than normoweight patients. Researchers hypothesize that patients with lower BMI and reduced adiposity may possess insufficient nutritional reserves to counteract the catabolic effects of acute cardiac decompensation, which means they have less reserve to prevent cardiac cachexia, potentially leading to a poor prognosis [36, 37]. Furthermore, our findings revealed significant gender differences in the influence of BMI on the predictive value of NT-proBNP, which may potentially be attributed to the mediating role of testosterone in the association between higher BMI and NPs [38]. Future studies are warranted to understand the mechanisms underlying the interrelationships between obesity and NT-proBNP and the risk of adverse outcomes for ACS patients.

Nonetheless, this study has some limitations. First, since this is a single-center observational study conducted on the Chinese population, the possibility of residual confounding cannot be excluded, limiting the generalization of our findings. Second, BMI was used to grade obesity severity in this study, which may not accurately reflect a patient’s metabolic status and body composition. Future imaging studies quantifying euvolemic body mass are necessary. Furthermore, both NT-proBNP and BMI in this study are based on single-measurement data, and any post-baseline changes in these parameters during the follow-up period could not be evaluated in the present analyses. Therefore, longitudinal prospective cohort studies are required to further validate our findings.

Conclusion

In summary, higher NT-proBNP levels were associated with an increased risk of MACCEs in ACS patients. Furthermore, this relationship varied with BMI and was related to the extent of NT-proBNP elevation. Future studies should investigate the clinical impact of the interrelationships between BMI and NT-proBNP in patients with ACS.

Data availability

No datasets were generated or analysed during the current study.

Abbreviations

ACEI:

Angiotensin-converting enzyme inhibitor

ACS:

Acute coronary syndrome

AMI:

Acute myocardial infarction

ARB:

Angiotensin receptor blocker

BMI:

Body mass index

CABG:

Coronary artery bypass grafting

CI:

Confidence interval

eGFR:

Estimated glomerular filtration rate

FPG:

Fasting plasma glucose

HbA1c:

Glycated hemoglobin

HDL-C:

High-density lipoprotein cholesterol

HF:

Heart failure

HR:

Hazard ratio

hs-CRP:

High-sensitivity C-reactive protein

IQR:

Interquartile range

LDL-C:

Low-density lipoprotein cholesterol

Ln:

Natural logarithm

LVEF:

Left ventricular ejection fraction

MACCEs:

Major adverse cardiovascular and cerebral events

MDRD:

Modification of diet in renal disease

NSTEMI:

Non-ST-segment elevation myocardial infarction

NT-proBNP:

N-terminal pro-B-type natriuretic peptide

PCI:

Percutaneous coronary intervention

SBP:

Systolic blood pressure

SD:

Standard deviation

STEMI:

ST-segment elevation myocardial infarction

UAP:

Unstable angina pectoris

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Acknowledgements

The authors thank Guoliang Zhao (Beijing Friendship Hospital, Capital Medical University) and Man Wang (China-Japan Friendship Hospital) for technical support.

Funding

This work was supported by the Beijing Natural Science Foundation (L232116).

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Author notes

  1. Xiaoquan He and Xiaojing Fang contributed equally to this work.

Authors and Affiliations

  1. Department of Cardiology, Cardiovascular Centre, Beijing Friendship Hospital, Capital Medical University, No.95, Yongan Road, Xicheng District, Beijing, 100050, People’s Republic of China

    Xiaoquan He, Jiali Wang, Shumei Zhao, Xiaosong Ding & Hui Chen

  2. Department of neurology, First Hospital of Tsinghua University, No.6 Jiuxianqiao 1st Street, Chaoyang District, Beijing, 100016, People’s Republic of China

    Xiaojing Fang

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  1. Xiaoquan He
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Contributions

“XQH and XJF performed the study, did statistical analysis, and wrote the manuscript. JLW and XSD participated in the study data collection. SMZ contributed discussion and edited the manuscript. HC provided funding support, designed the study, and reviewed the manuscript. All authors gave final approval and agree to be accountable for all aspects of the work ensuring integrity and accuracy.”

Corresponding authors

Correspondence to Xiaosong Ding or Hui Chen.

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Ethics approval and consent to participate

Our study was carried out in accordance with the Helsinki Declaration and was approved by the ethical review board of Beijing friendship hospital, capital medical university. Each participating patient in this study recruited written informed consent.

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Not applicable.

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He, X., Fang, X., Wang, J. et al. Body mass index modifies the major adverse cardiovascular and cerebral events risk of NT-proBNP in patients with acute coronary syndrome. Diabetol Metab Syndr 17, 88 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s13098-025-01668-x

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Keywords

Diabetology & Metabolic Syndrome

ISSN: 1758-5996

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