Skip to main content
Download PDF
Download ePub

Detecting heart stress using NT-proBNP in patients with type 2 diabetes mellitus and hypertension or high-normal blood pressure: a cross-sectional multicentric study

Cardiovascular Diabetology volume 23, Article number: 297 (2024) Cite this article

Abstract

Background

We evaluated the prevalence of “heart stress” (HS) based on NT-proBNP cut-points proposed by the 2023 Consensus of the Heart Failure Association (HFA) of the European Society of Cardiology (ESC) in asymptomatic patients with T2DM and hypertension or high-normal blood pressure (BP) eligible for SGLT2 inhibitors (SGLT2i) and/or GLP-1 receptor agonists (GLP1-RA), drugs with proven benefits on reducing the incidence of HF, hospitalizations, cardiovascular events and mortality.

Methods

A cross-sectional multicentric study was conducted on 192 consecutive outpatients, aged ≥ 55 years, with hypertension or high-normal BP, referred to three diabetology units. NT-proBNP was collected before starting new anti-diabetic therapy. Patients with known HF were excluded, and participants were classified based on the age-adjusted NT-proBNP cut-points.

Results

Mean age: 70.3 ± 7.8 years (67.5% males). Patients with obesity (BMI ≥ 30 Kg/m2): 63.8%. Median NT-proBNP: 96.0 (38.8–213.0) pg/mL. Prevalence of chronic kidney disease (CKD, eGFR < 60 mL/min/1.73m2): 32.1%. Mean arterial BP: 138.5/77.0 ± 15.8/9.9 mmHg. The NT-proBNP values, according to the proposed age-adjusted cut-points, classified 28.6% of patients as “HS likely” (organize elective echocardiography and specialist evaluation), 43.2% as “HS not likely” (a grey area, repeat NT-proBNP at six months) and 28.2% as “very unlikely HS” (repeat NT-proBNP at one year). The presence of CKD and the number of anti-hypertensive drugs, but not glycemic parameters, were independently associated with HS.

Conclusions

According to NT-proBNP, over a quarter of T2DM patients with hypertension/high-normal BP, among those eligible for SGLT2i and/or GLP1-RA, were already at risk of cardiac damage, even subclinical. Most would receive an indication to echocardiogram and be referred to a specialist, allowing the early implementation of effective strategies to prevent or delay the progression to advanced stages of cardiac disease and overt HF.

Introduction

Patients with type 2 diabetes mellitus (T2DM) and arterial hypertension are often overweight or obese (OW/OB) and have a higher risk of developing heart diseases up to any ejection fraction type of heart failure (HF) [1, 2]. Detection of patients with cardiovascular (CV) comorbidities at any risk for HF or those with subclinical HF would allow earlier implementation of effective strategies to prevent or delay the progression to overt and advanced stages of HF, such as optimizing the use of renin-angiotensin-aldosterone system (RAAS) inhibitors for blood pressure (BP) control or earlier initiation of other therapies with more recently proven ability to prevent HF progression. Indeed, many of these patients should receive GLP-1 receptor agonists (GLP1-RA) and SGLT2 inhibitors (SGLT2i) [3] after landmarking trials with both drug classes have proved considerable benefits in terms of reduction of HF incidence and hospitalization, major cardiovascular (CV) and renal events and CV mortality [4,5,6,7].

However, the implementation of available strategies to detect asymptomatic HF has been suboptimal in clinical practice, reducing the opportunities for more widespread awareness among patients and a more pragmatic application of beneficial therapies in such individuals. Although echocardiography might identify signs of maladaptive left ventricular remodeling, its routine use as a large-scale screening examination is not feasible and has not been considered cost-effective. It thus has not been systematically recommended for asymptomatic individuals, including those with T2DM. On the other hand, adding relatively inexpensive biomarker testing, such as natriuretic peptides (NPs), as part of the standard of care may help refine CV and HF risk prediction in T2DM individuals [8,9,10].

Based on extensive and solid clinical evidence, a recent Consensus Statement of the Heart Failure Association (HFA) of the European Society of Cardiology (ESC) [11] detailed the importance of assessing the levels of cardiac biomarker N-terminal-pro B-type Natriuretic Peptide (NT-proBNP) to evaluate T2DM patients at risk of HF in pre-failure or “heart stress” (HS), a new term introduced to identify asymptomatic individuals with risk factors and elevated plasma NPs, irrespective of the presence or absence of structural heart disease or cardiac dysfunction. Patients with T2DM serve as an example of this concept, as they often appear to have a structurally and functionally normal heart on imaging but with increased concentrations of NT-proBNP that predict an increased risk of developing HF [12]. However, despite NT-proBNP measuring should be part of an updated “Good Clinical Practice” (GCP), this biomarker is rarely (or even never) tested in real-life daily clinical practice, even in T2DM patients often affected by multiple comorbidities, such as older age, obesity and arterial hypertension.

The main objective of this study was to assess NT-proBNP levels to evaluate the prevalence of HS and its associated factors in outpatients affected by T2DM and arterial hypertension or high-normal BP who were eligible for SGLT2i and/or GLP1-RA treatment. For completeness, we also evaluated the prevalence of overt HF risk, always according to the NT-proBNP cut-points proposed by the HFA of the ESC, as a secondary outcome.

Methods

Study population and design

We performed an observational multicentric cross-sectional study on 192 consecutive T2DM outpatients referred to the Diabetology and Metabolic Diseases Centers of the IRCCS INRCA (Ancona, Italy), Clinic of Endocrinology and Metabolic Diseases of Azienda Ospedaliero Universitaria delle Marche (Ancona, Italy) and AST Pesaro-Urbino (Urbino, Italy) from May 2023 to April 2024. Inclusion criteria were the following: age ≥ 55 years, a history of arterial hypertension or high-normal BP (defined as the presence of anti-hypertensive treatment or office BP ≥ 130/85 mmHg on repeated and accurate measurements during medical visits [13]), an established diagnosis of T2DM, and clinical eligibility for treatment with GLP1-RA and/or SGLT2i [14] alone or on top of previous antidiabetics and lifestyle interventions. We included patients with high-normal BP in our study because these BP levels may also lead to cardiac remodeling over time [15, 16]. Exclusion criteria were the following: previous documented diagnosis of cardiac organ damage or HF, history of coronary artery disease or known cardiopathy, end-stage renal disease (ESRD), defined by an estimated glomerular filtration rate (eGFR using CKD-EPI creatinine equation) < 15 mL/min/1.73m2 or dialysis, advanced cancer or other terminal conditions (decompensated cirrhosis, severe dementia, bed-rest syndrome), any non-cardiac clinical conditions that could influence plasma value of laboratory parameters of interest, such as current liver cirrhosis or acute kidney injury (AKI). In this population, we evaluated the prevalence of HS and subclinical HF risk by measuring plasma NT-proBNP according to the recent 2023 Consensus Statement of the HFA of the ESC [11]. Before starting such additional pharmacological treatments, demographic, anthropometric, clinical and laboratory data were collected as part of GCP, including plasma NT-proBNP levels. Concerning CV and metabolic comorbidities, dyslipidemia was defined by the presence of lipid-lowering therapy (LLT) or low-density lipoprotein cholesterol (LDL-C) levels, calculated using the Friedewald equation modified by Martin et al. [17], above 70 or 55 mg/dL, according to the individual CV risk based on 2021 ESC Guidelines on Cardiovascular Disease Prevention in Clinical Practice [18]. Overweight and obesity were defined by a body mass index (BMI) ≥ 25 and ≥ 30 Kg/m2, respectively. Smoking habit was defined as the current or previous smoking of at least 100 cigarettes in a lifetime. Resistant hypertension was defined as uncontrolled hypertension despite the use of three anti-hypertensive medications of different classes, including a diuretic.

NT-proBNP assay

NT-proBNP was measured using Elecsys proBNPII electrochemiluminescence immunoassay in a Cobas e601 immunoassay Roche analyzer. This assay contains two monoclonal antibodies that recognize epitopes in the N-terminal part (1–76) of proBNP (1–108) [19].

NT-proBNP cut-points for the screening of heart stress and heart failure

The enrolled patients were classified according to NT-proBNP cut-points proposed by the 2023 Consensus Statement of the HFA of the ESC to diagnose and manage HS and HF [11], as summarized in Table 1. Regarding HS, evaluated in asymptomatic and clinically stable T2DM outpatients without significant and potentially confounding comorbidities, the study population has been classified into three subgroups according to age-adjusted NT-proBNP cut-points: “HS very unlikely”, “HS not likely”, and “HS likely” [11]. Similarly, the same population was also classified according to the “HF likely” risk proposed by the same Consensus Statement for the secondary outcome (Table 1).

Table 1 NT-proBNP cut-points for heart stress and heart failure risk in outpatients, according to the 2023 Clinical Consensus of the HFA of the ESC
Full size table

Statistical analysis

Data were analyzed using the Statistical Package for Social Science version 21 (SPSS Inc., Chicago, Illinois, USA). The study’s primary outcome was to evaluate the prevalence of “HS likely” and its associated factors in the enrolled population. Continuous variables were checked for normality and expressed as mean ± standard deviation (SD) or median and interquartile range (IQR) if markedly skewed. Frequencies were expressed as percentages. Analysis of variance (ANOVA) and Kruskal–Wallis tests were used to evaluate differences between continuous variables. Correlations between continuous variables were assessed using Pearson’s and Spearmans’ tests. The triglycerides variable was naturally logarithmically transformed to normalize its distribution. Those variables with a significant association identified upon univariate analyses were tested within a stepwise logistic regression model (entry value = 0.05 and removal value = 0.10) to evaluate the factors independently associated with the outcome of interest. We used the “forward model” that starts to include variables by their order of significance. This method is usual in exploratory studies, where there is no certainty of what variables may influence the outcome.

Results

A total of 192 T2DM patients with hypertension or high-normal BP eligible for GLP1-RA (n° 83) or SGLT2i (n° 109) treatment were enrolled in the study. General characteristics of the entire study population and according to the HS status are described in Table 2. In the overall population with a mean age of 70.3 ± 7.9 years and male prevalence of 67.7%, most patients were affected by obesity, dyslipidemia and poor BP control, with a 32.1% prevalence of chronic kidney disease (CKD) [eGFR < 60 mL/min/1.73m2, by CKD-EPI equation]. Regarding NT-proBNP values, the overall median was 96.0 (38.8–213.0) pg/mL. Figure 1 shows the classification of the patients according to age-adjusted NT-proBNP cut-points. The higher the probability of HS, the greater the age of patients and the presence of renal dysfunction. Patients with “HS likely” tended to have lower diastolic BP, a higher prevalence of resistant hypertension, although not statistically significant, and lower levels of triglycerides. Regarding CV treatments, the higher the probability of HS, the greater the number of anti-hypertensive drugs taken, while the lower the metformin use at baseline (Table 2). No associations were found with T2DM duration or vascular, retinal and cerebral organ damage.

Fig. 1
figure 1

Prevalence of the different Heart Stress states in the study population. HS: heart stress

Full size image

By Spearman’s test, NT-proBNP significantly and directly correlated with age (r = 0.526, p < 0.001), T2DM duration (r = 0.179, p = 0.015) and pulse pressure (r = 0.166, p = 0.031), while inversely correlated with eGFR (r = − 0.368, p < 0.001), BMI (r = − 0.202, p = 0.023), waist circumference (r = − 0.160, p = 0.028) and TyG index (r = − 0.234, p = 0.013).

Regarding the HF likely risk, NT-proBNP levels classified 60.9% (n = 117) as “HF very unlikely”, 22.4% (n = 43) as “HF not likely”, 15.1% (n = 29) as “HF likely”, and 1.6% (n = 3) as “HF very-high risk”.

Table 2 General characteristics of the overall study population and according to the heart stress status
Full size table

Factors associated with heart stress

A stepwise logistic regression was performed to evaluate factors independently associated with HS. For this analysis, we grouped patients with “HS very unlikely” and “HS not likely”, the two groups with recommendations that are more similar to each other (see below) and have less impact on patient management. The statistically significant variables in the univariate analyses were used as independent variables [age, CKD, Ln(Triglycerides), eGFR, metformin, MRA, beta-blocker, alpha-blocker, number of anti-hypertensive drugs]. Among these factors, only CKD [Wald = 6.3; OR = 2.8 (95% CI 1.3–6.2); p = 0.012] and the number of anti-hypertensive medications [Wald = 10.7; OR = 1.8 (95% CI 1.3–2.5); p = 0.001] were included in the final model, showing a significant independent association with “HS likely” (Table 3).

Table 3 Probability of heart stress in the study population
Full size table

Discussion

In our study, more than a quarter of patients with T2DM and high BP showed an underlying HS likely, which would not have been detected without the NT-proBNP dosage, a very relevant finding in this type of patient. Risk factors that emerged independently associated with this condition were the presence of chronic kidney disease and the number of anti-hypertensive drugs taken.

Core evidence from epidemiological studies reported an increasing incidence rate of HF among people with diabetes, even after adjustment for age and other comorbidities. HF is becoming the first presenting CV complication in T2DM individuals [20]. Our population of older T2DM patients showed a relatively high prevalence of CV, renal and metabolic comorbidities, establishing an even more fertile terrain for acute major cardiac events and worsening heart diseases, for which HF represents the inevitable consequence. In this clinical context, progressive cardiac dysfunction reflects complex interactions between ageing, adiposity and CV risk factors-related deleterious mechanisms that affect myocardial metabolism, structure and efficiency [21]. Consequently, clinical overt HF represents the epiphenomenon of a continuum of such cardiac abnormalities. The 2021 multi-society consensus statement on “Universal Definition and Classification of Heart Failure” places patients with hypertension, atherosclerotic CV disease, diabetes and obesity already in stage A HF (at risk for HF), even in the absence of current or prior symptoms or signs of HF and structural cardiac changes or elevated biomarkers of HF [22]. The correct management of CV-modifiable risk factors through lifestyle and pharmacological interventions is the cornerstone of managing stage A HF and can slow the progression to overt HF. Unfortunately, current trends suggest that control of modifiable risk factors is poor in patients with diabetes [23]. Our real-life sample reflects this concern, with the high prevalence of uncontrolled BP, high mean LDL-C and a quarter of T2DM hypertensive patients not taking a renin-angiotensin-aldosterone system inhibitor (RAASi), the first choice drug for the treatment of arterial hypertension, especially in the presence of T2DM, for its proven cardio-renal protection [24].

Recently, renewed emphasis has been placed on the potential role of myocardial stress biomarkers, particularly NT-proBNP, in detecting T2DM individuals with early cardiac dysfunction and at the highest risk of HF progression [11, 25,26,27]. The cardiac biomarker-guided screening approach is already included as a class IIa recommendation in the 2017 American College of Cardiology/American Heart Association (ACC/AHA) HF Focused Update [28]. Accordingly, the latest 2023 Clinical Consensus of the HFA of the ESC recommended that NT-proBNP levels should be assessed whenever a patient is at risk of developing CV disease and HF to identify “heart stress”, a new condition sitting in between stages A and B HF and identifying asymptomatic individuals with risk factors and elevated plasma NT-proBNP, irrespective of the presence or absence of structural heart disease or cardiac dysfunction [11]. In our investigation, despite the lack of overt HF-related clinical manifestations (i.e., dyspnoea, pulmonary rales, etc.), 28.6% of the enrolled patients had NT-proBNP values compatible with an HS condition, and about 40% fell in the grey zone. Along with the novelty represented by specific NT-proBNP cut-points, it is noteworthy that dosing NT-proBNP in stable asymptomatic outpatients with CV comorbidities represents not only a mere HF risk evaluation but strongly impacts management strategies. Indeed, according to the HFA Clinical Consensus recommendations, all patients in the “HS likely” spectrum of NT-proBNP values should be evaluated with elective echocardiography and assessed by the HF team if cardiac dysfunction is found. In contrast, all patients with values compatible with “HS not likely” and “HF very unlikely” should at least enter follow-up and repeat NT-proBNP dosing after six months or one year, respectively. Similarly, also the 2024 updated American Diabetes Association (ADA) Standards of Care in Diabetes (section of Cardiovascular Disease and Risk Management) recommended echocardiography to identify stage B HF in asymptomatic individuals with diabetes and abnormal natriuretic peptide levels (class A) [29].

No previous studies investigated the prevalence of unknown HS using NT-proBNP as an early and asymptomatic first stage of heart disease in T2DM patients. However, estimates of how HF is spread in the T2DM population are available. A study on a casual older T2DM population, using echocardiography as a screening tool, found a prevalence of 27.7% of unknown symptomatic HF with 25.1% of diastolic dysfunction [30]. A recent systematic review [31] summarized the studies which explored the prevalence of different degrees of heart damage in adults ≥ 18 years with T2DM, using mainly echocardiographic data. Based on 65 studies on 25,729 individuals, it found that there is a large pre-clinical group with left ventricular diastolic dysfunction / HFpEF [43% (95% CI 37%, 50%) and 17% (95% CI 7%, 35%), respectively] in which cardiac disease progression could be halted by early recognition and treatment. As expected, a high risk of bias and high levels of heterogeneity due to the different diagnostic criteria over the years and the different characteristics of study populations limited this analysis [31]. A recent study used the NT-proBNP point-of-care measurement as a screening tool for HF in a population with T2DM and hypertension. Although the mean age was slightly lower than ours, the authors found NT-proBNP levels ≥ 125 pg/ml in 39.4% of the study population [32].

In addition to the HS status, we also tested HF likely according to the age-adjusted NT-proBNP cut-points proposed by the 2023 Clinical Consensus of the HFA of the ESC for outpatients suspected of de novo HF. Considering the higher NT-proBNP cut-points for HF compared to HS, we found that 16.7% of patients had NT-proBNP values ​​compatible with at least HF likely. Considering the non-specificity of HF symptoms, including asthenia and dyspnea, that are not rare in obese T2DM patients with other CV risk factors, these data further reinforce the relevance of this biomarker in clinical practice.

In our study, unsurprisingly, older patients had a higher prevalence of HS, given that ageing acts by “giving time” to the other CV risk factors to produce vascular and cardiac damage [33]. In addition to age, we found that the number of anti-hypertensive drugs taken and the renal function are likely risk factors for HS. In contrast, no independent association was found with the glycemic parameters evaluated, such as baseline glycaemia and HbA1C. This last finding could be due to several hypotheses. It could reflect a pivotal role of the BP burden compared to alterations in glucose metabolism on cardiac organ damage, in which pressure and volume overload, especially in obese patients, leads to a modification of the left ventricular structure and function [34, 35]. On the other hand, the absence of association with glycemic parameters, as well as with BP values and control, could be due to the study’s cross-sectional design, which provides only a screenshot of the patient’s condition (we found only a direct correlation at unadjusted univariate analysis between NT-proBNP levels and T2DM duration in our sample). Instead, the number of anti-hypertensive drugs could better reflect the patient’s BP severity and burden over time.

A wide study of epidemiological cohorts showed that a biomarker-based risk score including NT-proBNP (cut-point ≥ 125 pg/ml) together with high-sensitivity cardiac troponin-T, high-sensitivity C-reactive protein and electrocardiographic-based LVH based on Sokolow-Lyon criteria, was able to predict diabetic and pre-diabetic patients at higher 5- and 10-year HF risk [36]. The same study also found that patients with higher scores and a higher risk of HF onset would benefit the most from SGLT2i therapy regarding incident HF prevention [36]. Our analysis focused on patients eligible for SGLT2i and GLP1-RA. Due to their multiple beneficial effects (renal protection, improvement of myocardial energy metabolism, positive impact on anaemia, etc.) and their hybrid diuretic action [37], several studies have confirmed the efficacy of SGLT2i, especially in preventing HF incidence and hospitalization. The risk reduction of this outcome resulted the more consistent across the trials examined by a recent metanalysis (HR, 0.68; 95% CI 0.61–0.76) [38]. Thus, from the clinical perspective, another relevant issue concerning the NT-proBNP dosing in the diabetic population is related to its usefulness in identifying those patients who would benefit the most from this drug class before initiating treatment, also in the wake of data on biomarker-guided therapy that controversially and limited to the chronic HF setting was demonstrated to reduce CV outcomes, especially when pharmacological treatments with first-line drugs reached target doses [39, 40]. In the RCTs, chronic administration of SGLT2i was associated with a significant and progressive reduction of NT-proBNP at each timepoint examined, independently of the molecule tested [41]. However, it was observed that a lower incidence of major adverse cardiac events (MACEs) was achieved regardless of their baseline NT-proBNP value [42].

Unlike SGLT2i, which can now be administered despite diabetic status in HF and CKD patients with albuminuria, GLP1-RA, which has a more significant influence on glycaemic control, can currently be prescribed in T2DM and/or obese patients only. Indeed, it is not yet indicated for HF, despite growing evidence of improvement in symptoms and quality of life is available regarding HF with preserved ejection fraction (HFpEF), the one most closely linked to adiposity and dysmetabolism [43, 44]. GLP1-RAs have also been proven to reduce NT-proBNP across all trials significantly [41]. Unlike SGLT2i, whenever compared with placebo, GLP1-RAs do not seem to have the same behaviour across all the EF spectrum. Indeed, they do not seem to significantly reduce the composite of HF hospitalization or CV death and all-cause mortality in patients with HF history, as in patients without HF history (HR 0.84, 95% CI: 0.76–0.92 and HR 0.85, 95% CI: 0.79–0.92, respectively) [45]. A recent meta-analysis of two RCTs questioned the potential risk of HF hospitalization following the introduction of GLP1-RA (liraglutide and exenatide) in T2DM patients with overt HF in the setting of HFrEF, finding a 50% augmented risk (OR 1.49, 95% CI 1.05–2.10, p = 0.02; I2 = 0%) [46]. These results prompted the same authors to suggest performing active HF screening by employing NP dosage and careful evaluation of clinical history, physical examination and ultrasound imaging before initiating GLP1-RA. However, these meta-analyses include trials in which hospitalization and mortality were not the primary objective and may not be conclusive. While waiting for the findings of future trials focused on these major outcomes in both HFrEF and HFpEF, secure evidence shows how GLP1-RAs improve symptoms and quality of life in obese subjects with HFpEF. Therefore, T2DM people without HF should expect a reduced risk of HF incidence due to the protection of CV events [47, 48].

Study limits

This study has several limitations that need to be addressed. The small sample size and the cross-sectional design are the primary limits, not allowing us to extend our findings to younger populations or patients not eligible for therapy with SGLT2i and/or GLP1-RA. However, the study population was enrolled in three different centres, reflecting the population encountered in “real-life” daily clinical practice. It can be configured as an exploratory study to launch future studies/registries on an epidemiological scale. Moreover, this study is the first to have evaluated the prevalence and associated factors for HS, a concept only recently introduced by the ESC, in T2DM patients with concomitant hypertension/high-normal BP and T2DM, eligible for SGLT2i and GLP1-RA, drugs that have been found to exert several benefits on cardiac dysfunction. In our paper, the echocardiographic data of the patients were not systematically available and therefore described. Our primary intention was to raise awareness of the potential usefulness of the readily available and low-cost NT-proBNP determination in the specific setting of T2DM hypertensive patients. Knowing the NT-proBNP values of my patient can already change his clinical management, as previously reported; therefore, knowing or not the presence of cardiac structural alterations is not one of the objectives of this study.

Conclusions

High BP and T2DM lead to an increased risk of cardiac remodeling and overt HF over time. Large-scale screening with cardiac biomarkers in these patients could allow early and appropriate clinical phenotyping and lead to a more focused implementation of preventive measures based on lifestyle and pharmacological intervention. Future studies on broader populations should evaluate such an approach’s feasibility and clinical impact. Our analysis reveals a non-negligible prevalence of HS in this population, that would have gone unnoticed if not for the NT-proBNP dosage. BP burden and concomitant renal damage were found to be the most relevant risk factors for HS in our study, stressing the pivotal role of higher blood pressure and hypertension in determining cardiac damage in T2DM patients. Therefore, NT-proBNP helps identify hypertensive patients with T2DM at risk of cardiac damage, even subclinical, with an indication to perform an echocardiogram and refer to a specialist team, allowing the early implementation of effective strategies to prevent or delay the progression to overt and advanced stages of the cardiac disease.

Data availability

The data supporting this study’s findings are available from the corresponding author (FS) upon reasonable request.

References

  1. Pop-Busui R, Januzzi JL, Bruemmer D, Butalia S, Green JB, Horton WB, et al. Heart failure: an underappreciated complication of diabetes. A Consensus Report of the American Diabetes Association. Diabetes Care. 2022;45(7):1670–90.

    Article  PubMed  PubMed Central  Google Scholar 

  2. Chen HF, Ho CA, Li CY. Risk of heart failure in a population with type 2 diabetes versus a population without diabetes with and without coronary heart disease. Diabetes Obes Metab. 2019;21(1):112–9.

    Article  PubMed  Google Scholar 

  3. ElSayed NA, Aleppo G, Aroda VR, Bannuru RR, Brown FM, Bruemmer D, et al. Erratum. 10. Cardiovascular disease and risk management: Standards of Care in Diabetes-2023. Diabetes Care 2023;46(Suppl. 1):S158-S190. Diabetes Care. 2023;46(4):898.

    PubMed  PubMed Central  Google Scholar 

  4. Vaduganathan M, Docherty KF, Claggett BL, Jhund PS, de Boer RA, Hernandez AF, et al. SGLT-2 inhibitors in patients with heart failure: a comprehensive meta-analysis of five randomised controlled trials. Lancet. 2022;400(10354):757–67.

    Article  CAS  PubMed  Google Scholar 

  5. Sattar N, Lee MMY, Kristensen SL, Branch KRH, Del Prato S, Khurmi NS, et al. Cardiovascular, mortality, and kidney outcomes with GLP-1 receptor agonists in patients with type 2 diabetes: a systematic review and meta-analysis of randomised trials. Lancet Diabetes Endocrinol. 2021;9(10):653–62.

    Article  CAS  PubMed  Google Scholar 

  6. Pérez-Belmonte LM, Sanz-Cánovas J, García de Lucas MD, Ricci M, Avilés-Bueno B, Cobos-Palacios L, et al. Efficacy and safety of Semaglutide for the management of obese patients with type 2 diabetes and chronic heart failure in real-world clinical practice. Front Endocrinol (Lausanne). 2022;13:851035.

    Article  PubMed  Google Scholar 

  7. Desai AS, Jhund PS, Claggett BL, Vaduganathan M, Miao ZM, Kondo T, et al. Effect of Dapagliflozin on cause-specific mortality in patients with heart failure across the Spectrum of Ejection Fraction: a participant-level pooled analysis of DAPA-HF and DELIVER. JAMA Cardiol. 2022;7(12):1227–34. https://doi.org/10.1001/jamacardio.2022.3736

    Article  PubMed  PubMed Central  Google Scholar 

  8. Wijkman MO, Claggett BL, Malachias MVB, Vaduganathan M, Ballantyne CM, Kitzman DW, et al. Importance of NT-proBNP and conventional risk factors for prediction of death in older adults with and without diabetes mellitus- A report from the atherosclerosis risk in communities (ARIC) study. Diabetes Res Clin Pract. 2022;194:110164.

    Article  CAS  PubMed  Google Scholar 

  9. Malachias MVB, Jhund PS, Claggett BL, Wijkman MO, Bentley-Lewis R, Chaturvedi N, et al. NT-proBNP by itself predicts Death and Cardiovascular events in high-risk patients with type 2 diabetes Mellitus. J Am Heart Assoc. 2020;9(19):e017462.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Malachias MVB, Wijkman MO, Bertoluci MC. NT-proBNP as a predictor of death and cardiovascular events in patients with type 2 diabetes. Diabetol Metab Syndr. 2022;14(1):64.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Bayes-Genis A, Docherty KF, Petrie MC, Januzzi JL, Mueller C, Anderson L, et al. Practical algorithms for early diagnosis of heart failure and heart stress using NT-proBNP: a clinical consensus statement from the Heart Failure Association of the ESC. Eur J Heart Fail. 2023;25(11):1891–8.

    Article  PubMed  Google Scholar 

  12. Natriuretic Peptides Studies C, Willeit P, Kaptoge S, Welsh P, Butterworth AS, Chowdhury R, et al. Natriuretic peptides and integrated risk assessment for cardiovascular disease: an individual-participant-data meta-analysis. Lancet Diabetes Endocrinol. 2016;4(10):840–9.

    Article  Google Scholar 

  13. Stergiou GS, Palatini P, Parati G, O’Brien E, Januszewicz A, Lurbe E, et al. 2021 European Society of Hypertension practice guidelines for office and out-of-office blood pressure measurement. J Hypertens. 2021;39(7):1293–302.

    Article  CAS  PubMed  Google Scholar 

  14. Marx N, Federici M, Schütt K, Müller-Wieland D, Ajjan RA, Antunes MJ, et al. 2023 ESC guidelines for the management of cardiovascular disease in patients with diabetes. Eur Heart J. 2023;44(39):4043–140.

    Article  CAS  PubMed  Google Scholar 

  15. Cuspidi C, Facchetti R, Bombelli M, Tadic M, Sala C, Grassi G, et al. High normal blood pressure and left ventricular hypertrophy echocardiographic findings from the PAMELA Population. Hypertension. 2019;73(3):612–9.

    Article  CAS  PubMed  Google Scholar 

  16. Ueda H, Miyawaki M, Hiraoka H. High-normal blood pressure is associated with new-onset electrocardiographic left ventricular hypertrophy. J Hum Hypertens. 2015;29(1):9–13.

    Article  CAS  PubMed  Google Scholar 

  17. Martins J, Steyn N, Rossouw HM, Pillay TS. Best practice for LDL-cholesterol: when and how to calculate. J Clin Pathol. 2023;76(3):145–52.

    Article  CAS  PubMed  Google Scholar 

  18. Visseren FLJ, Mach F, Smulders YM, Carballo D, Koskinas KC, Bäck M, et al. 2021 ESC guidelines on cardiovascular disease prevention in clinical practice. Eur Heart J. 2021;42(34):3227–337.

    Article  PubMed  Google Scholar 

  19. Lee-Lewandrowski E, Januzzi JL, Green SM, Tannous B, Wu AH, Smith A, et al. Multi-center validation of the Response Biomedical Corporation RAMP NT-proBNP assay with comparison to the Roche Diagnostics GmbH Elecsys proBNP assay. Clin Chim Acta. 2007;386(1–2):20–4.

    Article  CAS  PubMed  Google Scholar 

  20. Park JJ, Epidemiology. Pathophysiology, diagnosis and treatment of Heart failure in diabetes. Diabetes Metab J. 2021;45(2):146–57.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Ndumele CE, Neeland IJ, Tuttle KR, Chow SL, Mathew RO, Khan SS, et al. A synopsis of the evidence for the Science and Clinical Management of Cardiovascular-kidney-metabolic (CKM) Syndrome: A Scientific Statement from the American Heart Association. Circulation. 2023;148(20):1636–64.

    Article  PubMed  Google Scholar 

  22. Bozkurt B, Coats AJ, Tsutsui H, Abdelhamid M, Adamopoulos S, Albert N, et al. Universal Definition and classification of Heart failure: a report of the Heart Failure Society of America, Heart Failure Association of the European Society of Cardiology, Japanese Heart Failure Society and Writing Committee of the Universal Definition of Heart failure. J Card Fail. 2021;27(4):387–413.

    Article  Google Scholar 

  23. Wang L, Li X, Wang Z, Bancks MP, Carnethon MR, Greenland P, et al. Trends in Prevalence of diabetes and control of risk factors in diabetes among US adults, 1999–2018. JAMA. 2021;326(8):1–13.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Mancia G, Kreutz R, Brunström M, Burnier M, Grassi G, Januszewicz A, et al. 2023 ESH guidelines for the management of arterial hypertension the Task Force for the management of arterial hypertension of the European Society of Hypertension: endorsed by the International Society of Hypertension (ISH) and the European Renal Association (ERA). J Hypertens. 2023;41(12):1874–2071.

    Article  CAS  PubMed  Google Scholar 

  25. Huelsmann M, Neuhold S, Strunk G, Moertl D, Berger R, Prager R, et al. NT-proBNP has a high negative predictive value to rule-out short-term cardiovascular events in patients with diabetes mellitus. Eur Heart J. 2008;29(18):2259–64.

    Article  CAS  PubMed  Google Scholar 

  26. Betti I, Castelli G, Barchielli A, Beligni C, Boscherini V, De Luca L, et al. The role of N-terminal PRO-brain natriuretic peptide and echocardiography for screening asymptomatic left ventricular dysfunction in a population at high risk for heart failure. The PROBE-HF study. J Card Fail. 2009;15(5):377–84.

    Article  CAS  PubMed  Google Scholar 

  27. Said F, Arnott C, Voors AA, Heerspink HJL, Ter Maaten JM. Prediction of new-onset heart failure in patients with type 2 diabetes derived from ALTITUDE and CANVAS. Diabetes Obes Metab. 2024.

  28. Yancy CW, Jessup M, Bozkurt B, Butler J, Casey DE Jr., Colvin MM, et al. 2017 ACC/AHA/HFSA focused update of the 2013 ACCF/AHA Guideline for the management of Heart failure: a report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice guidelines and the Heart Failure Society of America. Circulation. 2017;136(6):e137–61.

    Article  PubMed  Google Scholar 

  29. 10. Cardiovascular Disease and Risk Management: standards of Care in Diabetes-2024. Diabetes Care. 2024;47(Suppl 1):S179–218.

    Google Scholar 

  30. Boonman-de Winter LJ, Rutten FH, Cramer MJ, Landman MJ, Liem AH, Rutten GE, et al. High prevalence of previously unknown heart failure and left ventricular dysfunction in patients with type 2 diabetes. Diabetologia. 2012;55(8):2154–62.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Hoek AG, Dal Canto E, Wenker E, Bindraban N, Handoko ML, Elders PJM, et al. Epidemiology of heart failure in diabetes: a disease in disguise. Diabetologia. 2024;67(4):574–601.

    Article  PubMed  PubMed Central  Google Scholar 

  32. Ceriello A, Lalic N, Montanya E, Valensi P, Khunti K, Hummel M, et al. NT-proBNP point-of-care measurement as a screening tool for heart failure and CVD risk in type 2 diabetes with hypertension. J Diabetes Complications. 2023;37(3):108410.

    Article  CAS  PubMed  Google Scholar 

  33. Spannella F, Di Pentima C, Giulietti F, Buscarini S, Ristori L, Giordano P, et al. Prevalence of subclinical carotid atherosclerosis and role of Cardiovascular Risk factors in older adults: atherosclerosis and aging are not synonyms. High Blood Press Cardiovasc Prev. 2020;27(3):231–8.

    Article  PubMed  Google Scholar 

  34. Lembo M, Strisciuglio T, Fonderico C, Mancusi C, Izzo R, Trimarco V, et al. Obesity: the perfect storm for heart failure ESC Heart Fail. 2024;11(4): 1841–60. https://doi.org/10.1002/ehf2.14641

    Article  PubMed  PubMed Central  Google Scholar 

  35. Sarzani R, Allevi M, Di Pentima C, Schiavi P, Spannella F, Giulietti F. Role of Cardiac natriuretic peptides in Heart structure and function. Int J Mol Sci. 2022;23(22):14415. https://doi.org/10.3390/ijms232214415

    Article  PubMed  PubMed Central  Google Scholar 

  36. Pandey A, Vaduganathan M, Patel KV, Ayers C, Ballantyne CM, Kosiborod MN, et al. Biomarker-based risk prediction of Incident Heart failure in Pre-diabetes and Diabetes. JACC Heart Fail. 2021;9(3):215–23.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Sarzani R, Giulietti F, Di Pentima C, Spannella F. Sodium-glucose co-transporter-2 inhibitors: peculiar hybrid diuretics that protect from target organ damage and cardiovascular events. Nutr Metab Cardiovasc Dis. 2020;30(10):1622–32.

    Article  CAS  PubMed  Google Scholar 

  38. McGuire DK, Shih WJ, Cosentino F, Charbonnel B, Cherney DZI, Dagogo-Jack S, et al. Association of SGLT2 inhibitors with Cardiovascular and kidney outcomes in patients with type 2 diabetes: a Meta-analysis. JAMA Cardiol. 2021;6(2):148–58.

    Article  PubMed  Google Scholar 

  39. Januzzi JL Jr., Rehman SU, Mohammed AA, Bhardwaj A, Barajas L, Barajas J, et al. Use of amino-terminal pro-B-type natriuretic peptide to guide outpatient therapy of patients with chronic left ventricular systolic dysfunction. J Am Coll Cardiol. 2011;58(18):1881–9.

    Article  CAS  PubMed  Google Scholar 

  40. Felker GM, Anstrom KJ, Adams KF, Ezekowitz JA, Fiuzat M, Houston-Miller N, et al. Effect of natriuretic peptide-guided therapy on hospitalization or Cardiovascular Mortality in high-risk patients with heart failure and reduced ejection fraction: a Randomized Clinical Trial. JAMA. 2017;318(8):713–20.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Chen J, Jiang C, Guo M, Zeng Y, Jiang Z, Zhang D, et al. Effects of SGLT2 inhibitors on cardiac function and health status in chronic heart failure: a systematic review and meta-analysis. Cardiovasc Diabetol. 2024;23(1):2.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Januzzi JL Jr., Zannad F, Anker SD, Butler J, Filippatos G, Pocock SJ, et al. Prognostic importance of NT-proBNP and effect of Empagliflozin in the EMPEROR-Reduced trial. J Am Coll Cardiol. 2021;78(13):1321–32.

    Article  CAS  PubMed  Google Scholar 

  43. Butler J, Shah SJ, Petrie MC, Borlaug BA, Abildstrøm SZ, Davies MJ, et al. Semaglutide versus placebo in people with obesity-related heart failure with preserved ejection fraction: a pooled analysis of the STEP-HFpEF and STEP-HFpEF DM randomised trials. Lancet. 2024;403(10437):1635–48.

    Article  CAS  PubMed  Google Scholar 

  44. Sarzani R, Landolfo M, Di Pentima C, Ortensi B, Falcioni P, Sabbatini L, et al. Adipocentric origin of the common cardiometabolic complications of obesity in the young up to the very old: pathophysiology and new therapeutic opportunities. Front Med (Lausanne). 2024;11:1365183.

    Article  PubMed  Google Scholar 

  45. Ferreira JP, Saraiva F, Sharma A, Vasques-Nóvoa F, Angélico-Gonçalves A, Leite AR, et al. Glucagon-like peptide 1 receptor agonists in patients with type 2 diabetes with and without chronic heart failure: a meta-analysis of randomized placebo-controlled outcome trials. Diabetes Obes Metab. 2023;25(6):1495–502.

    Article  CAS  PubMed  Google Scholar 

  46. Neves JS, Packer M, Ferreira JP. Increased risk of heart failure hospitalization with GLP-1 receptor agonists in patients with reduced ejection fraction: a Meta-analysis of the EXSCEL and FIGHT trials. J Card Fail. 2023;29(7):1107–9.

    Article  PubMed  Google Scholar 

  47. Ferreira JP, Sharma A, Butler J, Packer M, Zannad F, Vasques-Nóvoa F, et al. Glucagon-like Peptide-1 receptor agonists across the Spectrum of Heart failure. J Clin Endocrinol Metab. 2023;109(1):4–9.

    Article  PubMed  Google Scholar 

  48. Kumar S, Blaha MJ. GLP-1 RA for cardiometabolic risk reduction in obesity– how do we best describe benefit and value? Am J Prev Cardiol. 2024;18:100682.

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Funding

This study was supported by Ricerca Corrente funding from the Italian Ministry of Health to IRCCS INRCA.

Author information

Authors and Affiliations

  1. Internal Medicine and Geriatrics, IRCCS INRCA, Ancona, Italy

    Matteo Landolfo, Francesco Spannella, Federico Giulietti, Beatrice Ortensi, Roberto Zampa & Riccardo Sarzani

  2. Department of Clinical and Molecular Sciences, Politecnica delle Marche University, Ancona, Italy

    Matteo Landolfo, Francesco Spannella, Beatrice Ortensi, Lucia Stella, Roberto Zampa, Sofia Cecchi & Riccardo Sarzani

  3. Unit of Diabetology– Endocrinology and Metabolic Diseases, AST Pesaro-Urbino, Urbino, Italy

    Maria A. Carlucci

  4. Clinic of Laboratory and Precision Medicine, IRCCS INRCA, Ancona, Italy

    Roberta Galeazzi

  5. Metabolic Diseases and Diabetology, IRCCS INRCA, Ancona, Italy

    Federica Turchi, Maria P. Luconi & Elena Tortato

  6. Clinic of Endocrinology and Metabolic Diseases, Azienda Ospedaliero Universitaria delle Marche, Ancona, Italy

    Massimiliano Petrelli

Authors
  1. Matteo Landolfo
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Francesco Spannella
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Federico Giulietti
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Beatrice Ortensi
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Lucia Stella
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Maria A. Carlucci
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Roberta Galeazzi
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Federica Turchi
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Maria P. Luconi
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Roberto Zampa
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Sofia Cecchi
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Elena Tortato
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Massimiliano Petrelli
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Riccardo Sarzani
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

RS, ML, FS, FG: conceptualization, investigation, methodology, formal analysis, writing manuscript. BO, RZ, LS, SC, MAC, RG, FT, MPL, ET, MP: patient enrollment, data curation. RS: resources, supervision, validation, project administration. All authors gave final approval and agreed to be accountable for all aspects of the work, ensuring integrity and accuracy.

Corresponding author

Correspondence to Francesco Spannella.

Ethics declarations

Competing interests

The authors declare no competing interests.

Ethics approval and informed consent

All patients gave their written informed consent to participate in the present study. Clinical investigations have been conducted per the ethical standards in the 1964 Declaration of Helsinki and its later amendments. This observational study was approved by the local institutional ethics committee (Comitato Etico INRCA).

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Landolfo, M., Spannella, F., Giulietti, F. et al. Detecting heart stress using NT-proBNP in patients with type 2 diabetes mellitus and hypertension or high-normal blood pressure: a cross-sectional multicentric study. Cardiovasc Diabetol 23, 297 (2024). https://doi.org/10.1186/s12933-024-02391-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12933-024-02391-z

Keywords

Cardiovascular Diabetology

ISSN: 1475-2840