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Type 2 diabetes mellitus negatively affects the functional performance of 6-min step test in chronic heart failure: a 3-year follow-up study

Abstract

Background

Type 2 diabetes mellitus (T2DM) and chronic heart failure (CHF) present a decrease in functional capacity due to the intrinsic nature of both pathologies. It is not known about the potential impact of T2DM on functional capacity when assessed by 6-min step test (6MST) and its effect as a prognostic marker for fatal and non-fatal events in patients with CHF.

Objective

to evaluate the coexistence of T2DM and CHF in functional capacity through 6MST when compared to CHF non-T2DM, as well as to investigate the different cardiovascular responses to 6MST and the risk of mortality, decompensation of CHF and acute myocardial infarction (AMI) over 36 months.

Methods

This is a prospective cohort study with 36 months of follow-up in individuals with T2DM and CHF. All participants completed a clinical assessment, followed by pulmonary function testing, echocardiography, and 6MST. The 6MST was performed on a 20 cm high step and cardiovascular responses were collected: heart rate, systemic blood pressure, oxygen saturation, BORG dyspnea and fatigue. The risk of mortality, acute myocardial infarction and decompensation of CHF was evaluated.

Results

Eighty-six participants were included. The CHF-T2DM group had a significantly lower functional capacity than the CHF non-T2DM group (p < 0.05). Forced Expiratory Volume in one second (L), ejection fraction (%), gender and T2DM influence and are predictors of functional capacity (p < 0.05; adjusted R squared: 0.419). CHF-T2DM group presented a higher risk of mortality and acute myocardial infarction over the 36 months of follow-up (p < 0.05), but not to the risk of decompensation (p > 0.05).

Conclusion

T2DM negatively affects the functional performance of 6MST in patients with CHF. Gender, ejection fraction (%), FEV1 (L) and T2DM itself negatively influence exercise performance.

Introduction

Common, highly prevalent, closely related and frequently associated, CHF and T2DM have a bidirectional relationship, that is, the origin and evolution of each pathology can be mutually influenced [1,2,3,4]. The interactions between both diseases is widely known [5, 6], however, the treatment approach continues to be a challenge, from screening to optimizing therapeutic decision-making that addresses aspects of rehabilitation of these individuals due to the high rate of morbidity and mortality and the heterogeneous clinical presentation of both conditions [1, 6, 7].

In both diseases, exercise capacity has been adopted as an important outcome and the main guidelines and international campaigns have drawn attention to the importance of this assessment and the inclusion of this outcome in therapeutic optimization [8,9,10,11]. Since the results that reflect exercise capacity have discriminative prognostic value for mortality risk, risk of unfavorable outcomes, the assessment of treatment efficacy in both conditions is highly desirable [12,13,14].

When it comes to exercise capacity, cardiopulmonary exercise testing (CPET) has established itself as the most effective tool for assessing this outcome [10, 15], however, the arsenal of equipment used and the need for a team that involves trained professionals led scientists to develop options that could reflect the CPET's ability to exercise in a more economically accessible and simple, but not replaceable [16, 17]. The 6-min step test (6MST) has gained notoriety and clinical and scientific popularity due to its practicality and simple, low-cost and easily available alternative option, especially in environments where the most sophisticated resources and equipment for achieving the gold standard are not available, in addition to having an important correlation with CPET [16, 18]. In both individuals with CHF [16] and individuals with T2DM [18], the reliability and validity of the 6MST has already been scientifically proven and the test has strong concurrent validity when compared to the CPET.

Undoubtedly, both disease negatively impact on exercise capacity, affecting the cardiovascular, respiratory and metabolic dynamic for the supply of oxygen to peripheral muscles [19, 20]. However, although the coexistence of T2DM and CHF has been growingly reported, description of fatal and nonfatal events and its relation with functional (in)capacity considering the presence of both conditions is still scarce. Therefore, the objective of this investigation is to evaluate whether individuals with CHF with T2DM have worse functional capacity when compared to a group with CHF without T2DM. Secondarily, we aimed to investigate the different cardiovascular responses presented in both groups and the risk of mortality, decompensation of heart failure and acute myocardial infarction over 36 months. Our hypothesis is, based on all the previously described aspects, that T2DM not only negatively affects the functional performance of individuals with CHF, but also presents itself as an independent factor for reducing functional capacity in the 6MST, worse cardiovascular responses and presents greater mortality, decompensation of CHF and acute myocardial infarction risk.

Methodology

Study design

This is a prospective longitudinal investigation with a follow-up of 3 years (36 months) carried out by the Cardiopulmonary Physiotherapy Laboratory (LACAP) of the Federal University of São Carlos—UFSCar, located in São Carlos, SP, Brazil. The participant recruitment process took place between December 2017 and November 2020. The university's ethics committee previously approved the development of the investigation under protocol number 5.188.654 and the research followed the principles of the Declaration of Helsinki. The STrengthening the Reporting of OBservational Studies in Epidemiology (STROBE) guideline was used to conduct the study [21]. All participants were informed about the research objectives and gave their informed consent before being evaluated.

Participants

The Cardiology Outpatient Clinics of the Medical Specialties Center (CEME) and the São Carlos University Hospital (HU-UFSCar) were used to actively search for participants eligible for the investigation. We included patients over 40 years of age, confirmed diagnosis of heart failure with left ventricular ejection fraction below 50% by echocardiography, with or without clinical diagnosis of T2DM, clinical stability and absence of medication changes in the last 3 months. Those aged over 80 years, diagnosed with heart failure with preserved ejection fraction, history of cardiovascular events in the last 6 months, decompensation of the disease in the last 3 months, presence of any implantable cardiac pacemaker, unstable angina, diagnosis of any neoplasms, uncontrolled systemic arterial hypertension, cognitive impairment or lack of understanding of the study proposal were excluded of study.

Initial assessment

Initially, a prior anamnesis was carried out using an assessment form developed by the laboratory and researchers involved so that personal information, associated pathologies and medications used were collected. The medical records of the included patients were also used as a tool to search for important information.

Anthropometric variables

To estimate the height of participants, a stadiometer (Welmy R-110, Santa Bárbara do Oeste, São Paulo, Brazil) was used. Body mass in kilograms (kg), body fat mass (kg), body fat percentage (%) and skeletal muscle mass (kg) were determined through bioelectrical impedance analysis, using the InBody 720 device. Participants were instructed to fast for at least 4 h, wear light clothing, remove all metallic objects in contact with the body, urinate before the exam, avoid drinking alcoholic beverages for 12 h and not perform strenuous physical exercise the day before the evaluation. During the examination, participants were positioned in an upright position, barefoot, with their shoulders slightly abducted and their elbows flexed at approximately 15°, as recommended by the manufacturer (BIOSPACE, 2004). The Body Mass Index (BMI) was calculated by dividing body mass (kg) by height squared in meters (kg/m2). The BMI classification was established as follows: low weight (15–19.9 kg/m2); normal weight (20–24.9 kg/m2); overweight (25–29.9 kg/m2); obesity I (30–34.9 kg/m2); obesity II (35–39.9 kg/m2); and obesity III (≥ 40 kg/m2)[22].

Minnesota Questionnaire

Previously validated for the Brazilian population [23], this questionnaire consists of 21 questions relating to the limitations associated with heart failure considering the last month. The answers to each question range from 0 to 5, where 0 represents no limitations and 5 the maximum limitation. These questions involve a physical dimension (1–7, 12 and 13), which are highly related to dyspnea, fatigue; emotional dimension (17- 21); and other issues (number 8, 9, 10, 11, 14, 15 and 16) which, together with the previous dimensions, form the total score.

New York Heart Association—NYHA

The New York Heart Association (NYHA) functional classification was used to assess the severity of functional limitations resulting from the CHF condition based on the symptoms experienced by the participant during physical activity. It allows stratifying the degree of limitation imposed by it: class I—absence of symptoms during daily activities, with limitation in efforts similar to that expected in healthy individuals; class II—symptoms triggered by daily activities; class III—symptoms triggered by activities less intense than everyday activities; class IV—symptoms at rest [24].

Pulmonary function—spirometry

The assessment of lung function was conducted using spirometry (Masterscreen Body, Mijnhardt/Jäger, Würzburg, Germany) by a previously trained researcher, following conventional techniques and the acceptability and reproducibility guidelines of the American Thoracic and European Respiratory Societies (ATS/ERS). At least three slow and forced maneuvers considered acceptable and reproducible were performed, as recommended, and repeated 20 min after administration of 400 µg of Albuterol Sulfate. Participants with overlapping chronic obstructive pulmonary disease were diagnosed according to the GOLD criteria (post-bronchodilator forced expiratory volume in one second (FEV1)/forced vital capacity (FVC) ratio < 0.70) [25, 26].

Transthoracic echocardiogram

The transthoracic echocardiogram was performed by a cardiologist, using an ultrasound device with a 3 MHz transducer (Phillips, HD11 XE, Bothell, Washington, United States) according to recommendations [27]. The end systolic and diastolic diameter of the left ventricle, early diastolic mitral filling velocities (E wave), early diastolic velocity of the mitral annulus (E' wave) and left ventricular ejection fraction (LFEV) were obtained using the Simpson method [28].

6-min step test—6MST

The 6MST has been previously validated for individuals with CHF [16]. Prior to the test, upon arrival at the laboratory, participants were informed about the nature and dynamics of the test so that any doubts regarding carrying it out could be clarified. Then, they underwent a period of 4 min of rest (2 min sitting and 2 min standing) so that vital signs could be collected (resting heart rate [HR], peripheral oxygen saturation [SpO2] and blood pressure systemic) in addition to perceived exertion for dyspnea and fatigue of the lower limbs using the BORG 10 scale in each position. At the end of the 4 min, they were instructed to go up and down a single step with a height of 20 cm (cm) in a self-paced manner, being allowed to slow down, if necessary, and even interrupt the test to rest. Verbal encouragement commands were used for each minute of testing and the time remaining until completion. The step numbers were counted from the beginning to the end of the 6-min time and recorded. Vital signs collected prior to the test, as well as feelings of lower limb fatigue and dyspnea were obtained immediately at the end of the test and the 6th min of recovery.

Despite being considered a test of a submaximal nature, some criteria for interrupting the exam were adopted so that the integrity of the patient's health was guaranteed: reaching 85% of maximum HR, arterial oxygen saturation ≤ 87%, systolic blood pressure (SBP) greater than 170 mmHg and DBP greater than 110 mmHg, BORG score greater than 7 for dyspnea and lower limb fatigue, anginal pain > 2, dizziness, vertigo and nausea. The prediction of functional performance of participants in the 6MST for the Brazilian population was made using the equations proposed by Arcuri et al.[29] 6MST = 209 – (1.05 × age) for men and 6MST = 174 – (1.05 × age) for women, where age is expressed in years; and Albuquerque et al.[30] 6MST = 106 + (17.02 × [0:woman; 1:man]) + (− 1.24 × age) + (0.8 × height) + (− 0.39 × weight) where 6MST is expressed in number of steps; age, in years; height, in cm; and weight, in kg.

Participants follow-up

Information on mortality, AMI and acute decompensated heart failure was collected through periodic telephone calls every 6 months and/or through hospital records from the date of the patient's initial evaluation in the laboratory. According to the European Society of Cardiology [28], acute decompensation of heart failure was understood as a rapid or gradual clinical presentation of the signs and symptoms of heart failure at rest, severe enough to cause unplanned office visits, emergency room visits or hospitalization requiring urgent assessment and subsequent initiation or intensification of treatment that includes therapies or procedures.

Statistical analyses

Data are presented as mean and standard deviation or absolute values and percentages of occurrence when appropriate. The Kolmogorov–Smirnov test was used to verify the normality of the data. For the analysis between the groups test T for independent samples was used when the data presented a normal distribution. When the data presented a non-parametric distribution, the Mann–Whitney test was used. The χ2 test was used to compare categorical variables. Kaplan–Meier analysis was used to test the risk of all-cause mortality, acute decompensated heart failure, and acute myocardial infarction over 36 months of follow-up. Differences between curves were evaluated using the Log-rank test, Breslow and Tarone-Ware.

The covariates included in the present analysis constitute a broad spectrum of factors associated with unfavorable outcomes (mortality, decompensation of heart failure and AMI). Univariate linear regression analyses were performed to verify the association between the independent variables and the dependent variable (steps in the 6MST) [31]. For the multiple linear regression model, variables that presented a p-value < 0.20 in the univariate analysis were selected as covariates [32]. Comparisons of 6MST performance and cardiovascular responses between groups were expressed as mean, standard deviation (SD), mean difference (MD), and effect size calculated using Cohen’s d, with the categorization based on the values established by Cohen [33]. The effect size was calculated based on the Cohen d, according to the website: <https://www.psychometrica.de/effect_size.html>. It was considered the following interpretation of the d value: 0.2 (weak), 0.5 (moderate) and > 0.8 (large effect size) [33]. Raincloud plots were produced using the JASP 0.18.2 software [34] for data visualization of the step test performance and predictive values <https://jasp-stats.org/>. All analyzes were performed using GraphPad Software, Inc. (2019). GraphPad Prism (versão 8.0.1). San Diego, CA <https://www.graphpad.com>. The probability of type 1 error occurrence was established at 5% for all tests (p < 0.05).

Results

Initially, one hundred and twenty-one participants were recruited, however thirty-five were not included. Finally, eighty-six participants were included: 34 CHF-T2DM group and 52 in CHF non-T2DM group (Fig. 1). Information about the characteristics of the sample included in the study can be viewed in Table 1. The groups did not differ in terms of age (years), sex distribution and height (m). However, the CHF-T2DM group had higher body weight and BMI when compared to the CHF non-T2DM and, consequently, a greater number of participants with obesity (65%) (class I [40%], class II [18%] and class III [5%]). Additionally, this same group had a higher prevalence of coronary artery disease (12%), dyslipidemia (72%), use of beta-blockers (85%) and lower LVEF (%). No statistically significant differences were observed in the outcomes of quality of life (Minnesotta questionnaire), functional classification (NYHA) and lung function (spirometry). In total, 14 individuals died over the 36 months of follow-up (9 in the CHF-T2DM group and 5 in the CHF non-T2DM). Furthermore, 13 individuals progressed to acute decompensation of heart failure and 10 to AMI.

Fig. 1
figure 1

Flowchart

Table 1 General characteristics of the study sample at initial assessment (n = 86)

In Fig. 2, when we evaluated functional performance comparing to 6MST in both groups, we observed that the CHF-T2DM group had a significantly lower functional capacity than the CHF non-T2DM group (60 ± 29 versus 87 ± 31; Cohen’s d = 0.875) and that they achieved an average percentage of 45 ± 20 versus 64 ± 22 when considering the prediction equation by Arcuri et al., and 43 ± 19 versus 60 ± 19 when considering the prediction equation by Albuquerque et al. Regarding cardiovascular responses (Table 2), we only found a lower heart rate chronotropic response by heart rate in beats per minute in the CHF-T2DM (bpm) at peak exercise (97 ± 26 versus 108 ± 21; Cohen’s d: 0.476).

Fig. 2
figure 2

Raincloud plots for functional capacity by 6MST and predicted values in CHF non-T2DM and CHF-T2DM. CHF non-T2DM chronic heart failure without type 2 diabetes mellitus, CHF-T2DM chronic heart failure with type 2 diabetes mellitus, % percentage, n number in absolute value, p < 0.05: statistical significance

Table 2 Cardiovascular responses through 6MST

The univariate linear regression model (Table 3) revealed that FEV1 (L), ejection fraction (%), gender and T2DM influence and are predictors of approximately 42% functional capacity (p < 0.05; adjusted R squared: 0.419). Secondarily, when we analyzed the Kaplan–Meier curves, we observed that the CHF-T2DM presented a higher risk of mortality (Fig. 3) and acute myocardial infarction (Fig. 4) over the 36 months of follow-up (p < 0.05 to Log-rank, Brelow and Tarone-ware), however, regarding the risk of heart failure decompensation (Fig. 5), there was no statistically significant difference between the groups (p > 0.05 to Log-rank, Brelow and Tarone-ware).

Table 3 Stepwise multiple linear regression model for the six-minute step test
Fig. 3
figure 3

Kaplan–Meier curve for mortality over a period of 36 months. CHF chronic heart failure, %: percentage

Fig. 4
figure 4

Kaplan–Meier curve for acute myocardial infarction over a period of 36 months. CHF chronic heart failure, % percentage

Fig. 5
figure 5

Kaplan–Meier curve for acute decompensation over a period of 36 months. CHF chronic heart failure, % percentage

Discussion

The main results of this investigation are associated with some important aspects: (1) for the first time, the impact of T2DM on CHF was investigated considering the performance and cardiovascular variables of 6MST; (2) we confirmed our hypothesis that the association of T2DM and CHF presents worse functional capacity compared to the CHF non-T2DM group; (3) secondarily, we observed a higher risk of mortality and AMI in the CHF-T2DM over 36 months of follow-up.

The heterogeneous presentation of CHF, that is, concomitant with other risk factors that contribute to the increase in unfavorable outcomes, with consequent development of disabling functional limitations [28, 35]. Particularly, in individuals affected by CHF, the decrease in functional capacity is linked to multifactorial mechanisms that involve, above all, early anaerobic metabolism resulting from a combination of reduced blood flow in skeletal muscle, decreased aerobic enzymes in skeletal muscle, morphological and functional changes of musculoskeletal fibers and inefficiency of the cardiovascular and respiratory system [36,37,38]. T2DM, in turn, presents peculiar characteristics that compromise exercise capacity in this population, mainly associated with ineffective glucose uptake, mitochondrial imbalance and the transition from oxidative to glycolytic fiber type [39, 40].

Paradoxically to the physiological limitations mentioned above, the effort required to perform the 6MST requires vertical displacement and the involvement of large muscle groups that demand greater cardiovascular stress when compared, for example, to the 6-min walk test, leading to an increase extraction oxygen [16, 29]. Considering oxygen uptake, it is nothing new that, individually, both diseases present a decrease in functional capacity when evaluated by field and laboratory tests. In individuals with CHF, whether with a reduced ejection fraction or with its preservation, different methods that reflect this outcome indicate functional impairment over time [41, 42]. The same reasoning can be observed in patients with T2DM [40, 43].

Previously, and in an unprecedented way, an investigation proved that in individuals with CHF the addition of T2DM is associated with a reduction in the distance covered during the 6-min walk test (6MWT) in addition to being an independent determinant of worse performance in the group with coexistence of both pathologies [44]. Still considering the phenotypic nature of CHF presentation, recently, a group of researchers observed that T2DM demonstrated to be the strongest predictor of limited exercise capacity in CHF and preserved ejection fraction when also assessed by the 6MWT [45].

In healthy individuals, variables such as weight (kg), height (cm), age (years) and gender influence 6MST performance and explained at least 42% of the variability in functional capacity [30]. Parallel to this, our results point to an influence of gender, T2DM, ejection fraction (%) and FEV1 (L) and, undoubtedly, we need to recognize how much each variable makes sense in our regression model since current literature has demonstrated the influence of each of them on exercise capacity. The influence of gender is associated with the nature of the physiological difference that men and women present in the cardiovascular, respiratory and musculoskeletal systems, both in healthy individuals and in individuals affected by heart failure [46, 47]. In turn, airflow limitation, more specifically when assessed by FEV1 (L), contributes to functional performance in this population also being compromised. The contribution of lung function to exercise capacity in patients with CHF has been previously discussed and accounts for approximately 30% of maximal exercise capacity during CPET [48].

Our sample presented some important characteristics that deserve discussion. At first, we must keep in mind that the majority of people affected by T2DM are overweight or obese [3]. Although there is a paradoxical relationship, that is, inversely proportional, between weight gain and 6MST performance, in practical terms, when we talk about T2DM it is practically utopian to disregard overweight or obesity in this population due to the close relationship between these two outcomes [30]. We minimally understand the importance of controlling the variable that reflects obesity in both groups so that this bias is minimized, but this may reflect a small portion of the population affected by CHF-T2DM since the coexistence of both pathologies is highly prevalent [49] and that obesity is strongly connected to T2DM [3]. Nevertheless, the impact of T2DM culminates in structural and functional changes in the heart muscle that lead to exercise intolerance in patients with CHF and, not surprisingly, the CHF-T2DM group showed a lower left ventricular ejection fraction that may be a reflection of coexistence of both diseases [20].

When we considered the characterization of our sample using the NYHA scale, we observed that most participants were categorized as NYHA I and II. Curiously, there was a significant risk of mortality and AMI in our sample, revealing a true paradox, as these functional classes typically reflect better functional capacity. Since our patients were followed during a pandemic period, we hypothesize several possible explanations for these unfavorable outcomes: (a) COVID-19 infection and its deleterious effects, leading to an increased risk of AMI and mortality [50]; (b) the impact of lockdown on increasing the risks associated with these outcomes [51]; (c) limited discrimination of the NYHA classification [52].

Clinically, our results contribute not only to recognizing the impact of T2DM in individuals with CHF on 6MST performance, but mainly so that the results can be used in more precise therapies that consider the nature of the coexistence of both pathologies once the evaluation of this outcome. It is routinely used for prognostic, diagnostic, pharmacological optimization, monitoring of disease progression and investigation of functional decline.

Limitations

This is a study with some limitations that deserve to be described. It was not possible to characterize the sample according to metabolic outcomes such as fasting blood glucose or glycated hemoglobin and we also do not have information about the time of diagnosis of T2DM.

Conclusion

T2DM negatively affects the functional performance of 6MST in patients with CHF. Sex, ejection fraction (%), FEV1 (L) and T2DM itself negatively influence this outcome and must be considered within the evaluation.

Availability of data and materials

The set of data generated and/or analyzed during the present study are available through the corresponding author upon reasonable request.

References

  1. Elendu C, Amaechi DC, Elendu TC, Ashna M, Ross-Comptis J, Ansong SO, et al. Heart failure and diabetes: understanding the bidirectional relationship. Medicine (Baltimore). 2023;102:E34906.

    Article  PubMed  Google Scholar 

  2. Palazzuoli A, Iacoviello M. Diabetes leading to heart failure and heart failure leading to diabetes: epidemiological and clinical evidence. Heart Fail Rev. 2023;28:585.

    Article  CAS  PubMed  Google Scholar 

  3. Theofilis P, Oikonomou E, Tsioufis K, Tousoulis D. Diabetes mellitus and heart failure: epidemiology, pathophysiologic mechanisms, and the role of SGLT2 inhibitors. Life. 2023;13:497.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Sugandh F, Chandio M, Raveena F, Kumar L, Karishma F, Khuwaja S, et al. Advances in the management of diabetes mellitus: a focus on personalized medicine. Cureus. 2023;15:e43697.

    PubMed  PubMed Central  Google Scholar 

  5. Thomas MC. Type 2 diabetes and heart failure: challenges and solutions. Curr Cardiol Rev. 2016;12:249.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Htay T, Soe K, Lopez-Perez A, Doan AHA, Romagosa MA, Aung KK. Mortality and cardiovascular disease in type 1 and type 2 diabetes. Curr Cardiol Rep. 2019;21:1407.

    Article  Google Scholar 

  7. Bytyçi I, Bajraktari G. Mortality in heart failure patients. Anatol J Cardiol. 2015;15:63.

    Article  PubMed  Google Scholar 

  8. Colberg SR, Sigal RJ, Yardley JE, Riddell MC, Dunstan DW, Dempsey PC, et al. Physical activity/exercise and diabetes: a position statement of the American Diabetes Association. Diabetes Care. 2016;39:2065.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Flotyńska J, Szybiak W, Naskręt D, Zozulińska-Ziółkiewicz D, Grzelka-Woźniak A, Uruska A. Methods of Assessment of Physical Capacity in People with Diabetes Mellitus Type 1. Curr Diabetes Rev . 2024;20.

  10. Herdy AH, Ritt LEF, Stein R, de Araújo CGS, Milani M, Meneghelo RS, et al. Cardiopulmonary exercise test: background, applicability and interpretation. Arq Bras Cardiol. 2016;107:467.

    CAS  PubMed  PubMed Central  Google Scholar 

  11. Heidenreich PA, Bozkurt B, Aguilar D, Allen LA, Byun JJ, Colvin MM, et al. 2022 AHA/ACC/HFSA guideline for the management of heart failure: a report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines. J Am Coll Cardiol. 2022;79:e263-421.

    Article  PubMed  Google Scholar 

  12. Huang WM, Chang HC, Chen CN, Huang CJ, Yu WC, Cheng HM, et al. Symptom-limited exercise capacity is associated with long-term survival. Medicine (Baltimore). 2023;102:E34948.

    Article  CAS  PubMed  Google Scholar 

  13. Zisman-Ilani Y, Fasing K, Weiner M, Rubin DJ. Exercise capacity is associated with hospital readmission among patients with diabetes. BMJ Open Diabetes Res Care. 2020;8:1771.

    Article  Google Scholar 

  14. Nojima H, Yoneda M, Watanabe H, Yamane K, Kitahara Y, Sekikawa K, et al. Association between aerobic capacity and the improvement in glycemic control after the exercise training in type 2 diabetes. Diabetol Metab Syndr. 2017;9:63.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Myers J, Arena R, Cahalin LP, Labate V, Guazzi M. Cardiopulmonary exercise testing in heart failure. Curr Probl Cardiol. 2015;40:322–72.

    Article  PubMed  Google Scholar 

  16. Marinho RS, Jürgensen SP, Arcuri JF, Goulart CL, Dos Santos PB, Roscani MG, et al. Reliability and validity of six-minute step test in patients with heart failure. Brazilian J Med Biol Res. 2021;54:e10514.

    Article  CAS  Google Scholar 

  17. Giannitsi S, Bougiakli M, Bechlioulis A, Kotsia A, Michalis LK, Naka KK. 6-minute walking test: a useful tool in the management of heart failure patients. Ther Adv Cardiovasc Dis. 2019;13:1–10.

    Article  Google Scholar 

  18. Lee MC. Validity of the 6-minute walk test and step test for evaluation of cardio respiratory fitness in patients with type 2 diabetes mellitus. J Exerc Nutr Biochem. 2018;22:49.

    Article  Google Scholar 

  19. Poole DC, Richardson RS, Haykowsky MJ, Hirai DM, Musch TI. Exercise limitations in heart failure with reduced and preserved ejection fraction. J Appl Physiol. 2018;124:208.

    Article  CAS  PubMed  Google Scholar 

  20. Nesti L, Pugliese NR, Sciuto P, Natali A. Type 2 diabetes and reduced exercise tolerance: a review of the literature through an integrated physiology approach. Cardiovasc Diabetol. 2020;19:134.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Malta M, Cardoso LO, Bastos FI, Magnanini MMF, da Silva CMFP. STROBE initiative: guidelines on reporting observational studies. Rev Saude Publica. 2010;44:559–65.

    Article  PubMed  Google Scholar 

  22. Nuttall FQ. Body mass index: obesity, BMI, and health: a critical review. Nutr Today. 2015;50:117.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Carvalho VO, Guimarães GV, Carrara D, Bacal F, Bocchi EA. Validação da versão em português do Minnesota Living with Heart Failure Questionnaire. Arq Bras Cardiol. 2009;93:39–44.

    Article  PubMed  Google Scholar 

  24. Rohde LEP, Montera MW, Bocchi EA, Clausell NO, de Albuquerque DC, Rassi S, et al. Diretriz brasileira de insuficiência cardíaca crônica e aguda. Arq Bras Cardiol. 2018;111:436–539.

    PubMed  Google Scholar 

  25. De Castro Pereira CA, Sato T, Rodrigues SC. New reference values for forced spirometry in white adults in Brazil. J Bras Pneumol. 2007;33:397–406.

    Google Scholar 

  26. Graham BL, Steenbruggen I, Barjaktarevic IZ, Cooper BG, Hall GL, Hallstrand TS, et al. Standardization of spirometry 2019 update. An Official American Thoracic Society and European Respiratory Society Technical Statement. Am J Respir Crit Care Med. 2019;200:e70.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Mitchell C, Rahko PS, Blauwet LA, Canaday B, Finstuen JA, Foster MC, et al. Guidelines for performing a comprehensive transthoracic echocardiographic examination in adults: recommendations from the American Society of Echocardiography. J Am Soc Echocardiogr. 2019;32:1–64.

    Article  PubMed  Google Scholar 

  28. McDonagh TA, Metra M, Adamo M, Gardner RS, Baumbach A, Böhm M, et al. 2021 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure: Developed by the Task Force for the diagnosis and treatment of acute and chronic heart failure of the European Society of Cardiology (ESC) With the special contribution of the Heart Failure Association (HFA) of the ESC. Rev Esp Cardiol (Engl Ed). 2022;75:523.

    PubMed  Google Scholar 

  29. Arcuri JF, Borghi-Silva A, Labadessa IG, Sentanin AC, Candolo C, Di Lorenzo VAP. Validity and reliability of the 6-minute step test in healthy individuals: a cross-sectional study. Clin J Sport Med. 2016;26:69–75.

    Article  PubMed  Google Scholar 

  30. Salles Albuquerque V, Dal Corso S, Pereira do Amaral D, Medina Dutrade Oliveira T, Fonseca Souza G, Naara Silva de Souza R, et al. Normative values and reference equation for the six-minute step test to evaluate functional exercise capacity: a multicenter study. J Bras Pneumol. 2022. https://doi.org/10.36416/1806-3756/e20210511.

    Article  Google Scholar 

  31. Anderson TW, Theodore W. An introduction to multivariate statistical analysis. 2003;721. Available from: https://www.wiley.com/en-us/An+Introduction+to+Multivariate+Statistical+Analysis%2C+3rd+Edition-p-9780471360919.

  32. Maldonado G, Greenland S. Simulation study of confounder-selection strategies. Am J Epidemiol. 1993;138:923–36. https://doi.org/10.1093/oxfordjournals.aje.a116813.

    Article  CAS  PubMed  Google Scholar 

  33. Cohen J. Statistical power analysis for the behavioral sciences. Stat Power Anal Behav Sci. 2013. https://doi.org/10.4324/9780203771587.

    Article  Google Scholar 

  34. JASP—Free and User-Friendly Statistical Software (version 0.18.2). Available from: https://jasp-stats.org/.

  35. Roh J, Hill JA, Singh A, Valero-Muñoz M, Sam F. Heart failure with preserved ejection fraction: heterogeneous syndrome, diverse preclinical models. Circ Res. 2022;130:1906–25.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Sullivan MJ, Hawthorne MH. Exercise intolerance in patients with chronic heart failure. Prog Cardiovasc Dis. 1995;38:1–22.

    Article  CAS  PubMed  Google Scholar 

  37. Tucker WJ, Haykowsky MJ, Seo Y, Stehling E, Forman DE. Impaired exercise tolerance in heart failure: role of skeletal muscle morphology and function. Curr Heart Fail Rep. 2018;15:323–31.

    Article  PubMed  PubMed Central  Google Scholar 

  38. Zizola C, Schulze PC. Metabolic and structural impairment of skeletal muscle in heart failure. Heart Fail Rev. 2013;18:623–30. https://doi.org/10.1007/s10741-012-9353-8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Bassi-Dibai D, Santos-de-Araújo AD, Dibai-Filho AV, de Azevedo LFS, Goulart CDL, Luz GCP, et al. Rehabilitation of individuals with diabetes mellitus: focus on diabetic myopathy. Front Endocrinol (Lausanne). 2022;13:869921.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Bilak JM, Gulsin GS, McCann GP. Cardiovascular and systemic determinants of exercise capacity in people with type 2 diabetes mellitus. Ther Adv Endocrinol Metab. 2021;12.

  41. Meyer K, Westbrook S, Schwaibold M, Hajric R, Lehmann M, Roskamm H. Cardiopulmonary determinants of functional capacity in patients with chronic heart failure compared with normals. Clin Cardiol. 1996;19:944–8.

    Article  CAS  PubMed  Google Scholar 

  42. Fuentes-Abolafio IJ, Stubbs B, Pérez-Belmonte LM, Bernal-López MR, Gómez-Huelgas R, Cuesta-Vargas AI. Physical functional performance and prognosis in patients with heart failure: a systematic review and meta-analysis. BMC Cardiovasc Disord. 2020;20:512.

    Article  PubMed  PubMed Central  Google Scholar 

  43. Kuziemski K, Słomiński W, Jassem E. Impact of diabetes mellitus on functional exercise capacity and pulmonary functions in patients with diabetes and healthy persons. BMC Endocr Disord. 2019;19:2.

    Article  PubMed  PubMed Central  Google Scholar 

  44. Ingle L, Reddy P, Clark AL, Cleland JGF. Diabetes lowers six-minute walk test performance in heart failure. J Am Coll Cardiol. 2006;47:1909–10.

    Article  PubMed  Google Scholar 

  45. Berisha-Muharremi V, Henein MY, Dini FL, Haliti E, Bytyçi I, Ibrahimi P, et al. Diabetes is the strongest predictor of limited exercise capacity in chronic heart failure and preserved ejection fraction (HFpEF). Front Cardiovasc Med. 2022;9:883615.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Rozenbaum Z, Granot Y, Sadeh B, Havakuk O, Arnold JH, Shimiaie J, et al. Sex differences in heart failure patients assessed by combined echocardiographic and cardiopulmonary exercise testing. Front Cardiovasc Med. 2023;10:1098395.

    Article  PubMed  PubMed Central  Google Scholar 

  47. Herdy AH, Uhlendorf D. Reference values for cardiopulmonary exercise testing for sedentary and active men and women. Arq Bras Cardiol. 2011;96:54–9.

    Article  PubMed  Google Scholar 

  48. Dimopoulou I, Tsintzas OK, Daganou M, Cokkinos DV, Tzelepis GE. Contribution of lung function to exercise capacity in patients with chronic heart failure. Respiration. 1999;66:144–9.

    Article  CAS  PubMed  Google Scholar 

  49. Echouffo-Tcheugui JB, Xu H, DeVore AD, Schulte PJ, Butler J, Yancy CW, et al. Temporal trends and factors associated with diabetes mellitus among patients hospitalized with heart failure: findings from get with the guidelines-heart failure registry. Am Heart J. 2016;182:9–20.

    Article  PubMed  Google Scholar 

  50. Zuin M, Rigatelli G, Battisti V, Costola G, Roncon L, Bilato C. Increased risk of acute myocardial infarction after COVID-19 recovery: a systematic review and meta-analysis. Int J Cardiol. 2023;372:138.

    Article  PubMed  Google Scholar 

  51. Chagué F, Boulin M, Eicher JC, Bichat F, Saint Jalmes M, Cransac-Miet A, et al. Impact of lockdown on patients with congestive heart failure during the coronavirus disease 2019 pandemic. ESC Hear Fail. 2020;7:4420.

    Article  Google Scholar 

  52. Caraballo C, Desai NR, Mulder H, Alhanti B, Wilson FP, Fiuzat M, et al. Clinical implications of the New York Heart Association Classification. J Am Hear Assoc Cardiovasc Cerebrovasc Dis. 2019;8:e014240.

    Google Scholar 

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Acknowledgements

To the patients who participated in the research. To the Coordination for the Improvement of Higher Education Personnel (CAPES), National Council for Scientific and Technological Development (CNPq) and São Paulo Research Foundation (FAPESP) for maintaining the postgraduate programs in Brazil. University Hospital of Federal University of São Carlos—SP-Brazil (HU-UFSCar) Brazilian Company of Hospital Services (EBSERH). Professor Ph.D. Audrey Borghi-Silva is CNPq Research Productivity Scholarship—Level 1B.

Funding

This work was supported by São Paulo Research Foundation (FAPESP Process 15/26501-1).

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Authors and Affiliations

Authors

Contributions

Study design: ADS, DB, IMD, CLG, RSM, JAM, GSS, PBS, MGR, SAP, AB. Conceptualization: ADS, DB, IMD, CLG, RSM, JAM, GSS, PBS, MGR, SAP, AB. Methodology: ADS, DB, IMD, CLG, RSM, JAM, GSS, PBS, MGR, SAP, AB. Data collection: ADS, DB, IMD, CLG, RSM, JAM, GSS, PBS, MGR, SAP, AB. Data analysis and interpretation: ADS, DB, IMD, CLG, RSM, JAM, GSS, PBS, MGR, SAP, AB. Initial manuscript writing: ADS, DB, IMD, CLG, RSM, JAM, GSS, PBS, MGR, SAP, AB. All the authors read and approved the final manuscript.

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Correspondence to Audrey Borghi-Silva.

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This study was approved by the Ethics Committee on Research of Universidade Federal de São Carlos (number 5.188.654).

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An informed consent was obtained from all the individuals included in the study. All participants agreed to publish.

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The authors do not have any relevant financial or nonfinancial interest to disclose. The authors declare that there is not any conflict of interest.

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Santos-de-Araújo, A.D., Bassi-Dibai, D., Dourado, I.M. et al. Type 2 diabetes mellitus negatively affects the functional performance of 6-min step test in chronic heart failure: a 3-year follow-up study. Diabetol Metab Syndr 16, 229 (2024). https://doi.org/10.1186/s13098-024-01464-z

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