Diabetes Is the Strongest Predictor of Limited Exercise Capacity in Chronic Heart Failure and Preserved Ejection Fraction (HFpEF)

Background and Aim: Type 2 diabetes mellitus (T2DM) is a known risk factor in patients with heart failure (HF), but its impact on phenotypic presentations remains unclear. This study aimed to prospectively examine the relationship between T2DM and functional exercise capacity, assessed by the 6-min walk test (6-MWT) in chronic HF.

Methods: We studied 344 chronic patients with HF (mean age 61 ± 10 years, 54% female) in whom clinical, biochemical, and anthropometric data were available and all patients underwent an echo-Doppler study and a 6-MWT on the same day. The 6-MWT distance divided the cohort into; Group I: those who managed ≤ 300 m and Group II: those who managed >300 m. Additionally, left ventricular (LV) ejection fraction (EF), estimated using the modified Simpson's method, classified patients into HF with preserved EF (HFpEF) and HF with reduced EF (HFrEF).

Results: The results showed that 111/344 (32%) patients had T2DM, who had a higher prevalence of arterial hypertension (p = 0.004), higher waist/hips ratio (p = 0.041), higher creatinine (p = 0.008) and urea (p = 0.003), lower hemoglobin (p = 0.001), and they achieved shorter 6-MWT distance (p < 0.001) compared with those with no T2DM. Patients with limited exercise (<300 m) had higher prevalence of T2DM (p < 0.001), arterial hypertension (p = 0.004), and atrial fibrillation (p = 0.001), higher waist/hips ratio (p = 0.041), higher glucose level (p < 0.001), lower hemoglobin (p < 0.001), larger left atrium (LA) (p = 0.002), lower lateral mitral annular plane systolic excursion (MAPSE) (p = 0.032), septal MAPSE (p < 0.001), and tricuspid annular plane systolic excursion (TAPSE) (p < 0.001), compared with those performing >300 m. In the cohort as a whole, multivariate analysis, T2DM (p < 0.001), low hemoglobin (p = 0.008), atrial fibrillation (p = 0.014), and reduced septal MAPSE (p = 0.021) independently predicted the limited 6-MWT distance.

In patients with HFpEF, diabetes [6.083 (2.613–14.160), p < 0.001], atrial fibrillation [6.092 (1.769–20.979), p = 0.002], and septal MAPSE [0.063 (0.027–0.184), p = 0.002], independently predicted the reduced 6-MWT, whereas hemoglobin [0.786 (0.624–0.998), p = 0.049] and TAPSE [0.462 (0.214–0.988), p = 0.041] predicted it in patients with HFrEF.

Conclusion: Predictors of exercise intolerance in patients with chronic HF differ according to LV systolic function, demonstrated as EF. T2DM seems the most powerful predictor of limited exercise capacity in patients with HFpEF.

Introduction

Heart failure (HF) has become a major public health problem in the past decades (1, 2), and it remains a clinical syndrome with poor prognosis in both patients with reduced ejection fraction (HFrEF) and preserved (HFpEF) (3–6). In those patients, exercise intolerance is one of the most important clinical manifestations and has been shown to be a strong predictor of all-cause mortality (7). Assessment of exercise capacity using the 6-min walk test (6-MWT) has been used as a simple, reproducible, and inexpensive method (8, 9). Indeed, 6-MWT has been shown to have a good correlation with objective measures of exercise tolerance, such as exercise duration and oxygen uptake at peak exercise (10). Type 2 diabetes mellitus (T2DM) is one of the most frequently seen risk factors and comorbidities in patients with congestive heart failure (CHF) (11, 12), and it adversely affects outcomes in these patients (13, 14). The impact of T2DM on different phenotypic presentations of HF, especially in patients with HF and preserved ejection fraction (HFpEF), remains unclear (15, 16). Impaired energy metabolism and muscle fiber-type switches (17, 18) found in T2DM, similar to what is seen in CHF, have been previously shown. Accordingly, it can be assumed that T2DM may further reduce the aerobic capacity of patients with HF as a potential mechanism for the known limited exercise tolerance, as has been previously suggested (16, 19, 20). However, the evidence regarding the direct relationship between 6-MWT and phenotypic type of HF, reduced EF (HFrEF), and preserved (HFpEF), remains lacking. In this study, we aimed to investigate the direct impact of T2DM on the reduced 6-MWT distance in patients with CHF due to various presentations, HFrEF and HFpEF.

Methods

Study Population

We studied 344 (mean age 61 ± 10 years, 54% female) patients with the clinical diagnosis of symptomatic CHF, and New York Heart Association (NYHA) functional class I–III, secondary to ischemic or non-ischemic etiology, based on the current definitions (21). Patients were referred to the Clinic of Cardiology, University Clinical Centre of Kosovo, between May 2013 and September 2017. At the time of the study, all patients were on optimum HF medications, optimized at least 2 weeks prior to enrollment. Based on patient's symptoms and renal function: 85% were receiving ACE inhibitors or ARB, 76% beta-blockers, 11% calcium-blockers, 8% digoxin, 54% spironolactone, and 58% diuretics. Of the enrolled patients, 45% had ischemic etiology, 38% hypertensive, and 17% had unknown etiology. Furthermore, 17% of the included patients were in atrial fibrillation. Patients with clinical evidence for cardiac decompensation (NYHA class IV, those with peripheral edema), limited physical activity due to factors other than cardiac symptoms (e.g., arthritis), severe mitral regurgitation, more than mild renal failure (in patients with raised creatinine, the glomerular filtration rate (GFR) was measured and patients with values <60 ml/min/1.73 m² were excluded), chronic obstructive pulmonary disease or those with recent acute coronary syndrome, stroke, or anemia were excluded from the study. Type 2 DM was defined as a fasting blood glucose level ≥7.0 mmol/L, a glycohemoglobin A1c (HbA1c) level ≥6.5%, and/or the need for oral hypoglycemic medications or insulin. All patients gave written informed consent to participate in the study, which was approved by the local Ethics Committee.

Data Collection

Detailed history and clinical assessment were obtained in all patients, in whom routine biochemical tests were also performed, such as hemoglobin, lipid profile, blood glucose level, and kidney function tests. Estimated body mass index (BMI) was calculated from weight and height measurements. Body surface area (BSA) was calculated using the Du Bois formula: BSA (m²) = 0.007184 × (height in cm) ^0.725 × (weight in kg)^0.425 (22). Waist and hip measurements were also made and a waist/hips ratio was calculated.

Echocardiographic Examination

A single operator performed all echocardiographic examinations using a Philips Intelligent E-33 system with a multi-frequency transducer, and harmonic imaging as appropriate. Images were obtained with the patient in the left lateral decubitus position and during quiet expiration. Measurements of interventricular septal thickness, posterior wall thickness, and LV dimensions were made at end-diastole and end-systole, as recommended by the American Society of Echocardiography (23).

Left ventricular volumes and EF were calculated from the apical 2 and 4 chamber views using the modified Simpson's method. Ventricular long axis motion was studied by placing the M-mode cursor at the lateral and septal angles of the mitral annulus and the lateral angle of the tricuspid annulus. The total amplitude of ventricular long-axis motion was measured as previously described (24) from peak inward to peak outward points. The indices were registered as lateral and septal mitral annular plane systolic excursion (MAPSE) and tricuspid annular plane systolic excursion (TAPSE). LV and right ventricular (RV) long-axis myocardial velocities were also studied using the Doppler myocardial imaging technique. From the apical 4-chamber view, longitudinal velocities were recorded with the sample volume placed at the basal part of LV lateral and septal segments as well as the RV free wall. Systolic (s′) as well as early and late (e′ and a′) diastolic myocardial velocities were measured with the gain optimally adjusted. A mean value of lateral and septal LV velocities was calculated. The left atrial diameter was measured from aortic root recordings with the M-mode cursor positioned at the level of the aortic valve leaflets.

Diastolic LV and RV functions were assessed from filling velocities using spectral pulsed wave Doppler with the sample volume positioned at the tips of the mitral and tricuspid valve leaflets, respectively, during a brief apnea. Peak LV and RV early (E wave) and late (A wave) diastolic velocities were measured and E/A ratios were calculated. E wave deceleration time (DT) was also measured from the peak E wave to the end of its deceleration. The E/e′ ratio was calculated from the trans-mitral E wave and mean lateral and septal segments myocardial e′ wave velocities. The LV filling pattern was considered “restrictive” when the E/A ratio was >2.0, the E wave deceleration time <140 ms, and the left atrium (LA) dilated >40 mm in transverse diameter (25). Total LV filling time was measured from the onset of the E wave to the end of the A wave and ejection time from the onset to the end of the aortic Doppler flow velocity.

Mitral regurgitation severity was assessed by color and continuous wave Doppler and was graded as mild, moderate, or severe according to the relative jet area to that of the LA as well as the flow velocity profile, in line with the recommendations of the American and European Society of Echocardiography (26, 27). Similarly, tricuspid regurgitation was assessed by color Doppler and continuous-wave Doppler. Retrograde trans-tricuspid pressure drop >35 mmHg was taken as evidence for pulmonary hypertension (27, 28). All M-mode and Doppler recordings were made at a fast speed of 100 mm/s with a superimposed ECG (lead II).

6-Min Walk Test

Within 24 h of the echocardiographic examination, a 6-MWT was performed on a level hallway surface, administered by a specialized nurse who was blinded to the results of the echocardiogram. According to the method of Gyatt et al. (29), patients were informed of the purpose and protocol of the 6 MWT, which was conducted in a standardized fashion while patients were on their regular medications (30, 31). A 15-m flat, obstacle-free corridor was used and patients were instructed to walk as far as they can, turning 180 degrees after they have reached the end of the corridor, during the allocated time of 6 min. Patients walked unaccompanied so as not to influence their walking speed. At the end of the 6 min, the supervising nurse measured the total distance walked by the patient.

Statistical Analysis

Data are presented as mean ± SD or proportions (% of patients). Continuous data were compared with two-tailed unpaired Student's t-test and discrete data with a chi-square test. Correlations were tested with Pearson's coefficients. Predictors of the 6MWT distance were identified with univariate analysis, and multivariate logistic regression was performed using the step-wise method. A significant difference was defined as p < 0.05 (two-tailed). Patients were divided according to their ability to walk >300 m into good and limited exercise performance groups, and were compared using unpaired Student's t-test. Additionally, patients with HFpEF (LVEF ≥ 40%) were compared with those with HFrEF (LVEF < 40%) using the unpaired t-test. Due to the possible interaction of age with echocardiographic parameters, we used the general linear model to compare age-adjusted mean values of echocardiographic indices between groups.

Results

Patients With HF and T2DM vs. Patients With HF but No T2DM

Patients with HF and T2DM had a higher prevalence of arterial hypertension (p = 0.004), higher waist/hips ratio (p = 0.041), higher creatinine (p = 0.008), urea (p = 0.003), and lower hemoglobin (p = 0.001), and completed the 6-MWT for a shorter distance (<0.001) than those with HF but no T2DM (Table 1; Figure 1). The rest of the clinical indices and echocardiographic parameters were not different between groups (Table 2).

TABLE 1

Table 1. Clinical data in diabetic and non-diabetic patients with chronic heart failure (HF).

FIGURE 1

Figure 1. A 6-min walk test (6-MWT) distance in non-diabetic and diabetic patients with heart failure (HF).

TABLE 2

Table 2. Echocardiographic data in diabetic and non-diabetic patients with chronic HF.

Patients With Good vs. Limited 6 MWT Performance

Patients with limited exercise capacity had a higher prevalence of T2DM (p < 0.001), arterial hypertension (p = 0.004), and atrial fibrillation (p = 0.001), a higher waist/hips ratio (p = 0.041), a level of fasting glucose (p < 0.001), and a lower level of hemoglobin (p < 0.001), compared with those with good exercise capacity. In addition, they had larger LA (p = 0.002), reduced lateral MAPSE (p = 0.032), septal MAPSE (p < 0.001), and TAPSE (p < 0.001), compared to patients with good 6-MWT performance. The rest of the clinical and echocardiographic indices were not different between subgroups (Tables 3, 4).

TABLE 3

Table 3. Clinical and biochemical data in patients with limited exercise vs. good exercise capacity.

TABLE 4

Table 4. Echocardiographic data in patients with limited exercise vs. good exercise capacity (6-MWT distance).

Predictors of Limited 6-MWT Distance in All Patients

In the univariate analysis model, T2DM (p < 0.001), low hemoglobin level (p < 0.001), atrial fibrillation (p < 0.001), and NYHA class (p = 0.008) predicted limited 6-MWT distance, as did enlarged LA (p = 0.003), increased E wave velocity (p = 0.019), raised E/e′ (p = 0.028), reduced lateral MAPSE (p = 0.033) septal MAPSE (p < 0.001), TAPSE (p < 0.001) and septal a′ and s′ (p = 0.032 and p = 0.041, respectively), and increased E/e′ (p = 0.028). In multivariate analysis [odds ratio (OR) 95% confidence interval (CI)], only diabetes [3.366 (1.907–5.939), p < 0.001], low hemoglobin [0.847 (0.729–0.985), p = 0.031], atrial fibrillation [2.684 (1.273–5.657), p = 0.009], and reduced septal MAPSE [0.308 (0.125–0.759), p = 0.010], independently predicted the limited 6-MWT distance (Table 5).

TABLE 5

Table 5. Predictors of limited exercise in All patients with HF.

Predictors of Limited 6 MWT Distance in HFpEF

Type 2 diabetes mellitus (p < 0.001), low hemoglobin (p = 0.022), atrial fibrillation (p = 0.020), NYHA class (p = 0.005), LA (p = 0.03), septal MAPSE (p < 0.001), and lateral MAPSE (p = 0.044) predicted limited 6-MWT distance in HFpEF. In multivariate analysis [OR 95% CI], only diabetes [6.083 (2.613–14.160), p < 0.001], atrial fibrillation [6.092 (1.769–20.979), p = 0.004], and septal MAPSE [0.063 (0.027–0.184), p = 0.002], independently predicted the limited 6-MWT distance in HFpEF (Tables 6, 7).

TABLE 6

Table 6. Univariate predictors of limited exercise capacity (6-MWT < 300 m) in patients with non-reduced and those with reduced left ventricular ejection fraction (LVEF).

TABLE 7

Table 7. Multivariate predictors of limited exercise capacity (6-MWT <300 m) in patients with non-reduced and those with reduced LVEF.

Predictors of Limited 6 MWT Distance in Patients With HFrEF

In univariate analysis, low hemoglobin (p = 0.001), reduced TAPSE (p = 0.001), and enlarged LA (p = 0.043) predicted limited 6-MWT distance in patients with HFrEF. In multivariate analysis, only low hemoglobin [0.786 (0.624–0.998), p = 0.049] and reduced TAPSE [0.462 (0.214–0.988), p = 0.041] independently predicted the limited 6-MWT distance in HFrEF (Tables 6, 7).

Discussion

Findings

Heart failure patients with limited exercise capacity had a higher prevalence of T2DM, arterial hypertension, and atrial fibrillation, compared with those with good exercise capacity. They also had a higher waist/hips ratio, lower hemoglobin, a larger LA, and compromised LV and RV long-axis systolic function. Patients with combined HF and T2DM had a higher prevalence of arterial hypertension, a higher waist/hips ratio, more compromised renal function, lower hemoglobin, and a shorter 6-MWT distance, compared with those with HF with no T2DM. Multivariate analysis showed diabetes, lowered hemoglobin level, atrial fibrillation, and reduced LV long-axis function as independent predictors of limited exercise capacity in patients with HF.

While the above common knowledge on the relationship between atherosclerosis risk factors and HF is confirmed in our patients, their impact on predicting exercise capacity differed significantly according to LVEF. In patients with reduced LVEF, low hemoglobin and compromised RV long-axis systolic function were the two independent predictors of exercise capacity. However, in patients with LV preserved EF, T2DM, low hemoglobin level, atrial fibrillation, higher NYHA class, and compromised LV long-axis systolic function were the respective predictors.

Data Interpretation

Exercise intolerance is the main symptom in patients with HF, regardless of LVEF (32, 33). In these patients, different echocardiographic indices have been shown as important predictors of exercise capacity, particularly raised LV filling pressures (34–42). Such a relationship can be explained on the basis of reduced stroke volume and pulmonary venous hypertension (43). This is, however, only one explanation of exercise intolerance in HF. Our results provide a clearer image as to the potential mechanisms involved in reduced exercise capacity in patients with HF, when they are classified according to EF. HF with reduced EF is commonly caused by ischemic myopathy that involves both ventricles with their impact on cardiac output and kidney function (44). Indeed, our findings confirm that, having shown that low hemoglobin (45) and compromised RV systolic function (46) are the two main predictors of limited exercise. However, in patients with preserved LVEF, the scenario differs having shown that T2DM and atrial fibrillation are two additional predictors of exercise capacity. Atrial fibrillation is a very common finding in HFpEF. Most such patients are known to have long-standing hypertensive LV disease and left atrial enlargement with its known complications (47). Atrial fibrillation loses the atrial systolic filling component of the LV, hence compromising overall stroke volume with its impact on exercise capacity (48). T2DM, on the other hand, enhances the atherosclerosis pathology at both main coronary arteries level as well as microcirculation with resulting subendocardial fibrosis and LV cavity stiffness, raising the filling pressures and eventually causing atrial fibrillation (49). Through the same atherosclerotic pathophysiology, T2DM also impacts the peripheral circulation and, over the years, causes peripheral neuropathy. Although our analysis identified individual independent predictors of the limited exercise capacity in patients with HF, it must be mentioned that the pathomechanisms are closely related, particularly T2DM and atrial fibrillation, and their impact on LV myocardial function with its consequence on left atrial enlargement, atrial fibrillation, and its complications.

Limitations

The main limitation of our study is that we did not assess the response of echocardiographic measurements to exercise, at the time of symptoms development. However, the main objective of the study was to identify predictors of ordinary walking exercise limitations rather than a heavy exercise in patients with HF. The lack of left atrial pressure invasive measurements is another limitation, but the study was based on conventional Doppler measurements, which have been shown to be reproducible and correlate closely with invasive pressure measurements (50). We did not have myocardial deformation measurements in our cohort, which might have altered the results.

Clinical Implications

Type 2 diabetes mellitus has a significant impact on exercise intolerance in patients with HFpEFEF. While the cardiac pump function looks better preserved than in patients with HFrEF, the multi-system complications associated with diabetes should be acknowledged, particularly myocardial microcirculation and peripheral arterial disease as well as peripheral neuropathic complications.

Conclusion

Predictors of exercise intolerance in patients with chronic HF differ according to LV systolic function, judged as EF. T2DM seems the most powerful predictor of limited exercise capacity in patients with HFpEF.

Data Availability Statement

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author/s.

Ethics Statement

The studies involving human participants were reviewed and approved by Ethical Committee, Medical Faculty, University of Prishtina, Prishtina, Kosovo. The patients/participants provided their written informed consent to participate in this study.

Author Contributions

VB-H, MH, SE, and GB contributed to conception and design of the study. IB, PI, EH, AP, RT, and AB organized the database. GB, PI, and IB performed the statistical analysis. VB-M wrote the first draft of the manuscript. GB, IB, MH, and SE wrote sections of the manuscript. All authors contributed to manuscript revision, read, and approved the submitted version.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher's Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

References

1. Roger VL. Epidemiology of heart failure: a contemporary perspective. Circ Res. (2021) 128:1421–34. doi: 10.1161/CIRCRESAHA.121.318172

PubMed Abstract | CrossRef Full Text | Google Scholar

2. Tsao CW, Aday AW, Almarzooq ZI, Alonso A, Beaton AZ, Bittencourt MS, et al. Heart disease and stroke statistics-2022 update: a report from the American Heart Association. Circulation. (2022) 145:e153–639. doi: 10.1161/CIR.0000000000001052

PubMed Abstract | CrossRef Full Text | Google Scholar

3. Ho KK, Anderson KM, Kannel WB, Grossman W, Levy D. Survival after onset of congestive heart failure in Framingham Heart Study subjects. Circulation. (1993) 88:107–15. doi: 10.1161/01.CIR.88.1.107

PubMed Abstract | CrossRef Full Text | Google Scholar

4. Davies M, Hobbs F, Davis R, Kenkre J, Roalfe AK, Hare R, et al. Prevalence of left-ventricular systolic dysfunction and heart failure in the Echocardiographic Heart of England Screening study: a population based study. Lancet. (2001) 358:439–45. doi: 10.1016/S0140-6736(01)05620-3

PubMed Abstract | CrossRef Full Text | Google Scholar

5. Bytyçi I, Bajraktari G. Mortality in heart failure patients. Anatol J Cardiol. (2015) 15:63–8. doi: 10.5152/akd.2014.5731

PubMed Abstract | CrossRef Full Text | Google Scholar

6. Chen L, Huang Z, Zhao X, Liang J, Lu X, He Y, et al. Predictors and mortality for worsening left ventricular ejection fraction in patients with HFpEF. Front Cardiovasc Med. (2022) 9:820178. doi: 10.3389/fcvm.2022.820178

PubMed Abstract | CrossRef Full Text | Google Scholar

7. Mancini DM, Eisen H, Kussmaul W, Mull R, Edmunds LH Jr, Wilson JR. Value of peak exercise oxygen consumption for optimal timing of cardiac transplantation in ambulatory patients with heart failure. Circulation. (1991) 83:778–86. doi: 10.1161/01.CIR.83.3.778

PubMed Abstract | CrossRef Full Text | Google Scholar

8. Faggiano P, D'Aloia A, Gualeni A, Brentana L, Dei Cas L. The 6minute walking test in chronic heart failure: indications, interpretation and limitations from a review of the literature. Eur J Heart Fail. (2004) 6:687–91. doi: 10.1016/j.ejheart.2003.11.024

PubMed Abstract | CrossRef Full Text | Google Scholar

9. Ingle L, Shelton RJ, Rigby AS, Nabb S, Clark AL, Cleland JG. The reproducibility and sensitivity of the 6-min walk test in elderly patients with chronic heart failure. Eur Heart J. (2005) 26:1742–51. doi: 10.1093/eurheartj/ehi259

PubMed Abstract | CrossRef Full Text | Google Scholar

10. Ingle L, Goode K, Rigby AS, Cleland JG, Clark AL. Predicting peak oxygen uptake from 6-min walk test performance in male patients with left ventricular systolic dysfunction. Eur J Heart Fail. (2006) 8:198–202. doi: 10.1016/j.ejheart.2005.07.008

PubMed Abstract | CrossRef Full Text | Google Scholar

11. Dries DL, Sweitzer NK, Drazner MH, Stevenson LW, Gersh BJ. Prognostic impact of diabetes mellitus in patients with heart failure according to the etiology of left ventricular systolic dysfunction. J Am Coll Cardiol. (2001) 38:421–8. doi: 10.1016/S0735-1097(01)01408-5

PubMed Abstract | CrossRef Full Text | Google Scholar

12. Varela-Roman A, Grigorian Shamagian L, Barge Caballero E, Mazon Ramos P, Rigueiro Veloso P, Gonzalez-Juanatey JR. Influence of diabetes on the survival of patients hospitalized with heart failure: a 12-year study. Eur J Heart Fail. (2005) 7:859–64. doi: 10.1016/j.ejheart.2005.01.017

PubMed Abstract | CrossRef Full Text | Google Scholar

13. Kenny HC, Abel ED. Heart failure in type 2 diabetes mellitus. Circ Res. (2019) 124:121–41. doi: 10.1161/CIRCRESAHA.118.311371

PubMed Abstract | CrossRef Full Text | Google Scholar

14. Owan TE, Hodge DO, Herges RM, Jacobsen SJ, Roger VL, Redfield MM, et al. Trends in prevalence and outcome of heart failure with preserved ejection fraction. N Engl J Med. (2006) 355:251–9. doi: 10.1056/NEJMoa052256

PubMed Abstract | CrossRef Full Text | Google Scholar

15. Mgbemena O, Zhang Y, Velarde G. Role of diabetes mellitus in heart failure with preserved ejection fraction: a review article. Cureus. (2021) 13:e19398. doi: 10.7759/cureus.19398

PubMed Abstract | CrossRef Full Text | Google Scholar

16. Liu C, Lai Y, Guan T, Zhan J, Pei J, Wu D, et al. Associations of ATP-sensitive potassium channel's gene polymorphisms with type 2 diabetes and related cardiovascular phenotypes. Front Cardiovasc Med. (2022) 9:816847. doi: 10.3389/fcvm.2022.816847

PubMed Abstract | CrossRef Full Text | Google Scholar

17. Mogensen M, Sahlin K, Fernstrom M, Glintborg D, Vind BF, Beck-Nielsen H, et al. Mitochondrial respiration is decreased in skeletal muscle of patients with type 2 diabetes. Diabetes. (2007) 56:1592–9. doi: 10.2337/db06-0981

PubMed Abstract | CrossRef Full Text | Google Scholar

18. Oberbach A, Bossenz Y, Lehmann S, Niebauer J, Adams V, Paschke R, et al. Altered fiber distribution and fiber-specific glycolytic and oxidative enzyme activity in skeletal muscle of patients with type 2 diabetes. Diabetes Care. (2006) 29:895–900. doi: 10.2337/diacare.29.04.06.dc05-1854

PubMed Abstract | CrossRef Full Text | Google Scholar

19. Tibb AS, Ennezat PV, Chen JA, Haider A, Gundewar S, Cotarlan V, et al. Diabetes lowers aerobic capacity in heart failure. J Am Coll Cardiol. (2005) 46:930–1. doi: 10.1016/j.jacc.2005.06.001

PubMed Abstract | CrossRef Full Text | Google Scholar

20. Guazzi M, Brambilla R, Pontone G, Agostoni P, Guazzi MD. Effect of non-insulin-dependent diabetes mellitus on pulmonary function and exercise tolerance in chronic congestive heart failure. Am J Cardiol. (2002) 89:191–7. doi: 10.1016/S0002-9149(01)02199-3

PubMed Abstract | CrossRef Full Text | Google Scholar

21. Bozkurt B, Coats AJS, Tsutsui H, Abdelhamid CM, 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: Endorsed by the Canadian Heart Failure Society, Heart Failure Association of India, Cardiac Society of Australia and New Zealand, and Chinese Heart Failure Association. Eur J Heart Fail. (2021) 23:352–80. doi: 10.1002/ejhf.2115

PubMed Abstract | CrossRef Full Text | Google Scholar

22. Du Bois D, Du Bois EF. A formula to estimate the approximate surface area if height and weight be known. Arch Intern Med. (1916) 17:863–71. doi: 10.1001/archinte.1916.00080130010002

PubMed Abstract | CrossRef Full Text | Google Scholar

23. Cheitlin MD, Armstrong WF, Aurigemma GP, Beller GA, Bierman FZ, et al. A report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines (ACC/AHA/ASE Committee to Update the 1997 Guidelines for the Clinical Application of Echocardiography). Circulation. (2003) 108:1146–62. doi: 10.1016/S0894-7317(03)00685-0

PubMed Abstract | CrossRef Full Text | Google Scholar

24. Höglund C, Alam M, Thorstrand C. Atrioventricular valve plane displacement in healthy persons. An echocardiographic study. Acta Med Scand. (1988) 224: 557–62. doi: 10.1111/j.0954-6820.1988.tb19626.x

PubMed Abstract | CrossRef Full Text | Google Scholar

25. Appleton CP, Hatle LK, Popp RL. Relation of transmitral flow velocity patterns to left ventricular diastolic function: new insights from a combined hemodynamic and Doppler echocardiographic study. J Am Coll Cardiol. (1988) 12:426–40. doi: 10.1016/0735-1097(88)90416-0

PubMed Abstract | CrossRef Full Text | Google Scholar

26. Zoghbi WA, Adams D, Bonow RO, Enriquez-Sarano M, Foster E, Grayburn PA, et al. Recommendations for noninvasive evaluation of native valvular regurgitation: a report from the American Society of Echocardiography Developed in Collaboration with the Society for Cardiovascular Magnetic Resonance. J Am Soc Echocardiogr. (2017) 30:303–71. doi: 10.1016/j.echo.2017.01.007

PubMed Abstract | CrossRef Full Text | Google Scholar

27. Galderisi M, Henein MY., D'hooge J, Sicari R, Badano LP, Zamorano JL, et al. Recommendations of the European Association of Echocardiography: how to use echo-Doppler in clinical trials: different modalities for different purposes. Eur J Echocardiogr. (2011) 12:339–53. doi: 10.1093/ejechocard/jer051

PubMed Abstract | CrossRef Full Text | Google Scholar

28. Gardin JM, Adams DB, Douglas PS, Feigenbaum H, Forst DH, Fraser AG, et al. Recommendations for a standardized report for adult transthoracic echocardiography: a report from the American Society of Echocardiography's Nomenclature and Standards Committee and Task Force for a Standardized Echocardiography Report. J Am Soc Echocardiogr. (2002) 15:275–90. doi: 10.1067/mje.2002.121536

PubMed Abstract | CrossRef Full Text | Google Scholar

29. Guyatt GH, Sullivan MJ, Thompson PJ, Fallen EL, Pugsley SO, Taylor DW, Berman LB. The 6-minute walk test: a new measure of exercise capacity in patients with chronic heart failure. Can Med Assoc J. (1985) 132: 919-23.-

PubMed Abstract | Google Scholar

30. Guyatt GH, Thompson PJ, Berman LB, Sullivan MJ, Townsend M, Jones NL, et al. How should we measure function in patients with chronic heart and lung disease? J Chronic Dis. (1985) 28:517–24. doi: 10.1016/0021-9681(85)90035-9

PubMed Abstract | CrossRef Full Text | Google Scholar

31. Ingle L, Rigby AS, Nabb S, Jones PK, Clark AL, Cleland JG. Clinical determinants of poor six-minute walk test performance in patients with left ventricular systolic dysfunction and no major structural heart disease. Eur J Heart Fail. (2006) 8:321–5. doi: 10.1016/j.ejheart.2005.08.006

PubMed Abstract | CrossRef Full Text | Google Scholar

32. Nadruz W, West E, Sengelov M, Santos M, Groarke JD, Forman DE. Prognostic value of cardiopulmonary exercise testing in heart failure with reduced, midrange, and preserved ejection fraction. J Am Heart Assoc. (2017) 6:11. doi: 10.1161/JAHA.117.006000

PubMed Abstract | CrossRef Full Text | Google Scholar

33. Batalli A, Ibrahimi P, Bytyçi I, Ahmeti A, Haliti E, Elezi S, et al. Different determinants of exercise capacity in HFpEF compared to HFrEF. Cardiovasc Ultrasound. (2017) 15:12. doi: 10.1186/s12947-017-0103-x

PubMed Abstract | CrossRef Full Text | Google Scholar

34. Bajraktari G, Elezi S, Berisha V, Lindqvist P, Rexhepaj N, Henein MY. Left ventricular asynchrony and raised filling pressure predict limited exercise performance assessed by 6 minute walk test. Int J Cardiol. (2011) 146:385–9. doi: 10.1016/j.ijcard.2009.07.018

PubMed Abstract | CrossRef Full Text | Google Scholar

35. Ohara T, Iwano H, Thohan V, Kitzman DW, Upadhya B, Pu M, et al. Role of diastolic function in preserved exercise capacity in patients with reduced ejection fractions. J Am Soc Echocardiogr. (2015) 28:1184–93. doi: 10.1016/j.echo.2015.06.004

PubMed Abstract | CrossRef Full Text | Google Scholar

36. Bajraktari G, Batalli A, Poniku A, Ahmeti A, Olloni R, Hyseni V, et al. Left ventricular markers of global dyssynchrony predict limited exercise capacity in heart failure, but not in patients with preserved ejection fraction. Cardiovasc Ultrasound. (2012) 10:36. doi: 10.1186/1476-7120-10-36

PubMed Abstract | CrossRef Full Text | Google Scholar

37. Hasselberg NE, Haugaa KH, Sarvari SI, Gullestad L, Andreassen AK, Smiseth OA, et al. Left ventricular global longitudinal strain is associated with exercise capacity in failing hearts with preserved and reduced ejection fraction. Eur Heart J Cardiovasc Imaging. (2015) 16:217–24. doi: 10.1093/ehjci/jeu277

PubMed Abstract | CrossRef Full Text | Google Scholar

38. Mohammed SF, Borlaug BA, McNulty S, Lewis GD, Lin G, Zakeri R, et al. Resting ventricular-vascular function and exercise capacity in heart failure with preserved ejection fraction: a RELAX trial ancillary study. Circ Heart Fail. (2014) 7:580–9. doi: 10.1161/CIRCHEARTFAILURE.114.001192

PubMed Abstract | CrossRef Full Text | Google Scholar

39. Kosmala W, Rojek A, Przewlocka-Kosmala M, Mysiak A, Karolko B, Marwick TH. Contributions of nondiastolic factors to exercise intolerance in heart failure with preserved ejection fraction. J Am Coll Cardiol. (2016) 67:659–70. doi: 10.1016/j.jacc.2015.10.096

PubMed Abstract | CrossRef Full Text | Google Scholar

40. Bytyçi I, Bajraktari G, Ibrahimi P, Berisha G, Rexhepaj N, Henein MY. Left atrial emptying fraction predicts limited exercise performance in heart failure patients. Int J Cardiol Heart Vessel. (2014) 4:203–7. doi: 10.1016/j.ijchv.2014.04.002

PubMed Abstract | CrossRef Full Text | Google Scholar

41. Bytyci I, Bajraktari G, Fabiani I, Lindqvist P, Poniku A, Pugliese NR, et al. Left atrial compliance index predicts exercise capacity in patients with heart failure and preserved ejection fraction irrespective of right ventricular dysfunction. Echocardiography. (2019) 36:1045–53. doi: 10.1111/echo.14377

PubMed Abstract | CrossRef Full Text | Google Scholar

42. Abe T, Yokota T, Fukushima A, Kakutani N, Katayama T, Shirakawa R, et al. Type 2 diabetes is an independent predictor of lowered peak aerobic capacity in heart failure patients with non-reduced or reduced left ventricular ejection fraction. Cardiovasc Diabetol. (2020) 19:142. doi: 10.1186/s12933-020-01114-4

PubMed Abstract | CrossRef Full Text | Google Scholar

43. Pugliese NR, Mazzola M, Fabiani I, Gargani L, De Biase N, Pedrinelli R, et al. Haemodynamic and metabolic phenotyping of hypertensive patients with and without heart failure by combining cardiopulmonary and echocardiographic stress test. Eur J Heart Fail. (2020) 22:458–68. doi: 10.1002/ejhf.1739

PubMed Abstract | CrossRef Full Text | Google Scholar

44. Damman K, Kjekshus J, Wikstrand J, Cleland JG, Komajda M, Wedel H, et al. Loop diuretics, renal function and clinical outcome in patients with heart failure and reduced ejection fraction. Eur J Heart Fail. (2016) 18:328–36. doi: 10.1002/ejhf.462

PubMed Abstract | CrossRef Full Text | Google Scholar

45. O'Meara E, Murphy C, McMurray JJ. Anemia and heart failure. Curr Heart Fail Rep. (2004) 1:176–82. doi: 10.1007/s11897-004-0006-7

PubMed Abstract | CrossRef Full Text | Google Scholar

46. Guazzi M, Dixon D, Labate V, Beussink-Nelson L, Bandera F, Cuttica MJ, Shah SJ. RV Contractile function and its coupling to pulmonary circulation in heart failure with preserved ejection fraction: stratification of clinical phenotypes and outcomes. JACC Cardiovasc Imaging. (2017) 10(10 Pt B):1211–21. doi: 10.1016/j.jcmg.2016.12.024

PubMed Abstract | CrossRef Full Text | Google Scholar

47. Uijl A, Veenis JF, Brunner-La Rocca HP, van Empel V, Linssen GCM, Asselbergs FW, et al. Clinical profile and contemporary management of patients with heart failure with preserved ejection fraction: results from the CHECK-HF registry. Neth Heart J. (2021) 29:370–6. doi: 10.1007/s12471-020-01534-7

PubMed Abstract | CrossRef Full Text | Google Scholar

48. Zakeri R, Borlaug BA, McNulty SE, Mohammed SF, Lewis GD, Semigran MJ, et al. Impact of atrial fibrillation on exercise capacity in heart failure with preserved ejection fraction: a RELAX trial ancillary study. Circ Heart Fail. (2014) 7:123–30. doi: 10.1161/CIRCHEARTFAILURE.113.000568

PubMed Abstract | CrossRef Full Text | Google Scholar

49. Michniewicz E, Mlodawska E, Lopatowska P, Tomaszuk-Kazberuk A, Malyszko J. Patients with atrial fibrillation and coronary artery disease - Double trouble. Adv Med Sci. (2018) 63:30–5. doi: 10.1016/j.advms.2017.06.005

PubMed Abstract | CrossRef Full Text | Google Scholar

50. Redfield MM. Heart Failure with Preserved Ejection Fraction. N Engl J Med. (2016) 375:1868–77. doi: 10.1056/NEJMcp1511175

PubMed Abstract | CrossRef Full Text | Google Scholar