Central and peripheral exercise-related factors independently associated with presence of HFpEF

Central and Peripheral Determinants of Exercise Capacity in Heart Failure Patients With Preserved Ejection Fraction

Literature - Wolsk E, Kaye D, Komtebedde J et al. - JACC Heart Failure 2019; DOI: 10.1016/j.jchf.2019.01.006

Introduction and methods

The underlying mechanisms of reduced exercise capacity in patients with heart failure with preserved ejection fraction (HFpEF) remain unknown [1]. Studies have identified central factors (e.g. heart rate [HR], stroke volume [SV], filling pressures) and peripheral factors (e.g. oxygen use by skeletal muscle, BMI, renal function) that are involved in exercise intolerance in HFpEF. However, only a few studies used gold standard invasive measures to directly assess the relationship between symptoms and aerobic capacity [2-4]. Further, none of the studies included a control group exercising at the matched workload to the peak level of HFpEF patients.

This cohort study therefore assessed which hemodynamic variables (central and peripheral factors) were independently associated with presence of HFpEF (n=108) at peak exercise capacity, compared with healthy control individuals (n=42) exercising at the same workload to examine hemodynamic differences that were specific to the HFpEF phenotype, rather than being attributable to the workload achieved at peak exercise. In addition, a complementary analysis was performed, using changes relative to the workload performed at peak exercise for both groups.

Data were obtained from 3 of the largest prospective trials of patients with HFpEF (REDUCE LAP-HF and REDUCE LAP-HF I [5,6]) and healthy participants (HemReX [7]) aged ≥40 years (enrollment 2013-2016). The hemodynamic response was measured during ergometer exercise in supine position using right-sided heart catherization. Ergometer resistance was increased every 3 to 4 min with increments of either 20 W (patients with HFpEF) or 25 W (control subjects) until maximal effort was achieved. In HFpEF patients peak exercise was defined as maximal effort when they were not able to maintain 60 revolutions/min on the ergometer at a given workload and in controls as 4 min of exercise in a supine ergometer with lactate buildup and objective signs of severe exertion at a workload corresponding to 75% of maximal oxygen consumption.

The following hemodynamic data were examined: central venous pressure (CVP), mean pulmonary artery pressure (mPAP), pulmonary capillary wedge pressure (PCWP), cardiac output using thermodilution technique (CO), non-invasive systolic blood pressure (SBP), non-invasive diastolic blood pressure (DBP), non-invasive peripheral oxygen saturation (SaO2), and HR. In addition, mixed venous oxygen (SVO2) was sampled from the pulmonary artery. Other hemodynamic parameters were derived from these measured variables.

Main results

Changes in central and peripheral exercise factors at matched workload

  • Maximal workload achieved by patients with HFpEF (n=107) was 43±18 W, compared with a matched mean workload of 45±22 W in healthy subjects (n=72; data obtained at various workloads from a single healthy individual could be included more than once in the matched workload analysis) (P-difference=0.41).
  • From baseline to peak exercise, changes in HR (+29±19 beats/min vs. +29±16 beats/min, P=0.94), CO (+3,1±1.9 L/min vs. +5.4±2.0 L/min, P<0.0001), cardiac index (+1.5±0.9 L/min/m² vs. +2.9±1.1 L/min/m², P<0.0001), SV (+8±21 mL vs. +35±20 mL, P<0.0001; SV [indexed] (+4±10 mL/m² vs. +19±10 mL/m², P<0.0001), arteriovenous oxygen difference (Ca-VO₂) (+3.7±2.5 mL/dL vs. +4.9±1.5 mL/dL, P=0.0004), and SVR (-367±365 dyne x s/cm5 vs. -716±234 dyne x s/cm5, P<0.0001) were observed in HFpEF patients vs. healthy subjects at matched workload.

Variables associated with the presence of HFpEF during exercise at matched workload

  • After multivariable analysis, lower SV (coefficient -0.04, 95%CI: -0.06 to -0.01, P=0.001) and higher PCWP (coefficient 0.4, 95%CI: 0.2-0.6, P<0.0001) were significantly associated with the presence of HFpEF during matched workloads.
  • When BMI and age were added to the base model of hemodynamic variables, BMI was the only additional independent variable significantly associated with HFpEF. This variable increased the r² value of the model from 0.66 to 0.90.
  • Contribution of PCWP, SV and BMI to the presence of HFpEF was 47%, 12%, and 31%, respectively.

Comparison of central and peripheral exercise factors adjusted for workload

  • Mean peak workload achieved by patients with HFpEF was 45±13 W vs. 137±35 W (P<0.0001) in healthy subjects.
  • Except for mean arterial pressure, all hemodynamic variables assessed were significantly different between healthy individuals and HFpEF patients at peak exercise.
  • In multivariable analysis, an independent association was found between PCWP and the presence of HFpEF after adjustment for workload (coefficient: 28.0, 95%CI: 10.1-45.8, P=0.002). This factor explained 87% of the variability (P<0.0001). After BMI and age where added to the model, BMI was an additional variable that was associated with HFpEF (coefficient:0.52, 95%CI:0.02-1.03, P=0.04).

Conclusion

In this cohort study, 3 key factors (PCWP, BMI and SV) were independently associated with the presence of HFpEF, compared to healthy subjects during supine exercise at matched workloads. In total, these factors explained 90% of the difference in exercise capacity between patients with HFpEF and healthy controls, with PCWP as the strongest contributor. These data suggest that treatments reducing high left-sided heart filling pressure during exercise could improve exercise capacity and possibly prognosis in patients with HFpEF.

References

1. Ponikowski P, Voors AA, Anker SD, et al. 2016 ESC guidelines for the diagnosis and treatment of acute and chronic heart failure: the Task Force for the Diagnosis and Treatment of Acute and Chronic Heart Failure of the European Society of Cardiology (ESC) developed with the special contribution of the Heart Failure Association (HFA) of the ESC. Eur Heart J 2016;37:2129–200.

2. Reddy YNV, Olson TP, Obokata M, Melenovsky V, Borlaug BA. Hemodynamic correlates and diagnostic role of cardiopulmonary exercise testing in heart failure with preserved ejection fraction. J Am Coll Cardiol HF 2018.

3. Obokata M, Olson TP, Reddy YNV, Melenovsky V, Kane GC, Borlaug BA. Haemodynamics, dyspnoea, and pulmonary reserve in heart failure with preserved ejection fraction. Eur Heart J 2018;39: 2810–21.

4. Dhakal BP, Malhotra R, Murphy RM, et al. Mechanisms of exercise intolerance in heart failure with preserved ejection fraction: the role of abnormal peripheral oxygen extraction. Circ Heart Fail 2015;8:286–94.

5. Hasenfuß G, Hayward C, Burkhoff D, et al. A transcatheter intracardiac shunt device for heart failure with preserved ejection fraction (REDUCE LAP-HF): a multicentre, open-label, single-arm, phase 1 trial. Lancet 2016;387:1298–304.

6. Feldman T, Mauri L, Kahwash R, et al. A transcatheter interatrial shunt device for the treatment of heart failure with preserved ejection fraction (REDUCE LAP-HF I): a phase 2, randomized, sham-controlled trial. Circulation 2018;137: 364–75.

7. Wolsk E, Bakkestrøm R, Thomsen JH, et al. The influence of age on hemodynamic parameters during rest and exercise in healthy individuals. J Am Coll Cardiol HF 2017;5:337–46.

Find this article online at JACC Heart Failure

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