AIMS: Traditionally, VO(2peak) has been used to determine prognosis in heart failure; however, this measure has limitations. Hence, other exercise and gas exchange parameters measured submaximally, e.g. breathing efficiency (V(E)/VCO(2)), end-tidal CO(2) (P(ET)CO(2)), oxygen uptake efficiency slope (OUES), and circulatory power [ systolic blood pressure (SBP)], have been investigated. The aim of this study was to investigate the prognostic relevance of submaximal exercise gas exchange in heart failure patients. Method and results One hundred and thirty-two consecutive heart failure patients (mean age 56 ± 12 years, ejection fraction 29 ± 11%) performed peak treadmill testing. Gas exchange and haemodynamic variables were measured continuously. Gas exchange data obtained from the first 2 min of exercise and at a respiratory exchange ratio (RER) of 0.9 were the measurements of interest. Over a median follow-up period of 62.4 (range 0-114) months, there were 44 endpoints (death or transplant). Univariate analysis demonstrated submaximal predictors of survival, which included V(E)/VCO(2) slope and ratio, P(ET)CO(2), OUES, and circulatory power (P ≤ 0.01). When these and additional submaximal variables were included together in the multivariable analysis, the strongest submaximal exercise predictive model (C-statistic 0.75) comprised data from the first stage of exercise (V(E) and circulatory power) and at an RER of 0.9 (V(E)/VCO(2) ratio). The inclusion of VO(2 peak) and demographic data, with submaximal data (V(E)/VCO(2) ratio at an RER = 0.9), increased the predictiveness of the model (C-statistic 0.78). CONCLUSION: Submaximal exercise measures provide useful prognostic information for predicting survival in heart failure. This form of testing is logistically easier, cheaper, and safer for patients compared with maximal exercise.
AIMS: Traditionally, VO(2peak) has been used to determine prognosis in heart failure; however, this measure has limitations. Hence, other exercise and gas exchange parameters measured submaximally, e.g. breathing efficiency (V(E)/VCO(2)), end-tidal CO(2) (P(ET)CO(2)), oxygen uptake efficiency slope (OUES), and circulatory power [ systolic blood pressure (SBP)], have been investigated. The aim of this study was to investigate the prognostic relevance of submaximal exercise gas exchange in heart failurepatients. Method and results One hundred and thirty-two consecutive heart failurepatients (mean age 56 ± 12 years, ejection fraction 29 ± 11%) performed peak treadmill testing. Gas exchange and haemodynamic variables were measured continuously. Gas exchange data obtained from the first 2 min of exercise and at a respiratory exchange ratio (RER) of 0.9 were the measurements of interest. Over a median follow-up period of 62.4 (range 0-114) months, there were 44 endpoints (death or transplant). Univariate analysis demonstrated submaximal predictors of survival, which included V(E)/VCO(2) slope and ratio, P(ET)CO(2), OUES, and circulatory power (P ≤ 0.01). When these and additional submaximal variables were included together in the multivariable analysis, the strongest submaximal exercise predictive model (C-statistic 0.75) comprised data from the first stage of exercise (V(E) and circulatory power) and at an RER of 0.9 (V(E)/VCO(2) ratio). The inclusion of VO(2 peak) and demographic data, with submaximal data (V(E)/VCO(2) ratio at an RER = 0.9), increased the predictiveness of the model (C-statistic 0.78). CONCLUSION: Submaximal exercise measures provide useful prognostic information for predicting survival in heart failure. This form of testing is logistically easier, cheaper, and safer for patients compared with maximal exercise.
Authors: Raymond J Gibbons; Gary J Balady; J Timothy Bricker; Bernard R Chaitman; Gerald F Fletcher; Victor F Froelicher; Daniel B Mark; Ben D McCallister; Aryan N Mooss; Michael G O'Reilly; William L Winters; Raymond J Gibbons; Elliott M Antman; Joseph S Alpert; David P Faxon; Valentin Fuster; Gabriel Gregoratos; Loren F Hiratzka; Alice K Jacobs; Richard O Russell; Sidney C Smith Journal: J Am Coll Cardiol Date: 2002-10-16 Impact factor: 24.094
Authors: T P Chua; P Ponikowski; D Harrington; S D Anker; K Webb-Peploe; A L Clark; P A Poole-Wilson; A J Coats Journal: J Am Coll Cardiol Date: 1997-06 Impact factor: 24.094
Authors: Lewis Ceri Davies; Roland Wensel; Panagiota Georgiadou; Mariantonietta Cicoira; Andrew J S Coats; Massimo F Piepoli; Darrel P Francis Journal: Eur Heart J Date: 2005-12-07 Impact factor: 29.983
Authors: P Ponikowski; D P Francis; M F Piepoli; L C Davies; T P Chua; C H Davos; V Florea; W Banasiak; P A Poole-Wilson; A J Coats; S D Anker Journal: Circulation Date: 2001-02-20 Impact factor: 29.690
Authors: Bryan J Taylor; Eric M Snyder; Maile L Richert; Courtney M Wheatley; Steven C Chase; Lyle J Olson; Bruce D Johnson Journal: J Heart Lung Transplant Date: 2016-10-02 Impact factor: 10.247