Aims: The aim of this study was to determine the ability to predict all-cause mortality using established per cent-predicted (%PRED) equations for peak oxygen consumption (VO2peak) estimated by a submaximal walk test in outpatients with cardiovascular disease.
Methods: Male patients (N = 1491) aged 62 ± 10 years at baseline underwent a moderate and perceptually regulated (11-13 on the 6-20 Borg scale) 1-km treadmill-walking test to estimate VO2peak. %PRED was derived from the Fitness Registry and the Importance of Exercise: A National Data Base (FRIEND) and the Wasserman/Hansen equations.
Results: There were 215 deaths during a median 9.4-year follow-up. The FRIEND prediction equation provided better prognostic information with receiver operating curve analysis showing significantly different areas under the curve (0.72 and 0.69 for the FRIEND and the Wasserman/Hansen equations respectively, p = 0.001). Overall mortality rate was higher across decreasing tertiles of %PRED using FRIEND, with 26%, 11% and 5% for the least fit, intermediate and high fit tertiles, respectively (p for trend < 0.0001). Compared with the least fit tertile, the adjusted hazard ratios for the second and third tertiles were 0.54 (95% confidence interval 0.34-0.87, p = 0.01) and 0.45 (95% confidence interval 0.25-0.81, p = 0.008), respectively. Each 1% increase in %PRED conferred a 3% improvement in survival (p = 0.0004).
Conclusion: Low %PRED VO2peak in cardiac outpatients determined by the FRIEND equation was associated with a high mortality rate independent of traditional cardiovascular risk factors and clinical history. The FRIEND equation may provide a suitable normal standard when applied to clinically stable outpatients with cardiovascular disease.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1177/2047487319871728 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Quantifying assumptions underlying peak oxygen consumption equations across the body mass spectrum.
Clin Obes
August 2024
Division of Cardiovascular Medicine, Department of Medicine, Stanford University, Stanford, California, USA.
The goal of this study is to quantify the assumptions associated with the Wasserman-Hansen (WH) and Fitness Registry and the Importance of Exercise: A National Database (FRIEND) predictive peak oxygen consumption (pVO) equations across body mass index (BMI). Assumptions in pVO for both equations were first determined using a simulation and then evaluated using exercise data from the Stanford Exercise Testing registry. We calculated percent-predicted VO (ppVO) values for both equations and compared them using the Bland-Altman method.
View Article and Find Full Text PDFBackground Percentage of age-predicted peak oxygen uptake (VO) achieved (ppVO) has been widely used to stratify risk in patients with heart failure. However, there are limitations to traditional normal standards. We compared the recently derived FRIEND (Fitness Registry and the Importance of Exercise: A National Data Base) equation to the widely used Wasserman-Hansen (WH) ppVO equation to predict outcomes in patients with heart failure.
View Article and Find Full Text PDFPrognostic comparison of the FRIEND and Wasserman/Hansen peak VO2 equations applied to a submaximal walking test in outpatients with cardiovascular disease.
Eur J Prev Cardiol
April 2021
Centre for Exercise Science and Sport, University of Ferrara, Italy.
Aims: The aim of this study was to determine the ability to predict all-cause mortality using established per cent-predicted (%PRED) equations for peak oxygen consumption (VO2peak) estimated by a submaximal walk test in outpatients with cardiovascular disease.
Methods: Male patients (N = 1491) aged 62 ± 10 years at baseline underwent a moderate and perceptually regulated (11-13 on the 6-20 Borg scale) 1-km treadmill-walking test to estimate VO2peak. %PRED was derived from the Fitness Registry and the Importance of Exercise: A National Data Base (FRIEND) and the Wasserman/Hansen equations.
Applying current normative data to prognosis in heart failure: The Fitness Registry and the Importance of Exercise National Database (FRIEND).
Int J Cardiol
July 2018
Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA, USA; Stanford Center for Inherited Cardiovascular Diseases (SCICD), Stanford Hospital and Clinics, Stanford, CA, USA. Electronic address:
Introduction: Percent of predicted peak VO (ppVO) is considered a standard measure for establishing disease severity, however, there are known limitations to traditional normative values. This study sought to compare ppVO from the newly derived "Fitness Registry and the Importance of Exercise: a National Database" (FRIEND) registry equation to conventional prediction equations in a clinical cohort of patients undergoing cardiopulmonary exercise testing (CPX).
Methods And Results: We selected 1094 patients referred for evaluation of heart failure (HF) symptoms who underwent CPX.
A non-exercise based V02max prediction using FRIEND dataset with a neural network.
Annu Int Conf IEEE Eng Med Biol Soc
July 2017
The main goal of this work is the development of models, based on computational intelligence techniques, in particular neural networks, to predict the maximum oxygen consumption value. While the maximum oxygen consumption is a direct mark of the cardiorespiratory fitness, several studies have also confirmed it also as a powerful predictor of risk for adverse outcomes, such as hypertension, obesity, and diabetes. Therefore, the existence of simpler and accurate models, establishing an alternative to standard cardiopulmonary exercise tests, with the potential to be employed in the stratification of the general population in daily clinical practice, would be of major importance.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!