OBJECTIVES: The purpose of this study was to externally validate the prognostic value of age- and gender-based nomograms and categorical definitions of impaired exercise capacity (EC). BACKGROUND: Exercise capacity predicts death, but its use in routine clinical practice is hampered by its close correlation with age and gender. METHODS: For a median of 5 years, we followed 22,275 patients without known heart disease who underwent symptom-limited stress testing. Models for predicted or impaired EC were identified by literature search. Gender-specific multivariable proportional hazards models were constructed. Four methods were used to assess validity: Akaike Information Criterion (AIC), right-censored c-index in 100 out-of-bootstrap samples, the Nagelkerke Index R2, and calculation of calibration error in 100 bootstrap samples. RESULTS: There were 646 and 430 deaths in 13,098 men and 9,177 women, respectively. Of the 7 models tested in men, a model based on a Veterans Affairs cohort (predicted metabolic equivalents [METs] = 18 - [0.15 x age]) had the highest AIC and R2. In women, a model based on the St. James Take Heart Project (predicted METs = 14.7 - [0.13 x age]) performed best. Categorical definitions of fitness performed less well. Even after accounting for age and gender, there was still an important interaction with age, whereby predicted EC was a weaker predictor in older subjects (p for interaction <0.001 in men and 0.003 in women). CONCLUSIONS: Several methods describe EC accounting for age and gender-related differences, but their ability to predict mortality differ. Simple cutoff values fail to fully describe EC's strong predictive value.
OBJECTIVES: The purpose of this study was to externally validate the prognostic value of age- and gender-based nomograms and categorical definitions of impaired exercise capacity (EC). BACKGROUND: Exercise capacity predicts death, but its use in routine clinical practice is hampered by its close correlation with age and gender. METHODS: For a median of 5 years, we followed 22,275 patients without known heart disease who underwent symptom-limited stress testing. Models for predicted or impaired EC were identified by literature search. Gender-specific multivariable proportional hazards models were constructed. Four methods were used to assess validity: Akaike Information Criterion (AIC), right-censored c-index in 100 out-of-bootstrap samples, the Nagelkerke Index R2, and calculation of calibration error in 100 bootstrap samples. RESULTS: There were 646 and 430 deaths in 13,098 men and 9,177 women, respectively. Of the 7 models tested in men, a model based on a Veterans Affairs cohort (predicted metabolic equivalents [METs] = 18 - [0.15 x age]) had the highest AIC and R2. In women, a model based on the St. James Take Heart Project (predicted METs = 14.7 - [0.13 x age]) performed best. Categorical definitions of fitness performed less well. Even after accounting for age and gender, there was still an important interaction with age, whereby predicted EC was a weaker predictor in older subjects (p for interaction <0.001 in men and 0.003 in women). CONCLUSIONS: Several methods describe EC accounting for age and gender-related differences, but their ability to predict mortality differ. Simple cutoff values fail to fully describe EC's strong predictive value.
Authors: Andrew D Robertson; David E Crane; A Saeed Rajab; Walter Swardfager; Susan Marzolini; Zahra Shirzadi; Laura E Middleton; Bradley J MacIntosh Journal: Exp Brain Res Date: 2015-05-24 Impact factor: 1.972
Authors: Sean Tan; Yi Wen Thang; William R Mulley; Kevan R Polkinghorne; Satish Ramkumar; Kevin Cheng; Jasmine Chan; John Galligan; Mark Nolan; Adam J Brown; Stuart Moir; James D Cameron; Stephen J Nicholls; Philip M Mottram; Nitesh Nerlekar Journal: J Am Heart Assoc Date: 2022-06-14 Impact factor: 6.106
Authors: Marco Guazzi; Volker Adams; Viviane Conraads; Martin Halle; Alessandro Mezzani; Luc Vanhees; Ross Arena; Gerald F Fletcher; Daniel E Forman; Dalane W Kitzman; Carl J Lavie; Jonathan Myers Journal: Circulation Date: 2012-09-05 Impact factor: 29.690
Authors: Daniel E Forman; Jonathan Myers; Carl J Lavie; Marco Guazzi; Bartolome Celli; Ross Arena Journal: Postgrad Med Date: 2010-11 Impact factor: 4.379