External prognostic validations and comparisons of age- and gender-adjusted exercise capacity predictions.
Open accessAbstract
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.
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In respective sexes, the formulas used to estimate metabolic equivalents have been previously reported to perform best in terms of their ability to determine outcomes.
“In respective sexes, these formulas have been previously reported to perform best in terms of their ability to determine outcomes.31”
From Association of Cardiorespiratory Fitness with Long-term Mortality Among Adults Undergoing Exercise Treadmill Testing (2018) · cites this paper as [31]
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- Authors
- Kim, E. S. H., Ishwaran, H., Blackstone, E., & Lauer, M. S.
- Affiliations
- Cleveland Clinic (US)
- National Institutes of Health (US)
- Corresponding author
- Lauer, Michael S.
- Venue
- Journal of the American College of Cardiology
- Publisher
- Elsevier BV
- Published
- 2007-11
- Volume
- 50
- Issue
- 19
- Pages
- 1867-1875
- ISSN
- 0735-1097 (ISSN-L)
- OpenAlex
- W2107660014
- Cited by
- 77
- References
- 39
- Citations by year
- 2026: 1 · 2025: 1 · 2024: 8 · 2023: 2 · 2022: 1 · 2021: 3 · 2020: 5 · 2019: 6 · 2018: 6 · 2017: 1 · 2016: 4 · 2015: 8 · 2014: 9 · 2013: 8 · 2012: 7
- FWCI
- 6.13
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Journal of the American College of Cardiology (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health
- National Heart, Lung, and Blood Institute (R01 HL-66004-2, R01 HL-072771-02, P50HL077107, R01HL066004, R01HL072771, P50 HL77107)
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (K12HD049091)
- Topics
- Health Sciences › Medicine › Complementary and alternative medicine › Cardiovascular and exercise physiology
- Health Sciences › Medicine › Physiology › Physical Activity and Health
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Cardiac Imaging and Diagnostics
- Keywords
- exercise capacity, exercise capacity prediction, nomogram, mortality prediction, prognostic validity, external validation, metabolic equivalents, age-gender interaction, cardiovascular mortality, asymptomatic patients, stress testing
- MeSH terms
- Adult, Age Factors, Aged, Aged, 80 and over, Blood Pressure, Cause of Death, Coronary Disease, Electrocardiography, Exercise Test, Physical Exertion, Female, Heart Rate, Humans, Male, Middle Aged, Physical Fitness, Predictive Value of Tests, Prognosis, Prospective Studies, Risk Factors, Sex Factors, Multivariate Analysis, Survival Analysis, Nomograms
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