A nomogram to predict exercise capacity from a specific activity questionnaire and clinical data

Am J Cardiol. 1994 Mar 15;73(8):591-6. doi: 10.1016/0002-9149(94)90340-9.


Recent investigations suggested that clinical exercise testing can be optimized by individualizing the protocol, depending on the purpose of the test and the subject tested. This requires some knowledge of a patient's exercise capacity before beginning the test. The accuracy of a simple physical activity questionnaire and readily available clinical data in predicting subsequent treadmill performance was examined. A brief, self-administered questionnaire (VSAQ) was developed for veterans who were referred to exercise testing for clinical reasons. The VSAQ was designed to determine which specific daily activities were associated with symptoms of cardiovascular disease (fatigue, chest pain and shortness of breath). Two hundred twelve consecutive patients (mean age 62 +/- 8 years) referred for maximal exercise testing were studied. Clinical and demographic variables were added to VSAQ responses in a stepwise regression model to determine their ability to predict treadmill performance. Only metabolic equivalents by VSAQ, and age were significant predictors of treadmill performance; these 2 variables yielded R = 0.82 (SEE 1.43; p < 0.001), and explained 67% of the variance in exercise capacity. The regression equation reflecting the relation between age, VSAQ and exercise capacity was: achieved metabolic equivalents = 4.7 + 0.97 (VSAQ) - 0.06 (age). Using this equation, a nomogram was developed. Incorporating the VSAQ with the nomogram requires only a few minutes, and yields a reasonably accurate estimate of a patient's exercise capacity. Although the present equation is population-specific, a similar approach in different populations may be useful for individualizing protocols for clinical exercise testing.

MeSH terms

  • Activities of Daily Living
  • Age Factors
  • Disability Evaluation
  • Energy Metabolism
  • Exercise Test / statistics & numerical data
  • Exercise Tolerance* / physiology
  • Female
  • Heart Diseases / diagnosis*
  • Heart Diseases / epidemiology
  • Humans
  • Male
  • Middle Aged
  • Reference Values
  • Regression Analysis
  • Surveys and Questionnaires
  • Veterans