Symptom-limited exercise capacity is associated with long-term survival

Medicine (Baltimore). 2023 Sep 29;102(39):e34948. doi: 10.1097/MD.0000000000034948.

Abstract

The prognostic value of exercise capacity has been demonstrated in subjects with established cardiovascular diseases. We aim to evaluate the independence of exercise capacity measured by treadmill exercise test (TET) in predicting long-term outcomes among various comorbidities. This study was conducted from January 2003 to December 2012 in a tertiary medical center in Taiwan. Subjects referred for symptom-limited TET were recruited. Peak achieved metabolic equivalents (METs) were determined by treadmill grade and speed at peak exercise. The main outcomes were cardiovascular and all-cause mortality by linking to the National Death Registry. A total of 18,954 participants (57.8 ± 12.8 years, 62% men) achieved a mean peak METs of 9.2. Subjects in the lowest tertile of peak METs were older, had poorer renal function, lower hemoglobin, and more comorbidities. During a median follow-up of 4.3 years, there were 642 mortalities and 132 cardiovascular deaths. Peak METs significantly predicted cardiovascular death and all-cause mortality in the multivariable Cox regression models [hazard ratio (95% confidence intervals): 0.788 (0.660-0.940) and 0.835 (0.772-0.903), respectively]. The prognostic influence of peak METs consistently appeared in the subgroups, regardless of age, gender, body weight, comorbidities, use of beta-blockers, or the presence of exercise-induced ischemia. The fitness was more predictive of long-term outcomes in young or those with ischemic changes during TET (P for interaction: 0.035 and 0.018, respectively). The benefit of fitness was nonlinearly associated with long-term survival. The prognostic impacts of exercise capacity were universally observed in subjects with or without various comorbidities.

MeSH terms

  • Cardiovascular Diseases*
  • Exercise
  • Exercise Test
  • Exercise Tolerance*
  • Female
  • Humans
  • Male
  • Proportional Hazards Models