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Exercise age, as derived from exercise testing, improves prediction of overall mortality compared to chronological age

Session Best Posters 2

Speaker Serge Harb

Event : ESC Congress 2017

  • Topic : preventive cardiology
  • Sub-topic : Exercise Testing
  • Session type : Best ePosters

Authors : S Harb (Cleveland,US), PC Cremer (Cleveland,US), V Menon (Cleveland,US), Y Wu (Cleveland,US), C Rouphael (Cleveland,US), T Guy (Cleveland,US), L Cho (Cleveland,US), WA Jaber (Cleveland,US)

S. Harb1 , P.C. Cremer1 , V. Menon1 , Y. Wu1 , C. Rouphael1 , T. Guy1 , L. Cho1 , W.A. Jaber1 , 1Cleveland Clinic Foundation - Cleveland - United States of America ,

Exercise testing and training

European Heart Journal ( 2017 ) 38 ( Supplement ), 257-258

Introduction: Functional capacity (FC) and chronotropic response (CR), as assessed by exercise treadmill testing (ETT), are among the strongest predictors of cardiovascular events. We hypothesized that FC and CR may be utilized to estimate exercise age (ExA), a novel measure for patients to understand their exercise performance and prognosis.

Purpose: Evaluate whether ExA is a better predictor of 10-year mortality when compared to chronological age (CA).

Methods: All patients who underwent ETT at our institution between January 1991 and February 2015 were included. ExA was computed as a function of peak estimated metabolic equivalents of task (METs), chronotropic reserve index (CRI) {= (peak heart rate − resting heart rate)/[(220 − age) − resting heart rate]}, beta-blocker (BB) and non-dihydropyridine calcium channel blocker (ND-CCB) use. The variable was evaluated in a derivation cohort (20%) and its utility confirmed in a validation cohort (80%). Survival at 10 years was determined using the social security death index and institutional death status. Linear discriminant analysis was performed between ExA and CA as predictors of death in both sexes.

Results: A total of 126,356 patients were included (mean age 53.5±12.6, 59% male). There were 9,929 deaths. Table 1 presents the baseline characteristics by mortality status at 10 years. The derived equations to estimate ExA were: for males = 63.829 − 2.043 METs + 10.502 CRI + 2.232 BB + 2.364 ND-CCB; and for females = 57.353 − 1.572 METs + 9.426 CRI + 2.572 BB + 2.919 ND-CCB. In the validation cohort, ExA was more predictive of overall mortality compared to CA in both sexes. For males, the area under the ROC curve was 0.79 for ExA, compared to 0.74 for CA (p<0.001) – fig 1A. Similarly, for females, the area under the ROC curve was 0.74 for ExA, compared to 0.72 for CA (p<0.001) – fig 1B.

Conclusion(s): Exercise age derived from METs, CRI, BB and ND-CCB use is a better predictor of mortality compared to chronological age and provides a convenient transformation of exercise parameters to a scale more easily understood by both patients and treating physicians.

Baseline charateristics
VariableAll (N=126,356)Alive (N=116,427)Dead (N=9,929)P value
Age (mean ±SD)53.5±12.652.7±12.462.7±11.5<0.001
Male sex (N,%)74724 (59.1)67715 (58.2)7009 (70.6)<0.001
BB use (N,%)30568 (24.2)27003 (21.4)3565 (2.8)<0.001
ND-CCB use (N,%)6330 (5)5393 (4.3)937 (0.7)<0.001
CRI (mean ± SD)0.88±0.250.89±0.250.74±0.29<0.001
METs (mean ± SD)9±2.89.2±2.76.3±2.4<0.001
Figure 1- Discriminant analysis

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