Affiliation:
1. Fisher Institute of Health and Well‐Being Ball State University Muncie IN
2. Clinical Exercise Physiology Laboratory Ball State University Muncie IN
3. Health and Human Performance Department George Fox University Newberg OR
4. College of Health Ball State University Muncie IN
5. Division of Cardiology Veterans Affairs Palo Alto Healthcare System and Stanford University Palo Alto CA
6. Department of Physical Therapy College of Applied Science University of Illinois Chicago IL
7. Department of Educational Psychology Ball State University Muncie IN
Abstract
Background
Repeated assessment of cardiorespiratory fitness (
CRF
) improves mortality risk predictions in apparently healthy adults. Accordingly, the American Heart Association suggests routine clinical assessment of
CRF
using, at a minimum, nonexercise prediction equations. However, the accuracy of nonexercise prediction equations over time is unknown. Therefore, we compared the ability of nonexercise prediction equations to detect changes in directly measured
CRF
.
Methods and Results
The sample included 987 apparently healthy adults from the BALL ST (Ball State Adult Fitness Longitudinal Lifestyle Study) cohort (33% women; average age, 43.1±10.4 years) who completed 2 cardiopulmonary exercise tests ≥3 months apart (3.2±5.4 years of follow‐up). The change in estimated
CRF
(
eCRF
) from 27 distinct nonexercise prediction equations was compared with the change in directly measured
CRF
. Analysis included Pearson product moment correlations,
SEE
values, intraclass correlation coefficient values, Cohen's κ coefficients, γ coefficients, and the Benjamini‐Hochberg procedure to compare
eCRF
with directly measured
CRF
. The change in
eCRF
from 26 of 27 equations was significantly associated to the change in directly measured
CRF
(
P
<0.001), with intraclass correlation coefficient values ranging from 0.06 to 0.63. For 16 of the 27 equations, the change in
eCRF
was significantly different from the change in directly measured
CRF
. The median percentage of participants correctly classified as having increased, decreased, or no change in
CRF
was 56% (range, 39%–61%).
Conclusions
Variability was observed in the accuracy between nonexercise prediction equations and the ability of equations to detect changes in
CRF
. Considering the appreciable error that prediction equations had with detecting even directional changes in
CRF
, these results suggest
eCRF
may have limited clinical utility.
Publisher
Ovid Technologies (Wolters Kluwer Health)
Subject
Cardiology and Cardiovascular Medicine
Cited by
30 articles.
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