| Autor: |
James E. Peterman, Matthew P. Harber, Mary T. Imboden, Mitchell H. Whaley, Bradley S. Fleenor, Jonathan Myers, Ross Arena, W. Holmes Finch, Leonard A. Kaminsky |
| Jazyk: |
angličtina |
| Rok vydání: |
2020 |
| Předmět: |
|
| Zdroj: |
Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease, Vol 9, Iss 11 (2020) |
| Druh dokumentu: |
article |
| ISSN: |
2047-9980 |
| DOI: |
10.1161/JAHA.119.015117 |
| Popis: |
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 |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
|
Plný text