RESUMO
Background: Cardiorespiratory fitness (CRF) is an important component of overall physical fitness and is associated with numerous health benefits, including a reduced risk of heart disease, diabetes, and obesity. However, direct measurement of CRF is time-consuming and therefore not feasible for screening purposes. Methods: A maximal treadmill exercise test with the Bruce protocol was performed to estimate VO2max in 1047 Spanish men and women aged 17 to 62 years. Weight, height, and heart rate were measured. Leisure-time physical activity (LTPA) was recorded using the Minnesota Leisure Time Physical Activity Questionnaire. A multiple linear regression model was developed to predict exercise-based VO2max. The validity of the model was examined by correlation, concordance, Bland-Altman analysis, cross-validation, and construct validity analysis. Results: There was no significant difference between VO2max obtained by the Bruce protocol (43.56 mL/kg/min) or predicted by the equation (43.59 mL/kg/min), with R2 of 0.57, and a standard error of the estimate of 7.59 mL/kg/min. Pearson's product-moment correlation and Lin's concordance correlation between measured and predicted CRF values were 0.75 and 0.72, respectively. Bland-Altman analysis revealed a significant proportional bias of non-exercise eCRF, overestimating unfit and underestimating highly fit individuals. However, 64.3% of participants were correctly classified into CRF tertile categories, with an important 69.9% in the unfit category. Conclusions: The eCRF equation was associated with several cardiovascular risk factors in the anticipated directions, indicating good construct validity. In conclusion, the non-exercise eCRF showed a reasonable validity to estimate true VO2max, and it may be a useful tool for screening CRF.
RESUMO
Pre-existing coronary artery disease (CAD), and thrombotic, inflammatory, or virus infectivity response phenomena have been associated with COVID-19 disease severity. However, the association of candidate single nucleotide variants (SNVs) related to mechanisms of COVID-19 complications has been seldom analysed. Our aim was to test and validate the effect of candidate SNVs on COVID-19 severity. CARGENCORS (CARdiovascular GENetic risk score for Risk Stratification of patients positive for SARS-CoV-2 [COVID-19] virus) is an age- and sex-matched case-control study with 818 COVID-19 cases hospitalized with hypoxemia, and 1636 controls with COVID-19 treated at home. The association between severity and SNVs related to CAD (n = 32), inflammation (n = 19), thrombosis (n = 14), virus infectivity (n = 11), and two published to be related to COVID-19 severity was tested with adjusted logistic regression models. Two external independent cohorts were used for meta-analysis (SCOURGE and UK Biobank). After adjustment for potential confounders, 14 new SNVs were associated with COVID-19 severity in the CARGENCORS Study. These SNVs were related to CAD (n = 10), thrombosis (n = 2), and inflammation (n = 2). We also confirmed eight SNVs previously related to severe COVID-19 and virus infectivity. The meta-analysis showed five SNVs associated with severe COVID-19 in adjusted analyses (rs11385942, rs1561198, rs6632704, rs6629110, and rs12329760). We identified 14 novel SNVs and confirmed eight previously related to COVID-19 severity in the CARGENCORS data. In the meta-analysis, five SNVs were significantly associated to COVID-19 severity, one of them previously related to CAD.