ABC | Volume 115, Nº1, July 2020

Original Article Benchimol-Barbosa et al. Dynamic AV-conduction to RR-interval Coupling Arq Bras Cardiol. 2020; 115(1):71-77 interval variability, assessed on resting supine ECG. It was hypothesized that, at rest, AV conduction would be affected by AV remodeling induced by high-end training, causing AVCT to RR-interval coupling to behave differently from sedentary conditions. In a linear model, AVCT to RR-interval coupling showed an average negative regression line slope in the Athlete group and, conversely, an average positive slope in the Control group, indicating that AV node remodeling due to training induces decremental conduction enhancement. A potentially distinguished measure of physical fitness, AVCT to RR-interval regression slope correctly identified 90% all subjects’ related physical fitness status. Although identification of decremental conduction in athletes is a common finding, the application of a linear modeling to quantify AVCT and its relation to RR- interval in highly trained athletes has not been yet reported, to the best of our knowledge. Previous studies evidenced a high prevalence of Mobitz I 2nd degree AV block in long distance runners at rest. 8-10 In the present study, the occurrence of spontaneous PR-peak-interval lengthening related to RR-interval shortening was amajor finding, Table 1 – Univariate analyses of studied variables (mean ± SD) M-RR SD-RR M-AVCT SD-AVCT RR-AVCT slope Control group (mean ± SD) 853.9 ± 94.0 44.5 ± 10.1 134.0 ± 17.7 2.8 ± 1.1 0.0376 ± 0.0219 Athlete group (mean ± SD) 1079.1 ± 207.9 76.4 ± 21.0 143.3 ± 27.6 3.8 ± 2.2 -0.0034 ± 0.0172 p Significance level 0.0084 0.0008 0.3820 0.2032 0.002 ROC statistics Area under the ROC curve (AUC) 0.89 0.9 0.56 0.61 0.92 Standard Error 0.07 0.08 0.14 0.14 0.06 95% Confidence Interval 0.67–0.98 0.68–0.98 0.32–0.78 0.37–0.82 0,71–0.99 z statistic 5.5 5.2 0.4 0.8 6.7 p Significance level (area=0.5) < 0.0001 < 0.0001 0.6721 0.4177 < 0.0001 Cut-off value 917.3 60.9 124.1 3.8 0.0044 Specificity 80 % 100 % 40 % 50 % 100 % Sensitivity 80 % 80 % 90 % 80 % 80 % Accuracy 80 % 90 % 65 % 65 % 90 % M-RR: mean of all normal RR-intervals; SD-RR: standard deviation of all normal RR-intervals; M-AVCT: mean of PR-peak intervals respective to normal RR-intervals; SD-AVCT: standard deviation of PR-peak intervals respective to normal RR-intervals; RR-AVCTslope: slope of the linear regression line between PR-peak intervals and respective RR interval Table 2 – Multivariable explanatory model of the maximal VO 2 consumption; 1100 bootstrap resampling procedure results and Internal validation of the maximal VO2 consumption multivariable explanatory model using bootstrap 2:1 ‘Test’ vs ‘Validation’ procedure results Multivariate model Bootstrap procedure Bootstrap test-validation Model Variables Coefficients ± p Coefficients ± p Coefficients ± p PR to RR slope (15 Hz) -100.36 ± 31.97 0.006 -105.76 ± 33.93 0.0009 -101.42 ± 29.39 0.0003 SD RR 0.115 ± 0.040 0.0099 0.115 ± 0.041 0.003 0.115 ± 0.036 0.0007 Constant 8.88 8.75 ± 3.22 0.003 8.85 ± 2.83 0.0009 ROC statistics Test group Validation group Area under the ROC curve (AUC) 0.99 0.99 0.97 0.87 Standard Error 0.02 0.02 0.06 0.13 95% Confidence Interval 0.94–1.00 0.94–1.00 0.85–1.00 0.61–1.00 z statistic 42.1 42.1 16.7 6.5 p Significance level (area=0.5) < 0.001 < 0.001 < 0.001 < 0.001 Cut-off value 12.3 12.0 14.2 Specificity 90% 90% 90.2% 81.0% Sensitivity 100% 100% 96.7% 80.4% Total accuracy 95% 95% 93.4% 80.7% * Procedimento de bootstrap realizado sem restituição. O modelo explicativo multivariado foi calculado no grupo Teste e validado no grupo Validação; ± = (média ± DP). 74