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. 2020 Mar 17;11:69. doi: 10.3389/fpsyt.2020.00069

Table 4.

Logistic regression analyses on the association between adverse cardiovascular outcome (aCVO) and xBRS and heart rate variability.

R2 β Odds Ratio 95% Confidence Interval p
xBRS
Model 1 0.041 −0.882 0.414 [0.356, 0.470] <0.001
Model 2* 0.118 −0.534 0.586 [0.499, 0.689] <0.001
Model 3* 0.135 −0.209 0.811 [0.673, 0.978] 0.028
Model 4*†‡ 0.192 −0.071 0.932 [0.769, 1.129] 0.470
RMSSD
Model 1 0.018 −0.652 0.521 [0.441, 0.616] <0.001
Model 2* 0.110 −0.360 0.698 [0.588, 0.828] <0.001
Model 3* 0.179 0.015 1.015 [0.844, 1.220] 0.877
Model 4*†‡ 0.197 0.011 1.011 [0.838, 1.220] 0.909
SDNN
Model 1 0.022 −0.868 0.420 [0.344, 0.513] <0.001
Model 2* 0.111 −0.442 0.643 [0.524, 0.789] <0.001
Model 3* 0.179 −0.117 0.890 [0.717, 1.103] 0.286
Model 4*†‡ 0.197 −0.080 0.923 [0.741, 1.150] 0.476

Each model shows the regression results of xBRS, RMSSD, and SDNN.

*Adjusted for antihypertensive medication.

Adjusted for sociodemographic covariates (sex, age, education, and ethnicity).

Adjusted for health-behavioral and psychosocial covariates (smoking, alcohol, body mass index, physical activity, current stress).

xBRS, baroreflex sensitivity; RMSSD, a parameter reflecting heart rate variability calculated as the square root of the mean squared successive differences between adjacent normal-to-normal interbeat intervals; SDNN, a parameter reflecting heart rate variability calculated as the standard deviation of normal-to-normal interbeat intervals.