Development of a heart rate variability and complexity model in predicting the need for life-saving interventions amongst trauma patients

Table 3 Multivariate logistic regression analysis for predicting the need for life-saving interventions amongst trauma patients

	OR (95% CI)	P value
All variable
Age	1.026 (0.987–1.066)	0.200
Age greater than 56	0.363 (0.079–1.674)	0.194
Systolic blood pressure	0.989 (0.972–1.006)	0.201
Heart rate	1.021 (0.997–1.044)	0.085
Glasgow Coma Scale	0.819 (0.699–0.960)	0.014
avHR	1.002 (0.973–1.031)	0.916
NN50	0.996 (0.958–1.036)	0.840
pNN50	1.043 (0.903–1.204)	0.570
LF	1.000 (0.999–1.002)	0.328
HF	0.999 (0.999–1.000)	0.224
LF norm	0.817 (0.574–1.162)	0.261
HF norm	0.842 (0.590–1.199)	0.340
LF/HF	1.000 (0.998–1.002)	0.837
Approximate entropy	1.866 (0.060–58.263)	0.723
Sample entropy	0.364 (0.056–2.366)	0.290
DFA1	10.157 (1.621–63.659)	0.013
DFA2	3.758 (0.653–21.629)	0.138
Variables after backward Wald selection
Glasgow Coma Scale	0.756 (0.660–0.864)	< 0.001
DFA-α1	3.932 (1.256–12.314)	0.019
DFA-α2	5.200 (1.060–25.504)	0.042

OR odds ratio, CI confidence interval, avHR mean of the instantaneous heart rate in electrocardiograms, NN50 number of consecutive RR intervals differing by more than 50 ms in electrocardiograms, pNN50 percentage of consecutive RR intervals differing by more than 50 ms in electrocardiograms, LF low frequency power in electrocardiograms, HF high frequency power in electrocardiograms, norm normalised, LF/HF ratio of LF power to HF power in electrocardiograms, TP total power derived from variance of all RR intervals in electrocardiograms, DFA detrended fluctuation analysis

ISSN: 2321-3876