Abstract
Recent studies have found that oxygen saturation (SpO(2) ) variability analysis has potential for noninvasive assessment of the functional connectivity of cardiorespiratory control systems during hypoxia. Patients with sepsis have suboptimal tissue oxygenation and impaired organ system connectivity. Our objective with this report was to highlight the potential use for SpO(2) variability analysis in predicting intensive care survival in patients with sepsis. MIMIC-III clinical data of 164 adults meeting Sepsis-3 criteria and with 30 min of SpO(2) and respiratory rate data were analyzed. The complexity of SpO(2) signals was measured through various entropy calculations such as sample entropy and multiscale entropy analysis. The sequential organ failure assessment (SOFA) score was calculated to assess the severity of sepsis and multiorgan failure. While the standard deviation of SpO(2) signals was comparable in the non-survivor and survivor groups, non-survivors had significantly lower SpO(2) entropy than those who survived their ICU stay (0.107 ± 0.084 vs. 0.070 ± 0.083, p < 0.05). According to Cox regression analysis, higher SpO(2) entropy was a predictor of survival in patients with sepsis. Multivariate analysis also showed that the prognostic value of SpO(2) entropy was independent of other covariates such as age, SOFA score, mean SpO(2) , and ventilation status. When SpO(2) entropy was combined with mean SpO(2) , the composite had a significantly higher performance in prediction of survival. Analysis of SpO(2) entropy can predict patient outcome, and when combined with SpO(2) mean, can provide improved prognostic information. The prognostic power is on par with the SOFA score. This analysis can easily be incorporated into current ICU practice and has potential for noninvasive assessment of critically ill patients.