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Table 2 Statistical analysis results

From: Integration of metabolic and inflammatory mediator profiles as a potential prognostic approach for septic shock in the intensive care unit

Model

Data

Sensitivity : Specificity

α

β

PPV : NPV

ACC

AUROC

Septic shock vs. ICU controls

Metabolomics

0.92 : 1.0

0

0.08

1.0 : 0.87

0.95

0.99 ± 0.01

Cytokines/chemokines

0.94 : 0.90

0.1

0.06

0.94 : 0.90

0.93

0.99 ± 0.01

Combined

0.94 : 1.0

0

0.06

1.0 : 0.91

0.96

1.0

APACHE

0.82 : 0.42

0.58

0.18

0.71 : 0.57

0.67

0.74 ± 0.07

SOFA

0.85 : 0.25

0.75

0.15

0.66 : 0.50

0.63

0.64 ± 0.07

Nonsurvivors vs. survivors

Combined

1.0 : 0.88

0.13

0

0.89 : 1.0

0.94

1.0

APACHE

0.63 : 0.75

0.25

0.38

0.71 : 0.67

0.69

0.78 ± 0.12

SOFA

0.75 : 0.63

0.38

0.25

0.67 : 0.71

0.69

0.81 ± 0.11

  1. Comparison of statistical measures for septic shock patients vs. ICU controls and septic shock nonsurvivors vs. septic shock survivors models based on metabolomics data, cytokine/chemokine data, combined dataset (metabolites together with inflammatory mediators), acute physiology and chronic health evaluation (APACHE) and sequential organ failure assessment (SOFA) scores. The receiver operating characteristic (ROC) curve plots for each dataset are shown in Figure 4. α, false positive rate; β, false negative rate; PPV, positive predictive value; NPV, negative predictive value; ACC, accuracy; AUROC, area under the receiver operating characteristic curve (value ± standard error as calculated from the ROC curves); ICU, intensive care unit.