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Table 2 Performance of DLM for screening sepsis and septic shock using electrocardiography

From: Deep-learning model for screening sepsis using electrocardiography

Prediction model Internal validation External validation
AUC (95% CI) SEN (95% CI) SPE (95% CI) PPV (95% CI) NPV (95% CI) AUC (95% CI) SEN (95% CI) SPE (95% CI) PPV (95% CI) NPV (95% CI)
Performance for screening sepsis
DLM using 12-lead ECG 0.901
(0.882–0.920)
0.904
(0.854–0.953)
0.776
(0.767–0.785)
0.067
(0.055–0.078)
0.998
(0.997–0.999)
0.863
(0.846–0.879)
0.765
(0.725–0.804)
0.810
(0.805–0.816)
0.083
(0.075–0.091)
0.994
(0.992–0.995)
DLM using 6-lead ECG 0.882
(0.856–0.907)
0.815
(0.749–0.880)
0.824
(0.816–0.833)
0.076
(0.062–0.089)
0.996
(0.994–0.998)
0.856
(0.841–0.872)
0.794
(0.756–0.832)
0.766
(0.760–0.772)
0.071
(0.064–0.078)
0.994
(0.993–0.995)
DLM using 1-lead ECG 0.874
(0.850–0.899)
0.933
(0.891–0.975)
0.688
(0.678–0.698)
0.050
(0.042–0.059)
0.998
(0.997–0.999)
0.845
(0.827–0.863)
0.796
(0.759–0.834)
0.746
(0.739–0.752)
0.066
(0.059–0.072)
0.994
(0.993–0.995)
C-reactive protein 0.723
(0.670–0.776)
0.638
(0.550–0.725)
0.763
(0.748–0.778)
0.091
(0.071–0.111)
0.983
(0.977–0.988)
0.741
(0.716–0.766)
0.607
(0.561–0.654)
0.783
(0.776–0.791)
0.087
(0.077–0.097)
0.983
(0.981–0.986)
Body temperature 0.671
(0.621–0.722)
0.679
(0.599–0.759)
0.667
(0.655–0.679)
0.041
(0.032–0.049)
0.990
(0.987–0.993)
0.671
(0.642–0.700)
0.669
(0.624–0.714)
0.601
(0.593–0.608)
0.044
(0.039–0.049)
0.985
(0.983–0.987)
Performance for screening septic shock
DLM using 12-lead ECG 0.906
(0.877–0.936)
0.895
(0.815–0.974)
0.822
(0.814–0.831)
0.036
(0.026–0.045)
0.999
(0.998–1.000)
0.899
(0.872–0.925)
0.807
(0.743–0.870)
0.875
(0.871–0.880)
0.046
(0.038–0.054)
0.998
(0.998–0.999)
DLM using 6-lead ECG 0.881
(0.843–0.918)
0.842
(0.747–0.937)
0.792
(0.783–0.801)
0.029
(0.021–0.037)
0.999
(0.998–0.999)
0.893
(0.868–0.917)
0.880
(0.828–0.932)
0.749
(0.743–0.755)
0.026
(0.021–0.030)
0.999
(0.998–0.999)
DLM using 1-lead ECG 0.879
(0.841–0.916)
0.930
(0.864–0.996)
0.684
(0.673–0.694)
0.021
(0.016–0.027)
0.999
(0.999–1.000)
0.860
(0.833–0.888)
0.773
(0.706–0.840)
0.801
(0.795–0.806)
0.028
(0.023–0.033)
0.998
(0.997–0.999)
C-reactive protein 0.676
(0.590–0.762)
0.745
(0.625–0.865)
0.573
(0.556–0.590)
0.027
(0.019–0.036)
0.993
(0.989–0.997)
0.724
(0.680–0.768)
0.585
(0.505–0.665)
0.781
(0.774–0.788)
0.030
(0.023–0.036)
0.994
(0.992–0.995)
Body temperature 0.659
(0.584–0.734)
0.685
(0.561–0.809)
0.663
(0.651–0.674)
0.017
(0.011–0.022)
0.996
(0.994–0.998)
0.680
(0.631–0.730)
0.697
(0.622–0.773)
0.596
(0.588–0.604)
0.016
(0.013–0.019)
0.995
(0.994–0.997)
  1. AUC area under the receiver operating characteristic curve; DLM deep learning-based model; ECG electrocardiography; NPV negative predictive value; PPV positive predictive value; SEN sensitivity; SPE specificity