Retrospective Study
Copyright ©The Author(s) 2019.
World J Gastroenterol. Oct 14, 2019; 25(38): 5838-5849
Published online Oct 14, 2019. doi: 10.3748/wjg.v25.i38.5838
Figure 1
Figure 1 Flowchart of the process of patient enrollment. PPOI: Prolonged postoperative ileus.
Figure 2
Figure 2 Nomogram prediction of prolonged postoperative ileus. The steps are: Determine the value of the variable on the corresponding axis, draw a vertical line to the total points axis to determine the points, add the points of each variable, and draw a line from the total point axis to determine the PPOI probabilities at the lower line of the nomogram. PPOI: Prolonged postoperative ileus.
Figure 3
Figure 3 Receiver operating characteristic curve. AUC: Area under the receiver operating characteristic curve.
Figure 4
Figure 4 Internal validation of the nomogram using the bootstrap sampling. A: The ROC curve was measured by bootstrapping for 500 repetitions, and the AUC of the bootstrap stepwise model was showed; B: Calibration curve for predicted probability of the PPOI nomogram. The X axis is the predicted probability of the nomogram, and the Y axis is the observed probability. The red line shows the ideal calibration line, while the yellow area shows the 95% confidence interval of the prediction model. AUC: Area under the receiver operating characteristic curve; ROC: Receiver operating characteristic; PPOI: Prolonged postoperative ileus.
Figure 5
Figure 5 Decision curve analysis for the prediction model. Red solid line: Prediction model. Tin slash line: Assume all patients have PPOI. Solid horizontal line: Assume no patients have PPOI. The graph indicates the expected net benefit per patient relative to the nomogram prediction of PPOI. PPOI: Prolonged postoperative ileus.