[Retracted] Influence Factors and Predictive Models for the Outcome of Patients with Ischemic Stroke after Intravenous Thrombolysis: A Multicenter Retrospective Cohort Study

Figure 3

The decision curve and clinical impact curve analysis of nomogram predicting the prognosis at 3 months after IVT. (a) The decision curve of nomogram predicting the prognosis at 3 months after IVT in training cohort; (b) the decision curve of nomogram predicting the prognosis at 3 months after IVT cohort; (c) the nomogram predicting the CICA of the prognosis at 3 months after IVT in training cohort; (d) the nomogram predicting the CICA of the prognosis at 3 months after IVT in verification cohort. Note: (1) In the decision curve, the abscissa represents the high-risk threshold probability to predict poor prognosis, and the ordinate represents net benefit. “Model” refers to the net benefit brought by intervention through predicting high-risk patients with poor prognosis under different threshold probabilities according to the risk model; “All” and “None” represent two extreme cases. “All” refers to the net benefit brought by intervention when all patients were at high risk with poor prognosis. “None” refers to no intervention when all patients were at low risk, and under this condition, the net benefit was 0. DCA was used to analyze and compare two extreme cases, the net benefit of the risk model and the corresponding threshold probability. (2) As to the CICA, we assumed that 1000 patients were applied to our model under simulated examination conditions. “Number high risk” represents the number of high-risk patients with poor prognosis predicted by the model at different threshold probabilities. “Number high-risk event” represents the actual number of high-risk patients with poor prognosis.

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