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The mortality risk prediction nomogram achieved good discrimination for in-hospital mortality (training set C-statistic = 0.987; model calibration P = 0.722; validation set C-statistic = 0.984, model calibration P = 0.669). Area under the curve (AUC) values for the training and validation sets are 0.987 (95% CI 0.981-0.994, P = 0.003) and 0.990 (95% CI 0.987-0.998, P = 0.007), respectively. DCA shows that the nomogram can achieve good net benefit. A novel nomogram was developed and is a simple and accurate tool for predicting the risk of
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