Objective  To construct and validate the risk prediction Nomogram model of hospital death in septic shock.

Methods  The clinical data of 324 cases of septic shock admitted to Anyang Hospital of Traditional Chinese Medicine from January 2019 to December 2022 were retrospectively analyzed, which were divided into training set (n=216) and validation set (n=108) by a random number table. The training set was divided into death group (n=91) and survival group (n=125) according to whether the deaths occurred in hospital. The general information was compared between the training set and validation set. Logistic regression analysis was used to analyze the factors of in-hospital death in the training set. R software package was used to build the Nomogram model for risk prediction of in-hospital death in training set. Bootstrap method was used for internal validation. The receiver operating characteristic curve (ROC) was used to evaluate the effectiveness of the model in predicting the in-hospital death risk of the training set and validation set. Decision curve analysis (DCA) was used for external validation.

Results  The mortality rate of patients was 41.98%. Acute physiology and chronic health evaluation II (APACHE II) score, albumin, platelet count (PLT), fibrinogen (FIB), D-dimer (D-D), lactate clearance rate, intravenous use of sodium bicarbonate, shock to volume recovery time, mechanical ventilation were all factors affecting the death of the training group. Based on this, the Nomogram model was constructed, and it was proved by Bootstrap method, ROC and DCA that its efficiency was good, the value of predicting death was ideal, and the net profit rate was high.

Conclusion  The risk of death in hospital of septic shock patients is high, and APACHE II score, albumin, PLT, FIB, D-D, lactate clearance rate, intravenous use of sodium bicarbonate, shock to volume resuscitation time, mechanical ventilation are all its influencing factors. The Nomogram model map established on this basis has good efficacy.

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