Objective:To construct a nomogram model that can be used to predict thrombocytosis after splenectomy in patients with traumatic splenic rupture.Methods:The clinical data of 54 patients with splenectomy in Lu′an People′s Hospital from November 2016 to November 2021 were retrospectively analyzed. Among them, postoperative thrombocytosis occurred in 33 cases (postoperative thrombocytosis group), and 21 cases had no significant changes in platelets (postoperative platelet normal group). The general clinical data were recorded; the platelet parameters 14 d after operation were measured, including platelet count, mean platelet volume (MPV), procalcitonin (PCT) and platelet distribution width (PDW). The receiver operating characteristic (ROC) curve was drawn to analyze the predictive value of platelet parameters for thrombocytosis after splenectomy in patients with traumatic splenic rupture. Multivariate Logistic regression analysis was used to analyze independent risk factors of thrombocytosis after splenectomy in patients with traumatic splenic rupture. A nomogram model to predict thrombocytosis after splenectomy in patients with traumatic splenic rupture was established with R language software 4.0.2 package, internal validation of the nomogram model was performed using correction curves, and the prediction efficiency of the nomogram model was evaluated using decision curves.Results:The incidence of shock, rate of blood transfusion volume≥2 000 ml, platelet count and PCT in postoperative thrombocytosis group were significantly higher than those in postoperative platelet normal group: 69.70% (23/33) vs. 19.05% (4/21), 66.67% (22/33) vs. 38.10% (8/21), (823.56 ± 129.81) ×10 9/L vs. (521.92 ± 85.89) ×10 9/L, (0.87 ± 0.11)% vs. (0.54 ± 0.09)%, the MPV and PDW were significantly lower than those in postoperative platelet normal group: (10.23 ± 1.03) fl vs. (11.57 ± 0.92) fl and 0.113 ± 0.012 vs. 0.125 ± 0.020, and there were statistical differences ( P<0.01 or <0.05). ROC curve analysis results show that the area under curve of platelet count, MPV, PCT and PDW in for predicting the thrombocytosis after splenectomy in patients with traumatic splenic rupture were 0.973, 0.835, 0.987 and 0.734, and the optimal cut-off values were 642.29 ×10 9/L, 11.02 fl, 0.7% and 0.120. Multivariate Logistic regression analysis result showed that the platelet count, MPV, PCT, PDW, shock and blood transfusion volume were independent risk factors for thrombocytosis after splenectomy in patients with traumatic splenic rupture ( OR = 1.571, 1.243, 1.042, 1.413, 1.436 and 1.726; 95% CI 0.014 to 1.762, 0.743 to 2.862, 0.954 to 2.563, 0.584 to 2.389, 0.045 to 2.643 and 0.154 to 2.143; P<0.01 or <0.05). When platelet count, MPV, PCT, PDW, shock and blood transfusion volume were included as predictors for constructing the nomogram model, the internal validation results showed that the C-index of the nomogram model for predicting thrombocytosis after splenectomy in patients with traumatic splenic rupture was 0.793 (95% CI 0.267 to 2.311); the threshold value of the nomogram model for predicting thrombocytosis after splenectomy in patients with traumatic splenic rupture was >0.067, and the nomogram model provided a net clinical benefit; the clinical net benefit of the nomogram model was greater than that of platelet count, MPV, PCT, PDW, shock and blood transfusion volume. Conclusions:The nomogram model based on platelet count, MPV, PCT, PDW, shock and blood transfusion volume that affect the high risk of thrombocytosis after splenectomy in patients with traumatic splenic rupture has great clinical value in screening and identifying high risk patients.