Efficacy of alteplase intravenous thrombolysis combined with tirofiban in preventing acute cerebral infarction progression and random forest model analysis of progression influencing factors

Zhang Senlin; Xu Fengping; Lin Xiaoli

doi:10.3760/j.issn.1673-4777.2026.01.011

Abstract：Objective To explore the efficacy of alteplase intravenous thrombolysis combined with tirofiban in preventing acute cerebral infarction(ACI)from progressing to progressive cerebral infarction(PCI),and to construct a random forest model for predicting the risk of PCI.Methods A total of 106 ACI patients admitted to Nanping First Hospital Affiliated to Fujian Medical University from January 2022 to December 2024 were selected and divided into control group(alteplase intravenous thrombolysis alone,26 cases)and observation group(alteplase intravenous thrombolysis combined with tirofiban,80 cases)according to different treatment regimens.The incidence of PCI,national institutes of health stroke scale(NIHSS)scores,coagulation indicators,and adverse reactions were compared between the two groups.Furthermore,the observation group was divided into progression group and non-progression group.Clinical data and laboratory indicators were compared between the two subgroups.Logistic regression analysis was used to screen the risk factors for PCI,and a random forest model was established to predict the risk of PCI.Results Among the 26 patients in the control group,17 patients(65.4％)progressed to PCI after treatment,while 34 of the 80 patients(42.5％)in the observation group developed PCI,with a statistically significant difference between the two groups(P=0.042).The post-treatment NIHSS score in the observation group was lower than that in the control group(P＜0.05).After treatment,thrombin time,activated partial thromboplastin time,and prothrombin time in the observation group were all longer than those in the control group(all P＜0.05).Multivariate Logistic regression analysis showed that diabetes mellitus(odds ratio=20.530,P=0.004),admission NIHSS score(odds ratio=1.368,P=0.018),admission systolic blood pressure(odds ratio=1.053,P=0.041),fibrinogen(FIB)(odds ratio=29.931,P＜0.001),and serum amyloid A(SAA)(odds ratio=1.116,P=0.033)were influencing factors for PCI.In the random forest model,the order of factor importance was FIB,SAA,systolic blood pressure,NIHSS score,and diabetes mellitus.The area under the curve(AUC)of the random forest model was 0.957,with a sensitivity of 94.12％and specificity of 86.96％,which was superior to the Logistic model(AUC=0.909,P=0.042).Conclusion Alteplase combined with tirofiban can effectively reduce the risk of PCI,improve neurological function and coagulation status without increasing adverse reactions.Diabetes mellitus,high NIHSS score,high systolic blood pressure,elevated FIB,and high SAA are independent risk factors for PCI.The random forest model exhibits higher predictive performance,which is conducive to early identification of high-risk patients and guidance of individualized interventions.