This study aims to investigate the risk factors of hemorrhagic transformation (HT) after thrombolysis with recombinant
tissue plasminogen activator (rt-PA) in patients with acute
cerebral infarction (ACI) and establish a logistic regression equation and the risk prediction model.
PATIENTS AND METHODS: One hundred and ninety patients with ACI were divided into the HT group (n=20) and non-HT group (n=170) according to whether HT occurred within 24 hours after rt-PA thrombolysis. The clinical data were collected for analyzing the influencing factors, and a logistic regression analysis model was then established. Besides, patients in the HT group were further grouped into symptomatic
hemorrhage (n=7) and non-symptomatic
hemorrhage (n=13) according to the type of
hemorrhage. The clinical diagnostic value of risk factors in symptomatic
hemorrhage after thrombolysis in ACI was analyzed using the ROC curve.
RESULTS: We found that history of
atrial fibrillation, time from onset to thrombolysis, pre-thrombolytic
glucose, pre-thrombolytic National Institute of Health
Stroke Scale (NIHSS) score, 24-hour post-thrombolytic NIHSS score, and proportion of patients with large
cerebral infarction were all the influencing factors of HT risk after rt-PA thrombolysis in patients with ACI (p<0.05). Logistic regression analysis model was established with an accuracy of 88.42% (168/190), a sensitivity of 75.00% (15/20), and a specificity of 90.00% (153/170). The time from onset to thrombolysis, pre-thrombolytic
glucose, and 24-hour post-thrombolytic NIHSS score had higher clinical value in predicting the risk of HT after rt-PA thrombolysis, with the AUCs of 0.874, 0.815 and 0.881, respectively.
Blood glucose and pre-thrombolytic NIHSS score were independent risk factors related to symptomatic
hemorrhage after thrombolysis in ACI (p<0.05). The AUCs for predicting symptomatic
hemorrhage alone and in combination were 0.813, 0.835, and 0.907, respectively, with sensitivities of 85.70%, 87.50% and 90.00%, and specificities of 62.50%, 60.00%, and 75.42% respectively.
CONCLUSIONS: The establishment of a prediction model based on the risk factors of HT after rt-PA thrombolysis had a good predictive value in patients with ACI. This model was helpful in guiding clinical judgment and improving the safety of intravenous thrombolysis. Early identification of symptomatic
bleeding risk factors provided a reference for clinical treatment and prognostic measures of patients with ACI.