Hemorrhagic risk factors after rt PA thrombolysis in acute cerebral infarction

L. Liu, G.-Q. Luo, Q. Liu, Z.-Y. Yang

Department of Casualty Management, General Hospital of Southern Theatre Command, Guangzhou, Guangdong, PR. China. luogaoquanlgq@21cn.com

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• Neurology

OBJECTIVE: 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.

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