Abstract

Objective To analyze the clinical characteristics and short-term prognostic factors in acute cerebral infarction patients who underwent recanalization. Methods This retrospective study enrolled 94 cases of acute cerebral ischemic patients in the First Affiliated Hospital of Nanjing Medical University between October 2014 and August 2016. Based on the clinical characteristics of the enrolled patients, a multivariate Logistic regression model was established to analyze the risk factors of unfavorable prognosis. Besides, patients were further divided into good collateral circulation group (1-2) and poor collateral circulation group (3-5) according to the Pial Collateral score, and the prognosis improvement rates between patients recanalized within 4 h and over 4 h were analyzed in each group. Chi-square test or Fisher’s exact test was used to analyze statistical difference as indicated. Results By multivariate Logistic regression analysis, age older than 70 years old (OR=2.651, 95%CI: 1.013-6.937) and poor collateral circulation (OR=3.160, 95%CI: 1.113-8.977) were independent risk factors of short-term poor prognosis. In the poor collateral circulation subgroup, patients recanalized within 4 h exerted a relatively better prognosis than patients recanalized over 4 h (42.9% vs.10.5%, P=0.047). However, the effect of recanalization duration on the prognosis in the good collateral circulation subgroups was not statistically significant (42.9% vs. 10.5%, P=0.047), however, the effect of recanalization duration on prognosis in patients with good collateral circulation was not statistically significant (58.3% vs. 37.8%, P=0.117). Conclusions For patients with acute cerebral infarction, age and collateral circulation status may influence the prognosis of recanalization therapy. The treatment time had a significant influence on the prognosis in patients with poor collateral, while it had minimal significance on patients with good collateral. Key words: Retrospective research; Cerebral infarction; Vascular recanalization; Prognosis; Influencing factor; Logistic regression model; National Institute of Health Stroke Scale; Collateral circulation

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