This study used electronic medical record (EMR) data to explore the risk factors for recurrence in patients with the first attack of cerebral infarction (CI). It expected to provide a scientific basis for improving the prognosis and reducing the recurrence rate of patients with CI. In this study, a retrospective search was performed for patients with the first attack of CI from 2017 to 2019 in the inpatient EMR system of a Traditional Chinese Medicine (TCM) hospital in Shandong. Patients were divided into 2 groups according to the recurrence of CI. The Mann-Whitney U Test and the chi-square test were used for statistical analysis. And the binary Logistic regression model and the Cox proportional hazards model were used to explore the risk factors affecting the recurrence of patients with CI and the factors affecting the recurrence days of patients with CI, respectively. Finally, 4597 patients with the first attack of CI were included, including 618 patients (13.44%) in the "recurrent CI group" and 3979 patients (86.56%) in the "non-recurrent CI group". Binary Logistic regression analysis showed that LOS (OR=1.035), type 2 diabetes mellitus (T2D) (OR=2.695), CMD (OR=3.272) and PLT (OR=2.628) were risk factors for recurrence in patients with CI. The results of Cox proportional hazards model analysis showed that the LOS at the first onset (HR=1.009) were the promoting factors affecting the recurrence days of patients with CI, and the CMD (HR=0.509) was the hindering factor affecting the recurrence days of patients with CI. This study proved the treatment of patients with CI with TCM decoction after discharge can delay the recurrence of CI. At the same time, attention should be paid to the treatment of patients with combined diseases, and the patients should be discharged after their condition being stable. When the patient was discharged from the hospital, a complete discharge doctor's order should be formulated to prevent recurrence, including medication for comorbid diseases, anti-platelet therapy, etc. In turn, it can improve the prognosis, reduce the recurrence, readmission rates, and reduce the disease burden of patients with CI.

recurrence of cerebral infarction  /  risk factors  /  binary Logistic regression model  /  Cox proportional hazards model