Abstract: Objective To analyze the association between blood pressure variability （BPV）  and early neurological deterioration (END) in patients with branch atheromatous disease (BAD). 
Methods A total of 200 BAD patients were consecutively enrolled in Aerospace Central Hospital from Jan. 2022 to Jun. 2023, and National Institutes of Health Stroke Scale (NIHSS) score at 1 d, 3 d, and 7 d after admission were recorded. According to the increase in NIHSS score, they were divided into END (n=69) and non-END groups (n=131). The basic data, infarct site,laboratory indicators, and BPV were recorded. The influencing factors between two groups was analyzed using t-test and Logistic regression analysis. The area under receiver operator characteristic (ROC) curve (AUC) was used to analyze the diagnostic value of BPV indicators for END. 
Results The fasting blood glucose, total cholesterol, low-density lipoprotein, infarct site, night mean systolic blood pressure （NMSBP)，  night mean diastolic blood pressure (NMDBP)， 24 hours systolic blood pressure standard deviation (24 hSBP-SD), day systolic blood pressure standard deviation（DSBP-SD）， night systolic blood pressure standard deviation (NSBP-SD), 24 hours diastolic blood pressure standard deviation (24 hDBP-SD), day diastolic blood pressure standard deviation (DDBP-SD), night diastolic blood pressure standard deviation （NDBP-SD)， day systolic blood pressure CV (DSBP- CV), night systolic blood pressure CV (NSBP- CV), 24 hours diastolic blood pressure CV (24 hDBP-CV), and day diastolic blood pressure CV (DDBP-CV) were compared between the two groups, showing significant differences (P＜0.05). T test， Logistic regression analysis and ROC curve were applied to statistical analysis. Logistic regression analysis showed that DSBP-SD, NSBP-SD, and DDBP-CV were independent risk factors for END in BAD patients (P＜0.05). The ROC curve revealed that the AUC of joint indicators of BPV was 0.746, and the specificity and sensitivity were 0. 817 and 0.609 respectively. 
Conclusion Patients with BAD are subjected to END, and BPV is an important influencing factor, which can predict the occurrence of END. The monitoring of BPV provides a new idea for disease diagnosis and treatment. 

Key words: atherosclerosis, blood pressure variability, blood pressure monitoring