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Updated: Nov 29, 2025

Real-Time Monitoring and Modulation of Blood Pressure in a Rabbit Model of Ischemic Stroke
Published on: February 10, 2023
Blood pressure variability and outcome in acute severe stroke: A post hoc analysis of CHASE-A randomized controlled
Jingjing Zhao1, Fang Yuan1, Feng Fu2
1Department of Neurology, Xijing Hospital, Fourth Military Medical University, Xi'an, China.
The influence of blood pressure variability (BPV) on outcomes in patients with severe stroke is still largely unsettled. Using the data of CHASE trial, the authors calculated the BPV during the acute phase and subacute phase of severe stroke, respectively. The primary outcome was to investigate the relationship between BPV and 90-day modified Rankin scale (mRS) ≥ 3. The BPV was assessed by eight measurements including standard deviation (SD), mean, maximum, minimum, coefficient of variation (CV), successive variation (SV), functional successive variation (FSV), and average real variability (ARV). Then, the SD of SBP was divided into quintiles and compared the quintile using logistic regression in three models. The acute phase included 442 patients, and the subacute phase included 390 patients. After adjustment, six measurements of BPV during the subacute phase rather than acute phase were strongly correlated with outcomes including minimum (odds ratio [OR]: 0.83, 95% confidence interval [CI]: 0.69-0.99, p = .037), SD (OR: 1.10, 95% CI: 1.03-1.17, p = .007), CV (OR: 1.12, 95% CI: 1.03-1.23, p = .012), ARV (OR: 1.13, 95% CI: 1.05-1.20, p < .001), SV (OR: 1.09, 95% CI: 1.04-1.15, p = .001), and FSV (OR: 1.12, 95% CI: 1.05-1.19, p = .001). In the logistic regression, the highest fifth of SD of SBP predicted poor outcome in all three models. In conclusion, the increased BPV was strongly correlated with poor outcomes in the subacute phase of severe stroke, and the magnitude of association was progressively increased when the SD of BP was above 12.
The influence of blood pressure variability (BPV) on outcomes in patients with severe stroke is still largely unsettled. Using the data of CHASE trial, the authors calculated the BPV during the acute phase and subacute phase of severe stroke, respectively. The primary outcome was to investigate the relationship between BPV and 90-day modified Rankin scale (mRS) ≥ 3. The BPV was assessed by eight measurements including standard deviation (SD), mean, maximum, minimum, coefficient of variation (CV), successive variation (SV), functional successive variation (FSV), and average real variability (ARV). Then, the SD of SBP was divided into quintiles and compared the quintile using logistic regression in three models. The acute phase included 442 patients, and the subacute phase included 390 patients. After adjustment, six measurements of BPV during the subacute phase rather than acute phase were strongly correlated with outcomes including minimum (odds ratio [OR]: 0.83, 95% confidence interval [CI]: 0.69-0.99, p = .037), SD (OR: 1.10, 95% CI: 1.03-1.17, p = .007), CV (OR: 1.12, 95% CI: 1.03-1.23, p = .012), ARV (OR: 1.13, 95% CI: 1.05-1.20, p < .001), SV (OR: 1.09, 95% CI: 1.04-1.15, p = .001), and FSV (OR: 1.12, 95% CI: 1.05-1.19, p = .001). In the logistic regression, the highest fifth of SD of SBP predicted poor outcome in all three models. In conclusion, the increased BPV was strongly correlated with poor outcomes in the subacute phase of severe stroke, and the magnitude of association was progressively increased when the SD of BP was above 12.
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