The Relationship Between Short-Term Mean Arterial Pressure Variability and Mortality in Critically Ill Patients

Abstract

Background: Increased or decreased blood pressure variability may affect the perfusion of tissues and organs, leading to acute kidney injury and death. This study was conducted to explore the relationship between mean arterial pressure variability and short- and long-term mortality in critically ill patients.

Methods: We used patient data from the MIMIC-III database for cohort study. According to the recorded mean arterial pressure during the first 24 h in the intensive care unit, we calculated each patient's two variability parameters -coefficient of variation and average real variability. The primary outcome was in-hospital mortality and the secondary outcomes were 28-day mortality and 1-year mortality. We conducted smooth spline models to examine the possible nonlinear associations between blood pressure variability and mortality. According to the smoothing curve, we further developed a two-piecewise linear regression model to find out the threshold effect. Multivariable logistic regression or Cox proportional hazards model was used to evaluate the relationship. Kaplan-Meier survival analysis for 28-day and 1-year mortality was performed. Subgroup analysis explored the factors modifying the relationship between them.

Results: A total of 12,867 patients were enrolled in the study, 1,320 in-hospital death, 1,399 28-day death, and 2,734 1-year death occurred. The smooth spline showed death risk was the lowest when average real variability was around 7.2 mmHg. After adjusting for covariates, logistic or Cox regression showed the highest MAP variability level was strongly associated with increased mortality in the hospital (odds ratio: 1.44; 95% CI, 1.21∼1.72), at 28 days (hazard ratio: 1.28; 95% CI, 1.1∼1.5), and at 1 year (hazard ratio: 1.27; 95% CI, 1.14∼1.42) compared with the second level of average real variability group. The survival curve plot showed patients with higher average real variability had a higher risk of 28-day and 1-year mortality. This relationship remained remarkable in patients with low or high Sequential Organ Failure Assessment scores in the sensitivity analysis. The two-piecewise linear regression model showed that lower ARV was a risk factor for 28-day (HR 0.72, 95% CI, 0.57∼0.91) and 1-year mortality (HR 0.81, 95% CI, 0.68∼0.96) when ARV was less than 7.2 mmHg, higher ARV was a risk factor for 28-day mortality (HR 1.1, 95% CI, 1.04∼1.17) and 1-year mortality (HR 1.07, 95% CI, 1.02∼1.12) when ARV was greater than 7.2 mmHg.

Conclusion: Blood pressure variability predicts mortality in critically ill patients. Individuals with higher or lower mean arterial pressure average real variability during the first day in ICU may have an increased risk of death.

Keywords: average real variability; blood pressure variability (BPV); intensive care unit; mean arterial pressure (MAP); mortality.

FIGURE 1

Flowchart of participant selection. A total of 12,867 patients were included in the analysis. MIMIC-III, Multiparameter Intelligent Monitoring in Intensive Care III.

FIGURE 2

Association between MAP variability and mortality. Smooth spline plots of the association between MAP ARV and in-hospital mortality (A) or 28-day mortality (B) or 1-year mortality (C), and the relationship between MAP CV and in-hospital mortality (D) or 28-day mortality (E) or 1-year mortality (F). ARV, average real variability; CV, coefficient of variation; MAP, mean arterial pressure.

FIGURE 3

Kaplan–Meier survival analysis plots for 28-day and 1-year mortality with MAP ARV. The curves show that patients with higher MAP ARV in the ICU had lower rates of 28-day survival (A) and 1-year survival (B). ICU indicates intensive care unit; ARV, average real variability; MAP, mean arterial pressure.