Analyzing Continuous Physiologic Data to Find Hemodynamic Signatures Associated With New Brain Injury After Congenital Heart Surgery

Abstract

Continuous data capture technology is becoming more common. Establishing analytic approaches for continuous data could aid in understanding the relationship between physiology and clinical outcomes.

Objectives: Our objective was to design a retrospective analysis for continuous physiologic measurements and their relationship with new brain injury over time after cardiac surgery.

Design setting and participants: Retrospective cohort study in the Cardiac Critical Care Unit at the Hospital for Sick Children in patients after repair of transposition of the great arteries (TGA) or single ventricle (SV) lesions.

Main outcomes and measures: Continuously acquired physiologic measurements for up to 72 hours after cardiac surgery were analyzed for association with new brain injury by MRI. Distributions of heart rate (HR), systolic blood pressure (BP), and oxygen saturation (Spo₂) for SV and TGA were analyzed graphically and with descriptive statistics over postoperative time for data-driven variable selection. Mixed-effects regression analyses characterized relationships between HR, BP, and Spo₂ and new brain injury over time while accounting for variation between patients, measurement heterogeneity, and missingness.

Results: Seventy-seven patients (60 TGA; 17 SV) were included. New brain injury was seen in 26 (34%). In SV patients, with and without new brain injury, respectively, in the first 24 hours after cardiac surgery, the median (interquartile range) HR was 172.0 beats/min (bpm) (169.7-176.0 bpm) versus 159.6 bpm (145.0-167.0 bpm); systolic BP 74.8 (67.9-78.5 mm Hg) versus 68.9 mm Hg (61.6-70.9 mm Hg). Higher postoperative HR (parameter estimate, 19.4; 95% CI, 7.8-31; p = 0.003 and BP, 8.6; 1.3-15.8; p = 0.024) were associated with new brain injury in SV patients. The strength of this relationship decreased with time.

Conclusions and relevance: Retrospective analysis of continuous physiologic measurements can provide insight into changes in postoperative physiology over time and their relationship with new brain injury. This technique could be applied to assess relationships between physiologic data and many patient interventions or outcomes.

Keywords: brain injuries; congenital heart disease; imaging; pediatric cardiac surgery; statistical model.

Figure 1.

Visualization of physiologic data for transposition of the great arteries (TGA) and single ventricle (SV) patients over time. Mean systolic blood pressure (BP) (A), heart rate (B), and oxygen saturation (Spo₂) (C) over an 18-min time window for each patient graphed over the 72 hr after surgery. Patients with new brain injury are labeled blue and those without new brain injury are labeled red. bpm = beats/min.

Figure 2.

Physiologic data distribution in transposition of the great arteries (TGA) and single ventricle (SV) patients. Median (interquartile range) systolic blood pressure (BP) (A), heart rate (HR) (B), and oxygen saturation (Spo₂) (C). Patients with new brain injury are labeled blue and those without new brain injury are labeled red. bpm = beats/min.

Figure 3.

Regression model fit in sample of single ventricle patient with and without new injury. Patient data points for systolic blood pressure (BP) (A), heart rate (B), and oxygen saturation (Spo₂) (C) shown relative to the line predicted by the model. The patients selected in A illustrate a good model fit in a patient with new brain injury (blue). The patients selected in B illustrates a good model fit in patients without new brain injury (red). The patients selected in C illustrates relatively poor model fit in patients with (blue) or without (red) new brain injury. bpm = beats/min.

Figure 4.

Principal component axis of postoperative physiology in single ventricle patients. Three-dimensional illustration of the 24-hr mean heart rate (HR), oxygen saturation (Spo₂), and systolic blood pressure (BP) reduced into an axis that maximizes the variance of the projected data using principal component analysis. Patients with new postoperative brain injury are labeled blue and those without new postoperative brain injury are labeled red. The circle indicates patient data and the square demonstrates the projected point on the first principal component axis. The resulting axis shows points with high BP, HR, and low Spo₂ on one end and points with low BP, HR, and high Spo₂ on the other. The separation along the axis between patients with and without new brain injury qualitatively suggests that patients varied primarily according to the degree in which they express the phenotype of high BP, HR, and low Spo₂. bpm = beats/min.