Early Autonomic Dysfunction Characterization After Severe Traumatic Brain Injury: A Case Series of Ten Patients

Document Type

Conference Proceeding

Publication Date

5-1-2025

Publication Title

Anesth Analg

Keywords

Anesthesiology

Abstract

Introduction: Traumatic brain injury (TBI) evolves after initial injury and early autonomic dysfunction (eAD) may predict poor outcomes but little is known about eAD after severe TBI. We aimed to characterize early eAD following severe TBI. Methods: We employed a secondary analysis of prospectively collected data from the BOOST-3 Trial of patients with severe TBI. The Moberg monitoring system (CNS Monitor, Moberg ICU Solutions, Amber, Pennsylvania, USA) collected waveform data [cardiac telemetry, arterial blood pressure (ABP), and intracranial pressure (ICP)]. Time-synchronized continuous lead-II cardiac telemetry and ABP waveform data with other vital signs (intracranial pressure, systolic/diastolic/mean ABP, and heart rate) during the first 24 hours of intensive care unit (ICU) stay were examined. We computed heart rate variability metrics to characterize eAD. We divided the continuous monitoring waveforms into 5-minute windows and assessed the signal quality of each segment. For high-quality ECG waveforms, we calculated time-domain metrics: 1) root mean square of successive RR interval differences (RMSSD), 2) standard deviation of RR intervals (SDNN), 3) percentage of successive RR intervals differing by more than 50 milliseconds (PNN50) and 4) a frequency-domain metric (low-to-high-frequency ratio (ratio_lfhf). The eAD metrics were characterized using descriptive statistics, and compared to normal ranges derived from published population mean values: 1) 20–100 ms for normal RMSSD, 2) below 100 ms for normal SDNN, 3) over 3% for normal PNN50, and 4) 1.5–5 for the normal ratio_lfhf. Results: The summary of metrics for all ten patients is presented in Figure 1 and Table 1. All patients had data segments that were abnormal and consistent with autonomic dysfunction within the 24-hour observation period. These abnormalities were observed in both time and frequency domains. Nine patients exhibited abnormalities in RMSSD, eight in PNN50, and all patients showed abnormalities in SDNN and the ratio_lfhf. Particularly, autonomic dysfunction was observed in nearly every segment of SDNN. Furthermore, based on the results in Figure 1 and Table 1, other metrics (such as ABP and ICP) had abnormal values during various segments over the first 24 hours. Conclusions: Measures of autonomic dysfunction revealed that all patients with severe TBI had autonomic dysfunction during the first 24 hours of ICU stay. There was variation in eAD within autonomic dysfunction metric domains (time versus frequency), vital signs, and ICP. Future studies are necessary to define eAD measures and understand implications of eAD on secondary brain injury, multi-organ dysfunction, and clinical outcomes.

Volume

140

Issue

5

First Page

206

Last Page

209

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