Ultra-Early Autonomic Dysfunction Characterization After Severe Traumatic Brain Injury

Tuesday, March 24, 2026

8:45 AM - 9:45 AM Central Time

Location: Connections Central - RST 06

Pattrapun Wongsripuemtet, MD (she/her/hers)

North Carolina, THA

Disclosure(s): No relevant financial relationship(s) to disclose.
VK

Vijay Krishnamoorthy, MD, PhD

Duke University

Disclosure information not submitted.
TO

Tetsu Ohnuma, MD, MPH, PhD (he/him/his)

Duke University, North Carolina

Disclosure(s): No relevant financial relationship(s) to disclose.
JN

Jarret Novak, BS

Student
Campbell University

Disclosure information not submitted.
KD

Kejun Dong, PhD

Post-doctoral Researcher
Emory University

Disclosure information not submitted.
ZW

Zigui Wang, BS, MS

Student
Duke University

Disclosure information not submitted.
MV

Monica Vavilala, MD

Professor
University of Washington

Disclosure information not submitted.
JM

Joseph Miller, MD

Associate Professor
Henry Ford Health System

Disclosure information not submitted.

Introduction: Heart rate variability (HRV) reflects the balance between sympathetic and parasympathetic activity; its imbalance indicates autonomic dysfunction (eAD), a common cardiovascular effect after traumatic brain injury (TBI). This study evaluates HRV metrics across sex and age groups during the first 24 hours of ICU admission in patients with severe TBI (sTBI).

Methods: We conducted a secondary analysis of patients with sTBI enrolled in the BOOST-3, an ongoing clinical trial that began in 2019. We included sTBI patient who had available continuous hemodynamic waveform data. Time-synchronized lead II ECG signals were collected and segmented into five-minute epochs during the first 24 hours of ICU admission. We extracted key HRV indices: root mean square of successive differences (RMSSD), standard deviation of normal-to-normal intervals (SDNN). Descriptive statistics summarized the data, and group comparisons assessed differences in HRV metrics between males and females and across age groups. Correlations between age and HRV metrics were assessed using Pearson’s correlation coefficients.

Results: This study included a total of 54 patients, the majority of whom were non-Hispanic White (50%), male (77.8%), and below the age of 45 (59.3%). The mean (SD) of GCS was 5.83(1.71). No statistically significant differences in HRV metrics were observed between sexes or age groups. Mean (SD) RMSSD was 48.55 ms (36.12) in males vs. 49.67 ms (33.87) in females (p = 0.894), and 53.46 ms (39.30) in patients < 45 vs. 42.71 ms (29.82) in those ≥45 (p = 0.259). Mean SDNN was 46.37 ms (29.11) in males vs. 47.56 ms (29.43) in females (p = 0.903); younger patients had higher SDNN (51.08 ms [31.73]) than older patients (41.48 ms [24.87], p = 0.219). Correlations between age and HRV metrics ranged from –0.107 to –0.236.

Conclusions: No statistically significant differences in ultra early HRV metrics were observed by sex or age in adult sTBI patients. These findings highlight HRV metrics in sTBI population and underscore the need for further research to better evaluate the prognostic utility of HRV in this population.