Autonomic Function Following Concussion in Youth Athletes: An Exploration of Heart Rate Variability Using 24-hour Recording Methodology.

Abstract

Participation in organized sports makes a significant contribution to youth development, but places youth at a higher risk for sustaining a concussion. To date, return-to-activity decision-making has been anchored in the monitoring of self-reported concussion symptoms and neurocognitive testing. However, multi-modal assessments that corroborate objective physiological measures with traditional subjective symptom reporting are needed and can be valuable. Heart rate variability (HRV) is a non-invasive physiological indicator of the autonomic nervous system, capturing the reciprocal interplay between the sympathetic and parasympathetic nervous systems. There is a dearth of literature exploring the effect of concussion on HRV in youth athletes, and developmental differences preclude the application of adult findings to a pediatric population. Further, the current state of HRV methodology has primarily included short-term (5-15 min) recordings, by using resting state or short-term physical exertion testing to elucidate changes following concussion. The novelty in utilizing a 24 h recording methodology is that it has the potential to capture natural variation in autonomic function, directly related to the activities a youth athlete performs on a regular basis. Within a prospective, longitudinal research setting, this novel approach to quantifying autonomic function can provide important information regarding the recovery trajectory, alongside traditional self-report symptom measures. Our objectives regarding a 24 h recording methodology were to (1) evaluate the physiological effects of a concussion in youth athletes, and (2) describe the trajectory of physiological change, while considering the resolution of self-reported post-concussion symptoms. To achieve these objectives, non-invasive sensor technology was implemented. The raw beat-to-beat time intervals captured can be transformed to derive time domain and frequency domain measures, which reflect an individual's ability to adapt and be flexible to their ever-changing environment. By using non-invasive heart rate technology, autonomic function can be quantified outside of a traditional controlled research setting.