# From acute injury to chronic comorbidity: Interrupted time series modeling of traumatic brain injury impact among post-9/11 veterans

## TL;DR

This study uses time series modeling to show how traumatic brain injury impacts veterans' health both immediately and in the long term.

## Contribution

A novel application of interrupted time series modeling to bridge early and late health impacts of TBI in post-9/11 veterans.

## Key findings

- TBI was linked to increased rates of PTSD, headaches, and adjustment disorders in the month of injury.
- Long-term, TBI was associated with higher rates of substance use and mental health disorders.
- Cognitive dysfunction and vestibular issues showed the highest incidence rate ratios compared to controls.

## Abstract

Traumatic brain injury (TBI) is associated with a variety of adverse health outcomes that display complex behavior over time. The objective of this study was to investigate both the early and late health impacts of TBI within a single framework. This study evaluated TBI associations among a cohort of post-9/11 Veterans with TBI documented between 2008 and 2017 in Veteran Health Administration (VHA) records. The cohort included 108,408 post-9/11 Veterans with any history of TBI documentation between 2008–2017 who were demographically matched with 108,408 TBI negative controls. Interrupted time series (ITS) models were used to fit the prevalence of comorbidities over time (±6 years from index date, i.e., date of first TBI). Three ITS measures were modeled for each comorbidity: 1) The incidence rate (IR) in the month of TBI index date, 2) The incidence rate ratio (IRR) between TBI and control groups in the month of index date, and 3) Long-term changes in year-over-year diagnosis rates, i.e., the annual incidence rate difference (IRD) before vs. after index date. Overall, TBI was associated with conditions related to somatic, cognitive, and psychological outcomes including headache, cognitive dysfunction, and PTSD. Neurological events were found to be elevated within the month of TBI documentation. Conditions with the largest IR were post-traumatic stress disorder (PTSD) (+29%, p < 0.001), headache (+22%, p < 0.001), and adjustment disorder (+22%, p < 0.001). Conditions with the highest IRR across TBI and control groups were cognitive dysfunction (474, p < 0.001), vestibular dysfunction (137, p < 0.001), and stroke (72, p < 0.001). Long term, the conditions with the highest IRD were substance use disorders (p < 0.001) and mental health conditions (p < 0.001). This work demonstrates how ITS modeling can help bridge traditional divides between early and late paradigms of TBI investigation to help inform research and care for Veterans living with TBI.