@article{ref1,
title="Mortality prediction and long-term outcomes for civilian cerebral gunshot wounds: a decision-tree algorithm based on a single trauma center",
journal="Journal of clinical neuroscience",
year="2020",
author="Kim, Lily H. and Quon, Jennifer L. and Cage, Tene A. and Lee, Marco B. and Pham, Lan and Singh, Harminder",
volume="ePub",
number="ePub",
pages="ePub-ePub",
abstract="Gunshot wounds (GSW) are one of the most lethal forms of head trauma. The lack of clear guidelines for civilian GSW complicates surgical management. We aimed to develop a decision-tree algorithm for mortality prediction and report long-term outcomes on survivors based on 15-year data from our level 1 trauma center. We retrospectively reviewed 96 consecutive patients who presented with cerebral GSWs between 2003 and 2018. Clinical information from our trauma database, EMR, and relevant imaging scans was reviewed. A decision-tree model was constructed based on variables showing significant differences between survivors and non-survivors. After excluding patients who died at arrival, 54 patients with radiologically confirmed intracranial injury were included. Compared to survivors (51.9%), non-survivors (48.1%) were significantly more likely to have perforating (entry and exit wound), as opposed to penetrating (entry wound only), injuries. Bi-hemispheric and posterior fossa involvement, cerebral herniation, and intraventricular hemorrhage were more commonly present in non-survivors. Based on the decision-tree, Glasgow Coma Scale (GCS) > 8 and penetrating, uni-hemispheric injury predicted survival. Among patients with GCS ≤ 8 and normal pupillary response, lack of 1) posterior fossa involvement, 2) cerebral herniation, 3) bi-hemispheric injury, and 4) intraventricular hemorrhage, were associated with survival. Favorable long-term outcomes (mean follow-up 34.4 months) were possible for survivors who required neurosurgery and stable patients who were conservatively managed. We applied clinical and radiological characteristics that predicted survival to construct a decision-tree to facilitate surgical decision-making for GSW. Further validation of the algorithm in a large patient setting is recommended.<br><br>Copyright © 2020 Elsevier Ltd. All rights reserved.<p /> <p>Language: en</p>",
language="en",
issn="0967-5868",
doi="10.1016/j.jocn.2020.03.027",
url="http://dx.doi.org/10.1016/j.jocn.2020.03.027"
}