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Prediction of Minimally Conscious State With Brain Stem Reflexes in Unconscious Patients After Traumatic Brain Injury

Bao, Yun MD, PhD*; Mao, Jian MD, PhD; Mei, Fen PhD; Liu, Fan MD, PhD*; Qi, Songtao MD, PhD*; Qiu, Binghui MD, PhD*

doi: 10.1097/SCS.0000000000005404
Original Articles

Objective: To evaluate the predictive power of the brain stem reflexes (BSRs) for minimally conscious state in unconscious patients after traumatic brain injury.

Materials and Methods: A total of 120 patients with duration of unconsciousness were enrolled in this study. BSRs were recorded 14 days after Traumatic brain injury, and classified into 3 grades. Predictors including BSRs, age, sex, Glasgow Coma Scale (GCS), and cause of injury were also analyzed, respectively. The outcome was divided into 2 groups including unconscious group and minimally conscious state (MCS) group.

Results: Seventy-two of 120 were minimally conscious and 48 of 120 were unconscious at 6 months from the onset of injury. The BSRs outmatched the predictive accuracy of the GCS for outcome (AUROC, 0.853; 95% confidence interval, 0.753–0.953; and AUROC, 0.655; 95% confidence interval, 0.512–0.799, respectively). BSRs grade (P < 0.001) and GCS (P < 0.05) were significantly associated with the outcome. The accuracy of the whole regression model for predicting unconscious and MCS was 91.7% and 79.2%, respectively.

Conclusion: The BSRs grade shows a significantly higher accuracy for prediction of MCS compared with the GCS. BSRs grade is a simple, yet reliable and stratification tool for early decision making.

*Department of Neurosurgery

Nanfang Neurosurgery Research Institution, Nanfang hospital, Southern Medical University, Guangzhou City, China.

Address correspondence and reprint requests to Binghui Qiu, MD, PhD, and Songtao Qi, MD, PhD, Southern Medical University, Guangzhou Dadao Bei Street 1838#, Guangzhou, PR China; E-mails:;

Received 6 October, 2018

Accepted 13 January, 2019

JM is the co-first author of this article.

This study was supported by the National Science and Technology Infrastructure Program (2014BAI04B01), Scienceand Technology Planning Project of Guangdong Province, China (2016A020213006) (2017A030303021), Chinese National Natural Science Foundation (81701197), Natural Science Foundation of Guangdong Province (2017A030310111), President Foundation of Nanfang Hospital, Southern Medical University (2017B009).

The authors report no conflicts of interest.

© 2019 by Mutaz B. Habal, MD.