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| Xia Li,Chao Lü,Jun Wang,Yi Wan,Shu-Hui Dai,Lei Zhang,Xue-An Hu,Xiao-Fan Jiang,Zhou Fei.[J].Chin J Traumatol,2020,23(5):284-289. [doi] |
| Establishment and validation of a model for brain injury state evaluation and prognosis prediction |
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| DOI： |
| KeyWord: Traumatic brain injuriesPrognosisInternational mission for prognosis andanalysis of clinical trials |
| FundProject: |
| Author Name | Affiliation | | Xia Li | Department of Neurosurgery, Xijing Hospital, Fourth Military Medical University, Xi'an 710032, China | | Chao Lü | Neurosurgical Institute of PLA, Xi'an 710032, China | | Jun Wang | Department of Digestive Surgery, Xijing Hospital, Fourth Military Medical University, Xi'an 710032, China | | Yi Wan | Department of Statistics, School of Preventive Medicine, Fourth Military Medical University, Xi'an 710032, China | | Shu-Hui Dai | Department of Neurosurgery, Xijing Hospital, Fourth Military Medical University, Xi'an 710032, China | | Lei Zhang | Department of Neurosurgery, Xijing Hospital, Fourth Military Medical University, Xi'an 710032, China | | Xue-An Hu | Department of Neurosurgery, Xijing Hospital, Fourth Military Medical University, Xi'an 710032, China | | Xiao-Fan Jiang | Department of Neurosurgery, Xijing Hospital, Fourth Military Medical University, Xi'an 710032, China | | Zhou Fei | Department of Neurosurgery, Xijing Hospital, Fourth Military Medical University, Xi'an 710032, China |
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| Abstract: |
| Purpose: Traumatic brain injury (TBI) is one of the leading causes of disability and death in modern times, whose evaluation and prognosis prediction have been one of the most critical issues in TBI management. However, the existed models for the abovementioned purposes were defective to varying degrees. This study aims to establish an ideal brain injury state clinical prediction model (BISCPM).
Methods: This study was a retrospective design. The six-month outcomes of patients were selected as the end point event. BISCPM was established by using the split-sample technology, and externally validated via different tests of comparison between the observed and predicted six-month mortality in validating group. TBI patients admitted from July 2006 to June 2012 were recruited and randomly divided into establishing model group and validating model group. Twenty-one scoring indicators were included in BISCPM and divided into three parts, A, B, and C. Part A included movement, pupillary reflex and diameter, CT parameters, and secondary brain insult factors, etc. Part B was age and part C was medical history of the patients. The total score of part A, B and C was final score of BISCPM.
Results: Altogether 1156 TBI patients were included with 578 cases in each group. The score of BISCPM from validating group ranged from 2.75 to 31.94, averaging 13.64 ± 5.59. There was not statistical difference between observed and predicted mortality for validating group. The discrimination validation showed that the BISCPM is superior to international mission for prognosis and analysis of clinical trials
(IMPACT) lab model.
Conclusion: BISCPM is an effective model for state evaluation and prognosis prediction of TBI patients. The use of BISCPM could be of great significance for decision-making in management of TBI. |
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