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World Journal of Emergency Medicine ›› 2021, Vol. 12 ›› Issue (3): 179-184.doi: 10.5847/wjem.j.1920-8642.2021.03.003

• Original Articles • Previous Articles     Next Articles

Risk factors and predictive model of adrenocortical insufficiency in patients with traumatic brain injury

Gui-long Feng1, Miao-miao Zheng2, Shi-hong Yao3, Yin-qi Li3, Shao-jun Zhang4(), Wei-jing Wen1, Kai Fan1, Jia-li Zhang1, Xiao Zhang1   

  1. 1 Department of Emergency, the First Hospital of Shanxi Medical University, Taiyuan 030001, China
    2 Department of Emergency, Zhenjiang First People’s Hospital, Zhenjiang 212000, China
    3 Department of Emergency, Yuncheng Central Hospital, Yuncheng 044500, China
    4 Department of Endocrinology, the Fourth Affiliated Hospital, Zhejiang University School of Medicine,Yiwu 322000, China
  • Received:2020-05-20 Accepted:2021-03-15 Online:2021-06-01 Published:2021-05-31
  • Contact: Shao-jun Zhang E-mail:8020221@zju.edu.cn

Abstract:

BACKGROUND: Neuroendocrine dysfunction after traumatic brain injury (TBI) has received increased attention due to its impact on the recovery of neural function. The purpose of this study is to investigate the incidence and risk factors of adrenocortical insufficiency (AI) after TBI to reveal independent predictors and build a prediction model of AI after TBI.

METHODS: Enrolled patients were grouped into the AI and non-AI groups. Fourteen preset impact factors were recorded. Patients were regrouped according to each impact factor as a categorical variable. Univariate and multiple logistic regression analyses were performed to screen the related independent risk factors of AI after TBI and develop the predictive model.

RESULTS: A total of 108 patients were recruited, of whom 34 (31.5%) patients had AI. Nine factors (age, Glasgow Coma Scale [GCS] score on admission, mean arterial pressure [MAP], urinary volume, serum sodium level, cerebral hernia, frontal lobe contusion, diffuse axonal injury [DAI], and skull base fracture) were probably related to AI after TBI. Three factors (urinary volume [X4], serum sodium level [X5], and DAI [X8]) were independent variables, based on which a prediction model was developed (logit P= -3.552+2.583X4+2.235X5+2.269X8).

CONCLUSIONS: The incidence of AI after TBI is high. Factors such as age, GCS score, MAP, urinary volume, serum sodium level, cerebral hernia, frontal lobe contusion, DAI, and skull base fracture are probably related to AI after TBI. Urinary volume, serum sodium level, and DAI are the independent predictors of AI after TBI.

Key words: Adrenocortical insufficiency, Risk factor, Predictor, Traumatic brain injury