The epidemiology of traumatic brain injuries in the fastest-paced city in China: a retrospective study

Jun-Feng Zou; Hai-Lan Fang; Jing Zheng; Yu-Qiang Ma; Chu-Wei Wu; Gao-Jian Su; Xian-Sheng Liu; Jun Liu; Jie Gao; Jie-Hua Zhang; Dong-Liang Zhu; Xin Shi; Xian-Jian Huang

doi:10.3389/fneur.2023.1255117

The epidemiology of traumatic brain injuries in the fastest-paced city in China: a retrospective study

Front Neurol. 2023 Nov 9:14:1255117. doi: 10.3389/fneur.2023.1255117. eCollection 2023.

Authors

Jun-Feng Zou^{1

2}, Hai-Lan Fang³, Jing Zheng⁴, Yu-Qiang Ma⁵, Chu-Wei Wu¹, Gao-Jian Su¹, Xian-Sheng Liu¹, Jun Liu¹, Jie Gao¹, Jie-Hua Zhang¹, Dong-Liang Zhu¹, Xin Shi^{6

7}, Xian-Jian Huang¹

Affiliations

¹ Department of Neurosurgery, Shenzhen Key Laboratory of Neurosurgery, The First Affiliated Hospital of Shenzhen University, Shenzhen Second People's Hospital, Shenzhen, China.
² Department of Emergency, Shenzhen Hyzen Hospital, Shenzhen, China.
³ Healthcare Services Department, Yantai City Health Comprehensive Service Center, Yantai, China.
⁴ Shenzhen Health Development Research and Data Management Center, Shenzhen Municipal Health Commission, Shenzhen, China.
⁵ Department of Neurosurgery, Peking University Shenzhen Hospital, Shenzhen, China.
⁶ China Medical University, Shenyang, China.
⁷ School of Maths and Information Science, Shandong Technology and Business University, Yantai, China.

Abstract

Introduction: Traumatic brain injury (TBI) seriously affects the quality of human health and the prognosis of the patient, but the epidemiological characteristics of TBI can vary among populations. Numerous changes have occurred in the epidemiological characteristics of individuals with TBI in the fast-paced city of Shenzhen, China. However, little is known about these characteristics. This study aimed to investigate the changes in TBI epidemiology, help clinicians improve medical treatment.

Methods: In this retrospective cross-sectional analysis, we collected the data of 4,229 patients with TBI admitted to 20 hospitals in Shenzhen in 2017. We collected data on age, gender, cause and severity of the injury, eventual diagnosis, time from injury to admission in a neurosurgery department, and patient outcomes. Two neurosurgeons simultaneously collected the data. We compared these results with a similar study conducted in Shenzhen during the period from 1994 to 2003 to clarify and explain the changes in the epidemiological characteristics of TBI.

Results: The majority of respondents were men [2,830 (66.9%)]. The mean age was 32.5 ± 21.4 years. The youngest patient was less than 1 year old, and the oldest patient was 101 years old. A total of 3,947 (93.3%) patients had a favorable outcome, 219 (5.2%) had an unfavorable outcome, and 63 (1.5%) died. The predominant external cause was falls (1,779 [42.1%]); this was the most common cause of TBI in children and older adults. Riders of electric bicycles (423 [29.0%]) were the most vulnerable to traffic accident-related injuries. Time greater than 50 h from injury to admission to a neurosurgical department had a significant effect on prognosis (p < 0.001).

Conclusion: The epidemiological characteristics of TBI have changed significantly over the past 20 years. Falls, rather than traffic accidents, were the most common cause of TBI. Further research is needed to devise solutions to decrease the incidence of falls and improve the outcomes of TBI.

Keywords: China; cross-sectional study; epidemiology; public health; traumatic brain injury.

Grants and funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This study was supported by the Natural Science Foundation of China (81301062), the Basic Research Projects of the Shenzhen Science and Technology Program (JCYJ20180228163034627); Shenzhen Double Chain Grant [2018] 256 and the Shenzhen Municipal Health Commission Discipline Construction Capacity Improvement Project (SZXJ2018057); Immersion Technology and Evaluation Shandong Engineering Research Center (2022); Immersive Smart Devices for Healthcare System R&D and Industrial Application Innovation Platform (2022); The National Natural Science Foundation of China (72074104); National Natural Science Foundation of China (61972235). These funds covered staff expenses, transport expenses, hotel expenses, among others.