Overview of Geriatric Trauma in an Urban Trauma Center in Eastern China: Implications from Computational Intelligence for Localized Trauma-Specific Frailty Index System Design
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Published:2023-04-18
Issue:1
Volume:16
Page:
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ISSN:1875-6883
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Container-title:International Journal of Computational Intelligence Systems
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language:en
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Short-container-title:Int J Comput Intell Syst
Author:
Dong Sheng,Wu Tie,Wu Yi-Feng,Min Zu-Liang,Xue Ming-Yu
Abstract
AbstractDue to the lifestyle and activity of the aging population, it is expected that geriatric trauma will increase and become one of the major challenges in health care. The objective of this study was to determine epidemiological differences between geriatric trauma patients and their younger counterparts, and to find the implications for localized Trauma-Specific Frailty Index (TSFI) system design. This study was a retrospective analysis of adult patients registered in the Trauma Registry, comparisons were made between the geriatric patients, aged over 65 years old, and the younger patients, aged 18–64 years old. Variables were collected include demography, injury mechanism, type, severity of injuries sustained, and outcomes. From July 2018 to July 2021, 2594 trauma patients were evaluated. Injury severity score (ISS) in the geriatric patients’ group is not higher than the younger patients’ group statistically (P = 0.066), and results in increased ICU occupancy and mortality risk as compared with the younger patients (P < 0.05). The majority of geriatric patients suffered falls from low heights and traffic accidents. The geriatric patients most suffered isolated injuries of the extremities/pelvis (31.8%) commonly. In contrast to the younger patients, they had more injuries of the head/neck or polytrauma (P < 0.05). This study provided a snapshot of the trauma burden in a proportion of the urban geriatric patients in Eastern China. The geriatric patients are unlike their younger counterparts, and their unique features should be considered in the future development of computational intelligence, particularly in the case of localized TSFI system design.
Funder
hospital-level funding of Wuxi No.9 People’s Hospital
Publisher
Springer Science and Business Media LLC
Subject
Computational Mathematics,General Computer Science
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