1
|
Kishawi SK, Adomshick VJ, Halkiadakis PN, Wilson K, Petitt JC, Brown LR, Claridge JA, Ho VP. Development of Imaging Criteria for Geriatric Blunt Trauma Patients. J Surg Res 2023; 283:879-888. [PMID: 36915016 DOI: 10.1016/j.jss.2022.10.037] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Revised: 10/07/2022] [Accepted: 10/18/2022] [Indexed: 12/12/2022]
Abstract
INTRODUCTION Current decision tools to guide trauma computed tomography (CT) imaging were not validated for use in older patients. We hypothesized that specific clinical variables would be predictive of injury and could be used to guide imaging in this population to minimize risk of missed injury. METHODS Blunt trauma patients aged 65 y and more admitted to a Level 1 trauma center intensive care unit from January 2018 to November 2020 were reviewed for histories, physical examination findings, and demographic information known at the time of presentation. Injuries were defined using the patient's final abbreviated injury score codes, obtained from the trauma registry. Abbreviated injury score codes were categorized by corresponding CT body region: Head, Face, Chest, C-Spine, Abdomen/Pelvis, or T/L-Spine. Variable groupings strongly predictive of injury were tested to identify models with high sensitivity and a negative predictive value. RESULTS We included 608 patients. Median age was 77 y (interquartile range, 70-84.5) and 55% were male. Ground-level fall was the most common injury mechanism. The most commonly injured CT body regions were Head (52%) and Chest (42%). Variable groupings predictive of injury were identified in all body regions. We identified models with 97.8% sensitivity for Head and 98.8% for Face injuries. Sensitivities more than 90% were reached for all except C-Spine and Abdomen/Pelvis. CONCLUSIONS Decision aids to guide imaging for older trauma patients are needed to improve consistency and quality of care. We have identified groupings of clinical variables that are predictive of injury to guide CT imaging after geriatric blunt trauma. Further study is needed to refine and validate these models.
Collapse
Affiliation(s)
- Sami K Kishawi
- Department of Surgery, Division of Trauma Surgery, Acute Care Surgery, Critical Care, and Burns, MetroHealth Medical Center, Cleveland, Ohio; Case Western Reserve University School of Medicine, Cleveland, Ohio
| | - Victoria J Adomshick
- Department of Surgery, Division of Trauma Surgery, Acute Care Surgery, Critical Care, and Burns, MetroHealth Medical Center, Cleveland, Ohio; Case Western Reserve University School of Medicine, Cleveland, Ohio
| | - Penelope N Halkiadakis
- Department of Surgery, Division of Trauma Surgery, Acute Care Surgery, Critical Care, and Burns, MetroHealth Medical Center, Cleveland, Ohio; Case Western Reserve University School of Medicine, Cleveland, Ohio
| | - Keira Wilson
- Department of Surgery, Division of Trauma Surgery, Acute Care Surgery, Critical Care, and Burns, MetroHealth Medical Center, Cleveland, Ohio; Northeast Ohio Medical University, Rootstown, Ohio
| | - Jordan C Petitt
- Department of Surgery, Division of Trauma Surgery, Acute Care Surgery, Critical Care, and Burns, MetroHealth Medical Center, Cleveland, Ohio; Case Western Reserve University School of Medicine, Cleveland, Ohio
| | - Laura R Brown
- Department of Surgery, Division of Trauma Surgery, Acute Care Surgery, Critical Care, and Burns, MetroHealth Medical Center, Cleveland, Ohio; Case Western Reserve University School of Medicine, Cleveland, Ohio
| | - Jeffrey A Claridge
- Department of Surgery, Division of Trauma Surgery, Acute Care Surgery, Critical Care, and Burns, MetroHealth Medical Center, Cleveland, Ohio; Case Western Reserve University School of Medicine, Cleveland, Ohio
| | - Vanessa P Ho
- Department of Surgery, Division of Trauma Surgery, Acute Care Surgery, Critical Care, and Burns, MetroHealth Medical Center, Cleveland, Ohio; Case Western Reserve University School of Medicine, Cleveland, Ohio; Case Western Reserve University, Department of Population and Quantitative Health Sciences, Cleveland, Ohio.
| |
Collapse
|