Background A consistent approach to cervical spine injury (CSI) clearance for patients 65 and older remains a challenge. Clinical clearance algorithms like the National Emergency X-Radiography Utilisation Study (NEXUS) criteria have variable accuracy and the Canadian C-spine rule excludes older patients. Routine CT of the cervical spine is performed to rule out CSI but at an increased cost and low yield. Herein, we aimed to identify predictive clinical variables to selectively screen older patients for CSI.
Methods The University of Iowa’s trauma registry was interrogated to retrospectively identify all patients 65 years and older who presented with trauma from a ground-level fall from January 2012 to July 2017. The relationship between predictive variables (demographics, NEXUS criteria and distracting injuries) and presence of CSI was examined using the generalised linear modelling (GLM) framework. A training set was used to build the statistical models to identify clinical variables that can be used to predict CSI and a validation set was used to assess the reliability and consistency of the model coefficients estimated from the training set.
Results Overall, 2312 patients ≥65 admitted for ground-level falls were identified; 253 (10.9%) patients had a CSI. Using the GLM framework, the best predictive model for CSI included midline tenderness, focal neurological deficit and signs of trauma to the head/face, with midline tenderness highly predictive of CSI (OR=22.961 (15.178–34.737); p<0.001). The negative predictive value (NPV) for this model was 95.1% (93.9%–96.3%). In the absence of midline tenderness, the best model included focal neurological deficit (OR=2.601 (1.340–5.049); p=0.005) and signs of trauma to the head/face (OR=3.024 (1.898–4.815); p<0.001). The NPV was 94.3% (93.1%–95.5%).
Conclusion Midline tenderness, focal neurological deficit and signs of trauma to the head/face were significant in this older population. The absence of all three variables indicates lower likelihood of CSI for patients≥65. Future observational studies are warranted to prospectively validate this model.
- clinical assessment
- fractures and dislocations
Data availability statement
Data are available upon reasonable request. Requests for data should be send to the listed corresponding author.
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Handling editor Edward Carlton
JE and PZ contributed equally.
Presented at This paper was presented in part at the Region 7 American College of Surgeons Committee on Trauma Resident Paper Competition in both the 2018 (State and Regional level) and the 2019 (State Level) competitions.
Contributors All authors contributed equally to this manuscript. Study concept and design: PZ, JE, CG, DS. Acquisition of the data: ML, JJ, JE, PZ. Analysis and interpretation of the data: YZ, PT-E, PZ, JE, CG, DS. Drafting of the manuscript: JE, PZ, CG, DS. Critical revision of the manuscript for important intellectual content: JE, CG, DS. Statistical expertise: YZ, PT-E.
Funding This study was supported in part by the University of Iowa Institute for Clinical and Translational Science, which is granted with Clinical and Translational Science Award funds from the National Institutes of Health (UL1TR002537). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
Competing interests None declared.
Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.
Provenance and peer review Not commissioned; externally peer reviewed.
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