Cervical spine fractures in patients 65 years and older: a clinical prediction rule for blunt trauma.

PURPOSE: To determine clinical predictors of cervical spine fracture in the elderly and to develop a clinical prediction rule to guide appropriate imaging in high-risk patients. MATERIALS AND METHODS: Institutional review board approval was received with waiver of informed consent. A retrospective case-control study was performed on blunt trauma patients 65 years and older with cervical spine fractures and on randomly selected control subjects without fracture. Potential predictors of fracture were evaluated through simple and multivariate logistic regression. Simple predictors were grouped into clinically similar composite variables and were analyzed with multivariate logistic regression and recursive partitioning. A clinical prediction rule was generated. The receiver operating characteristic curve was calculated and adjusted through bootstrap validation. Absolute cervical spine fracture probabilities were calculated by using Bayes theorem for all elderly patients and for patients who underwent computed tomography. Results were compared with a previous prediction rule for all adults. RESULTS: Composite predictors of fracture in the elderly included focal neurologic deficit (adjusted odds ratio, 17.7; 95% confidence interval [CI]: 3.8, 83.4), severe head injury (odds ratio, 3.2; 95% CI: 1.5, 7.1), high-energy mechanism (odds ratio 6.7; 95% CI: 3.1, 14.8), and moderate-energy mechanism (odds ratio 3.3; 95% CI: 1.3, 8.3). The prediction rule stratified patients into risk groups with fracture probabilities ranging from 0.4% (95% CI: 0.1%, 1.3%) to 24.2% (95% CI: 5.7%, 100%). CONCLUSION: Clinical factors can be used to stratify patients 65 years and older into risk groups with a wide range of probabilities of cervical spine fracture. Knowledge of cervical fracture risk can help guide appropriate imaging in high-risk patients.