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- Title
Clinical Identifiers for Detecting Underlying Closed Cervical Fractures.
- Authors
Cook, Chad E.; Sizer, Phillip S.; Isaacs, Robert E.; Wright, Alexis
- Abstract
Background Although uncommon, closed cervical fractures ( CCFs) may present in orthopedic clinical settings despite previous workup. The objective of this study was to describe the characteristics associated with missed CCF. Methods The study was a retrospective database exploration of a cohort of subjects within a department of surgery with cervical pain. The sample consisted of 162 patients seen for a surgical consult for a number of cervical conditions. The examination time frame represented a clinical examination and imaging confirmation of diagnosis after an original initial visit by another provider. Descriptive and diagnostic accuracy values including sensitivity/specificity and positive/negative likelihood ratios ( LR+/ LR−) were calculated for each targeted variable. Clustered analyses were calculated using the patient history and situational characteristics. Results Eleven patients in the sample were diagnosed with CCF (6.7%). Six variables were significantly associated with a missed CCF. Using these six variables, it was found that failure to exhibit a condition of 2 of the 6 variables (1 or fewer) was the strongest in ruling out the condition ( LR− = 0.0; post-test probability with a negative finding = 0%), whereas a finding of 4 of 6 was the most diagnostic for ruling in the condition ( LR+ = 32; post-test probability with a positive finding = 70%). Conclusions The findings in this sample suggest that select patient history or situational factors are still useful even after initial examination and clinicians must stay vigilant because CCFs may be missed during emergent care screens.
- Subjects
CERVICAL vertebrae; CHI-squared test; CONFIDENCE intervals; DIAGNOSTIC errors; FISHER exact test; LONGITUDINAL method; REGRESSION analysis; STATISTICS; T-test (Statistics); LOGISTIC regression analysis; RETROSPECTIVE studies; RECEIVER operating characteristic curves; CLOSED fractures; DATA analysis software; SYMPTOMS; DIAGNOSIS
- Publication
Pain Practice, 2014, Vol 14, Issue 2, p109
- ISSN
1530-7085
- Publication type
Article
- DOI
10.1111/papr.12061