Diagnostic accuracy of history taking to assess lumbosacral nerve root compression

Background context: The diagnosis of sciatica is primarily based on history and physical examination. Most physical tests used in isolation show poor diagnostic accuracy. Little is known about the diagnostic accuracy of history items. Purpose: To assess the diagnostic accuracy of history taking for the presence of lumbosacral nerve root compression or disc herniation on magnetic resonance imaging in patients with sciatica. Study design: Cross-sectional diagnostic study. Patient sample: A total of 395 adult patients with severe disabling radicular leg pain of 6 to 12 weeks duration were included. Outcome measures: Lumbosacral nerve root compression and disc herniation on magnetic resonance imaging were independently assessed by two neuroradiologists and one neurosurgeon blinded to any clinical information. Methods: Data were prospectively collected in nine hospitals. History was taken according to a standardized protocol. There were no study-specific conflicts of interest. Results: Exploring the diagnostic odds ratio of 20 history items revealed a significant contribution in diagnosing nerve root compression for "male sex," "pain worse in leg than in back," and "a non-sudden onset." A significant contribution to the diagnosis of a herniated disc was found for "body mass index <30," "a non-sudden onset," and "sensory loss." Multivariate logistic regression analysis of six history items pre-selected from the literature (age, gender, pain worse in leg than in back, sensory loss, muscle weakness, and more pain on coughing/sneezing/straining) revealed an area under the receiver operating characteristic curve of 0.65 (95% confidence interval, 0.58-0.71) for the model diagnosing nerve root compression and an area under the receiver operating characteristic curve of 0.66 (95% confidence interval, 0.58-0.74) for the model diagnosing disc herniation. Conclusions: A few history items used in isolation had significant diagnostic value and the diagnostic accuracy of a model with six pre-selected items was poor.

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