Murakami Tsuyoshi, Feeney Daniel A, Willey Jennifer L, Carlin Bradley P
Department of Veterinary Clinical Sciences, College of Veterinary Medicine University of Minnesota, Saint Paul, MN 55108.
Am J Vet Res. 2014 Mar;75(3):251-9. doi: 10.2460/ajvr.75.3.251.
To determine the accuracy of neurologic data, survey radiographic results, or both for localization of the site of thoracolumbar intervertebral disk herniation in dogs.
338 dogs with surgically confirmed intervertebral disk herniation from disk spaces T10-11 to L6-7.
Medical records and archived survey radiographs were reviewed for each case. Data were analyzed with multivariable logistic regression models. Three models were fit to develop subsets of the data consisting of survey radiographic data, neurologic examination data, and a combination of survey radiographic and neurologic examination data. The resulting models were validated by evaluating predictive performance against a validation subset of the data.
Models incorporating survey radiographic data and a combination of survey radiographic and neurologic data had similar predictive ability and performed better than the model based solely on neurologic data but resulted in substantial errors in predictions.
A combination of neurologic examination data as recorded in the medical records and radiographic data did not enhance predictive performance of multivariable logistic regression models over models limited to radiographic data. Neurologic and radiographic findings should not be used to completely exclude areas in an abnormal spinal cord region from further evaluation with advanced imaging.
确定神经学数据、X线检查结果或两者对于犬胸腰椎椎间盘突出部位定位的准确性。
338只经手术证实为T10 - 11至L6 - 7椎间盘间隙椎间盘突出的犬。
对每例病例的病历和存档的X线检查片进行回顾。数据采用多变量逻辑回归模型进行分析。拟合三个模型以生成由X线检查数据、神经学检查数据以及X线检查和神经学检查数据组合构成的数据子集。通过针对数据的验证子集评估预测性能来验证所得模型。
纳入X线检查数据以及X线检查和神经学数据组合的模型具有相似的预测能力，且比仅基于神经学数据的模型表现更好，但在预测中仍存在大量误差。
病历中记录的神经学检查数据与X线数据的组合，在多变量逻辑回归模型中，相较于仅限于X线数据的模型，并未提高预测性能。神经学和X线检查结果不应被用于完全排除异常脊髓区域中的某些部位进行进一步的高级影像学评估。
