Stratton Alexandra, Faris Peter, Thomas Kenneth
University of Calgary, Calgary, Alberta, Canada.
Global Spine J. 2018 May;8(3):279-285. doi: 10.1177/2192568217719437. Epub 2017 Jul 20.
Retrospective cohort study.
To test the external validity of the 2 published prediction criteria for failure of medical management in patients with spinal epidural abscess (SEA).
Patients with SEA over a 10-year period at a tertiary care center were identified using ICD-10 (International Classification of Diseases, 10th Revision) diagnostic codes; electronic and paper charts were reviewed. The incidence of SEA and the proportion of patients with SEA that were treated medically were calculated. The rate of failure of medical management was determined. The published prediction models were applied to our data to determine how predictive they were of failure in our cohort.
A total of 550 patients were identified using ICD-10 codes, 160 of whom had a magnetic resonance imaging-confirmed diagnosis of SEA. The incidence of SEA was 16 patients per year. Seventy-five patients were found to be intentionally managed medically and were included in the analysis. Thirteen of these 75 patients failed medical management (17%). Based on the published prediction criteria, 26% (Kim et al) and 45% (Patel et al) of our patients were expected to fail.
Published prediction models for failure of medical management of SEA were not valid in our cohort. However, once calibrated to our cohort, Patel's model consisting of positive blood culture, presence of diabetes, white blood cells >12.5, and C-reactive protein >115 was the better model for our data.
回顾性队列研究。
检验已发表的两项关于脊髓硬膜外脓肿(SEA)患者保守治疗失败的预测标准的外部有效性。
使用国际疾病分类第十版(ICD - 10)诊断编码,确定一家三级医疗中心10年间患有SEA的患者;回顾电子病历和纸质病历。计算SEA的发病率以及接受保守治疗的SEA患者比例。确定保守治疗失败率。将已发表的预测模型应用于我们的数据,以确定它们对我们队列中治疗失败的预测能力。
使用ICD - 10编码共识别出550例患者,其中160例经磁共振成像确诊为SEA。SEA的发病率为每年16例患者。发现75例患者接受了保守治疗并纳入分析。这75例患者中有13例保守治疗失败(17%)。根据已发表的预测标准,预计我们的患者中有26%(Kim等人)和45%(Patel等人)会治疗失败。
已发表的SEA保守治疗失败预测模型在我们的队列中无效。然而,一旦根据我们的队列进行校准,由血培养阳性、糖尿病、白细胞>12.5以及C反应蛋白>115组成的Patel模型对我们的数据来说是更好的模型。