Despite the increasing incidence of spinal epidural abscess (SEA), the baseline parameters potentially predictive of treatment failure remain poorly characterized. In this study, the authors identify the relevant baseline parameters that predict multimodal treatment failure in patients with either intravenous drug use (IVDU)–associated SEA or non-IVDU–associated SEA.
The authors reviewed the electronic medical records of a large institutional series of consecutive patients with diagnosed SEA between January 2011 and December 2017 to characterize epidemiological trends as well as the complement of baseline measures that are predictive of failure after multimodal treatment in patients with and without concomitant IVDU. The independent impact of clinical and imaging factors in detecting treatment failure was assessed by performing stepwise binary logistic regression analysis.
A total of 324 consecutive patients with diagnosed SEA were identified. Overall, 226 patients (69.8%) had SEA related to other causes and 98 (30.2%) had a history of recent IVDU. While non-IVDU SEA admission rates remained constant, year-over-year admissions of patients with IVDU SEA nearly tripled. At baseline, patients with IVDU SEA were distinct in many respects including younger age, greater unemployment and disability, less frequent diabetes mellitus (DM), and more frequent methicillin-resistant Staphylococcus aureus infection. However, differences in length of stay, loss to follow-up, and treatment failure did not reach statistical significance between the groups. The authors constructed independent multivariate logistic regression models for treatment failure based on identified parameters in the two cohorts. For the non-IVDU cohort, the authors identified four variables as independent factors: DM, hepatitis B/C, osteomyelitis, and compression deformity severity. In contrast, for patients with IVDU, the authors identified three variables: albumin, endocarditis, and endplate destruction. Receiver operating characteristic and area under the curve (AUC) analyses were undertaken for the multivariate models predicting the likelihood of treatment failure in the two cohorts (AUC = 0.88 and 0.89, respectively), demonstrating that the derived models could adequately predict the risk of multimodal treatment failure. Treatment failure risk factor point scales were derived for the identified variables separately for both cohorts.
Patients with IVDU SEA represent a unique population with a distinct set of baseline parameters that predict treatment failure. Identification of relevant prognosticating factors will allow for the design of tailored treatment and follow-up regimens.