• Jihye Kim, Hwan Ryu, Seok Woo Kim, Jae-Keun Oh, and Tae-Hwan Kim.
• Division of Infection, Department of Pediatrics, Kangdong Sacred Heart Hospital, Hallym University College of Medicine, Seoul, Korea.
• Spine. 2021 Sep 15; 46 (18): 1207-1217.

Study DesignA retrospective cohort study.ObjectiveThe aim of this study was to develop recurrence-prediction models of pyogenic vertebral osteomyelitis (PVO).Summary Of Background DataPrediction of recurrence in PVO is crucial to avoid additional prolonged antibiotic therapy and aggressive spinal surgery and to reduce mortality. However, prediction of PVO recurrence by previously identified, initial risk factors is limited in PVO patients who exceptionally require prolonged antibiotic therapy and experience various clinical events during the treatment. We hypothesized that time-series analysis of sequential C-reactive protein (CRP) routinely measured to estimate the response to the antibiotics in PVO patients could reflect such long treatment process and increase the power of the recurrence-prediction model.MethodsA retrospective study was performed to develop a PVO recurrence-prediction model, including initial risk factors and time-series data of CRP. Of 704 PVO patients, 493 and 211 were divided into training and test cohorts, respectively. Conventional stepwise logistic regression and artificial neural network (ANN) models were created from the training cohort, and the predictions of recurrence in the test cohort were compared.ResultsPrediction models using initial risk factors showed poor sensitivity (4.7%) in both conventional logistic model and ANN models. However, baseline ANN models using time-series CRP data showed remarkably increased sensitivity (55.8%-60.5%). Ensemble ANN model using both initial risk factors and time-series CRP data showed additional benefit in prediction power.ConclusionThe recurrence-prediction models for PVO created only using the initial risk factors showed low sensitivity, regardless of statistical method. However, ANN models using time-series data of CRP values and their ensemble model showed considerably increased prediction power. Therefore, clinicians treating PVO patients should pay attention to the treatment response including changes of CRP levels to identify high-risk patients for recurrence, and further studies to develop recurrence-prediction model for PVO should focus on the treatment response rather than initial risk factors.Level of Evidence: 4.Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.

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