Clinical prediction for surgical versus nonsurgical interventions in patients with vertebral osteomyelitis and discitis.

Background

Vertebral osteomyelitis and discitis (VOD), an infection of intervertebral discs, often requires spine surgical intervention and timely management to prevent adverse outcomes. Our study aims to develop a machine learning (ML) model to predict the indication for surgical intervention (during the same hospital stay) versus nonsurgical management in patients with VOD.

Methods

This retrospective study included adult patients (≥18 years) with VOD (ICD-10 diagnosis codes M46.2,3,4,5) treated at a single institution between 01/01/2015 and 12/31/2019. The primary outcome studied was surgery. Candidate predictors were age, sex, race, Elixhauser comorbidity index, first-recorded lab values, first-recorded vital signs, and admit diagnosis. After splitting the dataset, XGBoost, logistic regression, and K-neighbor classifier algorithms were trained and tested for model development.

Results

A total of 1,111 patients were included in this study, among which 30% (n=339) of patients underwent surgical intervention. Age and sex did not significantly differ between the two groups; however, race did significantly differ (P<0.0001), with the surgical group having a higher percentage of white patients. The top ten model features for the best-performing model (XGBoost) were as follows (in descending order of importance): admit diagnosis of fever, negative culture,

Conclusions

The XGBoost model reliably predicts the indication for surgical intervention based on several readily available patient demographic information and clinical features. The interpretability of a supervised ML model provides robust insight into patient outcomes. Furthermore, it paves the way for the development of an efficient hospital resource allocation instrument, designed to guide clinical suggestions.

Informations de copyright

2024 Journal of Spine Surgery. All rights reserved.

Déclaration de conflit d'intérêts

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jss.amegroups.com/article/view/10.21037/jss-23-111/coif). B.H.P. reports being a consultant for Cerapedics; N.A. reports receiving royalties from Thieme Medical Publishers and Springer International Publishing; C.A.M. reports being a consultant for Stryker, Augmedics, DePuy Synthes, and Kuros Biosciences; W.Z.R. reports serving as a consultant for Globus, DePuy Synthes, Nuvasive, Corelink, and Pacira and holding a patent with Acera outside the submitted work. The other authors have no conflicts of interest to declare.