دورية أكاديمية
Clinical prediction for surgical versus nonsurgical interventions in patients with vertebral osteomyelitis and discitis.
| العنوان: | Clinical prediction for surgical versus nonsurgical interventions in patients with vertebral osteomyelitis and discitis. |
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| المؤلفون: | Lee J; Department of Neurological Surgery, Washington University School of Medicine, Saint Louis, MO, USA., Ruiz-Cardozo MA; Department of Neurological Surgery, Washington University School of Medicine, Saint Louis, MO, USA., Patel RP; Department of Neurological Surgery, Washington University School of Medicine, Saint Louis, MO, USA., Javeed S; Department of Neurological Surgery, Washington University School of Medicine, Saint Louis, MO, USA., Lavadi RS; Department of Neurological Surgery, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA., Newsom-Stewart C; Department of Developmental Regenerative and Stem Cell Biology, Washington University in St. Louis, Saint Louis, MO, USA., Alyakin A; Department of Neurological Surgery, Washington University School of Medicine, Saint Louis, MO, USA., Molina CA; Department of Neurological Surgery, Washington University School of Medicine, Saint Louis, MO, USA., Agarwal N; Department of Neurological Surgery, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA., Ray WZ; Department of Neurological Surgery, Washington University School of Medicine, Saint Louis, MO, USA., Santacatterina M; Department of Population Health, New York University School of Medicine, New York City, NY, USA., Pennicooke BH; Department of Neurological Surgery, Washington University School of Medicine, Saint Louis, MO, USA. |
| المصدر: | Journal of spine surgery (Hong Kong) [J Spine Surg] 2024 Jun 21; Vol. 10 (2), pp. 204-213. Date of Electronic Publication: 2024 May 17. |
| نوع المنشور: | Journal Article |
| اللغة: | English |
| بيانات الدورية: | Publisher: OSS Press Ltd Country of Publication: China NLM ID: 101685460 Publication Model: Print-Electronic Cited Medium: Print ISSN: 2414-469X (Print) Linking ISSN: 24144630 NLM ISO Abbreviation: J Spine Surg Subsets: PubMed not MEDLINE |
| أسماء مطبوعة: | Original Publication: Hong Kong : OSS Press Ltd, [2015]- |
| مستخلص: | 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, Staphylococcus aureus culture, partial pressure of arterial oxygen to fractional inspired oxygen ratio (PaO 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. Competing Interests: 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. (2024 Journal of Spine Surgery. All rights reserved.) |
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| فهرسة مساهمة: | Keywords: Clinical prediction; machine learning (ML); spine surgery; surgical intervention; vertebral osteomyelitis discitis |
| تواريخ الأحداث: | Date Created: 20240708 Latest Revision: 20240709 |
| رمز التحديث: | 20240709 |
| مُعرف محوري في PubMed: | PMC11224782 |
| DOI: | 10.21037/jss-23-111 |
| PMID: | 38974494 |
| قاعدة البيانات: | MEDLINE |
| تدمد: | 2414-469X |
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| DOI: | 10.21037/jss-23-111 |