ArticlePloS one2023
A clinical prediction model to differentiate tuberculous spondylodiscitis from pyogenic spontaneous spondylodiscitis.
Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 13 citations in OpenAlex.
- Recommendations of the International Consensus Meeting (ICM) 2025 on Spinal Infections: Part B Tubercular Spondylodiscitis.Global spine journal · 2026Article
- Differentiating Tuberculous and Pyogenic Spondylodiscitis: Part II: MRI/CT Features, Prediction Models, and the Role of PET/CT-A Narrative Review.Diagnostics (Basel, Switzerland) · 2026Review
- Risk factors and a diagnostic nomogram for early prediction of gram-positive coccal etiology in spontaneous spinal infection.Infection · 2026Article
- MRI spondylodiscitis severity index: A novel scoring system based on contrast-enhanced MRI of the spine for predicting the clinical course and severity of pyogenic spondylodiscitis.Skeletal radiology · 2026Article
- Epidural abscess signal (EAS) and vertebral body signal (VBS) scores: MRI-based quantitative tools for early differentiation of pyogenic and tuberculous spondylitis to reduce inappropriate empirical therapy.Journal of orthopaedic surgery and research · 2026Article
- Clinical, laboratory, and MRI features differentiating tuberculous and pyogenic spondylodiscitis: a propensity score-matched analysis.BMC pulmonary medicine · 2026Article
- Tuberculosis in Turkiye: Epidemiological insights and recommendations for progress.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2025Review
- Global Insights Into Spondylodiscitis: A Bibliometric Analysis of Four Decades of Research.Cureus · 2025Review
- Infection ofRadiology case reports · 2025Article
- Article
- Hematologic Inflammation Indices for Differentiating between Brucella, Pyogenic, and Tuberculous Spondylodiscitis.Biomedicines · 2024Article
- A Comparative Factor Analysis and New Magnetic Resonance Imaging Scoring System for Differentiating Pyogenic Versus Tuberculous Spondylodiscitis.Neurospine · 2024Article
- Imaging of Spondylodiscitis: A Comprehensive Updated Review-Multimodality Imaging Findings, Differential Diagnosis, and Specific Microorganisms Detection.Microorganisms · 2024Review
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Authors and funding
9 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMicrobiological diagnosis of tuberculous spondylodiscitis (TS) and pyogenic spontaneous spondylodiscitis (PS) is sometime difficult. This study aimed to identify the predictive factors for differentiating TS from PS using clinical characteristics, radiologic findings, and biomarkers, and to develop scoring system by using predictive factors to stratify the probability of TS.
methodsA retrospective single-center study. Demographics, clinical characteristics, laboratory findings and radiographic findings of patients, confirmed causative pathogens of PS or TS, were assessed for independent factors that associated with TS. The coefficients and odds ratio (OR) of the final model were estimated and used to construct the scoring scheme to identify patients with TS.
resultsThere were 73 patients (51.8%) with TS and 68 patients (48.2%) with PS. TS was more frequently associated with younger age, history of tuberculous infection, longer duration of symptoms, no fever, thoracic spine involvement, ≥3 vertebrae involvement, presence of paraspinal abscess in magnetic-resonance-image (MRI), well-defined thin wall abscess, anterior subligamentous abscess, and lower biomarker levels included white blood cell (WBC) counts, erythrocyte-sedimentation-rate (ESR), neutrophil fraction, and C-reactive protein (all p < 0.05). Multivariate logistic regression analysis revealed significant predictors of TS included WBC ≤9,700/mm3 (odds ratio [OR] 13.11, 95% confidence interval [CI] 4.23-40.61), neutrophil fraction ≤78% (OR 4.93, 95% CI 1.59-15.30), ESR ≤92 mm/hr (OR 4.07, 95% CI 1.24-13.36) and presence of paraspinal abscess in MRI (OR 10.25, 95% CI 3.17-33.13), with an area under the curve of 0.921. The scoring system stratified the probability of TS into three categories: low, moderate, and high with a TS prevalence of 8.1%, 29.6%, and 82.2%, respectively.
conclusionsThis prediction model incorporating WBC, neutrophil fraction counts, ESR and presence of paraspinal abscess accurately predicted the causative pathogens. The scoring scheme with combination of these biomarkers and radiologic features can be useful to differentiate TS from PS.
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