A clinical prediction model to differentiate tuberculous spondylodiscitis from pyogenic spontaneous spondylodiscitis

Thamrong Lertudomphonwanit, Chirtwut Somboonprasert, Kittiphon Lilakhunakon, Suphaneewan Jaovisidha, Thumanoon Ruangchaijatuporn, Praman Fuangfa, Sasivimol Rattanasiri, Siriorn Watcharananan and Pongsthorn Chanplakorn

PLOS ONE, 2023, vol. 18, issue 8, 1-17

Abstract: Background: Microbiological 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. Methods: A 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. Results: There 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

Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0290361

DOI: 10.1371/journal.pone.0290361

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