TY - JOUR
T1 - A clinical prediction model to differentiate tuberculous spondylodiscitis from pyogenic spontaneous spondylodiscitis
AU - Lertudomphonwanit, Thamrong
AU - Somboonprasert, Chirtwut
AU - Lilakhunakon, Kittiphon
AU - Jaovisidha, Suphaneewan
AU - Ruangchaijatuporn, Thumanoon
AU - Fuangfa, Praman
AU - Rattanasiri, Sasivimol
AU - Watcharananan, Siriorn
AU - Chanplakorn, Pongsthorn
N1 - Publisher Copyright:
© 2023 Lertudomphonwanit et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
PY - 2023/8
Y1 - 2023/8
N2 - 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 < 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. Conclusions This 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.
AB - 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 < 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. Conclusions This 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.
UR - https://www.scopus.com/pages/publications/85168355683
U2 - 10.1371/journal.pone.0290361
DO - 10.1371/journal.pone.0290361
M3 - Article
C2 - 37594939
AN - SCOPUS:85168355683
SN - 1932-6203
VL - 18
JO - PLoS ONE
JF - PLoS ONE
IS - 8 August
M1 - e0290361
ER -