Current Study of the Detection and Treatment Targets of Spinal Tuberculosis

Trends and prospects in spinal tuberculosis research: a future-oriented approach

PURPOSE

Tuberculosis is one of the oldest diseases in human history, and spinal tuberculosis (STB) is the most common form of extrapulmonary tuberculosis. A large number of research has been conducted in this field. However, there has been no bibliometric analysis performed in recent years in STB. The aim of this study was to analyze trends and hotspots in research on STB.

METHODS

Publications regarding STB between 1980 and 2022 were extracted from the Web of Science database. CiteSpace (V5.7.R2) and VOSviewer (1.6.10) were used to perform global analyses of the number of publications, countries, institutions, authors, journals, keywords, and cited references.

RESULTS

A total of 1262 articles were published between 1980 and 2022. We observed rapid growth in the number of publications since 2010. Spine had the highest number of publications (47, 3.7%). Zhang HQ and Wang XY were key researchers. The Central South University published the most papers (90, 7.1%). China was the leading contributor in this field with 459 publications and 29 H-index. National partnerships are dominated by the USA, and there is a lack of active cooperation between other countries and authors.

CONCLUSION

research on STB has achieved great progress, with an increasing number of publications since 2010. Surgical treatment and debridement are current research hots pots, and diagnosis, drug resistance, and kyphosis are likely research frontiers. Cooperation between countries and authors needs to be further strengthened.

Structural Versus Nonstructural Bone Grafting Via the Posterior Approach in the Treatment of Thoracic and Lumbar Tuberculosis: A Systematic Review and Meta-Analysis

BACKGROUND

Bone grafting is necessary in spinal tuberculosis surgery. Structural bone grafting is considered the gold standard treatment for spinal tuberculosis bone defects; however, nonstructural bone grafting via the posterior approach has recently gained attention. In this meta-analysis, we evaluated the clinical efficacy of structural versus nonstructural bone grafting via the posterior approach in the treatment of thoracic and lumbar tuberculosis.

METHODS

Studies comparing the clinical efficacy of structural and nonstructural bone grafting via the posterior approach in spinal tuberculosis surgery were identified from 8 databases from inception to August 2022. Study selection, data extraction, and evaluation of the risk of bias were performed, and meta-analysis was conducted.

RESULTS

Ten studies including 528 patients with spinal tuberculosis were enrolled. Meta-analysis revealed no between-group differences in fusion rate (P = 0.29), complications (P = 0.21), postoperative Cobb angle (P = 0.7), visual analog scale score (P = 0.66), erythrocyte sedimentation rate (P = 0.74), or C-reactive protein level (P = 0.14) at the final follow-up. Nonstructural bone grafting was associated with less intraoperative blood loss (P < 0.00001), shorter operation time (P < 0.0001), shorter fusion time (P < 0.01), and shorter hospital stay (P < 0.00001), while structural bone grafting was associated with lower Cobb angle loss (P = 0.002).

CONCLUSIONS

Both techniques can achieve a satisfactory bony fusion rate for spinal tuberculosis. Nonstructural bone grafting has the advantages of less operative trauma, shorter fusion time, and shorter hospital stay, making it an attractive option for short-segment spinal tuberculosis. Nevertheless, structural bone grafting is superior for maintaining corrected kyphotic deformities.

A Predictive Clinical-Radiomics Nomogram for Differentiating Tuberculous Spondylitis from Pyogenic Spondylitis Using CT and Clinical Risk Factors

OBJECTIVE

The study aimed to develop and validate a nomogram model with clinical risk factors and radiomic features for differentiating tuberculous spondylitis (TS) from pyogenic spondylitis (PS).

METHODS

A total of 254 patients with TS (n = 141) or PS (n = 113) were randomly divided into training (n = 180) and validation (n = 74) groups. In addition, 43 patients (TS = 22 and PS = 21) were collected to construct a test cohort. t-test analysis, de-redundancy analysis, and minimum absolute shrinkage and selection operator (lasso) algorithm were utilized on the training set to obtain the optimal radiomics features from computed tomography (CT) for constructing the radiomics model and determine the radiomics score (Rad-score). Eight clinical risk predictors were identified to develop the clinical model. Combined with clinical risk predictors and Rad-scores, a nomogram model was constructed using multivariate logistic regression analysis.

RESULTS

A total of 1781 features were extracted, and 12 optimal radiomic features were utilized to construct the radiomic model and determine the Rad-score. The combined clinical radiomics model revealed good discrimination performance in both the training cohort and the validation cohort (AUC = 0.891 and 0.830) and was superior to the clinical (AUC = 0.807 and 0.785) and radiomics (AUC = 0.796 and 0.811) models. The calibration curve and DCA also depicted that the nomogram had better clinical efficacy. The discriminative performance of the model is well validated in the test cohort (AUC=0.877).

CONCLUSION

The clinical radiomic nomogram could serve as a promising predictive tool for differentiating TS from PS, which could be helpful for clinical decision-making.

Analysis of the diagnostic efficacy of the QuantiFERON-TB Gold In-Tube assay for preoperative differential diagnosis of spinal tuberculosis

Background

Differential diagnosis of spinal tuberculosis is important for the clinical management of patients, especially in populations with spinal bone destruction. There are few effective tools for preoperative differential diagnosis in these populations. The QuantiFERON-TB Gold In-Tube (QFT-GIT) test has good sensitivity and specificity for the diagnosis of tuberculosis, but its efficacy in preoperative diagnosis of spinal tuberculosis has rarely been investigated.

Method

A total of 123 consecutive patients with suspected spinal tuberculosis hospitalized from March 20, 2020, to April 10, 2022, were included, and the QFT-GIT test was performed on each patient. We retrospectively collected clinical data from these patients. A receiver operating characteristic (ROC) curve was plotted with the TB Ag-Nil values. The cutoff point was calculated from the ROC curve of 61 patients in the study cohort, and the diagnostic validity of the cutoff point was verified in a new cohort of 62 patients. The correlations between TB Ag-Nil values and other clinical characteristics of the patients were analyzed.

Results

Of the 123 patients included in the study, 51 had confirmed tuberculosis, and 72 had non-tuberculosis disease (AUC=0.866, 95% CI: 0.798-0.933, P&lt;0.0001). In patients with spinal tuberculosis, the QFT-GIT test sensitivity was 92.16% (95% CI: 80.25%-97.46%), and the specificity was 67.14% (95% CI: 54.77%-77.62%). The accuracy of diagnostic tests in the validation cohort increased from 77.42% to 80.65% when a new cutoff point was selected (1.58 IU/mL) from the ROC curve of the study cohort. The TB Ag-Nil values in tuberculosis patients were correlated with the duration of the patients’ disease (r=0.4148, P=0.0025).

Conclusion

The QFT-GIT test is an important test for preoperative differential diagnosis of spinal tuberculosis with high sensitivity but low specificity. The diagnostic efficacy of the QFT-GIT test can be significantly improved via application of a new threshold (1.58 IU/mL), and the intensity of the QFT-GIT test findings in spinal tuberculosis may be related to the duration of a patient’s disease.

Neutrophil-lymphocyte ratio as a potential marker for differential diagnosis between spinal tuberculosis and pyogenic spinal infection

Objective

Distinguishing spinal tuberculosis and pyogenic spinal infection is extremely important. The neutrophil–lymphocyte ratio (NLR), a simple indicator, has been shown to be a novel inflammatory marker. The objective of our study was to determine whether the NLR could be a potential indicator for discriminating spinal tuberculosis (STB) from pyogenic spinal infection (PSI).

Methods

We compared the clinical and laboratory characteristics of 146 patients diagnosed with STB and 60 participants with PSI from the First Affiliated Hospital of Nanjing Medical University. The NLR's diagnostic ability for differential diagnosis was assessed and compared to other hematological indicators, including the platelet–lymphocyte ratio (PLR).

Results

The NLR in STB patients was considerably lower than that in PSI patients [3.85 (2.70–5.71) vs. 10.82 (6.79–17.62), P < 0.001]. An NLR of 6.742 was proposed as an optimal cutoff value for distinguishing patients with STB from those with PSI (sensitivity 78.33%, specificity 83.56%). However, the NLR's area under the curve [0.87, 95% confidence interval (CI) 0.81–0.92] was considerably higher than that of the PLR (0.73, 95% CI 0.65–0.80; P < 0.0001).

Conclusion

NLR levels could be a valuable laboratory diagnostic for distinguishing patients with STB from those who have PSI.

Predicting Surgical Site Infection Risk after Spinal Tuberculosis Surgery: Development and Validation of a Nomogram

Background:

The purpose of this study was to predict the surgical site infection risk after spinal tuberculosis surgery based on a nomogram.

Patients and Methods:

We collected the clinical data of patients who underwent spinal tuberculosis surgery in our hospital and included all the data in the least absolute shrinkage and selection operator (LASSO) regression analysis. Next, the selected parameters were analyzed using logistic regression. The logistic regression analysis and receiver operating characteristic (ROC) curve analysis were further used to obtain statistically significant parameters. These parameters were then used to construct a nomogram. The C-index, ROC curve, and decision curve analysis (DCA) were used to assess the predictive ability and accuracy of the nomogram, whereas internal verification was used to calculate the C-index by bootstrapping with 1,000 resamples.

Results:

A total of 394 patients with spinal tuberculosis surgery were included in the study, of whom 76 patients had surgical site infections whereas 318 patients did not. The predicted risk of surgical site infection in the nomogram ranged between 0.01 and 0.98. Both the value of the C-index of the nomogram (95% confidence interval [CI], 0.62–0.76) and the area under the curve (AUC) were found to be 0.69. The net benefit of the model ranged between 0.01 and 0.99. In contrast, the C-index calculated by the internal verification method of the nomogram was found to be 0.68.

Conclusions:

The risk factors predicting surgical site infection after spinal tuberculosis surgery included albumin, lesion segment, operation time, and incision length.

Tuberculosis-Specific Antigen/Phytohemagglutinin Ratio Combined With GeneXpert MTB/RIF for Early Diagnosis of Spinal Tuberculosis: A Prospective Cohort Study

Spinal tuberculosis (TB), the most common form of musculoskeletal tuberculosis, is an infection-related disease globally, with paraplegia occurring in severe cases. Therefore, identification of spinal TB at an early stage is important for early intervention and eventual therapy. In this study, we conducted a prospective cohort study in routine clinical practice to investigate the diagnosis of different TB tests. A total of 519 patients were recruited based on the radiology of spinal TB. The diagnostic model was computed by regression analysis and was determined by receiver operating characteristic (ROC) curve analysis. Specificity, sensitivity, predictive value, likelihood ratio, and accuracy were also computed and compared. GeneXpert MTB/RIF showed a higher positive rate compared to that in the acid-fast bacilli smear and Mycobacterium culture. The results also showed that the Mycobacterium tuberculosis-specific antigen/phytohemagglutinin ratio in the T-SPOT assay had a good performance in the preoperative diagnosis and prediction of spinal TB. The diagnostic model based on the ratio of tuberculosis-specific antigen/phytohemagglutinin combined with GeneXpert MTB/RIF showed better efficiency for spinal TB diagnosis. In summary, the tuberculosis-specific antigen/phytohemagglutinin ratio combined with GeneXpert MTB/RIF could provide an early diagnosis of spinal TB.

Pulmonary embolism following the third thoracic tuberculosis surgery: A case report and literature review

Background

The study aimed to analyze the clinical effects of pulmonary embolism succeeding a third surgery conducted for multiple recurrences in thoracic tuberculosis (TB).

Case report

A 74‐year‐old female patient developed thoracic tuberculosis and was subsequently treated in our hospital in March 2019, October 2020, and February 2021. The third surgical intervention included anterolateral thoracic lesion resection, internal fixation, posterior spinal tuberculous sinus resection, and debridement with suture. The operative time was 172 min resulting in a substantial intraoperative blood loss (2321 ml). Postoperative re‐examination of chest CTPA indicated a strip filling defect and pulmonary embolism in the external branch of the right middle lobe of the lung. After completing the active treatment, the D‐dimer quantification, WBC, CRP, and ESR values were 1261 ng/ml, 7.71 × 10⁹/L, 74.66 mg/L, and 63 mm, respectively. Chest CTPA re‐examination after the treatment showed no signs of pulmonary embolism.

Conclusion

Patients with a long‐term history of multiple operations, high BMI, cerebral infarction, diabetes, and older age group were more likely to develop pulmonary embolism after spinal tuberculosis surgery. Thus, the possibility of postoperative pulmonary embolism should be thoroughly analyzed before any subsequent surgical treatment in patients with recurrent spinal tuberculosis.

Development and validation of a novel predictive model and web calculator for evaluating transfusion risk after spinal fusion for spinal tuberculosis: a retrospective cohort study

Objectives

The incidence and adverse events of postoperative blood transfusion in spinal tuberculosis (TB) have attracted increasing attention. Our purpose was to develop a prediction model to evaluate blood transfusion risk after spinal fusion (SF) for spinal TB.

Methods

Nomogram and machine learning algorithms, support vector machine (SVM), decision tree (DT), multilayer perceptron (MLP), Naive Bayesian (NB), k-nearest neighbors (K-NN) and random forest (RF), were constructed to identified predictors of blood transfusion from all spinal TB cases treated by SF in our department between May 2010 and April 2020. The prediction performance of the models was evaluated by 10-fold cross-validation. We calculated the average AUC and the maximum AUC, then demonstrated the ROC curve with maximum AUC.

Results

The collected cohort ultimately was consisted of 152 patients, where 56 required allogeneic blood transfusions. The predictors were surgical duration, preoperative Hb, preoperative ABL, preoperative MCHC, number of fused vertebrae, IBL, and anticoagulant history. We obtained the average AUC of nomogram (0.75), SVM (0.62), k-NM (0.65), DT (0.56), NB (0.74), MLP (0.56) and RF (0.72). An interactive web calculator based on this model has been provided (https://drwenleli.shinyapps.io/STTapp/).

Conclusions

We confirmed seven independent risk factors affecting blood transfusion and diagramed them with the nomogram and web calculator.

Development and Validation of a Scoring System for Differential Diagnosis of Tuberculosis and Metastatic Tumor in the Spine

Purpose

Spinal tuberculosis (TB) and metastatic tumor (MT) are common diseases with similar manifestations. Although pathological evaluation is the gold standard to confirm diagnosis, performing biopsies in all patients is not feasible. This study is aimed to create a scoring system to facilitate the differential diagnosis of spinal TB and MT before invasive procedures.

Methods

Altogether, 447 patients with spinal TB (n=198) and MT (n=249) were retrospectively analyzed. Patients were randomly assigned at 2:1 ratio to a training cohort and a validation cohort. Clinical, laboratory, and radiological diagnostic factors were identified by χ² and multiple logistic regression analyses. The scoring system was then established based on the identified independent diagnostic factors scored by regression coefficient β value, with the cut-off value being determined by ROC curve. The sensitivity and specificity of the system was calculated by comparing the predicted diagnosis with their actual pathological diagnosis.

Results

This scoring system was composed of 5 items: pain worsens at night (0 or 2 points), CRP value (0 or 3 points), tumor marker values (0 or 2 points), skip lesions (0 or 3 points), and intervertebral space destruction (0 or 3 points). Patients scoring higher than 7.5 could be diagnosed as spinal TB, otherwise, MT. According to the internal validation, the sensitivity and specificity of the system were 87.9% and 91.6%, respectively.

Conclusion

This study established and validated a scoring system which could be used to differentiate spinal TB from MT, thus helping clinicians in quick and accurate differential diagnosis.