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Posterior transfacet approach has been proved to be a safe and effective access to treat thoracic disc herniation. However, the influencing factors of posterior modified transarticular debridement for thoracic tuberculosis have not been reported in the clinical literature. From 2009 to 2014, 37 patients with TST underwent a posterior modified transfacet debridement, interbody fusion following posterior instrumentation, under the cover of 18 months of antituberculosis chemotherapy. The patients were evaluated preoperatively and postoperatively in terms of Frankel Grade, visual analog scale (VAS) pain score, kyphotic Cobb angle, and bone fusion. Blood loss (positive correlation) and focal debridement (positive correlation) could affect operative time. Operative time (positive correlation) could affect blood loss. While, age (positive correlation), PostE (negative correlation), and T_FocalDebridement (positive correlation) could affect bone fusion. The accuracy of naive bayes classifier model is 86.11%. Our preliminary results show that blood loss and focal debridement could affect operative time; operative time could affect blood loss; age, PostE, and T_FocalDebridement could affect bone fusion; the naive Bayes classifier model can predict the KirkaldyWillis accurately.

Tuberculosis (TB), an infectious disease caused by mycobacterium tuberculosis (MTB), is the ninth leading cause of global death, ranking above acquired immune deficiency syndrome (AIDS). The spine is the most frequently involved part of extrapulmonary tuberculosis, which is more common in thoracolumbar vertebrae, 30.3% to 55.8% of which are thoracic tuberculosis and about 67% of thoracic tuberculosis patients are accompanied by tuberculosis [

As an important surgical intervention in the treatment of spinal tuberculosis, surgical treatment aims to effectively remove the lesion, completely relieve the neurospinal compression, restore the height of the affected vertebra as far as possible, and rebuild the stability of the spine. After continuous exploration and development, the current surgical treatment methods are classified according to the approach, mainly including anterior approach, posterior approach, and combined approach. (1) Anterior approach: compared with other methods, anterior approach is the most convenient method for removing lesions because it can directly reach the lesion and has a good operating field of vision [

Between 2009 and 2014, the authors treated 37 consecutive patients with TST via a modified transfacet approach [

Patients were treated with standard chemotherapy regimen of isoniazid (H), rifampicin (R), ethambutol (E), and pyrazinamide (Z) (HREZ) at least 4 weeks before surgery, including isoniazid (300 mg/d), rifampicin (450 mg/d), ethambutol (750 mg/d), and pyrazinamide (750 mg/d). ESR was 44.7 ± 23.3 mm/h. And the mean kyphosis angle was 29.4 ± 10.9°. Surgery is performed when ESR is significantly reduced (<40 mm/h). Preoperative antituberculosis treatment can reduce mycobacterium tuberculosis in focus and improve surgical safety. Bony spinal fusion was assessed according to the criteria defined by Lee et al. [

The modified criteria of Lee et al for radiological fusion.

Grade | Description |
---|---|

Definitive fusion | Definitive bony trabecular bridging across the graft-host interface, no movement (<3°) on a flexion-extension radiograph and no gap at the interface |

Probable fusion | No definitive bony trabecular crossing, but no detectable movement and no identifiable gap at the interface |

Possible pseudarthrosis | No bony trabecular crossing, no movement, but identifiable gap at the interface |

Definite pseudarthrosis | No traversing trabecular bone, definitive gap, and movement >3° |

In order to examine the factors that might affect operative time, the multivariable linear regression model is adopted. Operative time is considered as a continuous and dependent variable, whereas blood loss, PreK, FFUK, and focal debridement are constituted the independent variables. The multivariable linear regression model is also utilized for investigating whether operative time could affect blood loss. Blood loss is considered as a constant and dependent variable, whereas operative time, bone fusion, and PreK constituted the independent variables. The naive Bayes classifier model is also utilized for investigating what affects the KirkaldyWillis grade. All the statistical analyses were performed using the R Project (version 3.5.1, 2018, The R Foundation for Statistical Computing), the R package e1071, corrplot needs to be loaded. The results were considered statistically significant at

Multiple Linear Regression [

Let the dependent variable be

This is called the population regression model, and

The principle of naive Bayes classifier [

Calculate the prior probability and conditional probability:

For a given sample of

Determine the classification of sample

We find that blood loss (positive correlation) and focal debridement (positive correlation) could affect operative time, but not bone fusion, gender, PreA, PostA, FFUA, age, hospital stay, segments, follow-up, PreK, PostK, PreE, PostE, FUUK, FFUE, and T_Level. We also find that operative time (positive correlation) could affect blood loss, but not gender, PreA, PostA, FFUA, age, hospital stay, segments, follow-up, PostK, FUUK, PreK, PreE, PostE, FFUE, T_Level, and T_FocalDebridement. We also find age (positive correlation), PostE (negative correlation), and T_FocalDebridement (positive correlation) could affect bone fusion, but not gender, PreA, PostA, FFUA, hospital stay, segments, follow-up, PostK, PreE, FUUK, FFUE, and T_Level.

Final equation 1:

As for the influencing factor model of operative time, ^{2} is 0.7726, indicates that the model has a good fitting effect and can better explain the influencing factors of operative time. In patients with the same T_FocalDebridement, operative time increased by an average of 0.11575 if blood loss increases 1 ml, its

Model summary for operative time.

Primary independent variables | |||

Coefficient estimate | Standard error | ||

(Intercept) | 108.27007 | 17.71126 | <0.001 |

Blood loss | 0.11575 | 0.02739 | <0.001 |

T_FocalDebridement | 23.61903 | 10.76961 | 0.035 |

Statistic | Value | DF | |

57.76 | (2, 34) | <0.001 | |

^{2} | 0.7726 |

Final equation 2:

As for the influencing factor model of blood loss, F test is performed on the whole model (Table ^{2} is 0.7404, indicates that the model has a good fitting effect and can better explain the influencing factors of blood loss. Blood loss increased by an average of 4.4878 if operative time increased 1 min, its

Model summary for blood loss.

Primary independent variables | |||

Coefficient estimate | Standard error | ||

(Intercept) | −506.0542 | 103.9502 | <0.001 |

Operative time | 4.4878 | 0.4491 | <0.001 |

Statistic | Value | DF | |

99.85 | (1, 35) | <0.001 | |

^{2} | 0.7404 |

Final equation 3:

As for the influencing factor model of bone fusion, ^{2} is 0.5026, indicates that the model has a good fitting effect and can better explain the influencing factors of bone fusion. In patients with the same PostE and T_FocalDebridement, bone fusion increased by an average of 0.04326 if age increases 1, its

Model summary for bone fusion.

Primary independent variables | |||

Coefficient estimate | Standard error | ||

(Intercept) | 2. 75352 | 0. 97119 | <0.01 |

Age | 0.04326 | 0. 01342 | <0.01 |

PostE | −0.08810 | 0.03986 | <0.05 |

T_FocalDebridement | 1.53847 | 0.27879 | <0.001 |

Statistic | Value | DF | |

13.12 | (3, 33) | <0.001 | |

^{2} | 0.5026 |

After deleting one sample in which KirkaldyWillis is two, only the samples of KirkaldyWillis = 3 and KirkaldyWillis = 4 are trained. The correlation coefficient matrices of gender, bone fusion, follow-up, FFUK, FFUA, and FFUE are calculated, as shown in Table

Sample correlation matrix.

Gender | Bone fusion | Follow-up | FFUK | FFUA | FFUE | |
---|---|---|---|---|---|---|

Gender | 1.0000000 | −0.2805976 | −0.1155847 | 0.0715071 | −0.1428571 | 0.3157139 |

Bone fusion | −0.2805976 | 1.0000000 | 0.2229494 | 0.2665206 | −0.1624512 | −0.2556321 |

Follow-up | −0.1155847 | 0.2229494 | 1.0000000 | 0.3185323 | 0.0761168 | −0.0372737 |

FFUK | 0.0715071 | 0.2665206 | 0.3185323 | 1.0000000 | −0.0449019 | −0.0057099 |

FFUA | −0.1428571 | −0.1624512 | 0.0761168 | −0.0449019 | 1.0000000 | −0.1733689 |

FFUE | 0.3157139 | −0.2556321 | −0.0372737 | −0.0057099 | −0.1733689 | 1.0000000 |

As shown in Figure

Sample correlation diagram.

The confusion matrix is obtained in Table

Confusion matrix.

Predicted | |||
---|---|---|---|

KirkaldyWillis = 4 | KirkaldyWillis = 3 | ||

Actual | KirkaldyWillis = 4 | 3 | 4 |

KirkaldyWillis = 3 | 1 | 28 |

Because naive Bayes model is a kind of generating model, it directly models the joint probability to obtain the target probability. Through modeling, we can only get the classification probability of each sample, so as to determine the category, that is, no explicit model can be obtained. The classification accuracy is 86.11%, which indicates the percentage of all correctly predicted samples to all samples; recall is 96.6%, which indicates the correct percentage of all samples predicted with KirkaldyWillis = 4; precision is 87.5%, which indicates the proportion of all KirkaldyWillis samples predicted to be KirkaldyWillis = 4.

Operative data of 37 patients with TST were recorded with multiple indicators of the operative level. Multiple linear regression is also suitable for analyzing the influence of multiple surgical factors on one operative variable. The number of vertebral segments debridement is the most important factor affecting the operation time. When other surgical factors remain unchanged, the greater the amount of blood loss, the longer the operation time. Bone fusion time is the most important factor affecting blood loss. When other surgical factors remain unchanged, the longer the operation time, the longer the bone fusion time or the greater the preoperative the KirkaldyWillis score, the greater the blood loss. And both models have high ^{2} values. The posterior transfacet-modified approach has been reported to be a safe and effective method for the treatment of thoracic spinal tuberculosis (TST) with low morbidity in the precious report [

The data used to support the findings of the study are available from the corresponding author upon request.

Between 2009 and 2014, the authors treated 37 consecutive patients with TST via a modified transfacet approach [

The authors declare no conflicts of interest.

The authors sincerely thank the participants for their help and willingness to participate in this study. This study was supported by the National Natural Science Foundation of China (11601083 and U1805263), Natural Science Foundation of Fujian Province, China (2019J01451), Program for Probability and Statistics: Theory and Application (IRTL1704), and Innovative Research Team in Science and Technology in Fujian Province University (IRTSTFJ).

The supplementary information files contain the table of patients treated in this study.