scholarly journals Analysis of the independent risk factors of neurologic deficit after thoracolumbar burst fracture

2016 ◽  
Vol 11 (1) ◽  
Author(s):  
Peifu Tang ◽  
Anhua Long ◽  
Tao Shi ◽  
Licheng Zhang ◽  
Lihai Zhang
Keyword(s):  
Risk Factors ◽  
Burst Fracture ◽  
Neurologic Deficit ◽  
Thoracolumbar Burst Fracture ◽  
Independent Risk Factors

scholarly journals Development and validation of a nomogram for prediction of the risk of positive hidden blood loss in the perioperative period of single-level thoracolumbar burst fracture

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Haosheng Wang ◽  
Tingting Fan ◽  
Zhi-Ri Tang ◽  
Wenle Li ◽  
Linjing Liu ◽  
...  
Keyword(s):  
Risk Factors ◽  
Prediction Model ◽  
Burst Fracture ◽  
Perioperative Period ◽  
Thoracolumbar Burst Fracture ◽  
Multivariate Logistic Regression ◽  
Decision Curve Analysis ◽  
Single Level ◽  
Hidden Blood Loss ◽  
Independent Risk Factors

Abstract Background This study aimed to develop and validate an individualized nomogram to predict the risk of positive hidden blood loss (HBL) in patients with single-level thoracolumbar burst fracture (TBF) during the perioperative period. Methods We conducted a retrospective investigation including 150 consecutive patients with TBL, and the corresponding patient data was extracted from March 2013 to March 2019. The independent risk factors for positive HBL were screened using univariate and multivariate logistic regression analyses. According to published literature and clinical experience, a series of variables were selected to develop a nomogram prediction model for positive HBL. The area under the receiver operating characteristic curves (AUC), C-index, calibration plot, and decision curve analysis (DCA) were used to evaluate the performance of the prediction model. Bootstrapping validation was performed to evaluate the performance of the model. Results Among the 150 consecutive patients, 62 patients were positive for HBL (38.0%). The multivariate logistic regression analysis showed that the six risk factors of age, length of surgical incision, duration of operation, percentage of vertebral height restoration (P1%), preoperative total cholesterol, and preoperative fibrinogen were independent risk factors of positive HBL. The C-index was 0.831 (95% CI 0.740–0.889) and 0.845 in bootstrapping validation, respectively. The calibration curve showed that the predicted probability of the model was consistent with the actual probability. Decision curve analysis (DCA) showed that the nomogram had clinical utility. Conclusion Overall, we explored the relationship between the positive HBL requirement and predictors. The individualized prediction model for patients with single-level TBF can accurately assess the risk of positive HBL and facilitate clinical decision making. However, external validation will be needed in the future.

scholarly journals Predictors of the failure of conservative treatment in patients with a thoracolumbar burst fracture

2020 ◽  
Vol 15 (1) ◽  
Author(s):  
Ehsan Alimohammadi ◽  
Seyed Reza Bagheri ◽  
Paniz Ahadi ◽  
Sahar Cheshmehkaboodi ◽  
Homa Hadidi ◽  
...  
Keyword(s):  
Risk Factors ◽  
Conservative Treatment ◽  
Burst Fracture ◽  
Binary Logistic Regression ◽  
Operative Management ◽  
Binary Logistic Regression Analysis ◽  
Thoracolumbar Burst Fracture ◽  
Potential Risk Factors ◽  
Non Operative Management

Abstract Background There is a controversy about the management of patients with a thoracolumbar burst fracture. Despite the success of the conservative treatment in most of the cases, some patients failed the conservative treatment. The present study aimed to evaluate risk factors for the need for surgery during the follow-up period in these patients. Methods We retrospectively evaluated 67 patients with a traumatic thoracolumbar burst fracture who managed conservatively at our center between May 2014 and May 2019. Suggested variables as potential risk factors for the failure of conservative treatment including age, gender, body mass index (BMI), smoking, diabetes, vertebral body compression rate (VBCR), percentage of anterior height compression (PAHC), Cobb angle, interpedicular distance (IPD), canal compromise, and pain intensity as visual analog scale (VAS) were compared between patients with successful conservative treatment and those with failure of non-operative management. Results There were 41 males (61.2%) and 26 females (38.8%) with the mean follow-up time of 15.52 ± 5.30 months. Overall, 51 patients (76.1%) successfully completed conservative treatment. However, 16 cases (23.9%) failed the non-operative management. According to the binary logistic regression analysis, only age (risk ratio [RR], 2.21; 95% confidence interval [95%], 1.78–2.64; P = 0.019) and IPD (RR 1.97; 95% CI 1.61–2.33; P = 0.005) were the independent risk factors for the failure of the non-operative management. Conclusions Our results showed that older patients and those with greater interpedicular distance are at a higher risk for failure of the conservative treatment. As a result, a closer follow-up should be considered for them.

scholarly journals Risk factor analysis for predicting kyphosis reoccurrence of thoracolumbar burst fracture patients treated with posterior short-segment fixation

2020 ◽  
Author(s):  
Xiangyao Sun ◽  
Zhaoxiong Chen ◽  
Siyuan Sun ◽  
Tongtong Zhang ◽  
Xinuo Zhang ◽  
...  
Keyword(s):  
Risk Factors ◽  
Risk Factor ◽  
Burst Fracture ◽  
Wedge Angle ◽  
Implant Removal ◽  
Thoracolumbar Burst Fracture ◽  
Height Ratio ◽  
Vertebral Height ◽  
Thoracolumbar Injury ◽  
Multi Center Study

Abstract Background: The thresholds of risk factors of kyphosis recurrence in thoracolumbar burst fracture patients were still controversial. The aim of this multi-center study was to identify these thresholds. Methods: 169 patients were included in this study. Upper intervertebral angle (UIVA), lower intervertebral angle (LIVA), Cobb angle (CA), anterior vertebral height ratio (AVH%), regional angle (RA), posterior vertebral height ratio (PVH%), vertebral wedge angle (VWA), anteroposterior ratio (A/P%), Clinical assessment included Load Sharing Classification (LSC) score, Thoracolumbar Injury Classification and Severity (TLICS) score, Visual Analogue Scale (VAS), and Body mass index (BMI) were perioperatively evaluated. Patients were divided into KR group and none KR (NKR) group according to whether the loss of CA correction was less than 5˚ or not. The risk factors of KR before or after implant removal were analyzed, respectively. Results: There were significant improvements in postoperative parameters compared with preoperative parameters, such as AVH%, A/P%, VAS, CA, VWA, PVH% ( P < 0.001, respectively), and UIVA ( P = 0.02). Age (AUC = 0.828) and BMI (AUC = 0.846) were good predictors of KR before implant removal. BMI (AUC = 0.871) was a good predictor of KR after implant removal. Conclusions: There were significant differences in risk factors of KR at different postoperative follow-up stages: age > 49 years, BMI > 24 were risk factors of KR before implant removal; BMI > 25.17 was a risk factor of KR after implant removal.

scholarly journals Risk factor analysis for predicting kyphosis reoccurrence of thoracolumbar burst fracture patients treated with posterior short-segment fixation

2019 ◽  
Author(s):  
Likun An ◽  
Tongtong Zhang ◽  
Xiangyao Sun ◽  
Xinuo Zhang ◽  
Siyuan Sun ◽  
...  
Keyword(s):  
Risk Factors ◽  
Risk Factor ◽  
Burst Fracture ◽  
Wedge Angle ◽  
Implant Removal ◽  
Thoracolumbar Burst Fracture ◽  
Height Ratio ◽  
Vertebral Height ◽  
Thoracolumbar Injury ◽  
Multi Center Study

Abstract Background The thresholds of risk factors of kyphosis recurrence in thoracolumbar burst fracture patients were still controversial. The aim of this multi-center study was to identify these thresholds.Methods 169 patients were included in this study. Upper intervertebral angle (UIVA), lower intervertebral angle (LIVA), Cobb angle (CA), anterior vertebral height ratio (AVH%), regional angle (RA), posterior vertebral height ratio (PVH%), vertebral wedge angle (VWA), anteroposterior ratio (A/P%), Clinical assessment included Load Sharing Classification (LSC) score, Thoracolumbar Injury Classification and Severity (TLICS) score, Visual Analogue Scale (VAS), and Body mass index (BMI) were perioperatively evaluated. Patients were divided into KR group and none KR (NKR) group according to whether the loss of CA correction was less than 5˚ or not. The risk factors of KR before or after implant removal were analyzed, respectively.Results There were significant improvements in postoperative parameters compared with preoperative parameters, such as AVH%, A/P%, VAS, CA, VWA, PVH% ( P < 0.001, respectively), and UIVA ( P = 0.02). Age (AUC = 0.828) and BMI (AUC = 0.846) were good predictors of KR before implant removal. BMI (AUC = 0.871) was a good predictor of KR after implant removal.Conclusions There were significant differences in risk factors of KR at different postoperative follow-up stages: age > 49 years, BMI > 24 were risk factors of KR before implant removal; BMI > 25.17 was a risk factor of KR.

scholarly journals Risk factor analysis for predicting kyphosis reoccurrence of thoracolumbar burst fracture patients treated with posterior short-segment fixation

2019 ◽  
Author(s):  
Likun An ◽  
Tongtong Zhang ◽  
Xiangyao Sun ◽  
Xinuo Zhang ◽  
Siyuan Sun ◽  
...  
Keyword(s):  
Risk Factors ◽  
Risk Factor ◽  
Burst Fracture ◽  
Wedge Angle ◽  
Implant Removal ◽  
Thoracolumbar Burst Fracture ◽  
Height Ratio ◽  
Vertebral Height ◽  
Thoracolumbar Injury ◽  
Multi Center Study

Abstract Background: The thresholds of risk factors of kyphosis recurrence in thoracolumbar burst fracture patients were still controversial. The aim of this multi-center study was to identify these thresholds. Methods: 169 patients were included in this study. Upper intervertebral angle (UIVA), lower intervertebral angle (LIVA), Cobb angle (CA), anterior vertebral height ratio (AVH%), regional angle (RA), posterior vertebral height ratio (PVH%), vertebral wedge angle (VWA), anteroposterior ratio (A/P%), Clinical assessment included Load Sharing Classification (LSC) score, Thoracolumbar Injury Classification and Severity (TLICS) score, Visual Analogue Scale (VAS), and Body mass index (BMI) were perioperatively evaluated. Patients were divided into KR group and none KR (NKR) group according to whether the loss of CA correction was less than 5˚ or not. The risk factors of KR before or after implant removal were analyzed, respectively. Results: There were significant improvements in postoperative parameters compared with preoperative parameters, such as AVH%, A/P%, VAS, CA, VWA, PVH% (P < 0.001, respectively), and UIVA (P = 0.02). Age (AUC = 0.828) and BMI (AUC = 0.846) were good predictors of KR before implant removal. BMI (AUC = 0.871) was a good predictor of KR after implant removal. Conclusions: There were significant differences in risk factors of KR at different postoperative follow-up stages: age > 49 years, BMI > 24 were risk factors of KR before implant removal; BMI > 25.17 was a risk factor of KR after implant removal.

scholarly journals Development and Validation of a Nomogram for Prediction of the Risk of Positive Hidden Blood Loss in the Perioperative Period of Thoracolumbar Burst Fracture

2021 ◽  
Author(s):  
Haosheng Wang ◽  
Tingting Fan ◽  
Zhi-Ri Tang ◽  
Wenle Li ◽  
Linjing Liu ◽  
...  
Keyword(s):  
Risk Factors ◽  
Prediction Model ◽  
Burst Fracture ◽  
Perioperative Period ◽  
Multivariate Logistic Regression ◽  
Vertebral Height ◽  
Decision Curve Analysis ◽  
Hidden Blood Loss ◽  
Independent Risk Factors ◽  
Duration Of Operation

Abstract Background: This study aimed to develop and validate an individualized nomogram to predict the risk of positive hidden blood loss (HBL) in patients with thoracolumbar burst fracture (TBF) during the perioperative period.Methods: We conducted a retrospective investigation including 161 consecutive patients with TBL, and the corresponding patient data was extracted from March 2013 to March 2019. The independent risk factors for positive HBL were screened using univariate and multivariate logistic regression analyses. According to published literature and clinical experience, a series of variables were selected to develop a nomogram prediction model for positive HBL. The area under the receiver operating characteristic curves (AUC), C-index, calibration plot, and decision curve analysis (DCA) were used to evaluate the performance of the prediction model. Bootstrapping validation was performed to evaluate the performance of the model.Results: Among the 161 consecutive patients, 62 patients were negative for HBL (14.13%). The Multivariate logistic regression analysis showed that the six risk factors of age, length of surgical incision, duration of operation, percentage of vertebral height restoration (P1%), preoperative total cholesterol, and preoperative fibrinogen were independent risk factors of positive HBL. The C-index was 0.862 (95% CI 0.788–0.903) and 0.8884 in bootstrapping validation, respectively. The calibration curve showed that the predicted probability of the model was consistent with the actual probability. Decision curve analysis (DCA) showed that the nomogram had clinical utility.Conclusion: Overall, we explored the relationship between the positive HBL requirement and predictors: age, duration from admission to surgery, duration of operation, percentages of vertebral height restoration (P1%), preoperative total cholesterol, and preoperative fibrinogen. The individualized prediction model for patients with TBF can accurately assess the risk of positive HBL and facilitate clinical decision making. However, external validation will be needed in the future.

scholarly journals Risk Factor Analysis for Predicting Kyphosis Reoccurrence of Thoracolumbar Burst Fracture Patients Treated with Posterior Short-Segment Fixation

2021 ◽  
Author(s):  
Xiangyao Sun ◽  
Wenzhi Sun ◽  
Hailiang Hu ◽  
Wei Wang ◽  
Tongtong Zhang ◽  
...  
Keyword(s):  
Risk Factors ◽  
Risk Factor ◽  
Burst Fracture ◽  
Wedge Angle ◽  
Implant Removal ◽  
Thoracolumbar Burst Fracture ◽  
Height Ratio ◽  
Vertebral Height ◽  
Thoracolumbar Injury ◽  
Multi Center Study

Abstract Background: The thresholds of risk factors of kyphosis recurrence in thoracolumbar burst fracture patients were still controversial. The aim of this multi-center study was to identify these thresholds.Methods: 169 patients were included in this study. Upper intervertebral angle (UIVA), lower intervertebral angle (LIVA), Cobb angle (CA), anterior vertebral height ratio (AVH%), regional angle (RA), posterior vertebral height ratio (PVH%), vertebral wedge angle (VWA), anteroposterior ratio (A/P%), Clinical assessment included Load Sharing Classification (LSC) score, Thoracolumbar Injury Classification and Severity (TLICS) score, Visual Analogue Scale (VAS), and Body mass index (BMI) were perioperatively evaluated. Patients were divided into KR group and none KR (NKR) group according to whether the loss of CA correction was less than 15˚ or not. The risk factors of KR before or after implant removal were analyzed, respectively. Result: There were significant improvements in postoperative parameters compared with preoperative parameters, such as AVH%, A/P%, VAS, CA, VWA, PVH% (P < 0.001, respectively), and UIVA (P = 0.02). Age (AUC = 0.828) and BMI (AUC = 0.846) were good predictors of KR before implant removal. BMI (AUC = 0.871) was a good predictor of KR after implant removal. Conclusion: There were significant differences in risk factors of KR at different postoperative follow-up stages: age > 49 years, BMI > 24 were risk factors of KR before implant removal; BMI > 25.17 was a risk factor of KR.

Controversies in Managing of Thoracic-Lumbar Upper Burst Fractures

2018 ◽  
Vol 1 (2) ◽  
Author(s):  
Sahat Edison Sitorus
Keyword(s):  
Decision Making ◽  
Spinal Cord ◽  
Posterior Instrumentation ◽  
Burst Fracture ◽  
Surgical Decompression ◽  
Neurologic Deficit ◽  
Retroperitoneal Approach ◽  
Burst Fractures ◽  
Lateral Fixation

Upper burst fracture of Th12-L1 has unique anatomy because it contains lower spinal cord, medullary cone, and diaphragm which separates between the thoracic and lumbar spine.The presence or absence of neurologic deficit is the single most important factor in the decision making. The presence of profound but incomplete neural deficit in association with canal compromise represents an urgent indication of surgical decompression. Antero-lateral direct decompression with trans-thoracic trans-pleural–retroperitoneal approach given the proximity the cord and conus is the most effective method, with inter-vertebral instrumentation with or without lateral fixation or posterior instrumentation.

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