| Home | Magazines | Editorial Board | Instruction | Subscribe Guide | Archive | Advertising | Template | Guestbook | Help |
| LIU Changfeng,SONG Wenhui,LIU Changwen.Evaluation and influencing factor analysis of bone cement distribution after percutaneous vertebroplasty[J].Chinese Journal of Spine and Spinal Cord,2019,(11):1001-1008. |
| Evaluation and influencing factor analysis of bone cement distribution after percutaneous vertebroplasty |
| Received:June 24, 2019 Revised:October 11, 2019 |
| English Keywords:Osteoporotic vertebral compression fracture Percutaneous vertebroplasty Bone cement distribution Filling rate |
| Fund:山西省应用基础研究项目（编号：201801D121324） |
|
| Hits: 3215 |
| Download times: 2483 |
| English Abstract: |
| 【Abstract】 Objectives: To explore a new method for evaluating the distribution of bone cement in percutaneous vertebroplasty(PVP), and then to analyze the influencing factors of bone cement distribution. Methods: From May 2015 to May 2018, a total of 132 patients(23 males and 109 females, mean age 77.33±8.27 years) with osteoporotic vertebral compression fracture(OVCF) who underwent PVP were recruited in this retrospective analysis study. The spatial distribution score of bone cement in the vertebral body was calculated according to postoperative X-ray and CT, and patients were allocated to two groups: group A: 0-7 points and group B: 8-10 points. The visual analogue scale(VAS) at preoperation, one-day, three-month, six-month and 12-month follow-up were compared between the two groups. The age, sex, preoperative bone mineral density, and number of fracture days (fracture date to surgery date) were recorded. Furthermore, the volume of the vertebral body, volume of bone cement and filling rate of bone cement were measured by using 3D reconstructed CT images. Potential influencing factors were screened after comparing the difference between the clinical and radiologic parameters in the two groups. Multivariate logistic regression analysis was performed to identify the independent influencing factors of bone cement distribution. Meanwhile, a receiver operating characteristic curve(ROC) was used to determine the cut-off value of the bone cement filling rate. Results: There were 62 patients in group A and 70 patients in group B. Distribution conditions of bone cement include: 2 points 2 cases, 3 points 8 cases, 4 points 6 cases, 5 points 8 cases, 6 points 10 cases, 7 points 28 cases, 8 points 32 cases, 9 points 22 cases, and 10 points 16 cases. VAS scores at one-day, three-month, six-month and 12-month follow-up improved significantly compared with preoperative ones in both groups(P<0.05). Group B had a better restoration of VAS scores at three-month follow-up than group A(P<0.05), but no significant difference was observed at one-day, six-month and 12-month follow-up. In group B, the number of days from fracture to surgery was significantly smaller than that of group A(P<0.05), while the bone cement volume and the filling rate were bigger than those in group A(P<0.05). Filling rate was identified as the independent risk factor influencing the distribution of bone cement by multivariate logistic regression analysis (OR=1.413, 95%CI: 1.202-1.660). The area under the receiver operating characteristic curve of filling rate was 0.778(95%CI: 0.697-0.846, P<0.05). The cut-off value of filling rate to reach a wide bone cement distribution was 28.1%, with a sensitivity of 67.14% and a specificity of 75.81% respectively. Conclutions: PVP can effectively relieve the pain of OVCF, and the bone cement distribution area gradually reduceswith the extension of fracture time. Filling rate was identified as the independent risk factor influencing the distribution of bone cement, and a wide bone cement distribution can be achieved when the filling rate reaches 28.1%. |
| View Full Text View/Add Comment Download reader |
| Close |
|
|
|
|
|