Schenk Philipp, Jacobi Arija, Graebsch Carolin, Mendel Thomas, Hofmann Gunther Olaf, Ullrich Bernhard Wilhelm
Department of Science, Research and Education, BG Klinikum Bergmannstrost Halle gGmbH, 06112 Halle, Germany.
Department of Orthopedic and Trauma Surgery, DIAKO Ev. Diakonie-Krankenhaus gGmbH, 28239 Bremen, Germany.
J Pers Med. 2022 Dec 17;12(12):2081. doi: 10.3390/jpm12122081.
Background: The correction of malposition according to vertebral fractures is difficult because the alignment at the time before the fracture is unclear. Therefore, we investigate whether the spinal alignment can be determined by the spino-pelvic parameters. Methods: Pelvic incidence (PI), pelvic tilt (PT), sacral slope (SS), adjacent endplate angles (EPA), age, sex, body weight, body size, BMI, and age were used to predict mono- and bisegmental EPA (mEPA, bEPA) in the supine position using linear regression models. This study was approved by the Ethics Committee of the Medical Association of Saxony-Anhalt Germany on 20 August 2020, under number 46/20. Results: Using data from 287 patients, the prediction showed R2 from 0.092 up to 0.972. The adjacent cranial and caudal EPA showed by far the most frequently significance in the prediction of all parameters used. Anthropometric and spino-pelvic parameters showed sparse impact, which was frequently in the lower lumbar regions. On average, a very good prediction was found. For two mEPA (L3/4 R2 = 0.914, L4/5 R2 = 0.953) and two bEPA (L3 R2 = 0.899, L4 R2 = 0.972), the R2 was >0.8. However, the predicted EPA differed for individual patients, even in these very effective prediction models—roughly around ±10° as compared to the measured EPA. Conclusions: In general, the prediction showed good to perfect results. In the supine position, the spinopelvic and anthropometric parameters show sparse impact on the prediction of mEPA or bEPA.
由于骨折前的脊柱排列情况不明，根据椎体骨折进行错位矫正很困难。因此，我们研究是否可以通过脊柱 - 骨盆参数来确定脊柱排列。方法：使用骨盆入射角（PI）、骨盆倾斜角（PT）、骶骨斜率（SS）、相邻终板角（EPA）、年龄、性别、体重、体型、BMI 和年龄，通过线性回归模型预测仰卧位下单节段和双节段 EPA（mEPA、bEPA）。本研究于2020年8月20日获得德国萨克森 - 安哈尔特州医学协会伦理委员会批准，批准号为46/20。结果：使用287例患者的数据，预测显示R2值从0.092到0.972。在所有使用的参数预测中，相邻的头侧和尾侧EPA显示出的显著性最为频繁。人体测量和脊柱 - 骨盆参数显示影响较小，且多在腰椎下部区域。平均而言，预测效果非常好。对于两个mEPA（L3/4，R2 = 0.914；L4/5，R2 = 0.953）和两个bEPA（L3，R2 = 0.899；L4，R2 = 0.972），R2大于0.8。然而，即使在这些非常有效的预测模型中，个体患者的预测EPA也有所不同，与测量的EPA相比大致相差±10°左右。结论：总体而言，预测显示出良好到完美的结果。在仰卧位时，脊柱 - 骨盆和人体测量参数对mEPA或bEPA预测的影响较小。
