Quantile regression-based prediction of intraoperative blood loss in patients with spinal metastases: model development and validation

被引:2
|
作者
Li, Jikai [1 ]
Zhang, Jingyu [1 ]
Zhang, Xiaozhao [2 ]
Lun, Dengxing [3 ]
Li, Ruifeng [4 ]
Ma, Rongxing [4 ]
Hu, Yongcheng [1 ]
机构
[1] Tianjin Hosp, Dept Bone & Soft Tissue Oncol, 406 Jiefang Southern Rd, Tianjin 300000, Peoples R China
[2] Qinghai Renji Hosp, Xining, Peoples R China
[3] Weifang Peoples Hosp, Dept Bone Oncol, Weifang, Peoples R China
[4] Tianjin Med Univ, Grad Sch, Tianjin, Peoples R China
关键词
Intraoperative blood loss; Spine metastasis; Prediction model; MICROWAVE ABLATION; PREOPERATIVE EMBOLIZATION; AMERICAN-COLLEGE; TRANSFUSION; SURGERY; COMPLICATIONS; DECOMPRESSION; MANAGEMENT; EFFICACY; DISEASE;
D O I
10.1007/s00586-023-07653-0
中图分类号
R74 [神经病学与精神病学];
学科分类号
摘要
Purpose To develop and evaluate a quantile regression-based blood loss prediction model for open surgery of spinal metastases. Methods This was a multicenter retrospective cohort study. Over a 11-year period, patients underwent open surgery for spinal metastases at 6 different institutions were reviewed. The outcome measure is intraoperative blood loss (in mL). The effects of baseline, histology of primary tumor and surgical procedure on blood loss were evaluated by univariate and multivariate analysis to determine the predictors. Multivariate ordinary least squares (OLS) regression and 0.75 quantile regression were used to establish two prediction models. The performance of the two models was evaluated in the training set and the test set, respectively. Results 528 patients were included in this study. Mean age was 57.6 +/- 11.2 years, with a range of 20-86 years. Mean blood loss was 1280.1 +/- 1181.6 mL, with a range of 10 similar to 10,000 mL. Body mass index (BMI), tumor vascularization, surgical site, surgical extent, total en bloc spondylectomy and microwave ablation use were significant predictors of intraoperative blood loss. Hypervascular tumor, higher BMI, and broader surgical extent were related with massive blood loss. Microwave ablation is more beneficial in surgery with substantial blood loss. Compared to the OLS regression model, the 0.75 quantile regression model may decrease blood loss underestimate. Conclusion In this study, we developed and evaluated a prediction model for blood loss in open surgery for spinal metastases based on 0.75 quantile regression, which may minimize blood loss underestimate.
引用
收藏
页码:2479 / 2492
页数:14
相关论文
共 50 条
  • [41] Metallurgical Copper Recovery Prediction Using Conditional Quantile Regression Based on a Copula Model
    Hernandez, Heber
    Diaz-Viera, Martin Alberto
    Alberdi, Elisabete
    Oyarbide-Zubillaga, Aitor
    Goti, Aitor
    MINERALS, 2024, 14 (07)
  • [42] Surgical treatment of spinal metastases from renal cell carcinoma—effects of preoperative embolization on intraoperative blood loss
    Matthias Reitz
    Klaus Christian Mende
    Christopher Cramer
    Theresa Krätzig
    ZSuzsanna Nagy
    Eik Vettorazzi
    Sven Oliver Eicker
    Marc Dreimann
    Neurosurgical Review, 2018, 41 : 861 - 867
  • [43] Development and validation of a prognostic nomogram for the overall survival of patients living with spinal metastases
    Yang, Xiong-gang
    Feng, Jiang-tao
    Wang, Feng
    He, Xin
    Zhang, Hao
    Yang, Li
    Zhang, Hao-ran
    Hu, Yong-cheng
    JOURNAL OF NEURO-ONCOLOGY, 2019, 145 (01) : 167 - 176
  • [44] Development and validation of a prognostic nomogram for the overall survival of patients living with spinal metastases
    Xiong-gang Yang
    Jiang-tao Feng
    Feng Wang
    Xin He
    Hao Zhang
    Li Yang
    Hao-ran Zhang
    Yong-cheng Hu
    Journal of Neuro-Oncology, 2019, 145 : 167 - 176
  • [45] Intraoperative blood loss, postoperative drainage, and recovery in patients undergoing lumbar spinal surgery
    Zou, Haibo
    Li, Zhongshi
    Sheng, Houfu
    Tan, Mingsheng
    Yang, Feng
    Liang, Li
    Zhao, Jingxin
    BMC SURGERY, 2015, 15
  • [46] Assessment of ridge regression-based machine learning model for the prediction of automotive sales based on the customer requirements
    Akash, C. Renga
    Vivekanandhan, P.K.
    Adam Khan, M.
    Ebenezer, G.
    Vinoth, K.
    Prithivirajan, J.
    Kishan, V. J. Pranesh
    Interactions, 2024, 245 (01)
  • [47] Intraoperative blood loss, postoperative drainage, and recovery in patients undergoing lumbar spinal surgery
    Haibo Zou
    Zhongshi Li
    Houfu Sheng
    Mingsheng Tan
    Feng Yang
    Li Liang
    Jingxin Zhao
    BMC Surgery, 15
  • [48] Development and validation of a survival prediction model for patients with advanced non-small cell lung cancer based on LASSO regression
    Guo, Yimeng
    Li, Lihua
    Zheng, Keao
    Du, Juan
    Nie, Jingxu
    Wang, Zanhong
    Hao, Zhiying
    FRONTIERS IN IMMUNOLOGY, 2024, 15
  • [49] Fuzzy support vector regression-based link quality prediction model for wireless sensor networks
    Shu, Jian
    Tang, Jin
    Liu, Linlan
    Hu, Gang
    Liu, Song
    Jisuanji Yanjiu yu Fazhan/Computer Research and Development, 2015, 52 (08): : 1842 - 1851
  • [50] Prospective validation of a clinical prediction score for survival in patients with spinal metastases: the New England Spinal Metastasis Score
    Schoenfeld, Andrew J.
    Ferrone, Marco L.
    Schwab, Joseph H.
    Blucher, Justin A.
    Barton, Lauren B.
    Tobert, Daniel G.
    Chi, John H.
    Shin, John H.
    Kang, James D.
    Harris, Mitchel B.
    SPINE JOURNAL, 2021, 21 (01): : 28 - 36