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Quantile regression-based prediction of intraoperative blood loss in patients with spinal metastases: model
Jikai Li1, Jingyu Zhang1, Xiaozhao Zhang2
1Department of Bone and Soft Tissue Oncology, Tianjin Hospital, 406 Jiefang Southern Road, Tianjin, 300000, MD, China.
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 ~ 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.
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