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Abstract：
Overestimated the cross-match of preoperative PRC preparation for elective primary lumbar spinal fusion needs revision for cost-effectiveness. We aimed to develop a novel preoperative predictive model for appropriate PRC preparation. This clinical prediction model in a retrospective cohort was studied between January 2015 and September 2022. Multivariate logistic regression models were used to assess predictive variables. The logistic coefficient of each predictor generated scores to establish a predictive model. The area under the receiver operating characteristic curve (AuROC) was used to evaluate the model. The predictive performance was validated using bootstrapping techniques and externally validated in 102 independent cases. Among 416 patients, 178 (43%) required transfusion. Four final predictors: preoperative hematocrit level, laminectomy level, transforaminal lumbar interbody fusion level, and sacral fusion. When categorized into two risk groups, the positive predictive values for the low-risk score (≤ 4) were 18.4 (95% Cl 13.9, 23.6) and 83.9 (95% CI 77.1, 89.3) for the high-risk score (> 4). AuROC was 0.90. Internal validation (bootstrap shrinkage = 0.993) and external validation (AuROC: 0.91). A new model demonstrated exemplary performance and discrimination in predicting the appropriate preparation for PRC. This study should be corroborated by rigorous external validation in other hospitals and by prospective assessments.
摘要：
为了成本效益，高估了术前PRC准备的交叉匹配，以进行选择性原发性腰椎融合术需要翻修。我们旨在开发一种新的术前预测模型，以进行适当的PRC准备。该临床预测模型在2015年1月至2022年9月之间进行了回顾性队列研究。多变量逻辑回归模型用于评估预测变量。每个预测因子的logistic系数产生分数,建立预测模型。使用受试者工作特征曲线下面积(AuROC)来评估模型。使用自举技术验证了预测性能，并在102个独立案例中进行了外部验证。在416名患者中，178（43%）需要输血。四个最终预测因子：术前血细胞比容水平，椎板切除术水平，经椎间孔腰椎椎间融合水平,和骶骨融合。当分为两个风险组时，低危评分(≤4)的阳性预测值分别为18.4(95%Cl13.9,23.6)和高危评分(>4)的83.9(95%CI77.1,89.3).AuROC为0.90。内部验证(引导收缩=0.993)和外部验证(AuROC:0.91)。一个新模型在预测PRC的适当准备方面表现出了示范性的表现和区别性。这项研究应该得到其他医院严格的外部验证和前瞻性评估的证实。
