机器学习预测大型鞍区肿瘤手术后的静脉血栓栓塞症。
Machine learning prediction of venous thromboembolism after surgeries of major sellar region tumors.
机构信息
Department of Neurosurgery, Huashan Hospital, Shanghai Medical School, Fudan University, Shanghai, China; National Center for Neurological Disorders, China; Shanghai Clinical Medical Center of Neurosurgery, Shanghai, China; Neurosurgical Institute of Fudan University, Shanghai, China; Shanghai Key Laboratory of Medical Brain Function and Restoration and Neural Regeneration, Fudan University, Shanghai, China.
Department of Neurosurgery, Huashan Hospital, Shanghai Medical School, Fudan University, Shanghai, China; National Center for Neurological Disorders, China; Shanghai Clinical Medical Center of Neurosurgery, Shanghai, China; Neurosurgical Institute of Fudan University, Shanghai, China; Shanghai Key Laboratory of Medical Brain Function and Restoration and Neural Regeneration, Fudan University, Shanghai, China.
出版信息
Thromb Res. 2023 Jun;226:1-8. doi: 10.1016/j.thromres.2023.04.007. Epub 2023 Apr 13.
PURPOSE
To describe and predict the risk of venous thromboembolism (VTE) after surgical resection of major sellar region tumors.
METHOD
Patients with sellar region tumors were identified from a database. The outcome was VTE, including deep vein thrombosis (DVT) and pulmonary embolism (PE) within 60 days after surgery. We trained regression and machine learning models to predict the outcome using baseline characteristics, surgical findings and postoperative laboratory tests.
RESULTS
Among 3818 patients included, 124 patients developed VTE after surgery. The total 60-day VTE incidence was 3.2 %, with incidence peak within ten days after the surgery. The risk increased in patients >65 years old (OR 2.96, p < 0.001), in patients with chordoma (OR 3.40, p = 0.006) or craniopharyngioma (OR 1.86, p = 0.036), in patients underwent craniotomy approach (OR 2.78, p = 0.017), in patients with high volume CSF leakage (OR 4.24, p < 0.001), and in patients with longer surgical duration (OR 1.78, p = 0.029). The linear discriminant analysis algorithm had the highest AUC (0.869, 95%CI, 0.840-0.898) in predicting the outcome. The specificity, accuracy, and sensitivity of the best model were 61.8 %, 93.6 %, and 92.8 %, respectively. Risk stratification using our best model suggested that 1.3 % and 24.5 % of the patient developed VTE in the low-risk group and in the high-risk group, respectively. We developed an online decision-support tool available on https://deepvep.shinyapps.io/VTEpred/.
CONCLUSION
The overall incidence of VTE after surgical resection of major sellar region tumors was clinically significant, especially in older patients with chordoma or craniopharyngioma.
目的
描述和预测大型鞍区肿瘤切除术后静脉血栓栓塞症（VTE）的风险。
方法
从数据库中确定了鞍区肿瘤患者。结果为术后 60 天内发生的 VTE，包括深静脉血栓形成（DVT）和肺栓塞（PE）。我们使用基线特征、手术发现和术后实验室检查来训练回归和机器学习模型以预测结果。
结果
在 3818 例患者中，有 124 例患者在手术后发生了 VTE。总 60 天 VTE 发生率为 3.2%，术后 10 天内发病风险最高。年龄>65 岁的患者（OR 2.96，p<0.001）、脊索瘤（OR 3.40，p=0.006）或颅咽管瘤（OR 1.86，p=0.036）患者、接受开颅手术的患者（OR 2.78，p=0.017）、脑脊液大量漏出的患者（OR 4.24，p<0.001）和手术时间较长的患者（OR 1.78，p=0.029）的风险增加。线性判别分析算法在预测结果方面具有最高 AUC（0.869，95%CI，0.840-0.898）。最佳模型的特异性、准确性和敏感性分别为 61.8%、93.6%和 92.8%。使用我们的最佳模型进行风险分层提示低风险组和高风险组分别有 1.3%和 24.5%的患者发生 VTE。我们开发了一个在线决策支持工具，可在 https://deepvep.shinyapps.io/VTEpred/ 上使用。
结论
大型鞍区肿瘤切除术后 VTE 的总体发生率具有临床意义，尤其是在老年患者、脊索瘤或颅咽管瘤患者中。
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