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开发和验证用于预测孤立跟骨骨折患者术前深静脉血栓形成(DVT)的预测列线图。

Development and validation of a predictive nomogram for preoperative deep vein thrombosis (DVT) in isolated calcaneal fracture.

机构信息

Department of Orthopaedic Surgery, The 3rd Hospital of Hebei Medical University, Shijiazhuang, 050051, Hebei, People's Republic of China.

Orthopaedic Institution of Hebei Province, Shijiazhuang, 050051, Hebei, People's Republic of China.

出版信息

Sci Rep. 2022 Apr 8;12(1):5923. doi: 10.1038/s41598-022-10002-8.

Abstract

The fact that most of the patients with preoperative DVTs after calcaneal fractures are asymptomatic brought challenges to the early intervention, and periodic imaging examinations aggravated the financial burden of the patients in preoperative detumescence period. This study aimed to use routine clinical data, obtained from the database of Surgical Site Infection in Orthopaedic Surgery (SSIOS), to construct and validate a nomogram for predicting preoperative DVT risk in patients with isolated calcaneal fracture. The nomogram was established base on 7 predictors independently related to preoperative DVT. The performance of the model was tested by concordance index (C-index), receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA), and the results were furtherly verified internally and externally. 952 patients were enrolled in this study, of which 711 were used as the training set. The AUC of the nomogram was 0.870 in the training set and 0.905 in the validation set. After internal verification, the modified C-index was 0.846. Calibration curve and decision curve analysis both performed well in the training set and validation set. In short, we constructed a nomogram for predicting preoperative DVT risk in patients with isolated calcaneal fracture and verified its accuracy and clinical practicability.

摘要

事实上,大多数跟骨骨折术后存在术前深静脉血栓的患者并无症状,这给早期干预带来了挑战,而定期影像学检查则加重了术前消肿期患者的经济负担。本研究旨在利用来自骨科手术部位感染(SSIOS)数据库的常规临床数据,构建并验证一个预测孤立性跟骨骨折患者术前深静脉血栓风险的列线图。该列线图基于 7 个与术前深静脉血栓独立相关的预测因素建立。通过一致性指数(C 指数)、接收者操作特征(ROC)曲线、校准曲线和决策曲线分析(DCA)来检验模型的性能,并在内部和外部进行了进一步验证。本研究共纳入 952 例患者,其中 711 例用于训练集。该列线图在训练集和验证集中的 AUC 分别为 0.870 和 0.905。经内部验证,改良 C 指数为 0.846。校准曲线和决策曲线分析在训练集和验证集中均表现良好。总之,我们构建了一个预测孤立性跟骨骨折患者术前深静脉血栓风险的列线图,并验证了其准确性和临床实用性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5db4/8993928/79f207624d59/41598_2022_10002_Fig1_HTML.jpg

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