Predictors of amputation in patients with acute compartment syndrome after tibial fracture: a nomogram prediction model

胫骨骨折后急性筋膜室综合征患者截肢的预测因素:列线图预测模型

阅读:1

Abstract

PURPOSES: Amputation is a serious complication in patients with acute compartment syndrome (ACS). However, it risk factors are still poorly understood. Our study aims to investigate the risk factors of amputation in patients with ACS. METHODS: We reviewed the data on ACS patients with tibial fractures from January 2010 to November 2022. Patients with amputation was grouped into the amputation group (AG) and those without amputation was grouped into non-amputation group (NG). We used univariate analysis, logistic regression analysis and nomogram prediction model to analyze the predictors of amputation. RESULTS: The rate of amputation was 8.8% (12 of 136) in our study. Crush injury (p = 0.047), heavy object injury (p = 0.045), the presence of blisters (p<0.0001), the number of debridements (p = 0.022), muscle necrosis (p = 0.004), deep venous thrombosis (DVT, p<0.0001), the level of osmotic pressure (p = 0.003) after fasciotomy were found to be associated with amputation in ACS patients by univariate analysis. Logistic regression analysis showed that crush injury [p = 0.036, OR = 16.403, 95% CI (1.198, 224.609)], heavy object injury [p = 0.010, OR = 50.751, 95% CI (2.577, 999.490)], muscle necrosis [p = 0.017, OR = 17.272, 95% CI (1.666, 179.102)], and DVT [p = 0.009, OR = 22.344, 95% CI (2.146, 232.589)] were risk factors of amputation. Then, we constructed a nomogram prediction model with 0.9066 in AUC of the prediction model with good consistency in the correction curve and good clinical practicality by decision curve analysis. CONCLUSIONS: We identified crush injury, heavy object injury, muscle necrosis, and DVT as independent risk factors for amputation in ACS patients. Our nomogram prediction model can availably predict amputation in ACS patients. Additionally, we found that the timing of fasciotomy is not associated with amputation in ACS patients. LEVEL OF EVIDENCE: Level III.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。