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哪些风险因素可预测重伤患者的膝关节韧带损伤?——一项国际多中心分析的结果

Which Risk Factors Predict Knee Ligament Injuries in Severely Injured Patients?-Results from an International Multicenter Analysis.

作者信息

Weber Christian D, Solomon Lucian B, Lefering Rolf, Horst Klemens, Kobbe Philipp, Hildebrand Frank, Dgu TraumaRegister

机构信息

Department of Orthopaedics and Trauma Surgery, RWTH Aachen University, 52074 Aachen, Germany.

Orthopaedic and Trauma Service, Royal Adelaide Hospital and Centre for Orthopaedic and Trauma Research, The University of Adelaide, SA 5005, Adelaide, Australia.

出版信息

J Clin Med. 2020 May 12;9(5):1437. doi: 10.3390/jcm9051437.

Abstract

INTRODUCTION

Ligament injuries around the knee joint and knee dislocations are rare but potentially complex injuries associated with high-energy trauma. Concomitant neurovascular injuries further affect their long-term clinical outcomes. In contrast to isolated ligamentous knee injuries, epidemiologic data and knowledge on predicting knee injuries in severely injured patients is still limited.

METHODS

The TraumaRegister DGU (TR-DGU) was queried (01/2009-12/2016). Inclusion criteria for selection from the database: maximum abbreviated injury severity ≥ 3 points (MAIS 3+). Participating countries: Germany, Austria, and Switzerland. The two main groups included a "control" and a "knee injury" group. The injury severity score (ISS) and new ISS (NISS) were used for injury severity classification, and the abbreviated injury scale (AIS) was used to classify the severity of the knee injury. Logistic regression analysis was performed to evaluate various risk factors for knee injuries.

RESULTS

The study cohort included 139,462 severely injured trauma patients. We identified 4411 individuals (3.2%) with a ligament injury around the knee joint ("knee injury" group) and 1153 patients with a knee dislocation (0.8%). The risk for associated injuries of the peroneal nerve and popliteal artery were significantly increased in dislocated knees when compared to controls (peroneal nerve from 0.4% to 6.7%, popliteal artery from 0.3% to 6.9%, respectively). Among the predictors for knee injuries were specific mechanisms of injury: e.g., pedestrian struck (Odds ratio [OR] 3.2, 95% confidence interval [CI]: 2.69-3.74 ≤ 0.001), motorcycle (OR 3.0, 95% CI: 2.58-3.48, ≤ 0.001), and motor vehicle accidents (OR 2.2, 95% CI: 1.86-2.51, ≤ 0.001) and associated skeletal injuries, e.g., patella (OR 2.3, 95% CI: 1.99-2.62, ≤ 0.001), tibia (OR 1.9, 95% CI: 1.75-2.05, ≤ 0.001), and femur (OR 1.8, 95% CI: 1.64-1.89, ≤ 0.001), but neither male sex nor general injury severity (ISS).

CONCLUSION

Ligament injuries and knee dislocations are associated with high-risk mechanisms and concomitant skeletal injuries of the lower extremity, but are not predicted by general injury severity or sex. Despite comparable ISS, knee injuries prolong the hospital length of stay. Delayed or missed diagnosis of knee injuries can be prevented by comprehensive clinical evaluation after fracture fixation and a high index of suspicion is advised, especially in the presence of the above mentioned risk factors.

摘要

引言

膝关节周围韧带损伤和膝关节脱位较为罕见,但却是与高能创伤相关的潜在复杂损伤。并发的神经血管损伤会进一步影响其长期临床预后。与单纯的膝关节韧带损伤不同,关于严重创伤患者膝关节损伤的流行病学数据及预测知识仍然有限。

方法

查询创伤注册数据库DGU(2009年1月至2016年12月)。从数据库中选择的纳入标准:最高简略损伤严重程度≥3分(MAIS 3+)。参与国家:德国、奥地利和瑞士。两个主要组包括一个“对照组”和一个“膝关节损伤组”。损伤严重程度评分(ISS)和新损伤严重程度评分(NISS)用于损伤严重程度分类,简略损伤量表(AIS)用于对膝关节损伤的严重程度进行分类。进行逻辑回归分析以评估膝关节损伤的各种危险因素。

结果

研究队列包括139462例严重创伤患者。我们确定了4411例膝关节周围韧带损伤患者(“膝关节损伤组”)和1153例膝关节脱位患者(0.8%)。与对照组相比,膝关节脱位时腓总神经和腘动脉相关损伤的风险显著增加(腓总神经从0.4%增至6.7%,腘动脉从0.3%增至6.9%)。膝关节损伤的预测因素包括特定的损伤机制,例如行人被撞(优势比[OR] 3.2,95%置信区间[CI]:2.69 - 3.74,≤0.001)、摩托车事故(OR 3.0,95% CI:2.58 - 3.48,≤0.001)和机动车事故(OR 2.2,95% CI:1.86 - 2.51,≤0.001)以及相关的骨骼损伤,例如髌骨(OR 2.3,95% CI:1.99 - 2.62,≤0.001)、胫骨(OR 1.9,95% CI:1.75 - 2.05,≤0.001)和股骨(OR 1.8,95% CI:1.64 - 1.89,≤0.001),但不包括男性性别或总体损伤严重程度(ISS)。

结论

韧带损伤和膝关节脱位与高危机制及下肢并发骨骼损伤相关,但不能通过总体损伤严重程度或性别来预测。尽管ISS相当,但膝关节损伤会延长住院时间。骨折固定后通过全面的临床评估可预防膝关节损伤的延迟诊断或漏诊,建议保持高度怀疑,尤其是在存在上述危险因素的情况下。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e09/7290858/4a2f414918fd/jcm-09-01437-g001.jpg

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