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大数据洞察急性间隔综合征的预测因素。

Big data insights into predictors of acute compartment syndrome.

机构信息

McGill University Health Center - Research Institute.

Hennepin County Hospital, Department of Orthopaedic Surgery.

出版信息

Injury. 2022 Jul;53(7):2557-2561. doi: 10.1016/j.injury.2022.02.041. Epub 2022 Feb 19.

DOI:10.1016/j.injury.2022.02.041
PMID:35249740
Abstract

BACKGROUND

There remain gaps in knowledge regarding the pathophysiology, initial diagnosis, treatment, and outcome of acute compartment syndrome (ACS). Most reported clinical outcomes are from smaller studies of heterogeneous patients. For a disease associated with a financial burden to society that represents billions of dollars worldwide the literature does not currently establish baseline diagnostic parameters and risk factors that may serve to predict treatment and outcomes.

METHODS

This study looks at a very large cohort of trauma patients obtained from four recent years of the Trauma Quality Programs data from the American College of Surgeons. From 3,924,127 trauma cases - 203,500 patients with tibial fractures were identified and their records examined for demographic information, potential risk factors for compartment syndrome, an associated coded diagnosis of muscle necrosis, and presence of other outcomes associated with compartment syndrome. A recurrent multiple logistic regression model was used to identify factors predictive of fasciotomy. The results were compared to the reported results from the literature to validate the findings.

RESULTS

The rate of fasciotomy treatment for ACS was 4.3% in the cohort of identified patients. The analysis identified several clinical predictors of fasciotomy. Proximal and midshaft tibial fractures (P <0.0001) showed highest increases in the likelihood of ACS. Open fractures were twice (O.R [2.20-2.42]) as likely to have ACS. Having a complex fracture (P<0.0001), substance abuse disorder (P<0.0002), cirrhosis (P = 0.002) or smoking (P<0.0051) all increased the likelihood of ACS. Age decreased the likelihood by 1% per year (OR= [0.99-0.993]). Crush and penetrating injuries showed an important increase in the likelihood of ACS (O.R of 1.83 and 1.37 respectively). Additionally, sex, BMI, cirrhosis, tobacco smoking and fracture pattern as defined by OTA group and OTA subgroup had predictive value on actual myonecrosis. Fasciotomies for open tibial fractures were more likely to uncover significant muscle necrosis compared to closed fractures. Amputation resulted after 5.4% of fasciotomies.

CONCLUSION

This big data approach shows us that ACS is primarily linked to the extent of soft tissue damage. However, newfound effect of some comorbidities like cirrhosis and hypertension on the risk of ACS imply other mechanisms.

摘要

背景

目前,人们对急性间隔综合征(ACS)的病理生理学、初步诊断、治疗和预后仍存在知识空白。大多数报告的临床结果来自于对异质性患者的较小研究。对于一种与全球数十亿美元的社会经济负担相关的疾病,目前的文献尚未确定可能有助于预测治疗和结果的基线诊断参数和危险因素。

方法

本研究从美国外科医师学院创伤质量计划的最近四年的大量创伤患者中进行了研究。从 3924127 例创伤病例中,确定了 203500 例胫骨骨折患者,并检查了他们的记录,以获取人口统计学信息、间隔综合征的潜在危险因素、相关编码的肌肉坏死诊断以及与间隔综合征相关的其他结果。使用复发性多逻辑回归模型来确定预测筋膜切开术的因素。将结果与文献中的报告结果进行比较,以验证发现。

结果

在所确定的患者队列中,ACS 的筋膜切开术治疗率为 4.3%。分析确定了几个筋膜切开术的临床预测因素。胫骨近端和中段骨折(P<0.0001)显示 ACS 的可能性增加最高。开放性骨折发生 ACS 的可能性增加了一倍(OR[2.20-2.42])。存在复杂骨折(P<0.0001)、物质滥用障碍(P<0.0002)、肝硬化(P=0.002)或吸烟(P<0.0051)均增加 ACS 的可能性。年龄每增加 1 年,可能性降低 1%(OR[0.99-0.993])。挤压伤和穿透伤的 ACS 发生几率显著增加(OR 分别为 1.83 和 1.37)。此外,性别、BMI、肝硬化、吸烟和 OTA 组和 OTA 亚组定义的骨折模式对实际肌坏死具有预测价值。与闭合性骨折相比,开放性胫骨骨折的筋膜切开术更有可能揭示明显的肌肉坏死。5.4%的筋膜切开术后需要截肢。

结论

这种大数据方法表明,ACS 主要与软组织损伤的程度有关。然而,一些合并症(如肝硬化和高血压)对 ACS 风险的新发现影响暗示了其他机制。

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