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院前生命体征缺失中的损伤严重程度偏差:患病率及其对创伤登记的影响。

Injury severity bias in missing prehospital vital signs: Prevalence and implications for trauma registries.

作者信息

O'Neill Melissa, Cheskes Sheldon, Drennan Ian, Keown-Stoneman Charles, Lin Steve, Nolan Brodie

机构信息

Institute of Medical Science, University of Toronto, Toronto, ON, Canada; Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, ON, Canada.

Institute of Medical Science, University of Toronto, Toronto, ON, Canada; Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, ON, Canada; Sunnybrook Centre for Prehospital Medicine, Toronto, ON, Canada; Sunnybrook Research Institute, Sunnybrook Health Science Centre, Toronto, ON, Canada; Department of Family and Community Medicine, Division of Emergency Medicine, University of Toronto, Toronto, ON, Canada.

出版信息

Injury. 2025 Jan;56(1):111747. doi: 10.1016/j.injury.2024.111747. Epub 2024 Jul 18.

DOI:10.1016/j.injury.2024.111747
PMID:39054233
Abstract

BACKGROUND

Vital signs are important factors in assessing injury severity and guiding trauma resuscitation, especially among severely injured patients. Despite this, physiological data are frequently missing from trauma registries. This study aimed to evaluate the extent of missing prehospital data in a hospital-based trauma registry and to assess the associations between prehospital physiological data completeness and indicators of injury severity.

METHODS

A retrospective review was conducted on all adult trauma patients brought directly to a level 1 trauma center in Toronto, Ontario by paramedics from January 1, 2015, to December 31, 2019. The proportion of missing data was evaluated for each variable and patterns of missingness were assessed. To investigate the associations between prehospital data completeness and injury severity factors, descriptive and unadjusted logistic regression analyses were performed.

RESULTS

A total of 3,528 patients were included. We considered prehospital data missing if any of heart rate, systolic blood pressure, respiratory rate or oxygen saturation were incomplete. Each individual variable was missing from the registry in approximately 20 % of patients, with oxygen saturation missing most frequently (n = 831; 23.6 %). Over 25 % (n = 909) of patients were missing at least one prehospital vital sign, of which 69.1 % (n = 628) were missing all four of these variables. Patients with incomplete data were more severely injured, had higher mortality, and more frequently received lifesaving interventions such as blood transfusion and intubation. Patients were most likely to have missing prehospital physiological data if they died in the trauma bay (unadjusted OR: 9.79; 95 % CI: 6.35-15.10), did not survive to discharge (unadjusted OR: 3.55; 95 % CI: 2.76-4.55), or had a prehospital GCS less than 9 (OR: 3.24; 95 % CI: 2.59-4.06).

CONCLUSION

In this single center trauma registry, key prehospital variables were frequently missing, particularly among more severely injured patients. Patients with missing data had higher mortality, more severe injury characteristics and received more life-saving interventions in the trauma bay, suggesting an injury severity bias in prehospital vital sign missingness. To ensure the validity of research based on trauma registry data, patterns of missingness must be carefully considered to ensure missing data is appropriately addressed.

摘要

背景

生命体征是评估损伤严重程度和指导创伤复苏的重要因素,尤其是在重伤患者中。尽管如此,创伤登记处经常缺少生理数据。本研究旨在评估基于医院的创伤登记处院前数据缺失的程度,并评估院前生理数据完整性与损伤严重程度指标之间的关联。

方法

对2015年1月1日至2019年12月31日由护理人员直接送往安大略省多伦多市一级创伤中心的所有成年创伤患者进行回顾性研究。评估每个变量的数据缺失比例,并评估缺失模式。为了研究院前数据完整性与损伤严重程度因素之间的关联,进行了描述性和未调整的逻辑回归分析。

结果

共纳入3528例患者。如果心率、收缩压、呼吸频率或血氧饱和度中的任何一项不完整,我们就认为院前数据缺失。每个单独变量在约20%的患者中登记缺失,其中血氧饱和度缺失最为频繁(n = 831;23.6%)。超过25%(n = 909)的患者至少缺失一项院前生命体征,其中69.1%(n = 628)的患者这四项变量全部缺失。数据不完整的患者损伤更严重,死亡率更高,更频繁地接受输血和插管等救命干预措施。如果患者在创伤室死亡(未调整OR:9.79;95%CI:6.35 - 15.10)、未存活至出院(未调整OR:3.55;95%CI:2.76 - 4.55)或院前格拉斯哥昏迷评分低于9分(OR:3.24;95%CI:2.59 - 4.06),则最有可能缺失院前生理数据。

结论

在这个单中心创伤登记处,关键的院前变量经常缺失,尤其是在伤势更严重的患者中。数据缺失的患者死亡率更高,损伤特征更严重,在创伤室接受更多的救命干预措施,这表明院前生命体征缺失存在损伤严重程度偏差。为确保基于创伤登记处数据的研究的有效性,必须仔细考虑缺失模式,以确保适当处理缺失数据。

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