Department of Paramedicine, School of Primary and Allied Health Care, Monash University, Frankston, Victoria, Australia.
Queensland Ambulance Service, Queensland Government Department of Health, Kedron, Queensland, Australia.
Acad Emerg Med. 2024 Nov;31(11):1139-1149. doi: 10.1111/acem.14963. Epub 2024 Jun 11.
Various prognosticative approaches to assist in recognizing clinical deterioration have been proposed. To date, early warning scores (EWSs) have been evaluated in hospital with limited research investigating their suitability in the prehospital setting. This study evaluated the predictive ability of established EWSs and other clinical factors for prehospital clinical deterioration.
A retrospective cohort study investigating adult patients of all etiologies attended by Queensland Ambulance Service paramedics between January 1, 2018, and December 31, 2020, was conducted. With logistic regression, several models were developed to predict adverse event outcomes. The National Early Warning Score (NEWS), Modified Early Warning Score (MEWS), Queensland Adult Deterioration Detection System (Q-ADDS), and shock index were calculated from vital signs taken by paramedics.
A total of 1,422,046 incidents met the inclusion criteria. NEWS, MEWS, and Q-ADDS were found to have comparably high predictive ability with area under the receiver operating characteristic curve (AUC-ROC) between 70% and 90%, whereas shock index had relatively low AUC-ROC. Sensitivity was lower than specificity for all models. Although established EWSs performed well when predicting adverse events, these scores require complex calculations requiring multiple vital signs that may not be suitable for the prehospital setting.
This study found NEWS, MEWS, and Q-ADDS all performed well in the prehospital setting. Although a simple shock index is easier for paramedics to use in the prehospital environment, it did not perform comparably to established EWSs. Further research is required to develop suitably performing parsimonious solutions until established EWSs are integrated into technological solutions to be used by prehospital clinicians in real time.
已经提出了各种预后方法来协助识别临床恶化。迄今为止，早期预警评分（EWS）已在医院进行了评估，但很少有研究调查其在院前环境中的适用性。本研究评估了既定 EWS 和其他临床因素对院前临床恶化的预测能力。
对昆士兰救护车服务护理人员在 2018 年 1 月 1 日至 2020 年 12 月 31 日期间救治的各种病因的成年患者进行了回顾性队列研究。通过逻辑回归，建立了几个模型来预测不良事件结局。NEWS、MEWS、昆士兰成人恶化检测系统（Q-ADDS）和休克指数是根据护理人员测量的生命体征计算得出的。
共有 1,422,046 起事件符合纳入标准。NEWS、MEWS 和 Q-ADDS 的预测能力相当高，ROC 曲线下面积（AUC-ROC）在 70%至 90%之间，而休克指数的 AUC-ROC 相对较低。所有模型的敏感性均低于特异性。尽管既定的 EWS 在预测不良事件方面表现良好，但这些评分需要复杂的计算，需要多个生命体征，可能不适合院前环境。
本研究发现 NEWS、MEWS 和 Q-ADDS 在院前环境中表现良好。虽然简单的休克指数更便于护理人员在院前环境中使用，但与既定的 EWS 相比表现并不相当。需要进一步研究以开发表现良好的简约解决方案，直到既定的 EWS 被整合到技术解决方案中，以便院前临床医生实时使用。
