Servicio de Urgencias y Emergencias, Althaia Xarxa Assistencial Universitària de Manresa, Manresa, España. Programa de Doctorado en Ciencias de la Salud, Universidad Internacional de Catalunya, Barcelona, España.
Servicio de Urgencias y Emergencias, Althaia Xarxa Assistencial Universitària de Manresa, Manresa, España. Departamento de Medicina, Universitat Internacional de Catalunya, Sant Cugat del Vallès, España.
Emergencias. 2022 Jun;34(3):165-173.
To prospectively validate a model to predict hospital admission of patients given a low-priority classification on emergency department triage and to indicate the safety of reverse triage.
Single-center observational study of a prospective cohort to validate a risk model incorporating demographic and emergency care process variables as well as vital signs. The cohort included emergency visits from patients over the age of 15 years with priority level classifications of IV and V according to the Andorran-Spanish triage system (Spanish acronym, MAT-SET) between October 2018 and June 2019. The area under the receiver operating characteristic curve (AUC) of the model was calculated to evaluate discrimination. Based on the model, we identified cut-off points to distinguish patients with low, intermediate, or high risk for hospital admission.
A total of 2110 emergencies were included in the validation cohort; 109 patients (5.2%) were hospitalized. The median age was 43.5 years (interquartile range, 31-60.3 years); 55.5% were female. The AUC was 0.71 (95% CI, 0.64-0.75). The model identified 357 patients (16.9%) at low risk of hospitalization and 240 (11.4%) at high risk. A total of 15.8% of the high-risk patients and 2.8% of the low-risk patients were hospitalized.
The validated model is able to identify risk for hospitalization among patients classified as low priority on triage. Patients identified as having high risk of hospitalization could be offered preferential treatment within the same level of priority at triage, while those at low risk of admission could be referred to a more appropriate care level on reverse triage.
前瞻性验证一种预测急诊分诊低优先级患者住院的模型,并说明反向分诊的安全性。
这是一项针对前瞻性队列的单中心观察性研究,旨在验证一种包含人口统计学和急救护理过程变量以及生命体征的风险模型。该队列包括 2018 年 10 月至 2019 年 6 月期间根据安道尔-西班牙分诊系统(西班牙语缩写为 MAT-SET)分类为 IV 和 V 级别的 15 岁以上患者的急诊就诊。计算模型的受试者工作特征曲线(ROC)下面积(AUC)以评估其区分度。根据模型,我们确定了区分低、中、高危住院的切点。
验证队列共纳入 2110 例急诊,109 例(5.2%)患者住院。中位年龄为 43.5 岁(四分位距 31-60.3 岁);55.5%为女性。AUC 为 0.71(95%CI 0.64-0.75)。该模型确定了 357 例(16.9%)低住院风险和 240 例(11.4%)高住院风险的患者。高危患者中有 15.8%和低危患者中有 2.8%住院。
验证后的模型能够识别出在分诊中被归类为低优先级的患者的住院风险。可以为那些被认为有高住院风险的患者在分诊的同一优先级水平内提供优先治疗,而那些低住院风险的患者则可以通过反向分诊转至更合适的护理级别。