Karolinska Institutet Department of Clinical Sciences, Danderyd Hospital Division of Medicine, Stockholm, Sweden.
Department of Emergency Medicine, Karolinska University Hospital, Solna, Stockholm, Sweden.
Scand J Trauma Resusc Emerg Med. 2023 Oct 18;31(1):55. doi: 10.1186/s13049-023-01123-8.
Previous studies have shown varying results on the validity of the rapid emergency triage and treatment system (RETTS), but have concluded that patient age is not adequately considered as a risk factor for short term mortality. Little is known about the RETTS system's performance between different chief complaints and on short term mortality. We therefore aimed to evaluate how well a model including both RETTS triage priority and patient age (TP and age model) predicts 3-day mortality compared to a univariate RETTS triage priority model (TP model). Secondarily, we aimed to evaluate the TP model compared to a univariate age model (age model) and whether these three models' predictive performance regarding 3-day mortality varies between patients with different chief complaints in an unsorted emergency department patient population.
This study was a prospective historic observational cohort study, using logistic regression on a cohort of patients seeking emergency department care in Stockholm during 2012-2016. Patient visits were stratified into the 10 chief complaint categories (CCC) with the highest number of deceased patients within 3 days of arrival, and to "other chief complaints". Patients with priority 1 were excluded.
The studied cohort contained 1,690,981 visits by 788,046 different individuals. The TP and age model predicted 3-day mortality significantly and substantially better than both univariate models in the total population and in each studied CCC. The age model predicted 3-day mortality significantly and substantially better than the TP model in the total population and for all but three CCCs and was not inferior in any CCC. There were substantial differences between the studied CCCs in the predictive ability of each of the three models.
Adding patient age to the RETTS triage priority system significantly and substantially improves 3-day mortality prediction compared to RETTS priority alone. Age alone is a non-inferior predictor of 3-day mortality compared to RETTS priority. The impact on 3-day mortality prediction of adding patient age to RETTS priority varies between CCCs but is substantial for all CCCs and for the total population. Including age as a variable in future revisions of RETTS could substantially improve patient safety.
先前的研究表明，快速紧急分类和治疗系统（RETTS）的有效性存在差异，但结论是患者年龄未被充分视为短期死亡率的一个风险因素。关于 RETTS 系统在不同主要投诉和短期死亡率方面的表现知之甚少。因此，我们旨在评估包括 RETTS 分类优先级和患者年龄（TP 和年龄模型）在内的模型在预测 3 天死亡率方面的表现与单变量 RETTS 分类优先级模型（TP 模型）相比如何。其次，我们旨在评估 TP 模型与单变量年龄模型（年龄模型）相比，以及这些三个模型在未分类急诊部患者人群中不同主要投诉患者的 3 天死亡率预测方面的表现是否存在差异。
这是一项前瞻性历史观察队列研究，使用逻辑回归对 2012-2016 年在斯德哥尔摩寻求急诊护理的患者队列进行分析。患者就诊被分为死亡人数最多的前 10 个主要投诉类别（CCC）和“其他主要投诉”。优先级 1 的患者被排除在外。
研究队列包含 1690981 次就诊，涉及 788046 名不同个体。TP 和年龄模型在总人群和每个研究的 CCC 中均显著且显著优于两个单变量模型预测 3 天死亡率。在总人群和除三个 CCC 之外的所有 CCC 中，年龄模型在预测 3 天死亡率方面均显著且显著优于 TP 模型，在任何 CCC 中均不劣。在每个模型的预测能力方面，研究的 CCC 之间存在很大差异。
与单独使用 RETTS 优先级相比，将患者年龄添加到 RETTS 分诊优先级系统中可显著且显著提高 3 天死亡率预测。年龄单独是 3 天死亡率的非劣预测因子，与 RETTS 优先级相当。将患者年龄添加到 RETTS 优先级中对 3 天死亡率预测的影响因 CCC 而异，但对所有 CCC 和总人群而言，影响都很大。在未来的 RETTS 修订中包含年龄作为变量可能会大大提高患者安全性。
