Simkins Tyrell J, Bissig David, Moreno Gabriel, Kahlon Nimar Pal K, Gorin Fredric, Duffy Alexandra
Department of Neurology University of California, Davis Sacramento California USA.
Touro University Vallejo California USA.
J Am Coll Emerg Physicians Open. 2021 Sep 10;2(5):e12522. doi: 10.1002/emp2.12522. eCollection 2021 Oct.
Approximately 5% of emergency department patients present with altered mental status (AMS). AMS is diagnostically challenging because of the wide range of causes and is associated with high mortality. We sought to develop a clinical decision rule predicting admission risk among emergency department (ED) patients with AMS.
Using retrospective chart review of ED encounters for AMS over a 2-month period, we recorded causes of AMS and numerous clinical variables. Encounters were split into those admitted to the hospital ("cases") and those discharged from the ED ("controls"). Using the first month's data, variables correlated with hospital admission were identified and narrowed using univariate and multivariate statistics, including recursive partitioning. These variables were then organized into a clinical decision rule and validated on the second month's data. The decision rule results were also compared to 1-year mortality.
We identified 351 encounters for AMS over a 2-month period. Significant contributors to AMS included intoxication and chronic disorder decompensation. ED data predicting hospital admission included vital sign abnormalities, select lab studies, and psychiatric/intoxicant history. The decision rule sorted patients into low, moderate, or high risk of admission (11.1%, 44.3%, and 89.1% admitted, respectively) and was predictive of 1-year mortality (low-risk group 1.8%, high-risk group 34.3%).
We catalogued common causes for AMS among patients presenting to the ED, and our data-driven decision tool triaged these patients for risk of admission with good predictive accuracy. These methods for creating clinical decision rules might be further studied and improved to optimize ED patient care.
约5%的急诊科患者存在精神状态改变(AMS)。由于病因范围广泛,AMS在诊断上具有挑战性,且与高死亡率相关。我们试图制定一项临床决策规则,以预测急诊科(ED)中患有AMS的患者的入院风险。
通过回顾性查阅两个月期间急诊科AMS患者的病历,我们记录了AMS的病因及众多临床变量。将就诊情况分为入院患者(“病例”)和急诊科出院患者(“对照”)。利用第一个月的数据,识别与入院相关的变量,并通过单变量和多变量统计(包括递归划分)进行筛选。然后将这些变量整理成临床决策规则,并在第二个月的数据上进行验证。决策规则的结果还与1年死亡率进行了比较。
在两个月期间,我们确定了351例AMS就诊病例。AMS的重要促成因素包括中毒和慢性疾病失代偿。预测入院的急诊科数据包括生命体征异常、特定实验室检查以及精神病史/中毒史。该决策规则将患者分为低、中、高入院风险组(分别为11.1%、44.3%和89.1%的入院率),并能预测1年死亡率(低风险组为1.8%,高风险组为34.3%)。
我们梳理了急诊科AMS患者的常见病因,我们的数据驱动决策工具对这些患者的入院风险进行了分类,预测准确性良好。这些创建临床决策规则的方法可能需要进一步研究和改进,以优化急诊科患者护理。