Hong Woo Suk, Rudas Akos, Bell Elijah J, Chiang Jeffrey N
Department of Emergency Medicine, University of California Los Angeles David Geffen School of Medicine, Los Angeles, California, USA.
Department of Computational Medicine, University of California Los Angeles David Geffen School of Medicine, Los Angeles, California, USA.
JAMIA Open. 2023 Jul 13;6(3):ooad053. doi: 10.1093/jamiaopen/ooad053. eCollection 2023 Oct.
To test the association between the initial red blood cell distribution width (RDW) value in the emergency department (ED) and hospital admission and, among those admitted, in-hospital mortality.
We perform a retrospective analysis of 210 930 adult ED visits with complete blood count results from March 2013 to February 2022. Primary outcomes were hospital admission and in-hospital mortality. Variables for each visit included demographics, comorbidities, vital signs, basic metabolic panel, complete blood count, and final diagnosis. The association of each outcome with the initial RDW value was calculated across 3 age groups (<45, 45-65, and >65) as well as across 374 diagnosis categories. Logistic regression (LR) and XGBoost models using all variables excluding final diagnoses were built to test whether RDW was a highly weighted and informative predictor for each outcome. Finally, simplified models using only age, sex, and vital signs were built to test whether RDW had additive predictive value.
Compared to that of discharged visits (mean [SD]: 13.8 [2.03]), RDW was significantly elevated in visits that resulted in admission (15.1 [2.72]) and, among admissions, those resulting in intensive care unit stay (15.3 [2.88]) and/or death (16.8 [3.25]). This relationship held across age groups as well as across various diagnosis categories. An RDW >16 achieved 90% specificity for hospital admission, while an RDW >18.5 achieved 90% specificity for in-hospital mortality. LR achieved a test area under the curve (AUC) of 0.77 (95% confidence interval [CI] 0.77-0.78) for hospital admission and 0.85 (95% CI 0.81-0.88) for in-hospital mortality, while XGBoost achieved a test AUC of 0.90 (95% CI 0.89-0.90) for hospital admission and 0.96 (95% CI 0.94-0.97) for in-hospital mortality. RDW had high scaled weights and information gain for both outcomes and had additive value in simplified models predicting hospital admission.
Elevated RDW, previously associated with mortality in myocardial infarction, pulmonary embolism, heart failure, sepsis, and COVID-19, is associated with hospital admission and in-hospital mortality across all-cause adult ED visits. Used alone, elevated RDW may be a specific, but not sensitive, test for both outcomes, with multivariate LR and XGBoost models showing significantly improved test characteristics.
RDW, a component of the complete blood count panel routinely ordered as the initial workup for the undifferentiated patient, may be a generalizable biomarker for acuity in the ED.
检验急诊科(ED)初始红细胞分布宽度(RDW)值与住院情况之间的关联,以及在住院患者中与院内死亡率之间的关联。
我们对2013年3月至2022年2月间210930例有全血细胞计数结果的成人ED就诊病例进行了回顾性分析。主要结局为住院情况和院内死亡率。每次就诊的变量包括人口统计学信息、合并症、生命体征、基本代谢指标、全血细胞计数和最终诊断。分别在3个年龄组(<45岁、45 - 65岁和>65岁)以及374个诊断类别中计算每个结局与初始RDW值之间的关联。使用排除最终诊断的所有变量构建逻辑回归(LR)模型和XGBoost模型,以检验RDW是否是每个结局的高权重且信息丰富的预测指标。最后,构建仅使用年龄、性别和生命体征的简化模型,以检验RDW是否具有附加预测价值。
与出院就诊病例(均值[标准差]:13.8[2.03])相比,导致住院的就诊病例中RDW显著升高(15.1[2.72]),在住院患者中,导致入住重症监护病房的病例(15.3[2.88])和/或死亡的病例(16.8[3.25])中RDW更高。这种关系在各年龄组以及各种诊断类别中均成立。RDW>16时对住院的特异性达到90%,而RDW>18.5时对院内死亡的特异性达到90%。LR模型对住院的曲线下面积(AUC)为0.77(95%置信区间[CI]0.77 - 0.78),对院内死亡的AUC为0.85(95%CI0.81 - 0.88),而XGBoost模型对住院的检验AUC为0.90(95%CI0.89 - 0.90),对院内死亡的AUC为0.96(95%CI0.94 - 0.97)。RDW对两个结局均具有高比例权重和信息增益,并且在预测住院情况的简化模型中具有附加价值。
既往研究表明,RDW升高与心肌梗死、肺栓塞、心力衰竭、脓毒症和新型冠状病毒肺炎(COVID - 19)的死亡率相关,在所有病因的成人ED就诊病例中,RDW升高与住院情况和院内死亡率相关。单独使用时,RDW升高可能是这两个结局的一种特异性但非敏感性的检测指标,多变量LR模型和XGBoost模型显示检验特征有显著改善。
RDW是全血细胞计数指标的一部分,通常作为未分化患者初始检查的常规项目,可能是急诊科病情严重程度的一个可推广的生物标志物。