Bharadwaj Maheetha, Jezmir Julia L, Kishore Sandeep P, Winkler Marisa, Diephus Bradford, Haider Hibah, Crowley Conor P, Pinilla-Vera Mayra, Varon Jack, Baron Rebecca M, Feldman William B, Kim Edy Y
Harvard Medical School, Boston, MA.
Department of Medicine, Brigham and Women's Hospital, Boston, MA.
Crit Care Explor. 2021 Jul 15;3(7):e0496. doi: 10.1097/CCE.0000000000000496. eCollection 2021 Jul.
To establish the feasibility of empirically testing crisis standards of care guidelines.
Retrospective single-center study.
ICUs at a large academic medical center in the United States.
Adult, critically ill patients admitted to ICU, with 27 patients admitted for acute respiratory failure due to coronavirus disease 2019 and 37 patients admitted for diagnoses other than coronavirus disease 2019.
Review of electronic health record.
Many U.S. states released crisis standards of care guidelines with algorithms to allocate scarce healthcare resources during the coronavirus disease 2019 pandemic. We compared state guidelines that represent different approaches to incorporating disease severity and comorbidities: New York, Maryland, Pennsylvania, and Colorado. Following each algorithm, we calculated priority scores at the time of ICU admission for a cohort of patients with primary diagnoses of coronavirus disease 2019 and diseases other than coronavirus disease 2019 (n = 64). We assessed discrimination of 28-day mortality by area under the receiver operating characteristic curve. We simulated real-time decision-making by applying the triage algorithms to groups of two, five, or 10 patients. For prediction of 28-day mortality by priority scores, area under the receiver operating characteristic curve was 0.56, 0.49, 0.53, 0.66, and 0.69 for New York, Maryland, Pennsylvania, Colorado, and raw Sequential Organ Failure Assessment score algorithms, respectively. For groups of five patients, the percentage of decisions made without deferring to a lottery were 1%, 57%, 80%, 88%, and 95% for New York, Maryland, Pennsylvania, Colorado, and raw Sequential Organ Failure Assessment score algorithms, respectively. The percentage of decisions made without lottery was higher in the subcohort without coronavirus disease 2019, compared with the subcohort with coronavirus disease 2019.
Inclusion of comorbidities does not consistently improve an algorithm's performance in predicting 28-day mortality. Crisis standards of care algorithms result in a substantial percentage of tied priority scores. Crisis standards of care algorithms operate differently in cohorts with and without coronavirus disease 2019. This proof-of-principle study demonstrates the feasibility and importance of empirical testing of crisis standards of care guidelines to understand whether they meet their goals.
确定经验性测试危机护理标准指南的可行性。
回顾性单中心研究。
美国一家大型学术医疗中心的重症监护病房。
入住重症监护病房的成年重症患者，其中27例因2019冠状病毒病导致急性呼吸衰竭入院，37例因2019冠状病毒病以外的诊断入院。
审查电子健康记录。
许多美国州发布了危机护理标准指南，其中包含在2019冠状病毒病大流行期间分配稀缺医疗资源的算法。我们比较了代表不同纳入疾病严重程度和合并症方法的州指南：纽约州、马里兰州、宾夕法尼亚州和科罗拉多州。按照每种算法，我们计算了一组以2019冠状病毒病为主要诊断的患者以及2019冠状病毒病以外疾病患者（n = 64）入住重症监护病房时的优先级分数。我们通过受试者操作特征曲线下面积评估对28天死亡率的区分度。我们将分诊算法应用于两组、五组或十组患者来模拟实时决策。对于通过优先级分数预测28天死亡率，纽约州、马里兰州、宾夕法尼亚州、科罗拉多州以及原始序贯器官衰竭评估分数算法的受试者操作特征曲线下面积分别为0.56、0.49、0.53、0.66和0.69。对于五组患者，纽约州、马里兰州、宾夕法尼亚州、科罗拉多州以及原始序贯器官衰竭评估分数算法不依赖抽签做出决策的比例分别为1%、57%、80%、88%和95%。与患有2019冠状病毒病的亚组相比，在没有2019冠状病毒病的亚组中不依赖抽签做出决策的比例更高。
纳入合并症并不能始终如一地提高算法预测28天死亡率的性能。危机护理标准算法导致相当比例的优先级分数相同。危机护理标准算法在有和没有2019冠状病毒病的队列中的运行方式不同。这项原理验证研究证明了对危机护理标准指南进行经验性测试以了解它们是否实现目标的可行性和重要性。
