Impact of Surge Strain and Pandemic Progression on Prognostication by an Established COVID-19–Specific Severity Score

Christina Yek, Jing Wang, J. Fintzi, A. Mancera, Michael B. Keller, S. Warner, S. Kadri
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Abstract

IMPORTANCE: Many U.S. State crisis standards of care (CSC) guidelines incorporated Sequential Organ Failure Assessment (SOFA), a sepsis-related severity score, in pandemic triage algorithms. However, SOFA performed poorly in COVID-19. Although disease-specific scores may perform better, their prognostic utility over time and in overcrowded care settings remains unclear. OBJECTIVES: We evaluated prognostication by the modified 4C (m4C) score, a COVID-19–specific prognosticator that demonstrated good predictive capacity early in the pandemic, as a potential tool to standardize triage across time and hospital-surge environments. DESIGN: Retrospective observational cohort study. SETTING: Two hundred eighty-one U.S. hospitals in an administrative healthcare dataset. PARTICIPANTS: A total of 298,379 hospitalized adults with COVID-19 were identified from March 1, 2020, to January 31, 2022. m4C scores were calculated from admission diagnosis codes, vital signs, and laboratory values. MAIN OUTCOMES AND MEASURES: Hospital-surge index, a severity-weighted measure of COVID-19 caseload, was calculated for each hospital-month. Discrimination of in-hospital mortality by m4C and surge index-adjusted models was measured by area under the receiver operating characteristic curves (AUC). Calibration was assessed by training models on early pandemic waves and measuring fit (deviation from bisector) in subsequent waves. RESULTS: From March 2020 to January 2022, 298,379 adults with COVID-19 were admitted across 281 U.S. hospitals. m4C adequately discriminated mortality in wave 1 (AUC 0.779 [95% CI, 0.769–0.789]); discrimination was lower in subsequent waves (wave 2: 0.772 [95% CI, 0.765–0.779]; wave 3: 0.746 [95% CI, 0.743–0.750]; delta: 0.707 [95% CI, 0.702–0.712]; omicron: 0.729 [95% CI, 0.721–0.738]). m4C demonstrated reduced calibration in contemporaneous waves that persisted despite periodic recalibration. Performance characteristics were similar with and without adjustment for surge. CONCLUSIONS AND RELEVANCE: Mortality prediction by the m4C score remained robust to surge strain, making it attractive for when triage is most needed. However, score performance has deteriorated in recent waves. CSC guidelines relying on defined prognosticators, especially for dynamic disease processes like COVID-19, warrant frequent reappraisal to ensure appropriate resource allocation.
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突发菌株和大流行进展对既定 COVID-19 特定严重性评分预判的影响
重要性:许多美国国家危机护理标准(CSC)指南将顺序器官衰竭评估(SOFA),一种败血症相关严重程度评分纳入大流行分类算法。然而,SOFA在COVID-19中的表现不佳。虽然疾病特异性评分可能表现更好,但随着时间的推移和在过度拥挤的护理环境中,其预后效用仍不清楚。目的:我们通过改进的4C (m4C)评分来评估预测,这是一种covid -19特异性预测指标,在大流行早期表现出良好的预测能力,可作为跨时间和医院高峰环境标准化分类的潜在工具。设计:回顾性观察队列研究。背景:在一个行政医疗数据集中有281家美国医院。参与者:从2020年3月1日至2022年1月31日,共发现298379名住院的COVID-19成人。m4C评分根据入院诊断代码、生命体征和实验室值计算。主要结局和措施:计算每个医院月的医院高峰指数,这是COVID-19病例量的严重程度加权指标。用受试者工作特征曲线下面积(AUC)来衡量m4C和浪涌指数调整模型对住院死亡率的区分。通过早期流行波的训练模型和随后流行波的测量拟合(与等分线的偏差)来评估校准。结果:从2020年3月到2022年1月,美国281家医院共有298379名成年COVID-19患者入院。m4C在波1中充分区分死亡率(AUC 0.779 [95% CI, 0.769-0.789]);在随后的波中,歧视率较低(波2:0.772 [95% CI, 0.765-0.779];波3:0.746 [95% CI, 0.743-0.750];δ: 0.707 [95% CI, 0.702-0.712];omicron: 0.729 [95% CI, 0.721-0.738])。m4C显示,尽管定期重新校准,但在同期波中仍然存在减少的校准。在调节浪涌和不调节浪涌的情况下,性能特征相似。结论和相关性:m4C评分对激增应变的死亡率预测仍然稳健,这使得它在最需要分诊时具有吸引力。然而,在最近的浪潮中,分数表现有所恶化。CSC指南依赖于明确的预后者,特别是对于COVID-19等动态疾病过程,需要经常重新评估,以确保适当的资源分配。
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