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Causes and characteristics of death in patients with acute hypoxemic respiratory failure and acute respiratory distress syndrome: a retrospective cohort study.急性低氧性呼吸衰竭和急性呼吸窘迫综合征患者死亡的原因和特征:一项回顾性队列研究。
Crit Care. 2020 Jul 3;24(1):391. doi: 10.1186/s13054-020-03108-w.
2
Automated abnormality classification of chest radiographs using deep convolutional neural networks.使用深度卷积神经网络对胸部X光片进行自动异常分类。
NPJ Digit Med. 2020 May 14;3:70. doi: 10.1038/s41746-020-0273-z. eCollection 2020.
3
The Integrated Calibration Index (ICI) and related metrics for quantifying the calibration of logistic regression models.综合校准指数(ICI)及其相关指标,用于量化逻辑回归模型的校准。
Stat Med. 2019 Sep 20;38(21):4051-4065. doi: 10.1002/sim.8281. Epub 2019 Jul 3.
4
Differences between Patients in Whom Physicians Agree and Disagree about the Diagnosis of Acute Respiratory Distress Syndrome.医师对急性呼吸窘迫综合征诊断意见一致和不一致患者之间的差异。
Ann Am Thorac Soc. 2019 Feb;16(2):258-264. doi: 10.1513/AnnalsATS.201806-434OC.
5
Patient and Population-Level Approaches to Persistent Critical Illness and Prolonged Intensive Care Unit Stays.患者和人群层面的持续危重症和长时间重症监护病房停留的处理方法。
Crit Care Clin. 2018 Oct;34(4):493-500. doi: 10.1016/j.ccc.2018.06.001. Epub 2018 Aug 10.
6
Physiologic Analysis and Clinical Performance of the Ventilatory Ratio in Acute Respiratory Distress Syndrome.急性呼吸窘迫综合征通气比的生理分析与临床性能。
Am J Respir Crit Care Med. 2019 Feb 1;199(3):333-341. doi: 10.1164/rccm.201804-0692OC.
7
Severity scoring of lung oedema on the chest radiograph is associated with clinical outcomes in ARDS.肺水肿在胸部 X 光片上的严重程度评分与 ARDS 的临床结果相关。
Thorax. 2018 Sep;73(9):840-846. doi: 10.1136/thoraxjnl-2017-211280. Epub 2018 Jun 14.
8
Interobserver Reliability of the Berlin ARDS Definition and Strategies to Improve the Reliability of ARDS Diagnosis.柏林急性呼吸窘迫综合征定义的观察者间可靠性和提高急性呼吸窘迫综合征诊断可靠性的策略。
Chest. 2018 Feb;153(2):361-367. doi: 10.1016/j.chest.2017.11.037. Epub 2017 Dec 14.
9
Oxygenation Saturation Index Predicts Clinical Outcomes in ARDS.氧合饱和度指数可预测急性呼吸窘迫综合征的临床结局。
Chest. 2017 Dec;152(6):1151-1158. doi: 10.1016/j.chest.2017.08.002. Epub 2017 Aug 16.
10
Prospective validation of a near real-time EHR-integrated automated SOFA score calculator.近实时电子健康记录集成自动序贯器官衰竭评估(SOFA)评分计算器的前瞻性验证
Int J Med Inform. 2017 Jul;103:1-6. doi: 10.1016/j.ijmedinf.2017.04.001. Epub 2017 Apr 3.

验证急性呼吸窘迫综合征疾病严重程度的测量方法。

Validating Measures of Disease Severity in Acute Respiratory Distress Syndrome.

机构信息

Department of Internal Medicine.

Department of Emergency Medicine, and.

出版信息

Ann Am Thorac Soc. 2021 Jul;18(7):1211-1218. doi: 10.1513/AnnalsATS.202007-772OC.

DOI:10.1513/AnnalsATS.202007-772OC
PMID:33347379
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8328371/
Abstract

Quantifying acute respiratory disease syndrome (ARDS) severity is essential for prognostic enrichment to stratify patients for invasive or higher-risk treatments; however, the comparative performance of many ARDS severity measures is unknown. To validate ARDS severity measures for their ability to predict hospital mortality and an ARDS-specific outcome (defined as death from pulmonary dysfunction or the need for extracorporeal membrane oxygenation [ECMO] therapy). We compared five individual ARDS severity measures including the ratio of arterial oxygen tension/pressure to fraction of inspired oxygen (Pa/Fi ratio), oxygenation index, ventilatory ratio, lung compliance, and radiologic assessment of lung edema (RALE); two ARDS composite severity scores including the Murray Lung Injury Score, and a novel score combining RALE, Pa/Fi ratio, and ventilatory ratio; and the Acute Physiology and Chronic Health Evaluation IV score, using data collected at ARDS onset in patients hospitalized at a single center in 2016 and 2017. Discrimination of hospital mortality and the ARDS-specific outcome was evaluated using the area under the receiver operator characteristic curve (AUROC). Measure calibration was also evaluated. Among 340 patients with ARDS, 125 (37%) died during hospitalization and 36 (10.6%) had the ARDS-specific outcome, including one who received ECMO. Among the five individual ARDS severity measures, the RALE score had the highest discrimination of the ARDS-specific outcome (AUROC = 0.67; 95% confidence interval [CI], 0.58-0.77), although other ARDS severity measures had similar performance. However, their ability to discriminate overall mortality was low. In contrast, the Acute Physiology and Chronic Health Evaluation IV score best discriminated overall mortality (AUROC = 0.73; 95% CI, 0.67-0.79) but was unable to discriminate the ARDS-specific outcome (AUROC = 0.54; 95% CI, 0.44-0.65). Among ARDS composite severity scores, the lung injury score had an AUROC = 0.67 (95% CI, 0.58-0.75) for the ARDS-specific outcome whereas the novel score had an AUROC = 0.70 (95% CI, 0.61-0.79). Patients grouped by quartile of the novel score had a 6%, 2%, 10%, and 24% rate of the ARDS-specific outcome. Although most ARDS severity measures had poor discrimination of hospital mortality, they performed better at predicting death from severe pulmonary dysfunction or ECMO needs. A novel composite score had the highest discrimination of this outcome.

摘要

定量评估急性呼吸窘迫综合征(ARDS)的严重程度对于预后分层至关重要,可用于将患者分层以接受有创或高风险治疗;然而,许多 ARDS 严重程度评估指标的比较性能尚不清楚。我们验证了 ARDS 严重程度评估指标预测医院死亡率和 ARDS 特定结局(定义为肺功能障碍死亡或需要体外膜氧合(ECMO)治疗)的能力。我们比较了五种 ARDS 严重程度评估指标,包括动脉氧分压/压力与吸入氧分数比(Pa/Fi 比值)、氧合指数、通气比、肺顺应性和肺部水肿的放射学评估(RALE);两种 ARDS 综合严重程度评分,包括 Murray 肺损伤评分和一种新的结合 RALE、Pa/Fi 比值和通气比的评分;以及急性生理学和慢性健康评估第四版评分,使用 2016 年和 2017 年在一家中心住院的 ARDS 患者发病时的数据。使用接收者操作特征曲线下面积(AUROC)评估医院死亡率和 ARDS 特定结局的区分度。还评估了评估指标的校准度。在 340 名 ARDS 患者中,125 名(37%)在住院期间死亡,36 名(10.6%)出现 ARDS 特定结局,包括 1 名接受 ECMO 治疗的患者。在五种 ARDS 严重程度评估指标中,RALE 评分对 ARDS 特定结局的区分度最高(AUROC=0.67;95%置信区间[CI],0.58-0.77),尽管其他 ARDS 严重程度评估指标的表现相似。然而,它们预测整体死亡率的能力较低。相比之下,急性生理学和慢性健康评估第四版评分对整体死亡率的区分度最佳(AUROC=0.73;95%CI,0.67-0.79),但无法区分 ARDS 特定结局(AUROC=0.54;95%CI,0.44-0.65)。在 ARDS 综合严重程度评分中,肺损伤评分对 ARDS 特定结局的 AUROC=0.67(95%CI,0.58-0.75),而新型评分的 AUROC=0.70(95%CI,0.61-0.79)。根据新型评分的四分位数,ARDS 特定结局的发生率分别为 6%、2%、10%和 24%。尽管大多数 ARDS 严重程度评估指标预测医院死亡率的能力较差,但它们在预测严重肺功能障碍或 ECMO 需求导致的死亡方面表现更好。新型综合评分对该结局的区分度最高。