School of Medicine, University of California, San Francisco, San Francisco, California.
Cardiovascular Research Institute, University of California, San Francisco, San Francisco, California.
Respir Care. 2022 Sep;67(9):1075-1081. doi: 10.4187/respcare.09854. Epub 2022 May 31.
How indices specific to respiratory compromise contribute to prognostication in patients with ARDS is not well characterized in general clinical populations. The primary objective of this study was to identify variables specific to respiratory failure that might add prognostic value to indicators of systemic illness severity in an observational cohort of subjects with ARDS.
Fifty subjects with ARDS were enrolled in a single-center, prospective, observational cohort. We tested the contribution of respiratory variables (oxygenation index, ventilatory ratio [VR], and the radiographic assessment of lung edema score) to logistic regression models of 28-d mortality adjusted for indicators of systemic illness severity (the Acute Physiology and Chronic Health Evaluation [APACHE] III score or severity of shock as measured by the number of vasopressors required at baseline) using likelihood ratio testing. We also compared a model utilizing APACHE III with one including baseline number of vasopressors by comparing the area under the receiver operating curve (AUROC).
VR significantly improved model performance by likelihood ratio testing when added to APACHE III ( = .036) or the number of vasopressors at baseline ( = .01). Number of vasopressors required at baseline had similar prognostic discrimination to the APACHE III. A model including the number of vasopressors and VR (AUROC 0.77 [95% CI 0.64-0.90]) was comparable to a model including APACHE III and VR (AUROC 0.81 [95% CI 0.68-0.93]; for comparison = .58.).
In this observational cohort of subjects with ARDS, the VR significantly improved discrimination for mortality when combined with indicators of severe systemic illness. The number of vasopressors required at baseline and APACHE III had similar discrimination for mortality when combined with VR. VR is easily obtained at the bedside and offers promise for clinical prognostication.
在一般临床人群中，特定于呼吸衰竭的指标如何对 ARDS 患者的预后产生影响尚不清楚。本研究的主要目的是确定与呼吸衰竭相关的特定变量，这些变量可能会增加 ARDS 患者观察队列中反映全身疾病严重程度的指标的预后价值。
将 50 例 ARDS 患者纳入单中心前瞻性观察队列。我们通过似然比检验测试了呼吸变量（氧合指数、通气比[VR]和肺部水肿评分的放射学评估）对 28 天死亡率的逻辑回归模型的贡献，这些模型调整了全身疾病严重程度的指标（急性生理学和慢性健康评估[APACHE]III 评分或基线时所需血管加压剂的数量来衡量休克的严重程度）。我们还通过比较接受者操作特征曲线（AUROC）下的面积来比较使用 APACHE III 的模型与包括基线时血管加压剂数量的模型。
当 VR 与 APACHE III（ =.036）或基线时所需的血管加压剂数量（ =.01）相加时，通过似然比检验，VR 显著改善了模型的性能。基线时所需的血管加压剂数量与 APACHE III 具有相似的预后判别能力。包括血管加压剂数量和 VR 的模型（AUROC 为 0.77 [95%CI 为 0.64-0.90]）与包括 APACHE III 和 VR 的模型（AUROC 为 0.81 [95%CI 为 0.68-0.93]； 比较 =.58）相当。
在这项 ARDS 患者的观察性队列研究中，VR 与反映严重全身疾病的指标相结合时，对死亡率的判别能力显著提高。基线时所需的血管加压剂数量和 APACHE III 与 VR 结合时对死亡率的判别能力相似。VR 易于在床边获得，并为临床预后提供了希望。
