Department of General Medicine & Community Healthcare, Kyoto Prefectural University of Medicine, Kajiicho 465, Kawaramachi-Hirokoji, Kamigyo, Kyoto, 602-8566, Japan.
Department of Anesthesiology, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kajiicho 465, Kawaramachi-Hirokoji, Kamigyo, Kyoto, 602-8566, Japan.
J Infect Chemother. 2024 May;30(5):406-416. doi: 10.1016/j.jiac.2023.11.013. Epub 2023 Nov 19.
In treating acute hypoxemic respiratory failure (AHRF) caused by coronavirus disease 2019 (COVID-19), clinicians choose respiratory therapies such as low-flow nasal cannula oxygenation, high-flow nasal cannula oxygenation, or mechanical ventilation after assessment of the patient's condition. Chest computed tomography (CT) imaging contributes significantly to diagnosing COVID-19 pneumonia. However, the costs and potential harm to patients from radiation exposure need to be considered. This study was performed to predict the quantitative extent of COVID-19 acute lung injury using clinical indicators such as an oxygenation index and blood test results.
We analyzed data from 192 patients with COVID-19 AHRF. Multiple logistic regression was used to determine correlations between the lung infiltration volume (LIV) and other pathophysiological or biochemical laboratory parameters.
Among 13 clinical parameters, we identified the oxygen saturation/fraction of inspired oxygen ratio (SF ratio) and serum lactate dehydrogenase (LD) concentration as factors associated with the LIV. In the binary classification of an LIV of ≥20 % or not and with the borderline LD = 2.2 × [SF ratio]-182.4, the accuracy, precision, diagnostic odds ratio, and area under the summary receiver operating characteristic curve were 0.828, 0.818, 23.400, and 0.870, respectively.
These data suggest that acute lung injury due to COVID-19 pneumonia can be estimated using the SF ratio and LD concentration without a CT scan. These findings may provide significant clinical benefit by allowing clinicians to predict acute lung injury levels using simple, minimally invasive assessment of oxygenation capacity and biochemical blood tests.
在治疗由 2019 年冠状病毒病(COVID-19)引起的急性低氧性呼吸衰竭(AHRF)时,临床医生会在评估患者病情后选择呼吸治疗方法,如低流量鼻导管给氧、高流量鼻导管给氧或机械通气。胸部计算机断层扫描(CT)成像对诊断 COVID-19 肺炎有重要作用。然而,需要考虑到辐射对患者的成本和潜在危害。本研究旨在使用氧合指数和血液检查结果等临床指标预测 COVID-19 急性肺损伤的定量程度。
我们分析了 192 例 COVID-19 AHRF 患者的数据。使用多因素逻辑回归分析确定肺浸润体积(LIV)与其他病理生理或生化实验室参数之间的相关性。
在 13 个临床参数中,我们确定氧饱和度/吸入氧分数比(SF 比)和血清乳酸脱氢酶(LD)浓度是与 LIV 相关的因素。在 LIV ≥20%或<20%的二元分类中,边界 LD=2.2×[SF 比]-182.4,其准确性、精确性、诊断优势比和总结接收者操作特征曲线下面积分别为 0.828、0.818、23.400 和 0.870。
这些数据表明,无需 CT 扫描即可使用 SF 比和 LD 浓度估计 COVID-19 肺炎引起的急性肺损伤。这些发现可能通过允许临床医生使用简单、微创的氧合能力和生化血液检查来预测急性肺损伤程度,从而为临床带来重大益处。