Emergency Medicine Unit, Luigi Sacco Hospital, ASST FBF Sacco, Milan, Italy.
Laboratory of Clinical Epidemiology, Department of Public Health, Istituto Di Ricerche Farmacologiche Mario Negri IRCCS Villa Camozzi, Via G.B. Camozzi 3, 24020, Ranica (BG), Italy.
Intern Emerg Med. 2023 Oct;18(7):2075-2082. doi: 10.1007/s11739-023-03324-6. Epub 2023 Jun 20.
While several studies have evaluated the prognostic weight of respiratory parameters in patients with COVID-19, few have focused on patients' clinical conditions at the first emergency department (ED) assessment. We analyzed a large cohort of ED patients recruited within the EC-COVID study over the year 2020, and assessed the association between key bedside respiratory parameters measured in room air (pO, pCO, pH, and respiratory rate [RR]) and hospital mortality, after adjusting for key confounding factors. Analyses were based on a multivariable logistic Generalized Additive Model (GAM). After excluding patients who did not perform a blood gas analysis (BGA) test in room air or with incomplete BGA results, a total of 2458 patients were considered in the analyses. Most patients were hospitalized on ED discharge (72.0%); hospital mortality was 14.3%. Strong, negative associations with hospital mortality emerged for pO, pCO and pH (p-values: < 0.001, < 0.001 and 0.014), while a significant, positive association was observed for RR (p-value < 0.001). Associations were quantified with nonlinear functions, learned from the data. No cross-parameter interaction was significant (all p-values were larger than 0.10), suggesting a progressive, independent effect on the outcome as the value of each parameter departed from normality. Our results collide with the hypothesized existence of patterns of breathing parameters with specific prognostic weight in the early stages of the disease.
虽然有几项研究评估了 COVID-19 患者呼吸参数的预后权重,但很少有研究关注患者在首次急诊就诊时的临床状况。我们分析了 2020 年 EC-COVID 研究中招募的大量急诊患者队列,并在调整了关键混杂因素后,评估了在室内空气中测量的关键床边呼吸参数(pO、pCO、pH 和呼吸频率 [RR])与医院死亡率之间的关联。分析基于多变量逻辑广义加性模型(GAM)。在排除未在室内空气中进行血气分析(BGA)测试或 BGA 结果不完整的患者后,共有 2458 名患者纳入分析。大多数患者在急诊出院时住院(72.0%);医院死亡率为 14.3%。pO、pCO 和 pH 与医院死亡率呈强负相关(p 值:<0.001、<0.001 和 0.014),而 RR 与医院死亡率呈显著正相关(p 值<0.001)。关联通过从数据中学习的非线性函数进行量化。没有发现参数间的交叉相互作用具有统计学意义(所有 p 值均大于 0.10),这表明随着每个参数值偏离正常值,对结果的影响是渐进的、独立的。我们的结果与疾病早期存在具有特定预后权重的呼吸参数模式的假设相冲突。