Identifying vital sign trajectories to predict 28-day mortality of critically ill elderly patients with acute respiratory distress syndrome

IF 4.7 2区 医学 Q1 RESPIRATORY SYSTEM
Mingzhuo Li, Fen Liu, Yang Yang, Jiahui Lao, Chaonan Yin, Yafei Wu, Zhongshang Yuan, Yongyue Wei, Fang Tang
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Abstract

The mortality rate of acute respiratory distress syndrome (ARDS) increases with age (≥ 65 years old) in critically ill patients, and it is necessary to prevent mortality in elderly patients with ARDS in the intensive care unit (ICU). Among the potential risk factors, dynamic subphenotypes of respiratory rate (RR), heart rate (HR), and respiratory rate-oxygenation (ROX) and their associations with 28-day mortality have not been clearly explored. Based on the eICU Collaborative Research Database (eICU-CRD), this study used a group-based trajectory model to identify longitudinal subphenotypes of RR, HR, and ROX during the first 72 h of ICU stays. A logistic model was used to evaluate the associations of trajectories with 28-day mortality considering the group with the lowest rate of mortality as a reference. Restricted cubic spline was used to quantify linear and nonlinear effects of static RR-related factors during the first 72 h of ICU stays on 28-day mortality. Receiver operating characteristic (ROC) curves were used to assess the prediction models with the Delong test. A total of 938 critically ill elderly patients with ARDS were involved with five and 5 trajectories of RR and HR, respectively. A total of 204 patients fit 4 ROX trajectories. In the subphenotypes of RR, when compared with group 4, the odds ratios (ORs) and 95% confidence intervals (CIs) of group 3 were 2.74 (1.48–5.07) (P = 0.001). Regarding the HR subphenotypes, in comparison to group 1, the ORs and 95% CIs were 2.20 (1.19–4.08) (P = 0.012) for group 2, 2.70 (1.40–5.23) (P = 0.003) for group 3, 2.16 (1.04–4.49) (P = 0.040) for group 5. Low last ROX had a higher mortality risk (P linear = 0.023, P nonlinear = 0.010). Trajectories of RR and HR improved the predictive ability for 28-day mortality (AUC increased by 2.5%, P = 0.020). For RR and HR, longitudinal subphenotypes are risk factors for 28-day mortality and have additional predictive enrichment, whereas the last ROX during the first 72 h of ICU stays is associated with 28-day mortality. These findings indicate that maintaining the health dynamic subphenotypes of RR and HR in the ICU and elevating static ROX after initial critical care may have potentially beneficial effects on prognosis in critically ill elderly patients with ARDS.
识别生命体征轨迹,预测急性呼吸窘迫综合征老年重症患者 28 天的死亡率
急性呼吸窘迫综合征(ARDS)的死亡率随着重症患者年龄(≥ 65 岁)的增长而增加,因此有必要预防重症监护室(ICU)中患有 ARDS 的老年患者的死亡。在潜在的风险因素中,呼吸频率(RR)、心率(HR)和呼吸氧合率(ROX)的动态亚型及其与 28 天死亡率的关系尚未得到明确探讨。本研究以电子重症监护室合作研究数据库(eICU-CRD)为基础,使用基于组的轨迹模型来识别重症监护室住院前 72 小时内 RR、HR 和 ROX 的纵向亚型。以死亡率最低的组别为参照,采用逻辑模型评估轨迹与 28 天死亡率的关联。限制立方样条曲线用于量化 ICU 住院前 72 小时内与 RR 相关的静态因素对 28 天死亡率的线性和非线性影响。利用接收者操作特征曲线(ROC)和德朗检验对预测模型进行评估。共有 938 名患有 ARDS 的老年重症患者的 RR 和 HR 轨迹分别为 5 条和 5 条。共有 204 名患者符合 4 个 ROX 轨迹。在 RR 亚型中,与第 4 组相比,第 3 组的几率比(OR)和 95% 置信区间(CI)为 2.74(1.48-5.07)(P = 0.001)。在 HR 亚型方面,与第 1 组相比,第 2 组的 OR 和 95% 置信区间分别为 2.20 (1.19-4.08) (P = 0.012),第 3 组为 2.70 (1.40-5.23) (P = 0.003),第 5 组为 2.16 (1.04-4.49) (P = 0.040)。RR和HR的轨迹提高了对28天死亡率的预测能力(AUC增加了2.5%,P = 0.020)。就 RR 和 HR 而言,纵向亚表型是 28 天死亡率的风险因素,并具有额外的预测丰富性,而在入住重症监护室的前 72 小时内的最后一次 ROX 与 28 天死亡率相关。这些研究结果表明,在重症监护室中保持RR和HR的健康动态亚型,并在初始重症监护后提高静态ROX,可能会对ARDS老年重症患者的预后产生潜在的有利影响。
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来源期刊
Respiratory Research
Respiratory Research 医学-呼吸系统
自引率
1.70%
发文量
314
期刊介绍: Respiratory Research publishes high-quality clinical and basic research, review and commentary articles on all aspects of respiratory medicine and related diseases. As the leading fully open access journal in the field, Respiratory Research provides an essential resource for pulmonologists, allergists, immunologists and other physicians, researchers, healthcare workers and medical students with worldwide dissemination of articles resulting in high visibility and generating international discussion. Topics of specific interest include asthma, chronic obstructive pulmonary disease, cystic fibrosis, genetics, infectious diseases, interstitial lung diseases, lung development, lung tumors, occupational and environmental factors, pulmonary circulation, pulmonary pharmacology and therapeutics, respiratory immunology, respiratory physiology, and sleep-related respiratory problems.
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