Tong-Minh Kirby, van der Does Yuri, van Rosmalen Joost, Ramakers Christian, Gommers Diederik, van Gorp Eric, Rizopoulos Dimitris, Endeman Henrik
Department of Emergency Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands.
Department of Biostatistics, Erasmus University Medical Center, Rotterdam, The Netherlands.
Biomark Insights. 2022 Jul 14;17:11772719221112370. doi: 10.1177/11772719221112370. eCollection 2022.
Predicting disease severity is important for treatment decisions in patients with COVID-19 in the intensive care unit (ICU). Different biomarkers have been investigated in COVID-19 as predictor of mortality, including C-reactive protein (CRP), procalcitonin (PCT), interleukin-6 (IL-6), and soluble urokinase-type plasminogen activator receptor (suPAR). Using repeated measurements in a prediction model may result in a more accurate risk prediction than the use of single point measurements. The goal of this study is to investigate the predictive value of trends in repeated measurements of CRP, PCT, IL-6, and suPAR on mortality in patients admitted to the ICU with COVID-19.
This was a retrospective single center cohort study. Patients were included if they tested positive for SARS-CoV-2 by PCR test and if IL-6, PCT, suPAR was measured during any of the ICU admission days. There were no exclusion criteria for this study. We used joint models to predict ICU-mortality. This analysis was done using the framework of joint models for longitudinal and survival data. The reported hazard ratios express the relative change in the risk of death resulting from a doubling or 20% increase of the biomarker's value in a day compared to no change in the same period.
A total of 107 patients were included, of which 26 died during ICU admission. Adjusted for sex and age, a doubling in the next day in either levels of PCT, IL-6, and suPAR were significantly predictive of in-hospital mortality with HRs of 1.523 (1.012-6.540), 75.25 (1.116-6247), and 24.45 (1.696-1057) respectively. With a 20% increase in biomarker value in a subsequent day, the HR of PCT, IL-6, and suPAR were 1.117 (1.03-1.639), 3.116 (1.029-9.963), and 2.319 (1.149-6.243) respectively.
Joint models for the analysis of repeated measurements of PCT, suPAR, and IL-6 are a useful method for predicting mortality in COVID-19 patients in the ICU. Patients with an increasing trend of biomarker levels in consecutive days are at increased risk for mortality.
预测疾病严重程度对于重症监护病房(ICU)中新冠肺炎患者的治疗决策至关重要。在新冠肺炎中,人们研究了不同的生物标志物作为死亡率的预测指标,包括C反应蛋白(CRP)、降钙素原(PCT)、白细胞介素-6(IL-6)和可溶性尿激酶型纤溶酶原激活剂受体(suPAR)。在预测模型中使用重复测量可能比使用单点测量产生更准确的风险预测。本研究的目的是调查新冠肺炎患者入住ICU时,CRP、PCT、IL-6和suPAR重复测量趋势对死亡率的预测价值。
这是一项回顾性单中心队列研究。如果患者通过PCR检测SARS-CoV-2呈阳性,且在任何ICU住院日测量了IL-6、PCT、suPAR,则纳入研究。本研究没有排除标准。我们使用联合模型预测ICU死亡率。该分析是在纵向和生存数据联合模型的框架下进行的。报告的风险比表示与同期无变化相比,生物标志物值在一天内翻倍或增加20%导致的死亡风险的相对变化。
共纳入107例患者,其中26例在ICU住院期间死亡。在对性别和年龄进行调整后,PCT、IL-6和suPAR水平在次日翻倍均显著预测院内死亡率,风险比分别为1.523(1.012 - 6.540)、75.25(1.116 - 6247)和24.45(1.696 - 1057)。生物标志物值在随后一天增加20%时,PCT、IL-6和suPAR的风险比分别为1.117(1.03 - 1.639)、3.116(1.029 - 9.963)和2.319(1.149 - 6.243)。
用于分析PCT、suPAR和IL-6重复测量的联合模型是预测ICU中新冠肺炎患者死亡率的有用方法。连续几天生物标志物水平呈上升趋势的患者死亡风险增加。