Meintrup David, Borgmann Stefan, Seidl Karlheinz, Stecher Melanie, Jakob Carolin E M, Pilgram Lisa, Spinner Christoph D, Rieg Siegbert, Isberner Nora, Hower Martin, Vehreschild Maria, Göpel Siri, Hanses Frank, Nowak-Machen Martina
Faculty of Engineering and Management, University of Applied Sciences Ingolstadt, 85049 Ingolstadt, Germany.
Department of Infectious Diseases and Infection Control, Ingolstadt Hospital, 85049 Ingolstadt, Germany.
J Clin Med. 2021 Aug 27;10(17):3855. doi: 10.3390/jcm10173855.
(1) Background: The aim of our study was to identify specific risk factors for fatal outcome in critically ill COVID-19 patients. (2) Methods: Our data set consisted of 840 patients enclosed in the LEOSS registry. Using lasso regression for variable selection, a multifactorial logistic regression model was fitted to the response variable survival. Specific risk factors and their odds ratios were derived. A nomogram was developed as a graphical representation of the model. (3) Results: 14 variables were identified as independent factors contributing to the risk of death for critically ill COVID-19 patients: age (OR 1.08, CI 1.06-1.10), cardiovascular disease (OR 1.64, CI 1.06-2.55), pulmonary disease (OR 1.87, CI 1.16-3.03), baseline Statin treatment (0.54, CI 0.33-0.87), oxygen saturation (unit = 1%, OR 0.94, CI 0.92-0.96), leukocytes (unit 1000/μL, OR 1.04, CI 1.01-1.07), lymphocytes (unit 100/μL, OR 0.96, CI 0.94-0.99), platelets (unit 100,000/μL, OR 0.70, CI 0.62-0.80), procalcitonin (unit ng/mL, OR 1.11, CI 1.05-1.18), kidney failure (OR 1.68, CI 1.05-2.70), congestive heart failure (OR 2.62, CI 1.11-6.21), severe liver failure (OR 4.93, CI 1.94-12.52), and a quick SOFA score of 3 (OR 1.78, CI 1.14-2.78). The nomogram graphically displays the importance of these 14 factors for mortality. (4) Conclusions: There are risk factors that are specific to the subpopulation of critically ill COVID-19 patients.
(1)背景:我们研究的目的是确定危重症新型冠状病毒肺炎(COVID-19)患者死亡结局的特定风险因素。(2)方法:我们的数据集由纳入LEOSS登记系统的840例患者组成。使用套索回归进行变量选择,将多因素逻辑回归模型拟合到反应变量生存情况。得出特定风险因素及其比值比。绘制了列线图以直观呈现该模型。(3)结果:确定了14个变量为危重症COVID-19患者死亡风险的独立影响因素:年龄(比值比1.08,95%置信区间1.06 - 1.10)、心血管疾病(比值比1.64,95%置信区间1.06 - 2.55)、肺部疾病(比值比1.87,95%置信区间1.16 - 3.03)、基线他汀类药物治疗(0.54,95%置信区间0.33 - 0.87)、血氧饱和度(单位 = 1%,比值比0.94,95%置信区间0.92 - 0.96)、白细胞(单位1000/μL,比值比1.04,95%置信区间1.01 - 1.07)、淋巴细胞(单位100/μL,比值比0.96,95%置信区间0.94 - 0.99)、血小板(单位100,000/μL,比值比0.70,95%置信区间0.62 - 0.80)、降钙素原(单位ng/mL,比值比1.11,95%置信区间1.05 - 1.18)、肾衰竭(比值比1.68,95%置信区间1.05 - 2.70)、充血性心力衰竭(比值比2.62,95%置信区间1.11 - 6.21)、严重肝衰竭(比值比4.93,95%置信区间1.94 -