Mateescu Diana-Maria, Cotet Ioana, Guse Cristina, Prodan-Barbulescu Catalin, Varga Norberth-Istvan, Iurciuc Stela, Craciun Maria-Laura, Ilie Adrian-Cosmin, Enache Alexandra
Doctoral School, Department of General Medicine, "Victor Babes" University of Medicine and Pharmacy, Eftimie Murgu Square 2, 300041 Timisoara, Romania.
Cardiology Department, "Victor Babes" University of Medicine and Pharmacy, Eftimie Murgu Square 2, 300041 Timisoara, Romania.
Viruses. 2025 Mar 21;17(4):455. doi: 10.3390/v17040455.
Sepsis is a leading cause of mortality in critically ill patients, arising from a dysregulated immune response to infection. While traditionally associated with bacterial pathogens, severe COVID-19 can induce a sepsis-like syndrome, characterized by systemic inflammation, endothelial dysfunction, and coagulation abnormalities. This study aimed to assess the prognostic value of age, inflammatory markers, coagulation dysfunction, comorbidity burden, and lung involvement on computer tomography (CT) scans in predicting poor outcomes. We conducted a prospective cohort study including 163 patients diagnosed with COVID-19-related sepsis. Univariate and multivariable logistic regression analyses were performed to identify the independent predictors of unfavorable outcomes. Higher D-dimer (OR: 1.417, = 0.020) and C-reactive protein (CRP) levels (OR: 1.010, = 0.027) were independently associated with poor outcomes. A greater than 50% lung involvement on CT (OR: 1.774, = 0.025) was also a significant predictor. The Charleson Comorbidity Index (CCI) showed a strong trend toward significance ( = 0.065), while age lost statistical significance after adjusting for comorbidities. Our findings suggest that D-dimers, CRP, and lung involvement on CT are key independent predictors of poor outcomes in COVID-19-related sepsis. These results emphasize the importance of inflammatory and coagulation markers, alongside comorbidity burden, in early risk assessment. Further prospective studies are warranted to refine predictive models for severe COVID-19 cases complicated by sepsis.
脓毒症是重症患者死亡的主要原因,源于对感染的免疫反应失调。虽然传统上与细菌病原体有关,但重症新型冠状病毒肺炎(COVID-19)可诱发类似脓毒症的综合征,其特征为全身炎症、内皮功能障碍和凝血异常。本研究旨在评估年龄、炎症标志物、凝血功能障碍、合并症负担以及计算机断层扫描(CT)肺部受累情况对预测不良结局的预后价值。我们进行了一项前瞻性队列研究,纳入了163例诊断为COVID-19相关脓毒症的患者。进行单因素和多因素逻辑回归分析以确定不良结局的独立预测因素。较高的D-二聚体(比值比:1.417,P = 0.020)和C反应蛋白(CRP)水平(比值比:1.010,P = 0.027)与不良结局独立相关。CT显示肺部受累超过50%(比值比:1.774,P = 0.025)也是一个显著的预测因素。查尔森合并症指数(CCI)显示出强烈的显著趋势(P = 0.065),而在调整合并症后年龄失去统计学意义。我们的研究结果表明,D-二聚体、CRP和CT肺部受累情况是COVID-19相关脓毒症不良结局的关键独立预测因素。这些结果强调了炎症和凝血标志物以及合并症负担在早期风险评估中的重要性。有必要进行进一步的前瞻性研究以完善重症COVID-19合并脓毒症病例的预测模型。