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HB-EGF血浆水平有助于构建重症COVID-19病例早期风险预测列线图。

HB-EGF Plasmatic Level Contributes to the Development of Early Risk Prediction Nomogram for Severe COVID-19 Cases.

作者信息

Moatar Alexandra Ioana, Chis Aimee Rodica, Nitusca Diana, Oancea Cristian, Marian Catalin, Sirbu Ioan-Ovidiu

机构信息

Doctoral School, University of Medicine and Pharmacy "Victor Babes", 300041 Timisoara, Romania.

Department of Biochemistry, University of Medicine and Pharmacy "Victor Babes", 300041 Timisoara, Romania.

出版信息

Biomedicines. 2024 Feb 5;12(2):373. doi: 10.3390/biomedicines12020373.

Abstract

(1) Background: Heparin-Binding Epidermal Growth Factor-like Growth Factor (HB-EGF) is involved in wound healing, cardiac hypertrophy, and heart development processes. Recently, circulant HB-EGF was reported upregulated in severely hospitalized COVID-19 patients. However, the clinical correlations of HB-EGF plasma levels with COVID-19 patients' characteristics have not been defined yet. In this study, we assessed the plasma HB-EGF correlations with the clinical and paraclinical patients' data, evaluated its predictive clinical value, and built a risk prediction model for severe COVID-19 cases based on the resulting significant prognostic markers. (2) Methods: Our retrospective study enrolled 75 COVID-19 patients and 17 control cases from May 2020 to September 2020. We quantified plasma HB-EGF levels using the sandwich ELISA technique. Correlations between HB-EGF plasma levels with clinical and paraclinical patients' data were calculated using two-tailed Spearman and Point-Biserial tests. Significantly upregulated parameters for severe COVID-19 cases were identified and selected to build a multivariate logistic regression prediction model. The clinical significance of the prediction model was assessed by risk prediction nomogram and decision curve analyses. (3) Results: HB-EGF plasma levels were significantly higher in the severe COVID-19 subgroup compared to the controls ( = 0.004) and moderate cases ( = 0.037). In the severe COVID-19 group, HB-EGF correlated with age ( = 0.028), pulse ( = 0.016), dyspnea ( = 0.014) and prothrombin time (PT) ( = 0.04). The multivariate risk prediction model built on seven identified risk parameters (age = 0.043, HB-EGF = 0.0374, Fibrinogen = 0.009, PT = 0.008, Creatinine = 0.026, D-Dimers = 0.024 and delta miR-195 < 0.0001) identifies severe COVID-19 with AUC = 0.9556 ( < 0.0001). The decision curve analysis revealed that the nomogram model is clinically relevant throughout a wide threshold probability range. (4) Conclusions: Upregulated HB-EGF plasma levels might serve as a prognostic factor for severe COVID-19 and help build a reliable risk prediction nomogram that improves the identification of high-risk patients at an early stage of COVID-19.

摘要

(1)背景:肝素结合表皮生长因子样生长因子(HB-EGF)参与伤口愈合、心脏肥大和心脏发育过程。最近,有报道称重症住院的COVID-19患者循环中的HB-EGF上调。然而,HB-EGF血浆水平与COVID-19患者特征的临床相关性尚未明确。在本研究中,我们评估了血浆HB-EGF与患者临床及辅助检查数据的相关性,评估其临床预测价值,并基于所得出的显著预后标志物建立了重症COVID-19病例的风险预测模型。(2)方法:我们的回顾性研究纳入了2020年5月至2020年9月期间的75例COVID-19患者和17例对照病例。我们使用夹心ELISA技术定量血浆HB-EGF水平。采用双尾Spearman检验和点二列相关检验计算HB-EGF血浆水平与患者临床及辅助检查数据之间的相关性。确定并选择重症COVID-19病例中显著上调的参数,以建立多因素逻辑回归预测模型。通过风险预测列线图和决策曲线分析评估预测模型的临床意义。(3)结果:与对照组(P = 0.004)和中度病例组(P = 0.037)相比,重症COVID-19亚组的血浆HB-EGF水平显著更高。在重症COVID-19组中,HB-EGF与年龄(P = 0.028)、脉搏(P = 0.016)、呼吸困难(P = 0.014)和凝血酶原时间(PT)(P = 0.04)相关。基于七个确定的风险参数(年龄P = 0.043、HB-EGF P = 0.0374、纤维蛋白原P = 0.009、PT P = 0.008、肌酐P = 0.026、D-二聚体P = 0.024和δmiR-195 P < 0.0001)建立的多因素风险预测模型识别重症COVID-19的曲线下面积(AUC)= 0.9556(P < 0.0001)。决策曲线分析表明,列线图模型在较宽的阈值概率范围内具有临床相关性。(4)结论:血浆HB-EGF水平上调可能是重症COVID-19的一个预后因素,并有助于建立一个可靠的风险预测列线图,以改善COVID-19早期高危患者的识别。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fdd3/10886796/9c476cf9b2a7/biomedicines-12-00373-g001.jpg

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