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能否通过 SARS-CoV-2 感染患者的非常规炎症标志物来预测重症监护死亡率?

Can we predict critical care mortality with non-conventional inflammatory markers in SARS-CoV-2 infected patients?

机构信息

Department of Anaesthesiology and Intensive Care, University of Pécs, Pécs, Hungary.

Department of Public Health Medicine, University of Pécs Medical School, Pécs, Hungary.

出版信息

Clin Hemorheol Microcirc. 2023;84(1):71-82. doi: 10.3233/CH-231697.

DOI:10.3233/CH-231697
PMID:36846995
Abstract

BACKGROUND

Severe COVID-19 disease is associated with multiple organ involvement,then failure and often fatal outcomes.In addition,inflammatory mechanisms and cytokine storms,documented in many COVID-19 patients,are responsible for the progression of the disease and high mortality rates.Inflammatory parameters,such as procalcitonin(PCT) and C-reactive protein(CRP), are widely used in clinical practice.

OBJECTIVE

To evaluate the predictive power of non-conventional inflammatory markers regarding mortality risk.

METHODS

In our prospective study 52 patients were followed for 5 days after admission to an intensive care unit immediately with severe SARS-CoV-2 infection.We compared leukocyte-,platelet antisedimentation rate (LAR, PAR),neutrophil lymphocyte ratio(NLR), CRP, PCT levels.

RESULTS

In non-surviving(NSU) patients LAR remained largely constant from D1 to D4 with a statistically significant drop(p < 0.05) only seen on D5.The NSU group showed statistically significant(p < 0.05) elevated LAR medians on D4 and D5, compared to the SU group.NLR values were continually higher in the non-survivor group.The difference between the SU and NSU groups were statistically significant on every examined day.PAR, CRP and PCT levels didn't show any significant differences between the SU and NSU groups.

CONCLUSIONS

In conclusion, this study suggests that LAR and NLR are especially worthy of further investigation as prognostic markers.LAR might be of particular relevance as it is not routinely obtained in current clinical practice.It would seem beneficial to include LAR in data sets to train prognostic artificial intelligence.

摘要

背景

严重的 COVID-19 疾病与多个器官受累、衰竭有关,且常导致死亡。此外,在许多 COVID-19 患者中发现的炎症机制和细胞因子风暴导致疾病进展和高死亡率。炎症参数,如降钙素原(PCT)和 C 反应蛋白(CRP),广泛用于临床实践。

目的

评估非传统炎症标志物对死亡率风险的预测能力。

方法

在我们的前瞻性研究中,52 名患者在重症 SARS-CoV-2 感染后立即入住重症监护病房 5 天。我们比较了白细胞、血小板沉降率(LAR、PAR)、中性粒细胞与淋巴细胞比值(NLR)、CRP、PCT 水平。

结果

在非存活(NSU)患者中,LAR 从 D1 到 D4 基本保持不变,仅在 D5 时出现统计学上的显著下降(p<0.05)。NSU 组在 D4 和 D5 时 LAR 中位数显著升高(p<0.05),与 SU 组相比。NLR 值在非存活组中持续升高。SU 和 NSU 组之间的差异在每个检查日均具有统计学意义。PAR、CRP 和 PCT 水平在 SU 和 NSU 组之间没有显示出任何显著差异。

结论

总之,这项研究表明,LAR 和 NLR 特别值得进一步研究作为预后标志物。LAR 可能具有特别重要的意义,因为它在当前的临床实践中没有常规获得。似乎将 LAR 纳入数据集以训练预后人工智能是有益的。

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