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IL-6/KL-6比值能否区分新型冠状病毒肺炎急性呼吸窘迫综合征的不同表型?一项基于前瞻性收集的临床、生物学和计算机断层扫描数据的观察性研究。

Does the IL-6/KL-6 ratio distinguish different phenotypes in COVID-19 Acute Respiratory Distress Syndrome? An observational study stemmed from prospectively derived clinical, biological, and computed tomographic data.

作者信息

Partouche Nicolas, Maumy Myriam, Chamaraux-Tran Thien-Nga, Bertrand Frederic, Schneider Francis, Meyer Nicolas, Solis Morgane, Fafi-Kremer Samira, Noll Eric, Pottecher Julien

机构信息

Service d'Anesthésie-Réanimation & Médecine Péri-Opératoire, Hôpital de Hautepierre, Hôpitaux Universitaires de Strasbourg, UR3072, FMTS, FHU Omicare, Faculté de Médecine, Maïeutique et Sciences de la Santé, Université de Strasbourg, Strasbourg, France.

LIST3N, University of Technology of Troyes, Troyes, France.

出版信息

PLoS One. 2025 May 21;20(5):e0321533. doi: 10.1371/journal.pone.0321533. eCollection 2025.

DOI:10.1371/journal.pone.0321533
PMID:40397955
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12094726/
Abstract

BACKGROUND

As new SARS-CoV-2 variants emerge and as treatment of COVID-19 ARDS remains exclusively supportive, there is an unmet need to better characterize its different phenotypes to tailor personalized treatments. Clinical, biological, spirometric and CT data hardly allow deciphering of Heavy (H), Intermediate (I) and Light (L) phenotypes of COVID-19 ARDS and the implementation of tailored specific strategies (prone positioning, PEEP settings, recruitment maneuvers). We hypothesized that the ratio of two pivotal COVID-19 biomarkers (interleukin 6 [IL-6] and Krebs von den Lungen 6 [KL-6], related to inflammation and pneumocyte repair, respectively) would provide a biologic insight into the disease timeline allowing 1) to differentiate H, I and L phenotypes, 2) to predict outcome and 3) to reflect some of CT findings.

METHODS AND FINDINGS

This was a retrospective analysis of prospectively acquired data (COVID HUS cohort). Inclusion concerned any patient with severe COVID-19 pneumonia admitted to two intensive care units between March 1st and May 1st, 2020, in a high-density cluster of the first epidemic wave (Strasbourg University Hospital, France). Demographic, clinical, biological (standard, IL-6 [new generation ELISA], KL-6 [CLEIA technique]), spirometric (driving pressure, respiratory system compliance) and CT data were collected longitudinally. CT analysis included semi-automatic and automatic lung measurements and allowed segmentation of lung volumes into 4 (poorly aerated, non-aerated, overinflated and normally aerated) and 3 (ground-glass, restricted normally aerated, and overinflated) zones, respectively. The primary outcome was to challenge the IL-6/KL-6 ratio capacity to decipher the three COVID-19 ARDS phenotypes (H, I and L) defined on clinical, spirometric and radiologic grounds. Secondary outcomes were the analysis of the prognostic value of the IL-6/KL-6 ratio and its correlates with CT-acquired data. Multivariate analysis was based on principal component analysis. One hundred and forty-eight ventilated COVID-19 ICU patients from the COVID HUS cohort were assessed for eligibility and 77 were included in the full analysis. Most were male, all were under invasive mechanical ventilation and vasopressor therapy and displayed high severity scores (SAPSII: 48 [42-56]; SOFA: 8 [7-10]). The L, I and H COVID ARDS phenotypes were identified in 11, 15 and 48 patients, respectively. In three patients, the phenotype could not be defined precisely. Thirty patients (39%) died in the ICU and the number of ventilator-free days was 2 [0-2] days. The IL-6/KL-6 ratio was not significantly different between the L, I and H phenotypes and evolved according to similar patterns over time. Surviving and deceased patients displayed an inverse kinetic of KL-6. IL-6 and the IL-6/KL-6 ratio were linearly associated with ground-glass volume on semi-automatic and automatic CT lung measurements.

CONCLUSIONS

In our population of severe ventilated COVID ARDS patients, the IL-6/KL-6 ratio was not clue to differentiate the H, I and L phenotypes and tailor a personalized ventilatory approach. There was an interesting correlation between IL-6/KL-6 ratio and ground-glass volume as determined by automated lung CT analysis. Such correlation deserves more in-depth pathophysiological study, at best gathered from a prospective cohort with a larger sample size and histological analysis.

TRIAL REGISTRATION

COVID HUS Trial registration number: NCT04405726.

摘要

背景

随着新型严重急性呼吸综合征冠状病毒2(SARS-CoV-2)变种的出现,以及冠状病毒病(COVID-19)急性呼吸窘迫综合征(ARDS)的治疗仍仅为支持性治疗,因此迫切需要更好地描述其不同表型,以制定个性化治疗方案。临床、生物学、肺功能和计算机断层扫描(CT)数据很难用于解读COVID-19 ARDS的重型(H)、中型(I)和轻型(L)表型,以及实施针对性的具体策略(俯卧位通气、呼气末正压通气设置、肺复张手法)。我们推测,两种关键的COVID-19生物标志物(分别与炎症和肺上皮细胞修复相关的白细胞介素6 [IL-6]和克雷布斯冯登肺6 [KL-6])的比值,将为疾病进程提供生物学见解,从而能够1)区分H、I和L表型,2)预测预后,以及3)反映部分CT检查结果。

方法和结果

这是一项对前瞻性收集的数据(COVID HUS队列)进行的回顾性分析。纳入标准为2020年3月1日至5月1日期间,在第一波疫情的高密度聚集区(法国斯特拉斯堡大学医院)入住两个重症监护病房的任何重症COVID-19肺炎患者。纵向收集人口统计学、临床、生物学(标准指标、IL-6 [新一代酶联免疫吸附测定法]、KL-6 [化学发光酶免疫分析技术])、肺功能(驱动压、呼吸系统顺应性)和CT数据。CT分析包括半自动和自动肺测量,并分别将肺容积分割为4个区域(通气不良、无通气、过度充气和正常通气)和3个区域(磨玻璃影、正常通气受限和过度充气)。主要结局是检验IL-6/KL-6比值区分基于临床、肺功能和影像学定义的三种COVID-19 ARDS表型(H、I和L)的能力。次要结局是分析IL-6/KL-6比值的预后价值及其与CT获取数据的相关性。多变量分析基于主成分分析。对COVID HUS队列中的148例接受机械通气的COVID-19重症监护病房患者进行了资格评估,其中77例纳入全面分析。大多数为男性,均接受有创机械通气和血管活性药物治疗,且病情严重程度评分较高(序贯器官衰竭评估[SAPSII]:48 [42 - 56];序贯器官衰竭评估[SOFA]:8 [7 - 10])。分别在11例、15例和48例患者中识别出L、I和H型COVID ARDS表型。3例患者的表型无法精确界定。30例患者(39%)在重症监护病房死亡,无呼吸机天数为2 [0 - 2]天。L、I和H表型之间的IL-6/KL-6比值无显著差异,且随时间呈现相似的变化模式。存活和死亡患者的KL-6呈现相反的变化趋势。半自动和自动CT肺测量显示,IL-6和IL-6/KL-6比值与磨玻璃影容积呈线性相关。

结论

在我们的重症COVID ARDS机械通气患者群体中,IL-6/KL-6比值并非区分H、I和L表型以及制定个性化通气方案的线索。通过自动肺CT分析确定,IL-6/KL-6比值与磨玻璃影容积之间存在有趣的相关性。这种相关性值得进行更深入的病理生理学研究,最好从前瞻性队列中收集更大样本量的数据并进行组织学分析。

试验注册

COVID HUS试验注册号:NCT04405726。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f834/12094726/f27924db71ec/pone.0321533.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f834/12094726/9f98a83f5ca6/pone.0321533.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f834/12094726/f27924db71ec/pone.0321533.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f834/12094726/9f98a83f5ca6/pone.0321533.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f834/12094726/f27924db71ec/pone.0321533.g002.jpg

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