Isha Shahin, Raavi Lekhya, Jonna Sadhana, Nataraja Hrishikesh, Craver Emily C, Jenkins Anna, Hanson Abby J, Balasubramanian Prasanth, Balavenkataraman Arvind, Tekin Aysun, Bansal Vikas, Reddy Swetha, Caples Sean M, Khan Syed Anjum, Jain Nitesh K, LaNou Abigail T, Kashyap Rahul, Cartin-Ceba Rodrigo, Milian Ricardo Diaz, Venegas Carla P, Shapiro Anna B, Bhattacharyya Anirban, Chaudhary Sanjay, Kiley Sean P, Quinones Quintin J, Patel Neal M, Guru Pramod K, Franco Pablo Moreno, Roy Archana, Sanghavi Devang K
Department of Critical Care Medicine, Mayo Clinic in Florida, Jacksonville, FL, USA.
Department of Quantitative Health Sciences, Mayo Clinic in Florida, Jacksonville, FL, USA.
Biomark Insights. 2025 May 15;20:11772719241296624. doi: 10.1177/11772719241296624. eCollection 2025.
Procalcitonin (PCT) is recognized as an inflammatory biomarker, often elevated in COVID-19 pneumonia alongside other biomarkers. Understanding its association with severe outcomes and comparing its predictive ability with other biomarkers is crucial for clinical management.
This retrospective multicenter observational study aimed to investigate the association between PCT levels and adverse outcomes in hospitalized COVID-19 patients. Additionally, it sought to compare the predictive performance of various biomarkers.
The study analyzed data from the Society of Critical Care Medicine (SCCM) Viral Infection and Respiratory Illness Universal Study (VIRUS) registry, comprising COVID-19 patients hospitalized across multiple Mayo Clinic sites between March 2020 and June 2022.
A total of 7851 adult COVID-19 patients were included. Patients were categorized into 6 groups based on the worst WHO ordinal scale. Multivariate models were constructed using peak biomarker levels within 72 hours of admission, adjusted for confounders.
Elevated PCT levels were independently associated with increased odds of adverse outcomes, including ICU admission (adjusted odds ratio [aOR] 1.32, 95%CI 1.27-1.38), IMV requirement (aOR 1.35, 95%CI: 1.28-1.42), and in-hospital mortality (aOR 1.30, 95%CI: 1.22-1.37). A 3.48-fold increase in IMV requirement and 3.55 times increase in in-hospital mortality were noted with peak PCT ⩾ 0.25 ng/ml. Similar associations were observed with other biomarkers like NLR (AUC 0.730), CRP, IL-6, LDH (AUC 0.800), and D-dimer (AUC 0.719). Models incorporating NLR, LDH, D-dimer, and PCT demonstrated the highest predictive accuracy, with a combined model exhibiting an area under the curve (AUC) of 0.826 (95%CI 0.803-0.849).
Higher PCT levels were significantly linked to worse outcomes in COVID-19 patients, emphasizing its potential as a prognostic marker. Biomarker-based predictive models, particularly those including PCT, showed promising utility for risk assessment and clinical decision-making. Further prospective studies are warranted to validate these findings on a larger scale.
降钙素原（PCT）被认为是一种炎症生物标志物，在新型冠状病毒肺炎（COVID-19）中，它常常与其他生物标志物一起升高。了解其与严重后果的关联，并将其预测能力与其他生物标志物进行比较，对临床管理至关重要。
这项回顾性多中心观察性研究旨在调查住院COVID-19患者的PCT水平与不良后果之间的关联。此外，该研究还试图比较各种生物标志物的预测性能。
该研究分析了危重病医学学会（SCCM）病毒感染和呼吸道疾病通用研究（VIRUS）登记处的数据，该登记处涵盖了2020年3月至2022年6月期间在梅奥诊所多个地点住院的COVID-19患者。
共纳入7851例成年COVID-19患者。根据世界卫生组织最严重等级量表将患者分为6组。使用入院72小时内的生物标志物峰值水平构建多变量模型，并对混杂因素进行校正。
PCT水平升高与不良后果的几率增加独立相关，包括入住重症监护病房（ICU）（校正优势比[aOR]为1.32，95%置信区间[CI]为1.27-1.38）、需要机械通气（IMV）（aOR为1.35，95%CI：1.28-1.42）和院内死亡（aOR为1.30，95%CI：1.22-1.37）。当PCT峰值⩾0.25 ng/ml时，IMV需求增加3.48倍，院内死亡率增加3.55倍。在NLR（曲线下面积[AUC]为0.730）、CRP、IL-6、乳酸脱氢酶（LDH）（AUC为0.800）和D-二聚体（AUC为0.719）等其他生物标志物中也观察到类似的关联。纳入NLR、LDH、D-二聚体和PCT的模型显示出最高的预测准确性，联合模型的曲线下面积（AUC）为0.826（95%CI为0.803-0.849）。
较高的PCT水平与COVID-19患者更差的预后显著相关，并强调了其作为预后标志物的潜力。基于生物标志物的预测模型，尤其是那些包括PCT的模型，在风险评估和临床决策方面显示出有前景的效用。有必要进行进一步的前瞻性研究以更大规模地验证这些发现。
