Shahin Isha, Lekhya Raavi, Sadhana Jonna, Hrishikesh Nataraja, Emily C Craver, Anna Jenkins, Abby J Hanson, Prasanth Balasubramanian, Arvind Balavenkataraman, Aysun Tekin, Vikas Bansal, Swetha Reddy, Sean M Caples, Syed Anjum Khan, Nitesh K Jain, Abigail T LaNou, Rahul Kashyap, Rodrigo Cartin-Ceba, Ricardo Diaz Milian, Carla P Venegas, Anna B Shapiro, Anirban Bhattacharyya, Sanjay Chaudhary, Sean P Kiley, Quintin J Quinones, Neal M Patel, Pramod K Guru, Pablo Moreno Franco, Archana Roy, Devang K Sanghavi
{"title":"Role of Procalcitonin as a Prognostic Biomarker in Hospitalized COVID-19 Patients: A Comparative Analysis.","authors":"Shahin Isha, Lekhya Raavi, Sadhana Jonna, Hrishikesh Nataraja, Emily C Craver, Anna Jenkins, Abby J Hanson, Prasanth Balasubramanian, Arvind Balavenkataraman, Aysun Tekin, Vikas Bansal, Swetha Reddy, Sean M Caples, Syed Anjum Khan, Nitesh K Jain, Abigail T LaNou, Rahul Kashyap, Rodrigo Cartin-Ceba, Ricardo Diaz Milian, Carla P Venegas, Anna B Shapiro, Anirban Bhattacharyya, Sanjay Chaudhary, Sean P Kiley, Quintin J Quinones, Neal M Patel, Pramod K Guru, Pablo Moreno Franco, Archana Roy, Devang K Sanghavi","doi":"10.1177/11772719241296624","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Objectives: </strong>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.</p><p><strong>Design: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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).</p><p><strong>Conclusions: </strong>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.</p>","PeriodicalId":47060,"journal":{"name":"Biomarker Insights","volume":"20 ","pages":"11772719241296624"},"PeriodicalIF":3.4000,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12084704/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biomarker Insights","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/11772719241296624","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"MEDICINE, RESEARCH & EXPERIMENTAL","Score":null,"Total":0}
引用次数: 0
Abstract
Background: 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.
Objectives: 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.
Design: 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.
Methods: 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.
Results: 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).
Conclusions: 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.