Prognostic Utility of Procalcitonin, Presepsin, and the VACO Index for Predicting 30-day Mortality in Hospitalized COVID-19 Patients
1
조회
0
다운로드
1
인용
0
참고문헌
키워드
초록
Background: Biomarkers and clinical indices have been investigated for predicting mortality in patients with coronavirus disease (COVID-19). We explored the prognostic utility of procalcitonin (PCT), presepsin, and the Veterans Health Administration COVID-19 (VACO) index for predicting 30-day-mortality in COVID-19 patients. Methods: In total, 54 hospitalized COVID-19 patients were enrolled. PCT and presepsin levels were measured using the Elecsys BRAHMS PCT assay (Roche Diagnostics GmbH, Mannheim, Germany) and HISCL Presepsin assay (Sysmex, Kobe, Japan), respectively. The VACO index was calculated based on age, sex, and comorbidities. PCT and presepsin levels and the VACO index were compared using ROC curve, Kaplan–Meier method, and reclassification analysis for the 30-day mortality. Results: ROC curve analysis was used to measure PCT and presepsin levels and the VACO index to predict 30-day mortality; the optimal cut-off values were 0.138 ng/mL for PCT, 717 pg/mL for presepsin, and 12.1% for the VACO index. On Kaplan–Meier survival analysis, hazard ratios (95% confidence interval) were 15.9 (4.1-61.3) for PCT, 26.3 (6.4-108.0) for presepsin, and 6.0 (1.7-21.1) for the VACO index. On reclassification analysis, PCT and presepsin in addition to the VACO index significantly improved the prognostic value of the index. Conclusions: This study demonstrated the prognostic utility of measuring PCT and presepsin levels and the VACO index in COVID-19 patients. The biomarkers in addition to the clinical index were more useful than the index alone for predicting clinical outcomes in COVID-19 patients.
Abstract
Background: Biomarkers and clinical indices have been investigated for predicting mortality in patients with coronavirus disease (COVID-19). We explored the prognostic utility of procalcitonin (PCT), presepsin, and the Veterans Health Administration COVID-19 (VACO) index for predicting 30-day-mortality in COVID-19 patients. Methods: In total, 54 hospitalized COVID-19 patients were enrolled. PCT and presepsin levels were measured using the Elecsys BRAHMS PCT assay (Roche Diagnostics GmbH, Mannheim, Germany) and HISCL Presepsin assay (Sysmex, Kobe, Japan), respectively. The VACO index was calculated based on age, sex, and comorbidities. PCT and presepsin levels and the VACO index were compared using ROC curve, Kaplan–Meier method, and reclassification analysis for the 30-day mortality. Results: ROC curve analysis was used to measure PCT and presepsin levels and the VACO index to predict 30-day mortality; the optimal cut-off values were 0.138 ng/mL for PCT, 717 pg/mL for presepsin, and 12.1% for the VACO index. On Kaplan–Meier survival analysis, hazard ratios (95% confidence interval) were 15.9 (4.1-61.3) for PCT, 26.3 (6.4-108.0) for presepsin, and 6.0 (1.7-21.1) for the VACO index. On reclassification analysis, PCT and presepsin in addition to the VACO index significantly improved the prognostic value of the index. Conclusions: This study demonstrated the prognostic utility of measuring PCT and presepsin levels and the VACO index in COVID-19 patients. The biomarkers in addition to the clinical index were more useful than the index alone for predicting clinical outcomes in COVID-19 patients.
참고문헌 (30)
- Ki Ho Hong, "Guidelines for Laboratory Diagnosis of Coronavirus Disease 2019 (COVID-19) in Korea", Annals of Laboratory Medicine, 40(5), pp.351~360 (2020), 대한진단검사의학회[DOI]
- Kim Shin-Woo, "Clinical Characteristics and Outcomes of COVID-19 Cohort Patients in Daegu Metropolitan City Outbreak in 2020", Journal of Korean Medical Science, 36(1), pp.1~15 (2021), 대한의학회[DOI]
- Lee JY, "Epidemiological and clinical characteristics of coronavirus disease 2019 in Daegu, South Korea", Int J Infect Dis, 98, pp.462~466 (2020)
- Yoo Eun-Hyung, "Comprehensive Laboratory Data Analysis to Predict the Clinical Severity of Coronavirus Disease 2019 in 1,952 Patients in Daegu, Korea", Annals of Laboratory Medicine, 42(1), pp.24~35 (2022), 대한진단검사의학회[DOI]
- "Current status of COVID-19 outbreak and vaccination in Korea (6.30.)" (2021)[URL]
- Shaw RJ, "COVID-19 and immunothrombosis : emerging understanding and clinical management", Br J Haematol, 194, pp.518~529 (2021)
- "Living guidance for clinical management of COVID-19" (2021)[URL]
- Singer M, "The third international consensus definitions for sepsis and septic shock(Sepsis-3)", JAMA, 315, pp.801~810 (2016)
- King JT Jr, "Development and validation of a 30-day mortality index based on pre-existing medical administrative data from 13, 323 COVID-19 patients : the Veterans Health Administration COVID-19(VACO)Index", PLoS One, 15, pp.e0241825~ (2020)
- King JT Jr, "Accuracy of the Veterans Health Administration COVID-19 (VACO) index for predicting short-term mortality among 1307 US academic medical centre inpatients and 427 224 US Medicare patients", J Epidemiol Community Health (2021)
- Bivona Giulia, "Biomarkers for Prognosis and Treatment Response in COVID-19 Patients", Annals of Laboratory Medicine, 41(6), pp.540~548 (2021), 대한진단검사의학회[DOI]
- Ponti G, "Biomarkers associated with COVID-19 disease progression", Crit Rev Clin Lab Sci, 57, pp.389~399 (2020)
- Henry BM, "Hematologic, biochemical and immune biomarker abnormalities associated with severe illness and mortality in coronavirus disease 2019 (COVID-19): a meta-analysis", Clin Chem Lab Med, 58, pp.1021~1028 (2020)
- Welder D, "Immature platelets as a biomarker for disease severity and mortality in COVID-19 patients", Br J Haematol, 194, pp.530~536 (2021)
- Hur M, "Diagnostic and prognostic utilities of multimarkers approach using procalcitonin, B-type natriuretic peptide, and neutrophil gelatinase-associated lipocalin in critically ill patients with suspected sepsis", BMC Infect Dis, 14, pp.224~ (2014)
- Vijayan AL, "Procalcitonin : a promising diagnostic marker for sepsis and antibiotic therapy", J Intensive Care, 5, pp.51~ (2017)
- Zhang G, "Clinical features and short-term outcomes of 221 patients with COVID-19 in Wuhan, China", J Clin Virol, 127, pp.104364~ (2020)
- Huang C, "Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China", Lancet, 395, pp.497~506 (2020)
- Tjendra Y, "Predicting disease severity and outcome in COVID-19 patients : a review of multiple biomarkers", Arch Pathol Lab Med, 144, pp.1465~1474 (2020)
- Hu R, "Procalcitonin levels in COVID-19 patients", Int J Antimicrob Agents, 56, pp.106051~ (2020)
- Yang HS, "Prognostic value of presepsin in adult patients with sepsis : systematic review and meta-analysis", PLoS One, 13, pp.e0191486~ (2018)
- Kim H, "Multi-marker approach using procalcitonin, presepsin, galectin-3, and soluble suppression of tumorigenicity 2 for the prediction of mortality in sepsis", Ann Intensive Care, 7, pp.27~ (2017)
- Iskandar A, "Comparison between presepsin and procalcitonin in early diagnosis of neonatal sepsis", J Matern Fetal Neonatal Med, 32, pp.3903~3908 (2019)
- Kocyigit A, "Circulating furin, IL-6, and presepsin levels and disease severity in SARS-CoV-2-infected patients", Sci Prog, 104, pp.368504211026119~ (2021)
- Zaninotto M, "Presepsin in risk stratification of SARS-CoV-2 patients", Clin Chim Acta, 507, pp.161~163 (2020)
- Fukada A, "Presepsin as a predictive biomarker of severity in COVID-19 : a case series", J Med Virol, 93, pp.99~101 (2021)
- Nagashima K, "Sample size calculations for single-arm survival studies using transformations of the Kaplan-Meier estimator", Pharm Stat, 20, pp.499~511 (2021)
- Pencina MJ, "Evaluating the added predictive ability of a new marker : from area under the ROC curve to reclassification and beyond", Stat Med, 27, pp.157~172 (2008)
- Raschke RA, "Discriminant accuracy of the SOFA score for determining the probable mortality of patients with COVID-19 pneumonia requiring mechanical ventilation", JAMA, 325, pp.1469~1470 (2021)
- Aguilar RB, "Current understanding of COVID-19 clinical course and investigational treatments", Front Med(Lausanne), 7, pp.555301~ (2020)