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Laboratory Biomarkers in the Clinical Management of COVID-19 and Post-COVID-19 Conditions

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A special issue of Journal of Clinical Medicine (ISSN 2077-0383). This special issue belongs to the section "Clinical Laboratory Medicine".

Deadline for manuscript submissions: closed (31 December 2024) | Viewed by 7184

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Special Issue Editors

Prof. Dr. Stefan Holdenrieder

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Guest Editor

Institute of Laboratory Medicine, German Heart Centre Munich, TUM School of Medicine, Technical University of Munich, 80636 Munich, Germany
Interests: molecular diagnostics; cardiac biomarkers; cancer biomarkers; immunological diagnostics; molecular oncology; tumor markers
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Perikles Simon

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Guest Editor

Department of Sports Medicine, Rehabilitation and Disease Prevention, Institute of Sports Sciences, Johannes Gutenberg University of Mainz, Mainz, Germany
Interests: preventive medicine; sports medicine; exercise immunology; exercise science

Special Issue Information

Dear Colleagues,

During the COVID-19 pandemic, laboratory diagnostics created a considerable impact for i) the diagnosis of diseases, ii) the guidance of infected patients, and iii) the monitoring of the immune response after infection and vaccination. In everyday clinical diagnostics and in well-defined clinical trials, an enormous amount of data were collected that were helpful for the management of the pandemic and that still provide a lot of valuable insights for the preparation for new viral pandemics in the future. Thereby, the value of well-established laboratory parameters and the value of new molecular approaches for the characterization of the disease have been uncovered. However, a thoroughful evaluation of the abundant laboratory data is still ongoing in many places and deserves a platform for its focussed presentation. Therefore the aim of this Special Issue is to provide a comprehensive overview of studies on diagnostic markers that have shown great value for i) the early and accurate molecular diagnosis of the SARS CoV-2 virus via the use of diverse methods; ii) the diagnosis of COVID-19 disease and the estimation of the prognosis for the outcome of patients, particularly patients with diverse comorbidities; iii) the monitoring of disease courses and the early idenfitication of severe complications; iv) the time-related immune response to SARS CoV-2 infection; v) the humoral and cellular immune responses after the administration of diverse vaccinations in relation to predisposition, comorbidities, and side effects; vi) the identification of possible correlates of protection (COP) or predictions of risk (POR) for severe disease courses to define the period for timely booster vaccination; and finally, vii) the characterization of pathophysiological mechanisms that underly the development of long-COVID and biomarkers that support the prognosis and guidance of affected patients. Therefore, lab doctors, pathologists, researchers, and clinicians are encouraged to submit their findings as original articles or reviews to this Special Issue.

Prof. Dr. Stefan Holdenrieder
Prof. Dr. Perikles Simon
Guest Editors

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Keywords

COVID-19 pandemic
SARS CoV-2 detection
diagnostic and prognostic lab parameters
humoral and cellular immune response
therapy monitoring during infection
correlate of protection after vaccination
long-COVID

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Published Papers (5 papers)

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Research

13 pages, 2325 KiB

Open AccessArticle

Interrelationships Between Plasma Levels of Brain Natriuretic Peptide and Prolonged Symptoms Due to Long COVID

by Yohei Masuda, Yuki Otsuka, Kazuki Tokumasu, Hiroyuki Honda, Yasue Sakurada, Yui Matsuda, Yasuhiro Nakano, Ryosuke Takase, Daisuke Omura, Toru Hasegawa, Keigo Ueda and Fumio Otsuka

J. Clin. Med. 2025, 14(3), 817; https://doi.org/10.3390/jcm14030817 - 26 Jan 2025

Viewed by 2022

Abstract

Objectives: Evidence for the usefulness of biomarkers that aid in diagnosis, assessment of severity, and prediction of prognosis in patients with long COVID is limited. The aim of this study was to clarify the characteristics of brain natriuretic peptide (BNP) in long COVID. Methods: We conducted a retrospective observational study of patients who visited the COVID-19 aftercare outpatient clinic at Okayama University Hospital from February 2021 to April 2024. Results: A total of 428 patients were enrolled in this study, and the patients were divided into a group with normal BNP (n = 314, ≤18.4 pg/mL) and a group with increased BNP (n = 114, >18.4 pg/mL). The long COVID group with increased BNP had a higher proportion of females (44.3% vs. 73.7%, p < 0.01) and an older median age (38 vs. 51 years, p < 0.01). Fatigue and brain fog were commonly manifested in both groups, while dyspnea was a more frequent complaint in the group with increased BNP. Various symptoms including fatigue, palpitations, and taste and/or olfactory disorders were associated with elevated BNP (23 to 24 pg/mL). Memory impairment was also linked to higher BNP (OR: 2.36, p = 0.05). In long COVID patients, plasma BNP elevation appears to be more pronounced in females and is often related to cardiogenic factors, in which inflammatory responses are also involved. Conclusions: Plasma BNP measurement may be useful for evaluating the severity of long COVID, especially in female patients and those with respiratory symptoms and/or memory impairment. Full article

(This article belongs to the Special Issue Laboratory Biomarkers in the Clinical Management of COVID-19 and Post-COVID-19 Conditions)

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15 pages, 829 KiB

Open AccessArticle

Associations Between Clinical Manifestations of SARS-CoV-2 Infection and HLA Alleles in a Caucasian Population: A Molecular HLA Typing Study

by Bogusław Tymoniuk, Maciej Borowiec, Joanna Makowska, Emilia Holwek, Joanna Sarnik, Filip Styrzyński, Izabela Dróżdż, Andrzej Lewiński and Magdalena Stasiak

J. Clin. Med. 2024, 13(24), 7695; https://doi.org/10.3390/jcm13247695 - 17 Dec 2024

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Abstract

Background and Objectives: Severe COVID-19 still constitutes an important health problem. Taking into account the crucial role of HLA in immune reactions, evaluation of the impact of HLA on COVID-19 risk and clinical course seemed necessary, as the already available data are inconsistent. The aim of the present study was to compare the HLA profiles of patients with symptomatic SARS-CoV-2 infection and a healthy control group, as well as to compare HLA allele frequencies in patients with severe and non-severe courses of COVID-19. Materials and Methods: HLA classes were genotyped using a next-generation sequencing method in 2322 persons, including 2217 healthy hematopoietic stem cell potential donors and 105 patients with symptomatic COVID-19. Results: Symptomatic course of SARS-CoV-2 infection appeared to be associated with the presence of HLA-A*30:01, B*44:02, B*52:01, C*05:01, C*17:01, and DRB1*11:02, while HLA-C*07:04 and DQB1*03:03 seem to play a protective role. Moreover, we demonstrated that the severe symptomatic course of COVID-19 can be associated with the presence of HLA-B*08:01, C*04:01, DRB1*03:01, and DQB1*03:01, while HLA-DRB1*08:01 appeared to be protective against severe COVID-19 disease. Conclusions: Identification of alleles that are potentially associated with symptomatic SARS-CoV-2 infection as well as the severe course of COVID-19 broadens the knowledge on the genetic background of COVID-19 course and can constitute an important step in the development of personalized medicine. Full article

(This article belongs to the Special Issue Laboratory Biomarkers in the Clinical Management of COVID-19 and Post-COVID-19 Conditions)

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14 pages, 1976 KiB

Open AccessArticle

Development of a Model for Predicting Mortality Among Patients Hospitalized with COVID-19 During Their Stay in a Clinical Centre

by Neftalí Guzmán, Pablo Letelier, Camilo Morales, Luis Alarcón, Hugo Delgado, Andrés San Martín, Paola Garcés, Claudia Barahona, Pedro Huenchulao, Felipe Morales, Eduardo Rojas, Dina Guzmán-Oyarzo and Rodrigo Boguen

J. Clin. Med. 2024, 13(23), 7300; https://doi.org/10.3390/jcm13237300 - 30 Nov 2024

Cited by 1 | Viewed by 858

Abstract

Background: Various tools have been proposed for predicting mortality among patients hospitalized with COVID-19 to improve clinical decision-making, the predictive capacities of which vary in different populations. The objective of this study was to develop a model for predicting mortality among patients hospitalized with COVID-19 during their time in a clinical centre. Methods: This was a retrospective study that included 201 patients hospitalized with COVID-19. Mortality was evaluated with the Kaplan–Meier curve and Cox proportional hazards models. Six models were generated for predicting mortality from laboratory markers and patients’ epidemiological data during their stay in a clinical centre. Results: The model that presented the best predictive power used D-dimer adjusted for C-reactive protein (CRP) and oxygen saturation. The sensitivity (Sn) and specificity (Sp) at 15 days were 75% and 71.9%, respectively. At 30 days, Sn was 75% and Sp was 75.4%. Conclusions: These results allowed us to establish a model for predicting mortality among patients hospitalized with COVID-19 based on D-dimer laboratory biomarkers adjusted for CRP and oxygen saturation. This mortality predictor will allow patients to be identified who require more continuous monitoring and health care. Full article

(This article belongs to the Special Issue Laboratory Biomarkers in the Clinical Management of COVID-19 and Post-COVID-19 Conditions)

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12 pages, 2758 KiB

Open AccessArticle

The Model for End-Stage Liver Disease (MELD) Score Predicting Mortality Due to SARS-CoV-2 in Mexican Patients

by José Manuel Reyes-Ruiz, Ana Citlali Avelino-Santiago, Gustavo Martínez-Mier, Claudia Vanessa López-López, Luis Adrián De Jesús-González, Moises León-Juárez, Juan Fidel Osuna-Ramos, Carlos Noe Farfan-Morales, Selvin Noé Palacios-Rápalo, Víctor Bernal-Dolores and Rosa María Del Ángel

J. Clin. Med. 2024, 13(19), 5777; https://doi.org/10.3390/jcm13195777 - 27 Sep 2024

Cited by 1 | Viewed by 1449

Abstract

Background/Objectives: Coronavirus Disease 2019 (COVID-19) can cause liver injury and a deterioration of hepatic function. The Model for End-Stage Liver Disease (MELD) score is a good predictor for poor prognosis of hospitalized COVID-19 patients in the United States, Egypt and Turkey. Nevertheless, the best cut-off value for the MELD score to predict mortality in the Mexican population has yet to be established. Methods: A total of 234 patients with COVID-19 were studied in a tertiary-level hospital. Patients were stratified into survivors (n = 139) and non-survivors (n = 95). Receiver operating characteristic curves, Cox proportional hazard models, Kaplan–Meier method, and Bonferroni corrections were performed to identify the predictors of COVID-19 mortality. Results: MELD score had an area under the curve of 0.62 (95% CI: 0.56–0.68; p = 0.0009), sensitivity = 53.68%, and specificity = 73.38%. Univariate Cox proportional hazard regression analysis suggested that the leukocytes > 10.6, neutrophils > 8.42, neutrophil-to-lymphocyte ratio (NLR) > 8.69, systemic immune-inflammation index (SII) > 1809.21, MELD score > 9, and leukocyte glucose index (LGI) > 2.41 were predictors for mortality. However, the multivariate Cox proportional hazard model revealed that only the MELD score >9 (Hazard Ratio [HR] = 1.83; 95% confidence interval [CI]: 1.2–2.8; P_corrected = 0.03) was an independent predictor for mortality of COVID-19. Conclusions: Although the MELD score is used for liver transplantation, we suggest that a MELD score >9 could be an accurate predictor for COVID-19 mortality at admission to ICU requiring mechanical ventilation. Full article

(This article belongs to the Special Issue Laboratory Biomarkers in the Clinical Management of COVID-19 and Post-COVID-19 Conditions)

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11 pages, 538 KiB

Open AccessArticle

Predictivity of the Prognostic Nutritional Index and Systemic Inflammation Index for All-Cause In-Hospital Mortality in Geriatric and Adult COVID-19 Inpatients

by Sibel Cavdar, Sumru Savas, Sezai Tasbakan, Abdullah Sayıner, Ozen Basoglu, Pervin Korkmaz and Fehmi Akcicek

J. Clin. Med. 2024, 13(15), 4466; https://doi.org/10.3390/jcm13154466 - 30 Jul 2024

Cited by 2 | Viewed by 1285

Abstract

Background: The prognostic nutritional index (PNI) and the systemic immune inflammation index (SII) have been used as simple risk-stratification predictors for COVID-19 severity and mortality in the general population. However, the associations between these indices and mortality might differ due to age-related changes such as inflammaging and several comorbid conditions in older patients. Therefore, we aimed to compare the predictivity of the PNI and SII for mortality among hospitalized older patients and patients under 65 years old. Methods: Patients hospitalized with COVID-19 from March 2020 to December 2020 were retrospectively included. The PNI and SII were calculated from hospital records within the first 48 h after admission. Data were evaluated in the whole group and according to age groups (≥65 < years). Receiver operating characteristic curves were drawn to evaluate the predictivity of the PNI and SII. Results: Out of 407 patients included in this study, 48.4% (n = 197) were older patients, and 51.6% (n = 210) were under 65 years old. For mortality, the area under the curve (AUC) of the PNI and SII in the adult group (<65 years) was 0.706 (95% CI 0.583–0.828) (p = 0.003) and 0.697 (95% CI 0.567–0.827) (p < 0.005), respectively. The AUC of the PNI and SII in the older group was 0.515 (95% CI 0.427–0.604) (p = 0.739) and 0.500 (95% CI 0.411–0.590) (p = 0.993). Conclusions: The accuracy of the PNI and SII in predicting mortality in adult COVID-19 patients seemed to be fair, but no association was found in geriatric patients in this study. The predictivity of the PNI and SII for mortality varies according to age groups. Full article

(This article belongs to the Special Issue Laboratory Biomarkers in the Clinical Management of COVID-19 and Post-COVID-19 Conditions)

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