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Biomarkers for Predicting Treatment Response and Guiding Therapy in COVID-19 Patients

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A special issue of Diagnostics (ISSN 2075-4418). This special issue belongs to the section "Diagnostic Microbiology and Infectious Disease".

Deadline for manuscript submissions: closed (31 December 2021) | Viewed by 27472

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Dr. Giulia Bivona

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Department of Biomedicine, Neurosciences and Advanced Diagnostics, University of Palermo, Palermo, Italy
Interests: laboratory medicine; vitamin D; biomarkers; neurodegeneration
Special Issues, Collections and Topics in MDPI journals

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Dear Colleagues,

With the SARS-CoV-2 outbreak, an unprecedented amount of literature data regarding the biological and clinical aspects of COVID-19 has been published, and papers addressing the role of biomarkers in COVID-19 are no exception. However, it is questionable whether this trendy wave has contributed to scientific progress. Indeed, almost any analyte can change during a severe infection like COVID-19 and correlate with disease severity and survival, but no biomarker can impact clinical practice until it has been proven to help clinicians guiding treatment. Although several studies have documented the association between COVID-19 severity and circulating levels of C-reactive protein (CRP), IL-6, prothrombin (PT), and D-dimer, the clinical usefulness of these biomarkers in COVID-19 is far from being proven, also because many studies were affected by several drawbacks, weakening the strength of their results (i.e., retrospective design, discrepancies in the assay methods used, in the cut-off used, in the time point of measurement, in the endpoints chosen). Additionally, data on treatment response are few and limited to CRP and IL-6. A recent IFCC recommendation encourages using caution before translating study results on biomarkers in COVID-19 patients into laboratory–clinical practice, especially when the use of cut-offs is proposed. Hence, reliable data from rigorous studies are needed to clarify whether and which biomarkers can be used to manage SARS-CoV-2-infected patients.

This Special Issue aims to collect novel, homogeneous data on biomarkers of treatment response in COVID-19 patients. Research and review articles attempting to prove how and which biomarkers can help clinicians to predict treatment response are highly encouraged.

Prof. Dr. Giulia Bivona
Guest Editor

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Keywords

Biomarkers
Coronavirus
Predictive value
COVID-19
Severity
Treatment response
C-reactive protein
IL-6

Published Papers (8 papers)

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Research

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12 pages, 549 KiB

Open AccessArticle

Factors Associated with Delirium in COVID-19 Patients and Their Outcome: A Single-Center Cohort Study

by Annabella Di Giorgio, Antonio Mirijello, Clara De Gennaro, Andrea Fontana, Paolo Emilio Alboini, Lucia Florio, Vincenzo Inchingolo, Michele Zarrelli, Giuseppe Miscio, Pamela Raggi, Carmen Marciano, Annibale Antonioni, Salvatore De Cosmo, Filippo Aucella, Antonio Greco, Massimo Carella, Massimiliano Copetti and Maurizio A. Leone

Diagnostics 2022, 12(2), 544; https://doi.org/10.3390/diagnostics12020544 - 20 Feb 2022

Cited by 5 | Viewed by 2388

Abstract

Background: A significant proportion of patients with coronavirus disease 2019 (COVID-19) suffer from delirium during hospitalization. This single-center observational study investigates the occurrence of delirium, the associated risk factors and its impact on in-hospital mortality in an Italian cohort of COVID 19 inpatients. Methods: Data were collected in the COVID units of a general medical hospital in the South of Italy. Socio-demographic, clinical and pharmacological features were collected. Diagnosis of delirium was based on a two-step approach according to 4AT criteria and DSM5 criteria. Outcomes were: dates of hospital discharge, Intensive Care Unit (ICU) admission, or death, whichever came first. Univariable and multivariable proportional hazards Cox regression models were estimated, and risks were reported as hazard ratios (HR) along with their 95% confidence intervals (95% CI). Results: A total of 47/214 patients (22%) were diagnosed with delirium (21 hypoactive, 15 hyperactive, and 11 mixed). In the multivariable model, four independent variables were independently associated with the presence of delirium: dementia, followed by age at admission, C-reactive protein (CRP), and Glasgow Coma Scale. In turn, delirium was the strongest independent predictor of death/admission to ICU (composite outcome), followed by Charlson Index (not including dementia), CRP, and neutrophil-to-lymphocyte ratio. The probability of reaching the composite outcome was higher for patients with the hypoactive subtype than for those with the hyperactive subtype. Conclusions: Delirium was the strongest predictor of poor outcome in COVID-19 patients, especially in the hypoactive subtype. Several clinical features and inflammatory markers were associated with the increased risk of its occurrence. The early recognition of these factors may help clinicians to select patients who would benefit from both non-pharmacological and pharmacological interventions in order to prevent delirium, and in turn, reduce the risk of admission to ICU or death. Full article

(This article belongs to the Special Issue Biomarkers for Predicting Treatment Response and Guiding Therapy in COVID-19 Patients)

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13 pages, 625 KiB

Open AccessArticle

Analysis of Early Biomarkers Associated with the Development of Critical Respiratory Failure in Coronavirus Disease 2019 (COVID-19)

by Hiroyoshi Yamada, Masaki Okamoto, Yoji Nagasaki, Suzuyo Yoshio, Takashi Nouno, Chiyo Yano, Tomohiro Tanaka, Fumi Watanabe, Natsuko Shibata, Yoko Arimizu, Yukako Fukamachi, Yoshiaki Zaizen, Naoki Hamada, Atsushi Kawaguchi, Tomoaki Hoshino and Shigeki Morita

Diagnostics 2022, 12(2), 339; https://doi.org/10.3390/diagnostics12020339 - 28 Jan 2022

Cited by 5 | Viewed by 2501

Abstract

Certain biomarkers predict death due to acute respiratory distress syndrome in COVID-19 patients. We retrospectively analyzed biomarkers associated with time to mechanical ventilation for respiratory failure due to COVID-19 (time-to-mechanical ventilation) in 135 consecutive patients in our hospital. We analyzed biomarkers that were elevated immediately (at admission) and later (3 days after admission) using Cox proportional hazards regression analysis. Independent biomarkers of time-to-mechanical ventilation were high C-reactive protein (CRP), interleukin (IL)-6, and Krebs von den Lungen-6 (KL-6) concentrations at admission and elevated CRP, high-mobility group box-1 protein (HMGB-1), and d-dimer levels and low platelets 3 days after admission. Receiver operating characteristic analysis for detecting the association between independent biomarkers associated with time-to-event in multivariate analyses and the start of mechanical ventilation revealed that these biomarkers had area under the curve values higher than 0.700. The present study suggests that CRP was the only biomarker associated with time-to-mechanical ventilation both at admission and 3 days after admission. Moreover, IL-6 (an inflammatory cytokine), HMGB-1 (a late inflammatory mediator), and KL-6 (reflecting injury and/or remodeling of type II pneumocytes) were associated with outcomes in COVID-19 as reported previously. In conclusion, increased CRP, IL-6, KL-6, HMGB-1, and d-dimer levels and decreased platelet counts were associated with the start of mechanical ventilation due to COVID-19. Full article

(This article belongs to the Special Issue Biomarkers for Predicting Treatment Response and Guiding Therapy in COVID-19 Patients)

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11 pages, 1573 KiB

Open AccessArticle

Early Routine Biomarkers of SARS-CoV-2 Morbidity and Mortality: Outcomes from an Emergency Section

by Flavio Maria Ceci, Marco Fiore, Francesca Gavaruzzi, Antonio Angeloni, Marco Lucarelli, Carolina Scagnolari, Enea Bonci, Francesca Gabanella, Maria Grazia Di Certo, Christian Barbato, Carla Petrella, Antonio Greco, Marco De Vincentiis, Massimo Ralli, Claudio Passananti, Roberto Poscia, Antonio Minni, Mauro Ceccanti, Luigi Tarani and Giampiero Ferraguti

Diagnostics 2022, 12(1), 176; https://doi.org/10.3390/diagnostics12010176 - 12 Jan 2022

Cited by 18 | Viewed by 2398

Abstract

Background. COVID-19 is a severe acute respiratory disease caused by SARS-CoV-2, a virus belonging to the Coronaviridae family. This disease has spread rapidly around the world and soon became an international public health emergency leading to an unpredicted pressure on the hospital emergency units. Early routine blood biomarkers could be key predicting factors of COVID-19 morbidity and mortality as suggested for C-reactive protein (CRP), IL-6, prothrombin and D-dimer. This study aims to identify other early routine blood biomarkers for COVID-19 severity prediction disclosed directly into the emergency section. Methods. Our research was conducted on 156 COVID-19 patients hospitalized at the Sapienza University Hospital “Policlinico Umberto I” of Rome, Italy, between March 2020 and April 2020 during the paroxysm’s initial phase of the pandemic. In this retrospective study, patients were divided into three groups according to their outcome: (1) emergency group (patients who entered the emergency room and were discharged shortly after because they did not show severe symptoms); (2) intensive care unit (ICU) group (patients who attended the ICU after admission to the emergency unit); (3) the deceased group (patients with a fatal outcome who attended the emergency and, afterward, the ICU units). Routine laboratory tests from medical records were collected when patients were admitted to the emergency unit. We focused on Aspartate transaminase (AST), Alanine transaminase (ALT), Lactate dehydrogenase (LDH), Creatine kinase (CK), Myoglobin (MGB), Ferritin, CRP, and D-dimer. Results. As expected, ANOVA data show an age morbidity increase in both ICU and deceased groups compared with the emergency group. A main effect of morbidity was revealed by ANOVA for all the analyzed parameters with an elevation between the emergency group and the deceased group. Furthermore, a significant increase in LDH, Ferritin, CRP, and D-dimer was also observed between the ICU group and the emergency group and between the deceased group and ICU group. Receiver operating characteristic (ROC) analyses confirmed and extended these findings. Conclusions. This study suggests that the contemporaneous presence of high levels of LDH, Ferritin, and as expected, CRP, and D-dimer could be considered as potential predictors of COVID-19 severity and death. Full article

(This article belongs to the Special Issue Biomarkers for Predicting Treatment Response and Guiding Therapy in COVID-19 Patients)

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12 pages, 14152 KiB

Open AccessArticle

Sequential Organ Failure Assessment Outperforms Quantitative Chest CT Imaging Parameters for Mortality Prediction in COVID-19 ARDS

by Daniel Puhr-Westerheide, Jakob Reich, Bastian O. Sabel, Wolfgang G. Kunz, Matthias P. Fabritius, Paul Reidler, Johannes Rübenthaler, Michael Ingrisch, Dietmar Wassilowsky, Michael Irlbeck, Jens Ricke and Eva Gresser

Diagnostics 2022, 12(1), 10; https://doi.org/10.3390/diagnostics12010010 - 22 Dec 2021

Cited by 4 | Viewed by 2367

Abstract

(1) Background: Respiratory insufficiency with acute respiratory distress syndrome (ARDS) and multi-organ dysfunction leads to high mortality in COVID-19 patients. In times of limited intensive care unit (ICU) resources, chest CTs became an important tool for the assessment of lung involvement and for patient triage despite uncertainties about the predictive diagnostic value. This study evaluated chest CT-based imaging parameters for their potential to predict in-hospital mortality compared to clinical scores. (2) Methods: 89 COVID-19 ICU ARDS patients requiring mechanical ventilation or continuous positive airway pressure mask ventilation were included in this single center retrospective study. AI-based lung injury assessment and measurements indicating pulmonary hypertension (PA-to-AA ratio) on admission CT, oxygenation indices, lung compliance and sequential organ failure assessment (SOFA) scores on ICU admission were assessed for their diagnostic performance to predict in-hospital mortality. (3) Results: CT severity scores and PA-to-AA ratios were not significantly associated with in-hospital mortality, whereas the SOFA score showed a significant association (p < 0.001). In ROC analysis, the SOFA score resulted in an area under the curve (AUC) for in-hospital mortality of 0.74 (95%-CI 0.63–0.85), whereas CT severity scores (0.53, 95%-CI 0.40–0.67) and PA-to-AA ratios (0.46, 95%-CI 0.34–0.58) did not yield sufficient AUCs. These results were consistent for the subgroup of more critically ill patients with moderate and severe ARDS on admission (oxygenation index <200, n = 53) with an AUC for SOFA score of 0.77 (95%-CI 0.64–0.89), compared to 0.55 (95%-CI 0.39–0.72) for CT severity scores and 0.51 (95%-CI 0.35–0.67) for PA-to-AA ratios. (4) Conclusions: Severe COVID-19 disease is not limited to lung (vessel) injury but leads to a multi-organ involvement. The findings of this study suggest that risk stratification should not solely be based on chest CT parameters but needs to include multi-organ failure assessment for COVID-19 ICU ARDS patients for optimized future patient management and resource allocation. Full article

(This article belongs to the Special Issue Biomarkers for Predicting Treatment Response and Guiding Therapy in COVID-19 Patients)

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13 pages, 3949 KiB

Open AccessArticle

Urinary SARS-CoV-2 RNA Is an Indicator for the Progression and Prognosis of COVID-19

by Lu Zhang, Maoqing Tian, Yuan Song, Wei Liang, Xiaogang Li, Yongqing Tong and Huiming Wang

Diagnostics 2021, 11(11), 2089; https://doi.org/10.3390/diagnostics11112089 - 12 Nov 2021

Cited by 3 | Viewed by 2981

Abstract

Background: We aimed to analyze clinical characteristics and find potential factors to predict poor prognosis in patients with coronavirus disease 2019 (COVID-19). Methods: We analyzed the clinical characteristics and laboratory tests of COVID-19 patients and detected SARS-CoV-2 RNA in urine sediments collected from 53 COVID-19 patients enrolled in Renmin Hospital of Wuhan University from 31 January 2020 to 18 February 2020 with qRT-PCR analysis. Then, we classified those patients based on clinical conditions (severe or non-severe syndrome) and urinary SARS-CoV-2 RNA (U_RNA⁻ or U_RNA⁺). Results: We found that COVID-19 patients with severe syndrome (severe patients) showed significantly higher positive rate (11 of 23, 47.8%) of urinary SARS-CoV-2 RNA than non-severe patients (4 of 30, 13.3%, p = 0.006). U_RNA⁺ patients or severe U_RNA⁺ subgroup exhibited higher prevalence of inflammation and immune discord, cardiovascular diseases, liver damage and renal dysfunction, and higher risk of death than U_RNA⁻ patients. To understand the potential mechanisms underlying the viral urine shedding, we performed renal histopathological analysis on postmortems of patients with COVID-19 and found severe renal vascular endothelium lesion characterized by an increase of the expression of thrombomodulin and von Willebrand factor, markers to assess the endothelium dysfunction. We proposed a theoretical and mathematic model to depict the potential factors that determine the urine shedding of SARS-CoV-2. Conclusions: This study indicated that urinary SARS-CoV-2 RNA detected in urine specimens can be used to predict the progression and prognosis of COVID-19 severity. Full article

(This article belongs to the Special Issue Biomarkers for Predicting Treatment Response and Guiding Therapy in COVID-19 Patients)

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10 pages, 1016 KiB

Open AccessArticle

The Value of Interleukin-6 among Several Inflammatory Markers as a Predictor of Respiratory Failure in COVID-19 Patients

by Mitsuhiro Fujino, Michiyo Ishii, Takuya Taniguchi, Hiroya Chiba, Masaki Kimata and Masahito Hitosugi

Diagnostics 2021, 11(8), 1327; https://doi.org/10.3390/diagnostics11081327 - 23 Jul 2021

Cited by 8 | Viewed by 1656

Abstract

Patients with coronavirus disease 2019 (COVID-19) develop severe respiratory failure within a short period during the clinical course. It is essential to predict respiratory deterioration in the short term. We investigated the use of inflammatory markers to predict respiratory distress within three days from their analysis in COVID-19 patients. This retrospective observational study included 81 patients admitted with COVID-19. Patients were divided into two groups according to whether the maximum fraction of inspired oxygen (FiO₂) for three days from the blood marker measurements was ≥0.4 (high FiO₂ group; HFG) or <0.4 (low FiO₂ group; LFG). Interleukin-6 (IL-6), C-reactive protein (CRP), lactate dehydrogenase (LDH), white blood cell, D-dimer, and creatinine levels were compared between the two groups. The levels of all markers were significantly higher in HFG patients. Areas under the receiver operating characteristic curve of IL-6, CRP, and LDH had high values of 0.85, 0.82, and 0.81, respectively. The odds ratio of IL-6 which was crude and adjusted for dexamethasone administration initiated before laboratory measurement, showed the high value of 29.1 (5.6–295.6) and 53.9 (4.5–3242.8), respectively. IL-6 can be used as a reliable marker for predicting respiratory illness within three days after assessment. Full article

(This article belongs to the Special Issue Biomarkers for Predicting Treatment Response and Guiding Therapy in COVID-19 Patients)

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9 pages, 2080 KiB

Open AccessArticle

Evaluation of Anti-SARS-Cov-2 S-RBD IgG Antibodies after COVID-19 mRNA BNT162b2 Vaccine

by Bruna Lo Sasso, Rosaria Vincenza Giglio, Matteo Vidali, Concetta Scazzone, Giulia Bivona, Caterina Maria Gambino, Anna Maria Ciaccio, Luisa Agnello and Marcello Ciaccio

Diagnostics 2021, 11(7), 1135; https://doi.org/10.3390/diagnostics11071135 - 22 Jun 2021

Cited by 65 | Viewed by 9424

Abstract

(1) Background: The evaluation of anti-spike protein receptor-binding domain (S-RBD) antibodies represents a useful tool to estimate the individual protection against Severe Acute Respiratory Syndrome CoronaVirus 2 (SARS-CoV-2) infection; (2) Methods: We evaluated anti S-RBD IgG levels by indirect chemiluminescence immunoassay on Maglumi 800 (SNIBE, California) in 2248 vaccinated subjects without previous SARS-CoV-2 infection, 91 vaccinated individuals recovered from COVID-19, and 268 individuals recovered from COVID-19 who had not been vaccinated. Among those who were healthy and vaccinated, 352 subjects performed a re-dosing after about 72 days from the first measurement. (3) Results: Anti S-RBD IgG levels were lower in subjects with previous infection than vaccinated subjects, with or without previous infection (p < 0.001). No difference was observed between vaccinated subjects, with and without previous SARS-CoV-2 infection. Overall, anti-RBD IgG levels were higher in females than males (2110 vs. 1341 BAU/mL; p < 0.001) as well as in subjects with symptoms after vaccination than asymptomatic ones (2085 vs. 1332 BAU/mL; p = 0.001) and lower in older than younger subjects. Finally, a significant decrease in anti-RBD IgG levels was observed within a short period from a complete two-dose cycle vaccination. (4) Conclusions: Our results show an efficacy antibody response after vaccination with age-, time- and sex-related differences. Full article

(This article belongs to the Special Issue Biomarkers for Predicting Treatment Response and Guiding Therapy in COVID-19 Patients)

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Review

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14 pages, 277 KiB

Open AccessReview

The Potential of Lung Epithelium Specific Proteins as Biomarkers for COVID-19-Associated Lung Injury

by Sultan Almuntashiri, Chelsea James, Xiaoyun Wang, Budder Siddiqui and Duo Zhang

Diagnostics 2021, 11(9), 1643; https://doi.org/10.3390/diagnostics11091643 - 08 Sep 2021

Cited by 10 | Viewed by 2225

Abstract

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection was first reported in Wuhan, China, and was declared a pandemic by the World Health Organization (WHO) on 20 March 2020. The respiratory system is the major organ system affected by COVID-19. Numerous studies have found lung abnormalities in patients with COVID-19, including shortness of breath, respiratory failure, and acute respiratory distress syndrome. The identification of lung-specific biomarkers that are easily measurable in serum would be valuable for both clinicians and patients with such conditions. This review is focused on the pneumoproteins and their potential to serve as biomarkers for COVID-19-associated lung injury, including Krebs von den Lungen-6 (KL-6), surfactant proteins (SP-A, SP-B, SP-C, SP-D), and Clara cell secretory protein (CC16). The current findings indicate the aforementioned pneumoproteins may reflect the severity of pulmonary manifestations and could serve as potential biomarkers in COVID-19-related lung injury. Full article

(This article belongs to the Special Issue Biomarkers for Predicting Treatment Response and Guiding Therapy in COVID-19 Patients)

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