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Review

Microbiological and Clinical Findings of SARS-CoV-2 Infection after 2 Years of Pandemic: From Lung to Gut Microbiota

by
Alessandro Russo
1,*,
Francesca Serapide
1,
Angela Quirino
2,
Maria Grazia Tarsitano
3,
Nadia Marascio
2,
Riccardo Serraino
1,
Salvatore Rotundo
1,
Giovanni Matera
2,
Enrico Maria Trecarichi
1 and
Carlo Torti
1
1
Infectious and Tropical Disease Unit, Department of Medical and Surgical Sciences, “Magna Graecia” University of Catanzaro, 88100 Catanzaro, Italy
2
Clinical Microbiology Unit, Department of Health Sciences, “Magna Graecia” University of Catanzaro, 88100 Catanzaro, Italy
3
Research Center for the Prevention and Treatment of Metabolic Diseases, “Magna Graecia” University of Catanzaro, 88100 Catanzaro, Italy
*
Author to whom correspondence should be addressed.
Diagnostics 2022, 12(9), 2143; https://0-doi-org.brum.beds.ac.uk/10.3390/diagnostics12092143
Submission received: 21 July 2022 / Revised: 29 August 2022 / Accepted: 2 September 2022 / Published: 2 September 2022
(This article belongs to the Special Issue Multidisciplinary Approaches to Manage COVID-19: From Surveillance to Diagnosis)
Browse Figure
Review Reports Versions Notes

Abstract

:
Early recognition and prompt management are crucial for improving survival in COVID-19 patients, and after 2 years of the pandemic, many efforts have been made to obtain an early diagnosis. A key factor is the use of fast microbiological techniques, considering also that COVID-19 patients may show no peculiar signs and symptoms that may differentiate COVID-19 from other infective or non-infective diseases. These techniques were developed to promptly identify SARS-CoV-2 infection and to prevent viral spread and transmission. However, recent data about clinical, radiological and laboratory features of COVID-19 at time of hospitalization could help physicians in early suspicion of SARS-CoV-2 infection and distinguishing it from other etiologies. The knowledge of clinical features and microbiological techniques will be crucial in the next years when the endemic circulation of SARS-CoV-2 will be probably associated with clusters of infection. In this review we provide a state of the art about new advances in microbiological and clinical findings of SARS-CoV-2 infection in hospitalized patients with a focus on pulmonary and extrapulmonary characteristics, including the role of gut microbiota.

1. Introduction

Because of the pandemic caused by severe acute respiratory coronavirus-2 (SARS-CoV-2), the clinical understanding of the coronavirus disease 2019 (COVID-19) in humans remains to be further deepened [1,2]. As a matter of fact, early recognition and prompt management of hospitalized patients are crucial for improving survival, but COVID-19 infection may have not peculiar signs and symptoms that can differentiate this infection from other infective or non-infective causes of acute respiratory failure and/or fever [3].
In the last few months, a huge number of experiences have been published but despite this, much information about COVID-19 is still missing. Currently, all patients admitted to the emergency department with acute respiratory failure and/or fever should be considered as a suspected SARS-CoV-2 infection [4,5]. Of importance, the new multiplex molecular assays are able to screen samples from the respiratory tract for multiple pathogens simultaneously, using the syndromic approach. Moreover, in the last two years of the SARS-CoV-2 pandemic, the use of COVID-19 vaccines has deeply modified the natural evolution of this disease and its progression to severe pneumonia.
The main objective of this review is to describe new advances in clinical and laboratory findings of hospitalized patients with suspected COVID-19. An early diagnosis should be the milestone for prompt management of hospitalized COVID-19 patients to identify those that are candidates for an early administration of antiviral agents and/or monoclonal antibodies (MoAbs) in the first stages of the disease.
Based on the above, an early microbiological and clinical diagnosis of hospitalized patients with suspected COVID-19 is crucial for improving survival; moreover, the knowledge of pulmonary and extrapulmonary characteristics of patients is mandatory for managing and treating COVID-19 patients. Recent data showed that SARS-CoV-2 has a direct effect on gut microbiota. This interaction could induce a pro-inflammatory state and an alteration of amino acid transport with excessive gut permeability and microbial translocation.

2. Methods

The literature research was conducted using the well-established PubMed database. Case series, controlled and uncontrolled studies and meta-analyses were included. Case reports were also included. Only English-language papers were considered. We did not set a specific time window for the research, but the focus was placed on papers published in the last 2 years. The main keywords used were “SARS-CoV-2”, “COVID-19”, “microbiological diagnosis”, “clinical diagnosis”, “RT-PCR”, “fever”, “acute respiratory failure”, “mortality”, “gut microbiota” and “suspected COVID-19”.
In the first step, papers were screened by abstract and title. Then, the full text of the selected papers was examined. Papers were excluded if their content had nothing to do with COVID-19 pathophysiology, microbiological and/or clinical diagnosis. However, an important limitation of this review is that were no applied criteria for a systematic review of the literature.

3. New Advances in Microbiological Diagnosis of SARS-CoV-2 Infection

Since January 2020, several techniques have been developed to perform the correct diagnosis of SARS-CoV-2 infection [6]. The routine methods include molecular assay by real-time polymerase chain reaction (RT-PCR), to detect SARS-CoV-2 RNA in biological samples, and serological tests, to evaluate the concentration of IgM, IgG and IgA antibodies.
Even if several methods are being developed to detect SARS-CoV-2 in biological samples, such as reverse transcription loop-mediated isothermal amplification (RT-LAMP), clustered regularly interspaced short palindromic repeats (CRISPR) and droplet digital reverse transcription polymerase chain reaction (ddRT-PCR) [7], the RT-PCR is currently the gold standard for detecting the new virus from nasopharyngeal, oropharyngeal and nasal swabs and saliva. Among PCR-based methods, syndromic tests are frequently used for patients who exhibit more than one respiratory symptom to improve diagnosis and clinical management and to monitor possible respiratory co-infections [8]. However, molecular assays are not able to perform mass population screening. On the contrary, serological tests can be used to monitor antibody responses in individuals who received the SARS-CoV-2 vaccine and those who had a natural infection in a large cohort of the population [9].
Currently, to prevent viral spread and transmission, antigen tests appear as a very valuable tool to reach early and rapid detection of SARS-CoV-2, considering that therapies using new antiviral treatment could be started promptly within five days from symptom onset [10]. A limitation of these rapid tests is the possibility of obtaining a negative result in patients with low viral loads and infected by new SARS-CoV-2 variants. Despite the wide availability of diagnostic tests, the sensitivity is related to the cycle threshold (Ct) value regardless of vaccine status and/or symptoms. All negative results must be verified using molecular assay [11].
Serological and molecular assays may differ in sensitivity and specificity. Sensitivity is defined as the ability to detect very low SARS-CoV-2 viral loads or antibody titers accurately measured [8,12]. Specificity stands for the capacity to identify the specific SARS-CoV-2 genomic regions or IgA, IgM and IgG against the current pandemic pathogen without cross-reactions.
A summary of multiple approaches and their performances was reported in Table 1. “In-house” and non-certified diagnostic tests were excluded.
Very close to diagnostic methods, sequencing of the SARS-CoV-2 genome helps in understanding the pathogenicity and transmissibility of variants of concern (VOCs) and variants of interest (VOI) [13]. Indeed, alpha (B.1.1.7), beta (B.1.351), delta (B.1.617.2), gamma (P.1) and omicron (B.1.1.529) VOCs were related to an increase in transmissibility, severe diseases and reduced vaccine efficacy, while lambda (C.37) and mu (B.1.621) VOIs showed a reduced antibody neutralization and increased transmissibility of infection [14,15]. To date, omicron is becoming the more prevalent VOC worldwide; it is phylogenetically distinct from any known variants, and it is classified in several sublineages, BA.1, BA.2, BA.3, BA.4 and BA.5 [16].
The epidemiology of SARS-CoV-2 variants is continuously evolving, next-generation sequencing (NGS) and Sanger methods were applied to monitor the spread and viral evolution [17]. Sequencing of the whole genome or specific genomic regions, such as the S gene, is the only way to identify known and unknown variants highlighting a pattern of mutations [18]. Even if the NGS approach is expensive and not available in all diagnostic laboratories, it may detect mutations in several genomic regions affecting rapid antigen test results. The undetected variants can carry out deletion or substitutions in N-protein [19]. Additionally, rapid genotyping is useful for improving the prophylaxis with MoAbs of patients infected by SARS-CoV-2 viral variants [16]. Currently, the Stanford Coronavirus Resistance Database, an interactive tool that shows the neutralizing susceptibility information comparing SARS-CoV-2 sequences, is available for this purpose [20].

4. Clinical Diagnosis of COVID-19

Data from the literature highlighted peculiar characteristics associated with SARS-CoV-2 etiology in suspected COVID-19 patients in the emergency department: a prompt identification of specific clinical characteristics (such as acute dyspnea, dry cough and/or duration of fever >3 days), and laboratory findings (such as lymphocytopenia and serum ferritin) can help physicians to distinguish between COVID-19 and other etiologies [21].
As previously reported, the application of a standard approach to the management of patients with acute respiratory failure and/or fever [5,22] associated with the knowledge of clinical and laboratory characteristics of COVID-19 can drive physicians to early therapeutic choices. Of importance, data confirmed that age ≥ 65 years and intensive care unit (ICU) admission are independently associated with all-cause 30-day mortality [3,4], while the use of steroids, low-molecular-weight heparin (LMWH), MoAbs and antiviral agents (such as molnupiravir, remdesivir or nirmatrelvir/ritonavir) were associated with lower rates of hospitalization and mortality [23,24].
Of interest, data from a large cohort of patients in Moscow [25] showed that typical fever, fatigue, cough and shortness of breath were the most frequent symptoms observed in suspected COVID-19 patients, in agreement with other studies in other countries [26,27]. However, it had been highlighted that every variant of the virus was selected during the different epidemic waves. These variants were characterized by changes in several viral proteins, reducing the efficacy of treatments such as MoAbs, and also a potential increase in disease severity and/or transmissibility or different clinical manifestations [28]. The WHO differentiated the novel SARS-CoV-2 strains in VOIs and VOCs. Of importance, VOCs were associated with a reduced susceptibility to the MoAbs and vaccination; interestingly, omicron VOC showed a higher transmissibility and a higher risk of re-infection, as reported below [29].
Regarding the clinical characteristics of COVID-19 patients, fever, fatigue, dry cough, dyspnea, myalgia, breathlessness and/or severe acute distress respiratory syndrome have been recognized as the most frequent in the first stages of the disease. However, the spreading of new VOCs, such as omicron, determined different clinical conditions involving mainly the upper respiratory tract [30]. This could be related to specific mutations that cause a modification in the viral interaction sites prevalently located in the upper airways [31]. In fact, some studies show how the omicron variant mainly replicates more rapidly in the bronchi than in the lung parenchyma [32] and how it replicates less in the lower airway tract compared to the delta variant [33]. Some studies on populations affected by the omicron variant highlighted how symptoms were characterized by a more moderate clinical presentation than the population affected by other variants of SARS-CoV-2 (dry cough, headache, asthenia and dyspnea), and lower respiratory airways are involved less frequently. These data were also confirmed by the lower rate of hospitalization, recovery in an intensive setting, the need for invasive and non-invasive mechanical ventilation and mortality during hospitalization compared to patients affected by different variants of SARS-CoV-2 [34,35].
It is important to underline, however, how these data may be affected by the greater vaccination coverage of the population compared to previous waves in which the vaccination campaign was still ongoing. In fact, in the group of patients with a complete vaccination course, a lower rate of need for non-invasive ventilation was observed, and stratifying by age, there were no statistically significant differences [34]. This, therefore, confirms the need to continue the vaccination campaign, despite a less severe clinical presentation related to omicron VOC.
Another important aspect to consider is re-infections; it was shown that the emergence of the omicron variant, and more recently the omicron-2 variant, is associated with several cases of re-infection that occurred even in vaccinated subjects. Re-infection is defined as follows: (1) persons with at least one detection of SARS-CoV-2 test, more than 90 days after the first detection of SARS-CoV-2, whether or not symptoms were present, and (2) persons with COVID-19-like symptoms and detection of SARS-CoV-2 RNA. Currently, poor data are available and highlighted as a majority of re-infected patients are asymptomatic or paucisymptomatic (resumption of respiratory or gastrointestinal symptoms) [36,37]. Hospitalization was required only in some cases at the time of re-infection, but this condition was mainly necessary for complications related to multiple comorbidities, such as diabetes mellitus, immunodeficiency or iatrogenic immunosuppression, as well as the age of patients rather than COVID-19-related symptoms [38,39]. In a subgroup analysis, it was found that the prevalence of re-infection is higher in male than in female subjects.
Of interest, recurrence or reactivation is defined as the manifestation of symptoms after hospitalization and refers to an infection of the same species and strain of SARS-CoV-2 that can occur due to host immunodeficiency [40]. As reported for re-infections, most patients with reactivation are asymptomatic or paucisymptomatic with comorbidities including diabetes mellitus, hypertension, chronic pulmonary disease and cardiovascular disease. Of importance, these underlying diseases may confuse the differential diagnosis of COVID-19 patients from other diseases, based only on clinical symptoms. Therefore, it is important to better understand information about the prevalence, risk factors, comorbidities and anamnestic data of the patient as they allow orienting the clinician toward the risk of re-infection or reactivation or the related risk for hospitalization.
An important aspect of SARS-CoV-2 is related to laboratory alterations. The most common laboratory test alterations are as follows: lymphocytopenia, increase in transaminases, C-reactive protein, interleukin-6 (IL-6), CPK, LDH, prothrombin time, ferritin, creatinine and D-dimer. Of importance, in the pediatric population, a reduction in lymphocyte counts is reported in about 16% of cases [41], while alteration of CK-MB values is reported in 37% of cases; out of these, over 80% of these alterations were observed in children <1 year of age. This evidence may suggest greater attention to myocardial damage in the pediatric population, especially in children <1 year of age. Of importance, children may develop severe inflammatory syndrome, with symptoms similar to Kawasaki disease or toxic shock syndrome. This condition is called multisystem inflammatory syndrome in children (MIS-C) [42].
Lymphocytopenia has been previously reported to be associated with higher severity and mortality in COVID-19 patients [43,44]. Of interest, data from an Italian cohort demonstrated that ferritin levels over the 25th percentile are associated with a more severe pulmonary involvement, independently of age and gender [45].
As a matter of fact, CT findings in COVID-19 patients were frequently indistinguishable from other etiologies, such as acute heart failure, bacterial pneumonia or pulmonary embolism [5,21]. Considering typical radiological findings in COVID-19, it is important to underline that this population, especially in the first stage, could present only extrapulmonary manifestations with a normal CT finding [46]. In this scenario, it is important to underline that a negative RT-PCR test result does not exclude the possibility of COVID-19, and repeated testing and sampling were shown to improve the sensitivity of RT-PCR [47]. Thus, a rigorous application of a standard approach to the management of suspected COVID-19, associated with clinical and laboratory findings, could help physicians in the emergency department.
Finally, a peculiar aspect of COVID-19 patients from the “second wave” of the pandemic was the widespread use of steroids, LMWH and remdesivir that could have modified the outcomes of this population [48]. A meta-analysis including seven RCTs [49,50,51,52,53,54] showed that the use of corticosteroids compared with usual care or placebo lowered the 28-day all-cause mortality [55], especially in patients receiving invasive mechanical ventilation [56,57]. Conversely, in patients with mild COVID-19, steroid treatment was associated with a worse clinical outcome [58], a higher risk of progression to severe disease and a prolonged hospital stay [59], highlighting the main role of steroid treatment prevalently in moderate to severe COVID-19. Important observations were reported about the role of LMWH in the survival of COVID-19 patients, especially in reducing thromboembolism complications in critically ill patients [60]. Of interest, different data were reported about worldwide the efficacy of remdesivir, taking into account different outcomes [61,62]. These data showed an important role for remdesivir in the early stage of the disease, to reduce progression to severe pneumonia.
A proposed system of management for patients with suspected COVID-19 at hospital admission is reported in Figure 1.

5. Extrapulmonary Manifestations and the Role of Gut Microbiota in COVID-19

Extrapulmonary manifestations can often occur prior to respiratory symptoms and could represent an important indicator for early clinical suspicion of COVID-19 [63]. Among these are included a broad spectrum of disorders with gastrointestinal, neurological, coagulation, renal, endothelial, cardiovascular and hepatobiliary involvement that are associated with increased mortality risk and prolonged hospitalization. Extrapulmonary damage may be associated with direct viral damage, cytokine cascade induced by systemic inflammatory response or endothelial damage [64].
Cardiovascular complications can occur in patients with heart failure or coronary artery disease. One of the most common is myocarditis that may be characterized by myocardial damage in the absence of ischemic causes and inflammatory infiltrates [65,66]. In almost a third of COVID-19 patients with myocardial involvement, cardiogenic shock occurred [67] with a mortality of about 26% [68]. In addition, COVID-19 patients have a high risk of arterial and venous thrombosis [69].
Other manifestations can involve other districts. Kidney damage is a frequent complication in hospitalized patients with COVID-19 with an incidence range between 10 and 80% and a significantly increased risk of intra-hospital mortality [70,71]. Neurological symptoms occur most commonly in patients with severe forms of COVID-19 [72,73]. COVID-19 is reported to be associated with an increased risk of mental disorders such as depression, anxiety, schizophrenia, phobia, obsessive–compulsive disorder and post-traumatic stress disorder. Loss of smell and taste was observed in 40% of COVID-19 patients [74]. A European multicenter study reported that about 12% of patients had ageusia and anosmia as early symptoms [75]. Ocular manifestations are often non-specific, and conjunctivitis, mainly manifested as redness, watering, discharge and foreign body sensations, is the most frequently reported; other ocular complications include dry eye, blurred vision, ocular pain, photophobia and itchiness [76]. Notably, ocular signs and symptoms were the initial presentations in 3.3% of COVID-19 patients [76]. Dermatological manifestations have been observed in 2–20% of patients [77,78]. The most common manifestations are maculopapular rash, urticaria, petechiae/purpura, blisters, chilblains, livedo racemose, and necrosis or distal ischemia [79]. Most of these skin lesions are self-limiting and do not appear to be associated with the severity of the disease.
Several COVID-19 patients present gastrointestinal symptoms, principally vomiting and diarrhea, and the severity rate was more than 40% in these patients [80]. The presence of gastrointestinal symptoms is associated with a more severe disease. It has been shown that the presence of nausea, vomiting, diarrhea and abdominal pain can precede or accompany the classic respiratory symptoms with an incidence between 10 and 60% [81]. This is relevant, as 10% of patients initially present only gastrointestinal symptoms without any respiratory symptoms, resulting in a possible delay in the diagnosis of COVID-19 [82]. In a meta-analysis of Cheung et al. that included 60 studies and 4243 patients, the three most common symptoms were anorexia, diarrhea, and nausea or vomiting [83]. The presence of such symptoms was associated with a high risk of ARDS, the need for non-invasive ventilation and orotracheal intubation, but not mortality [84]. Of importance, the prevalence of liver damage is around 15–55% [85,86], with an incidence rate of liver damage in deceased patients of 78%. Alteration of AST values shows a strong correlation with mortality compared to other liver damage indices such as ALT, TBIL and ALP [87,88]. Kaafarani et al. observed that of 141 critically ill patients, during hospitalization in intensive care, 4% developed acalculous cholecystitis and 1% developed pancreatitis [83,89].
Data show an important role of gut microbiota in COVID-19 patients [87]. Correlation between the immune system and gut microbiota has been demonstrated in germ-free mice, which presented a deficiency in regulatory T cells [90]. Recent studies make it evident that gut microbiota can modulate neutrophil migration and T-cell differentiation in subpopulations [91]. Viral infections change gut microbiota: reduction in lactobacilli and firmicutes leads to a dysbiosis that drives a dysfunction of the normal role of microbiota [92]. Angiotensin-converting enzyme 2 receptor is well represented in the intestinal tract [93] and acts as a functional receptor for SARS-CoV-2 [94]. This interaction could induce a pro-inflammatory state and an alteration of amino acid transport with excessive gut permeability and microbial translocation [80,95].
Of importance, probiotic supplementation is also recognized as an important therapeutic strategy in COVID-19 patients. Probiotic supplementation can maintain the enterocytic barrier [96]. In an open-label parallel-group trial, in a single center, by d’Ettorre et al., a probiotic multistrain modulation (streptococcus and lactobacillus) administration (2.4 × 10⁶ UFC/day for 14 days) in adjunction to standard therapy reduced gastrointestinal symptoms, mortality and intensive care unit transfer in hospitalized COVID-19 patients [97]. It is important to underline that a correct state of gut microbiota promotes reduced inflammation, and thus a better prognosis for the patient [98]. Thus, probiotic supplementation could have a beneficial role in COVID-19 patients with gastrointestinal symptoms. The limited expenditure for the treatment is a further factor to consider [97]. The most common strains commercially available belong to the Lactobacillus and Bifidobacterium species, which proved some beneficial effects on the human body when administered in adequate amounts. These mentioned bacterial species are known to be involved in some essential physiological functions such as stimulation of immune response, prevention of pathogenic and opportunistic microbial colonization, production of SCFA, catabolism of carcinogenic substances and synthesis of vitamins such as B and K. Thus, as part of post-acute COVID-19 syndrome, the dysbiosis of the gut microbiota could potentially become a target for evaluation of the state of health and consequentially for targeted intervention.
Immune-modulatory effects of probiotics might be relevant to preventing complications of COVID-19. The dysbiosis in COVID-19 patients may play a relevant role in determining the course of the disease by increasing systemic pro-inflammatory cytokine production. Microbiota could have therapeutic properties by reducing gastrointestinal symptoms. Although the underlying mechanism for the observed dysbiosis is unclear, it might happen via downregulation of ACE2 expression that alleviates the intestinal absorption of tryptophan leading to decreased secretion of antimicrobial peptides and changing the composition of gut microbiota. As a promising strategy, it might not only improve the quality of life of patients but also reduce the burden on the public health system because it will prevent the onset of comorbidities linked to dysbiosis of the gut microbiota [99,100].
The literature about COVID-19 and the microbiota is in a continuous evolution [99,100,101,102]. Many significant studies are published daily, especially on the aspects discussed in this review. Future studies are needed to improve our knowledge about the most important determinants of this disease. Of importance, the gut and respiratory tract microbiome may change in COVID-19 patients with opportunistic pathogen abundance. Further research should be conducted to elucidate the effect of alternation of the human microbiome in disease pathogenesis and progression to severe stages [103,104].

6. Conclusions

In conclusion, COVID-19 syndrome is characterized by a heterogeneous clinical, laboratory and radiological presentation, especially at its onset. However, data showed that patients with a confirmed diagnosis of COVID-19 can show peculiar characteristics at the time of hospitalization that could help physicians to distinguish COVID-19 from other infective or non-infective etiologies [105,106,107].
Considering the application of a standard approach to the management of patients with acute respiratory failure and/or fever, the knowledge of clinical and laboratory characteristics of COVID-19 can drive early therapeutic choices [108,109,110,111,112,113,114,115,116,117,118,119,120,121,122]. Of interest, in the management of extrapulmonary manifestations, mainly represented by gastrointestinal symptoms, the use of probiotic supplementation could be evaluated.

Author Contributions

Conceptualization, A.R. and F.S.; methodology, A.R.; validation, A.R., F.S., A.Q., M.G.T., N.M. and R.S.; writing—original draft preparation, A.R., F.S., A.Q., M.G.T., N.M. and R.S.; writing—review and editing, S.R., G.M., E.M.T. and C.T.; supervision, G.M. and C.T. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Huang, C.; Wang, Y.; Li, X.; Ren, L.; Zhao, J.; Hu, Y.; Zhang, L.; Fan, G.; Xu, J.; Gu, X.; et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet 2020, 395, 497–506. [Google Scholar] [CrossRef]
  2. Bassetti, M.; Vena, A.; Giacobbe, D.R. The novel Chinese coronavirus (2019-nCoV) infections: Challenges for fighting the storm. Eur. J. Clin. Investig. 2020, 50, e13209. [Google Scholar] [CrossRef]
  3. Zhou, F.; Yu, T.; Du, R.; Fan, G.; Liu, Y.; Liu, Z.; Xiang, J.; Wang, Y.; Song, B.; Gu, X.; et al. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: A retrospective cohort study. Lancet 2020, 395, 1054–1062. [Google Scholar] [CrossRef]
  4. Vena, A.; Giacobbe, D.R.; Di Biagio, A.; Mikulska, M.; Taramasso, L.; De Maria, A.; Ball, L.; Brunetti, I.; Loconte, M.; Patroniti, N.A.; et al. Clinical characteristics, management and in-hospital mortality of patients with coronavirus disease 2019 in Genoa, Italy. Clin. Microbiol. Infect. 2020, 26, 1537–1544. [Google Scholar] [CrossRef]
  5. Russo, A.; Bellelli, V.; Ceccarelli, G.; Marincola Cattaneo, F.; Bianchi, L.; Pierro, R.; Russo, R.; Steffanina, A.; Pugliese, F.; Mastroianni, C.M.; et al. Comparison Between Hospitalized Patients Affected or Not Affected by Coronavirus Disease 2019. Clin. Infect. Dis. 2021, 72, e1158–e1159. [Google Scholar] [CrossRef] [PubMed]
  6. Vandenberg, O.; Martiny, D.; Rochas, O.; van Belkum, A.; Kozlakidis, Z. Considerations for diagnostic COVID-19 tests. Nat. Rev. Microbiol. 2021, 19, 171–183. [Google Scholar] [CrossRef]
  7. Guaman-Bautista, L.P.; Moreta-Urbano, E.; Ona-Arias, C.G.; Torres-Arias, M.; Kyriakidis, N.C.; Malci, K.; Jonguitud-Borrego, N.; Rios-Solis, L.; Ramos-Martinez, E.; Lopez-Cortes, A.; et al. Tracking SARS-CoV-2: Novel Trends and Diagnostic Strategies. Diagnostics 2021, 11, 1981. [Google Scholar] [CrossRef]
  8. Lai, C.C.; Wang, C.Y.; Ko, W.C.; Hsueh, P.R. In vitro diagnostics of coronavirus disease 2019: Technologies and application. J. Microbiol. Immunol. Infect 2021, 54, 164–174. [Google Scholar] [CrossRef]
  9. Muecksch, F.; Wise, H.; Templeton, K.; Batchelor, B.; Squires, M.; McCance, K.; Jarvis, L.; Malloy, K.; Furrie, E.; Richardson, C.; et al. Longitudinal variation in SARS-CoV-2 antibody levels and emergence of viral variants: A serological analysis. Lancet Microbe 2022, 3, e493–e502. [Google Scholar] [CrossRef]
  10. Dal-Re, R.; Becker, S.L.; Bottieau, E.; Holm, S. Availability of oral antivirals against SARS-CoV-2 infection and the requirement for an ethical prescribing approach. Lancet Infect. Dis. 2022, 22, e231–e238. [Google Scholar] [CrossRef]
  11. Garcia-Salguero, C.; Culebras, E.; Merino, P.; Baos, E.; Delgado-Iribarren, A. Usefulness of SARS-CoV-2 antigen test sample as input for SARS-CoV-2 RT-PCR analysis. J. Med. Virol. 2022, 94, 1693–1695. [Google Scholar] [CrossRef]
  12. Scarcella, S.; Rizzelli, A.; Fontana, A.; Zecca, C.; Pasanisi, G.; Musio, K.; Putignano, A.L.; Aprile, V.; Fedele, A.; Errico, P.; et al. A CLEIA Antigen Assay in Diagnosis and Follow-Up of SARS-CoV-2-Positive Subjects. Microbiol. Spectr. 2022, 10, e0103221. [Google Scholar] [CrossRef]
  13. World Health Organization. Available online: https://www.who.int (accessed on 21 April 2022).
  14. Quirino, A.; Marascio, N.; Barreca, G.S.; Gallo, L.; Giancotti, A.; Lamberti, A.G.; Peronace, C.; Trecarichi, E.M.; Fusco, P.; Mazzitelli, M.; et al. SARS-CoV-2: Some Aspects of Molecular Evolution, Cellular Pathogenesis, and Immune System Mechanism Elusion. Appl. Sci. 2021, 11, 11605. [Google Scholar] [CrossRef]
  15. Bruel, T.; Hadjadj, J.; Maes, P.; Planas, D.; Seve, A.; Staropoli, I.; Guivel-Benhassine, F.; Porrot, F.; Bolland, W.H.; Nguyen, Y.; et al. Serum neutralization of SARS-CoV-2 Omicron sublineages BA.1 and BA.2 in patients receiving monoclonal antibodies. Nat. Med. 2022, 28, 1297–1302. [Google Scholar] [CrossRef]
  16. Viana, R.; Moyo, S.; Amoako, D.G.; Tegally, H.; Scheepers, C.; Althaus, C.L.; Anyaneji, U.J.; Bester, P.A.; Boni, M.F.; Chand, M.; et al. Rapid epidemic expansion of the SARS-CoV-2 Omicron variant in southern Africa. Nature 2022, 603, 679–686. [Google Scholar] [CrossRef]
  17. Alteri, C.; Cento, V.; Piralla, A.; Costabile, V.; Tallarita, M.; Colagrossi, L.; Renica, S.; Giardina, F.; Novazzi, F.; Gaiarsa, S.; et al. Genomic epidemiology of SARS-CoV-2 reveals multiple lineages and early spread of SARS-CoV-2 infections in Lombardy, Italy. Nat. Commun. 2021, 12, 434. [Google Scholar] [CrossRef]
  18. Anaclerio, F.; Ferrante, R.; Mandatori, D.; Antonucci, I.; Capanna, M.; Damiani, V.; Tomo, P.D.; Ferrante, R.; Ranaudo, M.; De Laurenzi, V.; et al. Different Strategies for the Identification of SARS-CoV-2 Variants in the Laboratory Practice. Genes 2021, 12, 1428. [Google Scholar] [CrossRef]
  19. Jian, M.J.; Chung, H.Y.; Chang, C.K.; Lin, J.C.; Yeh, K.M.; Chen, C.W.; Lin, D.Y.; Chang, F.Y.; Hung, K.S.; Perng, C.L.; et al. SARS-CoV-2 variants with T135I nucleocapsid mutations may affect antigen test performance. Int. J. Infect. Dis. 2022, 114, 112–114. [Google Scholar] [CrossRef]
  20. Tzou, P.L.; Tao, K.; Pond, S.L.K.; Shafer, R.W. Coronavirus Resistance Database (CoV-RDB): SARS-CoV-2 susceptibility to monoclonal antibodies, convalescent plasma, and plasma from vaccinated persons. PLoS ONE 2022, 17, e0261045. [Google Scholar] [CrossRef] [PubMed]
  21. Russo, A.; Gentilini Cacciola, E.; Borrazzo, C.; Filippi, V.; Bucci, T.; Vullo, F.; Celani, L.; Binetti, E.; Battistini, L.; Ceccarelli, G.; et al. Clinical Characteristics and Outcome of Patients with Suspected COVID-19 in Emergency Department (RESILIENCY Study II). Diagnostics 2021, 11, 1368. [Google Scholar] [CrossRef]
  22. Falcone, C.; Caracciolo, M.; Correale, P.; Macheda, S.; Vadala, E.G.; La Scala, S.; Tescione, M.; Danieli, R.; Ferrarelli, A.; Tarsitano, M.G.; et al. Can Adenosine Fight COVID-19 Acute Respiratory Distress Syndrome? J. Clin. Med. 2020, 9, 3045. [Google Scholar] [CrossRef] [PubMed]
  23. Gozzo, L.; Viale, P.; Longo, L.; Vitale, D.C.; Drago, F. The Potential Role of Heparin in Patients With COVID-19: Beyond the Anticoagulant Effect. A Review. Front. Pharmacol. 2020, 11, 1307. [Google Scholar] [CrossRef] [PubMed]
  24. Mehta, P.; McAuley, D.F.; Brown, M.; Sanchez, E.; Tattersall, R.S.; Manson, J.J. Hlh Across Speciality Collaboration, U.K. COVID-19: Consider cytokine storm syndromes and immunosuppression. Lancet 2020, 395, 1033–1034. [Google Scholar] [CrossRef]
  25. Munblit, D.; Nekliudov, N.A.; Bugaeva, P.; Blyuss, O.; Kislova, M.; Listovskaya, E.; Gamirova, A.; Shikhaleva, A.; Belyaev, V.; Timashev, P.; et al. Stop COVID Cohort: An Observational Study of 3480 Patients Admitted to the Sechenov University Hospital Network in Moscow City for Suspected Coronavirus Disease 2019 (COVID-19) Infection. Clin. Infect. Dis. 2021, 73, 1–11. [Google Scholar] [CrossRef]
  26. Docherty, A.B.; Harrison, E.M.; Green, C.A.; Hardwick, H.E.; Pius, R.; Norman, L.; Holden, K.A.; Read, J.M.; Dondelinger, F.; Carson, G.; et al. Features of 20 133 UK patients in hospital with COVID-19 using the ISARIC WHO Clinical Characterisation Protocol: Prospective observational cohort study. BMJ 2020, 369, m1985. [Google Scholar] [CrossRef]
  27. Guan, W.J.; Ni, Z.Y.; Hu, Y.; Liang, W.H.; Ou, C.Q.; He, J.X.; Liu, L.; Shan, H.; Lei, C.L.; Hui, D.S.C.; et al. Clinical Characteristics of Coronavirus Disease 2019 in China. N. Engl. J. Med. 2020, 382, 1708–1720. [Google Scholar] [CrossRef]
  28. Fernandes, Q.; Inchakalody, V.P.; Merhi, M.; Mestiri, S.; Taib, N.; Moustafa Abo El-Ella, D.; Bedhiafi, T.; Raza, A.; Al-Zaidan, L.; Mohsen, M.O.; et al. Emerging COVID-19 variants and their impact on SARS-CoV-2 diagnosis, therapeutics and vaccines. Ann. Med. 2022, 54, 524–540. [Google Scholar] [CrossRef]
  29. Bouzid, D.; Visseaux, B.; Kassasseya, C.; Daoud, A.; Femy, F.; Hermand, C.; Truchot, J.; Beaune, S.; Javaud, N.; Peyrony, O.; et al. Comparison of Patients Infected With Delta Versus Omicron COVID-19 Variants Presenting to Paris Emergency Departments: A Retrospective Cohort Study. Ann. Intern. Med. 2022, 175, 831–837. [Google Scholar] [CrossRef]
  30. Piersiala, K.; Kakabas, L.; Bruckova, A.; Starkhammar, M.; Cardell, L.O. Acute odynophagia: A new symptom of COVID-19 during the SARS-CoV-2 Omicron variant wave in Sweden. J. Intern. Med. 2022, 292, 154–161. [Google Scholar] [CrossRef]
  31. Hertanto, D.M.; Sutanto, H.; Lusida, M.I.; Kuntaman, K.; Santoso, D. The genomic and clinical features of the COVID-19 Omicron variant: A narrative review [version 1; peer review: 1 not approved]. F1000Research 2022, 11, 353. [Google Scholar] [CrossRef]
  32. Hui, K.P.Y.; Ho, J.C.W.; Cheung, M.C.; Ng, K.C.; Ching, R.H.H.; Lai, K.L.; Kam, T.T.; Gu, H.; Sit, K.Y.; Hsin, M.K.Y.; et al. SARS-CoV-2 Omicron variant replication in human bronchus and lung ex vivo. Nature 2022, 603, 715–720. [Google Scholar] [CrossRef]
  33. Meng, B.; Abdullahi, A.; Ferreira, I.; Goonawardane, N.; Saito, A.; Kimura, I.; Yamasoba, D.; Gerber, P.P.; Fatihi, S.; Rathore, S.; et al. Altered TMPRSS2 usage by SARS-CoV-2 Omicron impacts infectivity and fusogenicity. Nature 2022, 603, 706–714. [Google Scholar] [CrossRef] [PubMed]
  34. Modes, M.E.; Directo, M.P.; Melgar, M.; Johnson, L.R.; Yang, H.; Chaudhary, P.; Bartolini, S.; Kho, N.; Noble, P.W.; Isonaka, S.; et al. Clinical Characteristics and Outcomes Among Adults Hospitalized with Laboratory-Confirmed SARS-CoV-2 Infection During Periods of B.1.617.2 (Delta) and B.1.1.529 (Omicron) Variant Predominance—One Hospital, California, 15 July–23 September 2021, and 21 December 2021–27 January 2022. Morb. Mortal. Wkly. Rep. 2022, 71, 217–223. [Google Scholar] [CrossRef]
  35. Wolter, N.; Jassat, W.; Walaza, S.; Welch, R.; Moultrie, H.; Groome, M.; Amoako, D.G.; Everatt, J.; Bhiman, J.N.; Scheepers, C.; et al. Early assessment of the clinical severity of the SARS-CoV-2 omicron variant in South Africa: A data linkage study. Lancet 2022, 399, 437–446. [Google Scholar] [CrossRef]
  36. Abu-Raddad, L.J.; Chemaitelly, H.; Ayoub, H.H.; AlMukdad, S.; Yassine, H.M.; Al-Khatib, H.A.; Smatti, M.K.; Tang, P.; Hasan, M.R.; Coyle, P.; et al. Effect of mRNA Vaccine Boosters against SARS-CoV-2 Omicron Infection in Qatar. N. Engl. J. Med. 2022, 386, 1804–1816. [Google Scholar] [CrossRef]
  37. Caralis, P. Case Reports of COVID 19 Recurrence. J. Prim. Care Community Health 2021, 12, 2150132720982752. [Google Scholar] [CrossRef]
  38. Pilz, S.; Chakeri, A.; Ioannidis, J.P.; Richter, L.; Theiler-Schwetz, V.; Trummer, C.; Krause, R.; Allerberger, F. SARS-CoV-2 re-infection risk in Austria. Eur. J. Clin. Investig. 2021, 51, e13520. [Google Scholar] [CrossRef]
  39. Cavanaugh, A.M.; Spicer, K.B.; Thoroughman, D.; Glick, C.; Winter, K. Reduced Risk of Reinfection with SARS-CoV-2 After COVID-19 Vaccination—Kentucky, May–June 2021. MMWR Morb. Mortal. Wkly. Rep. 2021, 70, 1081–1083. [Google Scholar] [CrossRef]
  40. Green, H.; Yahav, D.; Eliakim-Raz, N.; Karny-Epstein, N.; Kushnir, S.; Shochat, T.; Tadmor, B.; Grossman, A. Risk-factors for re-admission and outcome of patients hospitalized with confirmed COVID-19. Sci. Rep. 2021, 11, 17416. [Google Scholar] [CrossRef]
  41. Velez-Paez, J.L.; Tercero-Martinez, W.; Jimenez-Alulima, G.; Navarrete-Dominguez, J.; Cornejo-Loor, L.; Castro-Bustamante, C.; Cabanillas-Lazo, M.; Barboza, J.J.; Rodriguez-Morales, A.J. Neutrophil-to-lymphocyte ratio and mean platelet volume in the diagnosis of bacterial infections in COVID-19 patients. A preliminary analysis from Ecuador. Infez. Med. 2021, 29, 530–537. [Google Scholar] [CrossRef]
  42. Alsaied, T.; Tremoulet, A.H.; Burns, J.C.; Saidi, A.; Dionne, A.; Lang, S.M.; Newburger, J.W.; de Ferranti, S.; Friedman, K.G. Review of Cardiac Involvement in Multisystem Inflammatory Syndrome in Children. Circulation 2021, 143, 78–88. [Google Scholar] [CrossRef] [PubMed]
  43. Chan, A.S.; Rout, A. Use of Neutrophil-to-Lymphocyte and Platelet-to-Lymphocyte Ratios in COVID-19. J. Clin. Med. Res. 2020, 12, 448–453. [Google Scholar] [CrossRef] [PubMed]
  44. Trecarichi, E.M.; Mazzitelli, M.; Serapide, F.; Pelle, M.C.; Tassone, B.; Arrighi, E.; Perri, G.; Fusco, P.; Scaglione, V.; Davoli, C.; et al. Clinical characteristics and predictors of mortality associated with COVID-19 in elderly patients from a long-term care facility. Sci. Rep. 2020, 10, 20834. [Google Scholar] [CrossRef]
  45. Carubbi, F.; Salvati, L.; Alunno, A.; Maggi, F.; Borghi, E.; Mariani, R.; Mai, F.; Paoloni, M.; Ferri, C.; Desideri, G.; et al. Ferritin is associated with the severity of lung involvement but not with worse prognosis in patients with COVID-19: Data from two Italian COVID-19 units. Sci. Rep. 2021, 11, 4863. [Google Scholar] [CrossRef] [PubMed]
  46. Harmon, S.A.; Sanford, T.H.; Xu, S.; Turkbey, E.B.; Roth, H.; Xu, Z.; Yang, D.; Myronenko, A.; Anderson, V.; Amalou, A.; et al. Artificial intelligence for the detection of COVID-19 pneumonia on chest CT using multinational datasets. Nat. Commun. 2020, 11, 4080. [Google Scholar] [CrossRef]
  47. Zhang, J.J.; Cao, Y.Y.; Dong, X.; Wang, B.C.; Liao, M.Y.; Lin, J.; Yan, Y.Q.; Akdis, C.A.; Gao, Y.D. Distinct characteristics of COVID-19 patients with initial rRT-PCR-positive and rRT-PCR-negative results for SARS-CoV-2. Allergy 2020, 75, 1809–1812. [Google Scholar] [CrossRef]
  48. Domingo, P.; Pomar, V.; Mur, I.; Castellvi, I.; Corominas, H.; de Benito, N. Not all COVID-19 pandemic waves are alike. Clin. Microbiol. Infect. 2021, 27, 1040.e7–1040.e10. [Google Scholar] [CrossRef]
  49. Group, R.C.; Horby, P.; Lim, W.S.; Emberson, J.R.; Mafham, M.; Bell, J.L.; Linsell, L.; Staplin, N.; Brightling, C.; Ustianowski, A.; et al. Dexamethasone in Hospitalized Patients with COVID-19. N. Engl. J. Med. 2021, 384, 693–704. [Google Scholar] [CrossRef]
  50. Villar, J.; Anon, J.M.; Ferrando, C.; Aguilar, G.; Munoz, T.; Ferreres, J.; Ambros, A.; Aldecoa, C.; Suarez-Sipmann, F.; Thorpe, K.E.; et al. Efficacy of dexamethasone treatment for patients with the acute respiratory distress syndrome caused by COVID-19: Study protocol for a randomized controlled superiority trial. Trials 2020, 21, 717. [Google Scholar] [CrossRef]
  51. Petersen, M.W.; Meyhoff, T.S.; Helleberg, M.; Kjaer, M.N.; Granholm, A.; Hjortso, C.J.S.; Jensen, T.S.; Moller, M.H.; Hjortrup, P.B.; Wetterslev, M.; et al. Low-dose hydrocortisone in patients with COVID-19 and severe hypoxia (COVID STEROID) trial-Protocol and statistical analysis plan. Acta Anaesthesiol. Scand. 2020, 64, 1365–1375. [Google Scholar] [CrossRef]
  52. Tomazini, B.M.; Maia, I.S.; Cavalcanti, A.B.; Berwanger, O.; Rosa, R.G.; Veiga, V.C.; Avezum, A.; Lopes, R.D.; Bueno, F.R.; Silva, M.; et al. Effect of Dexamethasone on Days Alive and Ventilator-Free in Patients With Moderate or Severe Acute Respiratory Distress Syndrome and COVID-19: The CoDEX Randomized Clinical Trial. JAMA 2020, 324, 1307–1316. [Google Scholar] [CrossRef] [PubMed]
  53. Dequin, P.F.; Heming, N.; Meziani, F.; Plantefeve, G.; Voiriot, G.; Badie, J.; Francois, B.; Aubron, C.; Ricard, J.D.; Ehrmann, S.; et al. Effect of Hydrocortisone on 21-Day Mortality or Respiratory Support Among Critically Ill Patients With COVID-19: A Randomized Clinical Trial. JAMA 2020, 324, 1298–1306. [Google Scholar] [CrossRef] [PubMed]
  54. Angus, D.C.; Derde, L.; Al-Beidh, F.; Annane, D.; Arabi, Y.; Beane, A.; van Bentum-Puijk, W.; Berry, L.; Bhimani, Z.; Bonten, M.; et al. Effect of Hydrocortisone on Mortality and Organ Support in Patients With Severe COVID-19: The REMAP-CAP COVID-19 Corticosteroid Domain Randomized Clinical Trial. JAMA 2020, 324, 1317–1329. [Google Scholar] [CrossRef] [PubMed]
  55. Group, W.H.O.R.E.A.f.C.-T.W.; Sterne, J.A.C.; Murthy, S.; Diaz, J.V.; Slutsky, A.S.; Villar, J.; Angus, D.C.; Annane, D.; Azevedo, L.C.P.; Berwanger, O.; et al. Association Between Administration of Systemic Corticosteroids and Mortality Among Critically Ill Patients With COVID-19: A Meta-analysis. JAMA 2020, 324, 1330–1341. [Google Scholar] [CrossRef]
  56. Welte, T.; Ambrose, L.J.; Sibbring, G.C.; Sheikh, S.; Mullerova, H.; Sabir, I. Current evidence for COVID-19 therapies: A systematic literature review. Eur. Respir. Rev. 2021, 30, 200384. [Google Scholar] [CrossRef]
  57. Ko, J.J.; Wu, C.; Mehta, N.; Wald-Dickler, N.; Yang, W.; Qiao, R. A Comparison of Methylprednisolone and Dexamethasone in Intensive Care Patients With COVID-19. J. Intensive Care Med. 2021, 36, 673–680. [Google Scholar] [CrossRef]
  58. Li, Q.; Li, W.; Jin, Y.; Xu, W.; Huang, C.; Li, L.; Huang, Y.; Fu, Q.; Chen, L. Efficacy Evaluation of Early, Low-Dose, Short-Term Corticosteroids in Adults Hospitalized with Non-Severe COVID-19 Pneumonia: A Retrospective Cohort Study. Infect. Dis. Ther. 2020, 9, 823–836. [Google Scholar] [CrossRef]
  59. Chatterjee, K.; Wu, C.P.; Bhardwaj, A.; Siuba, M. Steroids in COVID-19: An overview. Cleve Clin. J. Med. 2020. [Google Scholar] [CrossRef]
  60. Falcone, M.; Tiseo, G.; Barbieri, G.; Galfo, V.; Russo, A.; Virdis, A.; Forfori, F.; Corradi, F.; Guarracino, F.; Carrozzi, L.; et al. Role of Low-Molecular-Weight Heparin in Hospitalized Patients With Severe Acute Respiratory Syndrome Coronavirus 2 Pneumonia: A Prospective Observational Study. Open Forum. Infect. Dis. 2020, 7, ofaa563. [Google Scholar] [CrossRef]
  61. Olender, S.A.; Perez, K.K.; Go, A.S.; Balani, B.; Price-Haywood, E.G.; Shah, N.S.; Wang, S.; Walunas, T.L.; Swaminathan, S.; Slim, J.; et al. Remdesivir for Severe Coronavirus Disease 2019 (COVID-19) Versus a Cohort Receiving Standard of Care. Clin. Infect. Dis. 2021, 73, e4166–e4174. [Google Scholar] [CrossRef]
  62. Consortium, W.H.O.S.T.; Pan, H.; Peto, R.; Henao-Restrepo, A.M.; Preziosi, M.P.; Sathiyamoorthy, V.; Abdool Karim, Q.; Alejandria, M.M.; Hernandez Garcia, C.; Kieny, M.P.; et al. Repurposed Antiviral Drugs for COVID-19—Interim WHO Solidarity Trial Results. N. Engl. J. Med. 2021, 384, 497–511. [Google Scholar] [CrossRef] [PubMed]
  63. Milross, L.; Majo, J.; Cooper, N.; Kaye, P.M.; Bayraktar, O.; Filby, A.; Fisher, A.J. Post-mortem lung tissue: The fossil record of the pathophysiology and immunopathology of severe COVID-19. Lancet Respir. Med. 2022, 10, 95–106. [Google Scholar] [CrossRef]
  64. Nagele, M.P.; Haubner, B.; Tanner, F.C.; Ruschitzka, F.; Flammer, A.J. Endothelial dysfunction in COVID-19: Current findings and therapeutic implications. Atherosclerosis 2020, 314, 58–62. [Google Scholar] [CrossRef] [PubMed]
  65. Weckbach, L.T.; Schweizer, L.; Kraechan, A.; Bieber, S.; Ishikawa-Ankerhold, H.; Hausleiter, J.; Massberg, S.; Straub, T.; Klingel, K.; Grabmaier, U.; et al. Association of Complement and MAPK Activation With SARS-CoV-2-Associated Myocardial Inflammation. JAMA Cardiol. 2022, 7, 286–297. [Google Scholar] [CrossRef]
  66. Ferrara, F.; Vitiello, A. Scientific and pharmacological rationale for the treatment of cardiac damage caused by COVID-19. Discov. Med. 2020, 30, 155–161. [Google Scholar]
  67. Titi, L.; Magnanimi, E.; Mancone, M.; Infusino, F.; Coppola, G.; Del Nonno, F.; Colombo, D.; Nardacci, R.; Falasca, L.; d’Amati, G.; et al. Fatal Takotsubo syndrome in critical COVID-19 related pneumonia. Cardiovasc. Pathol. 2021, 51, 107314. [Google Scholar] [CrossRef]
  68. Guglin, M.; Ballut, K.; Ilonze, O.; Jones, M.; Rao, R. Clinical variants of myocardial involvement in COVID-19-positive patients: A cumulative experience of 2020. Heart Fail. Rev. 2022, 27, 1341–1353. [Google Scholar] [CrossRef]
  69. Bikdeli, B.; Garcia, D.A. In patients hospitalized with COVID-19, therapeutic- vs. prophylactic-dose heparin did not reduce a composite outcome at 28 d. Ann. Intern. Med. 2022, 175, JC16. [Google Scholar] [CrossRef]
  70. Lee, J.R.; Silberzweig, J.; Akchurin, O.; Choi, M.E.; Srivatana, V.; Lin, J.; Liu, F.; Malha, L.; Lubetzky, M.; Dadhania, D.M.; et al. Characteristics of Acute Kidney Injury in Hospitalized COVID-19 Patients in an Urban Academic Medical Center. Clin. J. Am. Soc. Nephrol. 2021, 16, 284–286. [Google Scholar] [CrossRef]
  71. Hirsch, J.S.; Ikizler, T.A.; Sharma, S.; Mohammed, A. Acute Kidney Injury and Advanced Kidney Disease in the COVID-19 Pandemic: Proceedings From a National Kidney Foundation Symposium. Kidney Med. 2021, 3, 426–432. [Google Scholar] [CrossRef]
  72. Karadas, O.; Ozturk, B.; Sonkaya, A.R. A prospective clinical study of detailed neurological manifestations in patients with COVID-19. Neurol. Sci. 2020, 41, 1991–1995. [Google Scholar] [CrossRef] [PubMed]
  73. Taquet, M.; Holmes, E.A.; Harrison, P.J. Depression and anxiety disorders during the COVID-19 pandemic: Knowns and unknowns. Lancet 2021, 398, 1665–1666. [Google Scholar] [CrossRef]
  74. Agyeman, A.A.; Chin, K.L.; Landersdorfer, C.B.; Liew, D.; Ofori-Asenso, R. Smell and Taste Dysfunction in Patients With COVID-19: A Systematic Review and Meta-analysis. Mayo Clin. Proc. 2020, 95, 1621–1631. [Google Scholar] [CrossRef]
  75. Lechien, J.R.; Chiesa-Estomba, C.M.; Beckers, E.; Mustin, V.; Ducarme, M.; Journe, F.; Marchant, A.; Jouffe, L.; Barillari, M.R.; Cammaroto, G.; et al. Prevalence and 6-month recovery of olfactory dysfunction: A multicentre study of 1363 COVID-19 patients. J. Intern. Med. 2021, 290, 451–461. [Google Scholar] [CrossRef]
  76. Al-Namaeh, M. Ocular manifestations of COVID-19. Ther. Adv. Ophthalmol. 2022, 14, 25158414221083374. [Google Scholar] [CrossRef]
  77. Kaya, G.; Kaya, A.; Saurat, J.H. Clinical and Histopathological Features and Potential Pathological Mechanisms of Skin Lesions in COVID-19: Review of the Literature. Dermatopathology 2020, 7, 3–16. [Google Scholar] [CrossRef] [PubMed]
  78. Mazzitelli, M.; Dastoli, S.; Mignogna, C.; Bennardo, L.; Lio, E.; Pelle, M.C.; Trecarichi, E.M.; Pereira, B.I.; Nistico, S.P.; Torti, C. Histopathology and immunophenotyping of late onset cutaneous manifestations of COVID-19 in elderly patients: Three case reports. World J. Clin. Cases 2021, 9, 5744–5751. [Google Scholar] [CrossRef]
  79. Gottlieb, M.; Long, B. Dermatologic manifestations and complications of COVID-19. Am. J. Emerg. Med. 2020, 38, 1715–1721. [Google Scholar] [CrossRef]
  80. Zeng, W.; Qi, K.; Ye, M.; Zheng, L.; Liu, X.; Hu, S.; Zhang, W.; Tang, W.; Xu, J.; Yu, D.; et al. Gastrointestinal symptoms are associated with severity of coronavirus disease 2019: A systematic review and meta-analysis. Eur. J. Gastroenterol. Hepatol. 2022, 34, 168–176. [Google Scholar] [CrossRef]
  81. Cheung, K.S.; Hung, I.F.N.; Chan, P.P.Y.; Lung, K.C.; Tso, E.; Liu, R.; Ng, Y.Y.; Chu, M.Y.; Chung, T.W.H.; Tam, A.R.; et al. Gastrointestinal Manifestations of SARS-CoV-2 Infection and Virus Load in Fecal Samples From a Hong Kong Cohort: Systematic Review and Meta-analysis. Gastroenterology 2020, 159, 81–95. [Google Scholar] [CrossRef]
  82. Zhang, X.; Tang, C.; Tian, D.; Hou, X.; Yang, Y. Management of Digestive Disorders and Procedures Associated With COVID-19. Am. J. Gastroenterol. 2020, 115, 1153–1155. [Google Scholar] [CrossRef] [PubMed]
  83. Kaafarani, H.M.A.; El Moheb, M.; Hwabejire, J.O.; Naar, L.; Christensen, M.A.; Breen, K.; Gaitanidis, A.; Alser, O.; Mashbari, H.; Bankhead-Kendall, B.; et al. Gastrointestinal Complications in Critically Ill Patients With COVID-19. Ann. Surg. 2020, 272, e61–e62. [Google Scholar] [CrossRef] [PubMed]
  84. Chen, H.; Tong, Z.; Ma, Z.; Luo, L.; Tang, Y.; Teng, Y.; Yu, H.; Meng, H.; Peng, C.; Zhang, Q.; et al. Gastrointestinal Bleeding, but Not Other Gastrointestinal Symptoms, Is Associated With Worse Outcomes in COVID-19 Patients. Front. Med. 2021, 8, 759152. [Google Scholar] [CrossRef] [PubMed]
  85. Wang, J.; Zhu, L.; Xue, L.; Liu, L.; Yan, X.; Yan, X.; Huang, S.; Zhang, B.; Xu, T.; Li, C.; et al. Risk factors of liver injury in patients with coronavirus disease 2019 in Jiangsu, China: A retrospective, multi-center study. J. Med. Virol. 2021, 93, 3305–3311. [Google Scholar] [CrossRef]
  86. Cai, Q.; Huang, D.; Yu, H.; Zhu, Z.; Xia, Z.; Su, Y.; Li, Z.; Zhou, G.; Gou, J.; Qu, J.; et al. COVID-19: Abnormal liver function tests. J. Hepatol. 2020, 73, 566–574. [Google Scholar] [CrossRef]
  87. Ceccarelli, G.; Scagnolari, C.; Pugliese, F.; Mastroianni, C.M.; d’Ettorre, G. Probiotics and COVID-19. Lancet Gastroenterol. Hepatol. 2020, 5, 721–722. [Google Scholar] [CrossRef]
  88. Wander, P.; Epstein, M.; Bernstein, D. COVID-19 Presenting as Acute Hepatitis. Am. J. Gastroenterol. 2020, 115, 941–942. [Google Scholar] [CrossRef] [PubMed]
  89. El Moheb, M.; Naar, L.; Christensen, M.A.; Kapoen, C.; Maurer, L.R.; Farhat, M.; Kaafarani, H.M.A. Gastrointestinal Complications in Critically Ill Patients With and Without COVID-19. JAMA 2020, 324, 1899–1901. [Google Scholar] [CrossRef]
  90. Round, J.L.; Mazmanian, S.K. The gut microbiota shapes intestinal immune responses during health and disease. Nat. Rev. Immunol. 2009, 9, 313–323. [Google Scholar] [CrossRef]
  91. Francino, M.P. Early development of the gut microbiota and immune health. Pathogens 2014, 3, 769–790. [Google Scholar] [CrossRef]
  92. Zhao, N.; Wang, S.; Li, H.; Liu, S.; Li, M.; Luo, J.; Su, W.; He, H. Influence of Novel Highly Pathogenic Avian Influenza A (H5N1) Virus Infection on Migrating Whooper Swans Fecal Microbiota. Front. Cell Infect. Microbiol. 2018, 8, 46. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  93. Xiao, F.; Tang, M.; Zheng, X.; Liu, Y.; Li, X.; Shan, H. Evidence for Gastrointestinal Infection of SARS-CoV-2. Gastroenterology 2020, 158, 1831–1833. [Google Scholar] [CrossRef] [PubMed]
  94. Li, W.; Moore, M.J.; Vasilieva, N.; Sui, J.; Wong, S.K.; Berne, M.A.; Somasundaran, M.; Sullivan, J.L.; Luzuriaga, K.; Greenough, T.C.; et al. Angiotensin-converting enzyme 2 is a functional receptor for the SARS coronavirus. Nature 2003, 426, 450–454. [Google Scholar] [CrossRef]
  95. Giron, L.B.; Dweep, H.; Yin, X.; Wang, H.; Damra, M.; Goldman, A.R.; Gorman, N.; Palmer, C.S.; Tang, H.Y.; Shaikh, M.W.; et al. Plasma Markers of Disrupted Gut Permeability in Severe COVID-19 Patients. Front. Immunol. 2021, 12, 686240. [Google Scholar] [CrossRef]
  96. McCarty, M.F.; Lerner, A. Perspective: Prospects for Nutraceutical Support of Intestinal Barrier Function. Adv. Nutr. 2021, 12, 316–324. [Google Scholar] [CrossRef] [PubMed]
  97. d’Ettorre, G.; Ceccarelli, G.; Marazzato, M.; Campagna, G.; Pinacchio, C.; Alessandri, F.; Ruberto, F.; Rossi, G.; Celani, L.; Scagnolari, C.; et al. Challenges in the Management of SARS-CoV-2 Infection: The Role of Oral Bacteriotherapy as Complementary Therapeutic Strategy to Avoid the Progression of COVID-19. Front. Med. 2020, 7, 389. [Google Scholar] [CrossRef]
  98. Al Bander, Z.; Nitert, M.D.; Mousa, A.; Naderpoor, N. The Gut Microbiota and Inflammation: An Overview. Int. J. Environ. Res. Public Health 2020, 17, 7618. [Google Scholar] [CrossRef]
  99. Liu, Q.; Mak, J.W.Y.; Su, Q.; Yeoh, Y.K.; Lui, G.C.Y.; Ng, S.S.S.; Zhang, F.; Li, A.Y.; Lu, W.; Hui, D.S.C.; et al. Gut microbiota dynamics in a prospective cohort of patients with post-acute COVID-19 syndrome. Gut 2022, 71, 544–552. [Google Scholar] [CrossRef]
  100. Mizutani, T.; Ishizaka, A.; Koga, M.; Ikeuchi, K.; Saito, M.; Adachi, E.; Yamayoshi, S.; Iwatsuki-Horimoto, K.; Yasuhara, A.; Kiyono, H.; et al. Correlation Analysis between Gut Microbiota Alterations and the Cytokine Response in Patients with Coronavirus Disease during Hospitalization. Microbiol. Spectr. 2022, 10, e01689-21. [Google Scholar] [CrossRef]
  101. Vestad, B.; Ueland, T.; Lerum, T.V.; Dahl, T.B.; Holm, K.; Barratt-Due, A.; Kåsine, T.; Dyrhol-Riise, A.M.; Stiksrud, B.; Tonby, K.; et al. Respiratory dysfunction three months after severe COVID-19 is associated with gut microbiota alterations. J. Intern. Med. 2022, 291, 801–812. [Google Scholar] [CrossRef]
  102. Brumfield, K.D.; Leddy, M.; Usmani, M.; Cotruvo, J.A.; Tien, C.T.; Dorsey, S.; Graubics, K.; Fanelli, B.; Zhou, I.; Registe, N.; et al. Microbiome Analysis for Wastewater Surveillance during COVID-19. mBio 2022, 13, e00591-22. [Google Scholar] [CrossRef] [PubMed]
  103. Yamamoto, S.; Saito, M.; Tamura, A.; Prawisuda, D.; Mizutani, T.; Yotsuyanagi, H. The human microbiome and COVID-19: A systematic review. PLoS ONE 2021, 16, e0253293. [Google Scholar] [CrossRef] [PubMed]
  104. Sulaiman, I.; Chung, M.; Angel, L.; Tsay, J.J.; Wu, B.G.; Yeung, S.T.; Krolikowski, K.; Li, Y.; Duerr, R.; Schluger, R.; et al. Microbial signatures in the lower airways of mechanically ventilated COVID-19 patients associated with poor clinical outcome. Nat. Microbiol. 2021, 6, 1245–1258. [Google Scholar] [CrossRef] [PubMed]
  105. Alhazzani, W.; Moller, M.H.; Arabi, Y.M.; Loeb, M.; Gong, M.N.; Fan, E.; Oczkowski, S.; Levy, M.M.; Derde, L.; Dzierba, A.; et al. Surviving Sepsis Campaign: Guidelines on the Management of Critically Ill Adults with Coronavirus Disease 2019 (COVID-19). Crit. Care Med. 2020, 48, e440–e469. [Google Scholar] [CrossRef] [PubMed]
  106. Bassetti, M.; Giacobbe, D.R.; Aliberti, S.; Barisione, E.; Centanni, S.; De Rosa, F.G.; Di Marco, F.; Gori, A.; Granata, G.; Mikulska, M.; et al. Balancing evidence and frontline experience in the early phases of the COVID-19 pandemic: Current position of the Italian Society of Anti-infective Therapy (SITA) and the Italian Society of Pulmonology (SIP). Clin. Microbiol. Infect. 2020, 26, 880–894. [Google Scholar] [CrossRef]
  107. Sinha, P.; Calfee, C.S.; Cherian, S.; Brealey, D.; Cutler, S.; King, C.; Killick, C.; Richards, O.; Cheema, Y.; Bailey, C.; et al. Prevalence of phenotypes of acute respiratory distress syndrome in critically ill patients with COVID-19: A prospective observational study. Lancet Respir. Med. 2020, 8, 1209–1218. [Google Scholar] [CrossRef]
  108. Falcone, M.; Bassetti, M.; Tiseo, G.; Giordano, C.; Nencini, E.; Russo, A.; Graziano, E.; Tagliaferri, E.; Leonildi, A.; Barnini, S.; et al. Time to appropriate antibiotic therapy is a predictor of outcome in patients with bloodstream infection caused by KPC-producing Klebsiella pneumoniae. Crit. Care 2020, 24, 29. [Google Scholar] [CrossRef]
  109. Falcone, M.; Russo, A.; Iacovelli, A.; Restuccia, G.; Ceccarelli, G.; Giordano, A.; Farcomeni, A.; Morelli, A.; Venditti, M. Predictors of outcome in ICU patients with septic shock caused by Klebsiella pneumoniae carbapenemase-producing K. pneumoniae. Clin. Microbiol. Infect. 2016, 22, 444–450. [Google Scholar] [CrossRef]
  110. Bassetti, M.; Vena, A.; Giacobbe, D.R.; Falcone, M.; Tiseo, G.; Giannella, M.; Pascale, R.; Meschiari, M.; Digaetano, M.; Oliva, A.; et al. Ceftolozane/Tazobactam for Treatment of Severe ESBL-Producing Enterobacterales Infections: A Multicenter Nationwide Clinical Experience (CEFTABUSE II Study). Open Forum. Infect. Dis. 2020, 7, ofaa139. [Google Scholar] [CrossRef]
  111. Bassetti, M.; Castaldo, N.; Cattelan, A.; Mussini, C.; Righi, E.; Tascini, C.; Menichetti, F.; Mastroianni, C.M.; Tumbarello, M.; Grossi, P.; et al. Ceftolozane/tazobactam for the treatment of serious Pseudomonas aeruginosa infections: A multicentre nationwide clinical experience. Int. J. Antimicrob. Agents 2019, 53, 408–415. [Google Scholar] [CrossRef]
  112. Russo, A.; Falcone, M.; Gutierrez-Gutierrez, B.; Calbo, E.; Almirante, B.; Viale, P.L.; Oliver, A.; Ruiz-Garbajosa, P.; Gasch, O.; Gozalo, M.; et al. Predictors of outcome in patients with severe sepsis or septic shock due to extended-spectrum beta-lactamase-producing Enterobacteriaceae. Int. J. Antimicrob. Agents 2018, 52, 577–585. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  113. Russo, A.; Bassetti, M.; Ceccarelli, G.; Carannante, N.; Losito, A.R.; Bartoletti, M.; Corcione, S.; Granata, G.; Santoro, A.; Giacobbe, D.R.; et al. Bloodstream infections caused by carbapenem-resistant Acinetobacter baumannii: Clinical features, therapy and outcome from a multicenter study. J. Infect. 2019, 79, 130–138. [Google Scholar] [CrossRef] [PubMed]
  114. Russo, A.; Giuliano, S.; Ceccarelli, G.; Alessandri, F.; Giordano, A.; Brunetti, G.; Venditti, M. Comparison of Septic Shock Due to Multidrug-Resistant Acinetobacter baumannii or Klebsiella pneumoniae Carbapenemase-Producing, K. pneumoniae in Intensive Care Unit Patients. Antimicrob. Agents Chemother. 2018, 62, e02562-17. [Google Scholar] [CrossRef] [PubMed]
  115. Russo, A.; Marincola Cattaneo, F.; Brunetti, G.; Picciarella, A.; Russo, R.; Hallgass, M.E.; Sabetta, F. Clinical features and outcome of difficult-to-treat infections in a high-intensity medical care ward. Minerva Med. 2020. [Google Scholar] [CrossRef] [PubMed]
  116. Bassetti, M.; Russo, A.; Righi, E.; Dolso, E.; Merelli, M.; D’Aurizio, F.; Sartor, A.; Curcio, F. Role of procalcitonin in bacteremic patients and its potential use in predicting infection etiology. Expert Rev. Anti. Infect. Ther. 2019, 17, 99–105. [Google Scholar] [CrossRef]
  117. Bassetti, M.; Russo, A.; Righi, E.; Dolso, E.; Merelli, M.; D’Aurizio, F.; Sartor, A.; Curcio, F. Role of procalcitonin in predicting etiology in bacteremic patients: Report from a large single-center experience. J. Infect. Public Health 2020, 13, 40–45. [Google Scholar] [CrossRef]
  118. Bassetti, M.; Righi, E.; Carnelutti, A.; Graziano, E.; Russo, A. Multidrug-resistant Klebsiella pneumoniae: Challenges for treatment, prevention and infection control. Expert Rev. Anti-Infect. Ther. 2018, 16, 749–761. [Google Scholar] [CrossRef]
  119. Bassetti, M.; Righi, E.; Vena, A.; Graziano, E.; Russo, A.; Peghin, M. Risk stratification and treatment of ICU-acquired pneumonia caused by multidrug- resistant/extensively drug-resistant/pandrug-resistant bacteria. Curr. Opin. Crit. Care 2018, 24, 385–393. [Google Scholar] [CrossRef]
  120. Bassetti, M.; Russo, A.; Carnelutti, A.; La Rosa, A.; Righi, E. Antimicrobial resistance and treatment: An unmet clinical safety need. Expert Opin. Drug Saf. 2018, 17, 669–680. [Google Scholar] [CrossRef]
  121. Alessandri, F.; Pugliese, F.; Angeletti, S.; Ciccozzi, M.; Russo, A.; Mastroianni, C.M.; d’Ettorre, G.; Venditti, M.; Ceccarelli, G. Procalcitonin in the Assessment of Ventilator Associated Pneumonia: A Systematic Review. Adv. Exp. Med. Biol. 2021, 1323, 103–114. [Google Scholar]
  122. Russo, A.; Gavaruzzi, F.; Ceccarelli, G.; Borrazzo, C.; Oliva, A.; Alessandri, F.; Magnanimi, E.; Pugliese, F.; Venditti, M. Multidrug-resistant Acinetobacter baumannii infections in COVID-19 patients hospitalized in intensive care unit. Infection 2022, 50, 83–92. [Google Scholar] [CrossRef] [PubMed]
Diagnostics 12 02143 g001 550
Figure 1. Management of patients with suspected COVID-19. Legend: RT-PCR: real-time polymerase chain reaction; CT: computed tomography; MoAbs: monoclonal antibodies; PCT: procalcitonin.
Figure 1. Management of patients with suspected COVID-19. Legend: RT-PCR: real-time polymerase chain reaction; CT: computed tomography; MoAbs: monoclonal antibodies; PCT: procalcitonin.
Diagnostics 12 02143 g001
Table
Table 1. Certified diagnostic methods routine used in clinical practice.
Table 1. Certified diagnostic methods routine used in clinical practice.
Test NameTechnologyManufacturerSpecimenSensitivity% (95%; C.I.)Specificity%
(95%; C.I.)		TAT (min)Reference
Molecular assay
ARGENE SARSCOV-2 RGENE
(RdRp, N, E)		Two triplex PCRbioMe’rieux (France)Nasopharyngeal swabsNANA3–4 hLai C-C et al., 2021 [8]
Allplex 2019-nCoV assay
Target genes
(E, N and RdRp)		Multiplex real-time PCRSeegene (Korea)Sputum, nasopharyngeal swab, nasopharyngeal aspirate, bronchoalveolar lavage, throat swab 98.2 (95%; 90.3–100.0)100 (95%; 94.9–100.0)110Zhou Y et al., 2021 [3]
TaqPath COVID-19 high throughput combo
Target genes
(S, N)		Multiplex real-time PCRThermo Fisher
Scientific (USA)		Saliva, nasal, nasopharyngeal samples100
(95%; 97.9–100.0)		100
(95%; 98.6–100)		Can run up to 8000 reactions
per day		Zhou Y et al., 2021 [3]
Xpert Xpress SARS-CoV-2
Target genes
(N2, E)		RT-PCR
(point of care)		Cepheid (USA)Nasopharyngeal swabs, nasal aspirate99
(95%; 97.0–99.0)		97
(95%; 95.0–98.0)		45Lai C-C et al., 2021 [8]
ID NOW COVID-19 assay
Target gene
(RdpRp)		Isothermal nucleic acid amplification Abbot (USA)Nasopharyngeal and nasal swabs95.0%97.9%≤13Lai C-C et al., 2021 [8]
iAMP COVID-19
detection kit
Target genes
(N, ORF1ab)		Isothermal real-time fluorescent reverse transcription Atilia BioSystems (USA)Nasopharyngeal, oropharyngeal swabsNANA90Guaman-Bautista et al., 2021 [7]
Agilent SARS-CoV-2 qRT-PCR Dx Kit
Target genes
(N1 and N2)		Real-time reverse transcription-polymerase chain reactionAgilentNasopharyngeal, nasal and oropharyngeal swabs95.0%NA90CDC
Syndromic test
BiofireFilmarrayRP.-2.1
Target genes
(RdRp, N, E)		Multiplex real-time PCRbioMérieux (France)Nasopharyngeal swabs98.4
(NA)		98.9
(NA)		45Lai C-C et al., 2021 [8];
https://www.fda.gov
QIAstat-Dx Respiratory 2019-nCoV Panel (22 targets)
(RdRp, E)		Multiplex real-time PCRQIAGEN
(Netherlands)		Nasopharyngeal swabs97.2
(NA)		96.1
(NA)		<70 minLai C-C et al., 2021 [8];
https://www.qiagen.com
Serological assay
SARS-CoV-2 IgG
(CMIA)
IgG		Chemiluminescent microparticle immunoassayAbbott Laboratories,
IL, USA		Serum or plasma3–7 days after
symptom onset: 25.0
8–13 days: 86.1
>14 days: 100		99.6–100NALai C-C et al., 2021 [8]
Elecsys Anti-SARSCoV-2
(ECLIA)
Total antibody (including IgG)		ElectrochemiluminescenceRoche Diagnostics Basel, SwitzerlandSerum or plasma0–6 days aftersymptom onset: 65.5
7–13 days: 88.1
>14 days: 100		99.818 minLai C-C et al., 2021 [8]
Anti-SARS-CoV-2 ELISA
(EIA)
IgA and IgG		ImmunoenzymaticEUROIMMUN AG (Germany)SerumNANA2–3 h/96 samplesLai C-C et al., 2021 [8]
LIAISON SARS-CoV-2 S1/S2 IgG
(CLIA)
IgG		ChemiluminescenceDiaSorinSerum97.5699.335Zhou Y et al., 2021 [8]
Platelia SARS-CoV-2 total antibody assay
(ELISA)
Total antibody		ImmunoenzymaticBio-RadSerum100.099.6NAZhou Y et al., 2021 [8]
Access SARS-CoV-2 IgG(CLIA)ChemiluminescenceBeckman Coulter, Inc.Serum96.899.6NAGuaman-Bautista LP., et al., 2021 [7]
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Russo, A.; Serapide, F.; Quirino, A.; Tarsitano, M.G.; Marascio, N.; Serraino, R.; Rotundo, S.; Matera, G.; Trecarichi, E.M.; Torti, C. Microbiological and Clinical Findings of SARS-CoV-2 Infection after 2 Years of Pandemic: From Lung to Gut Microbiota. Diagnostics 2022, 12, 2143. https://0-doi-org.brum.beds.ac.uk/10.3390/diagnostics12092143

AMA Style

Russo A, Serapide F, Quirino A, Tarsitano MG, Marascio N, Serraino R, Rotundo S, Matera G, Trecarichi EM, Torti C. Microbiological and Clinical Findings of SARS-CoV-2 Infection after 2 Years of Pandemic: From Lung to Gut Microbiota. Diagnostics. 2022; 12(9):2143. https://0-doi-org.brum.beds.ac.uk/10.3390/diagnostics12092143

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Russo, Alessandro, Francesca Serapide, Angela Quirino, Maria Grazia Tarsitano, Nadia Marascio, Riccardo Serraino, Salvatore Rotundo, Giovanni Matera, Enrico Maria Trecarichi, and Carlo Torti. 2022. "Microbiological and Clinical Findings of SARS-CoV-2 Infection after 2 Years of Pandemic: From Lung to Gut Microbiota" Diagnostics 12, no. 9: 2143. https://0-doi-org.brum.beds.ac.uk/10.3390/diagnostics12092143

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