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1.
PLoS One ; 17(7): e0264106, 2022.
Article in English | MEDLINE | ID: covidwho-1957098

ABSTRACT

BACKGROUND: The coronavirus disease 2019 (COVID-19) presents an urgent threat to global health. Identification of predictors of poor outcomes will assist medical staff in treatment and allocating limited healthcare resources. AIMS: The primary aim was to study the value of D-dimer as a predictive marker for in-hospital mortality. METHODS: This was a cohort study. The study population consisted of hospitalized patients (age >18 years), who were diagnosed with COVID-19 based on real-time PCR at 9 hospitals during the first COVID-19 wave in Lombardy, Italy (Feb-May 2020). The primary endpoint was in-hospital mortality. Information was obtained from patient records. Statistical analyses were performed using a Fine-Gray competing risk survival model. Model discrimination was assessed using Harrell's C-index and model calibration was assessed using a calibration plot. RESULTS: Out of 1049 patients, 507 patients (46%) had evaluable data. Of these 507 patients, 96 died within 30 days. The cumulative incidence of in-hospital mortality within 30 days was 19% (95CI: 16%-23%), and the majority of deaths occurred within the first 10 days. A prediction model containing D-dimer as the only predictor had a C-index of 0.66 (95%CI: 0.61-0.71). Overall calibration of the model was very poor. The addition of D-dimer to a model containing age, sex and co-morbidities as predictors did not lead to any meaningful improvement in either the C-index or the calibration plot. CONCLUSION: The predictive value of D-dimer alone was moderate, and the addition of D-dimer to a simple model containing basic clinical characteristics did not lead to any improvement in model performance.


Subject(s)
COVID-19 , Adolescent , Biomarkers , COVID-19/diagnosis , Cohort Studies , Fibrin Fibrinogen Degradation Products/analysis , Hospital Mortality , Humans , Retrospective Studies , SARS-CoV-2
2.
Eur J Intern Med ; 102: 63-71, 2022 Aug.
Article in English | MEDLINE | ID: covidwho-1944883

ABSTRACT

BACKGROUND: The coronavirus disease 2019 (COVID-19) presents an urgent threat to global health. Prediction models that accurately estimate mortality risk in hospitalized patients could assist medical staff in treatment and allocating limited resources. AIMS: To externally validate two promising previously published risk scores that predict in-hospital mortality among hospitalized COVID-19 patients. METHODS: Two prospective cohorts were available; a cohort of 1028 patients admitted to one of nine hospitals in Lombardy, Italy (the Lombardy cohort) and a cohort of 432 patients admitted to a hospital in Leiden, the Netherlands (the Leiden cohort). The endpoint was in-hospital mortality. All patients were adult and tested COVID-19 PCR-positive. Model discrimination and calibration were assessed. RESULTS: The C-statistic of the 4C mortality score was good in the Lombardy cohort (0.85, 95CI: 0.82-0.89) and in the Leiden cohort (0.87, 95CI: 0.80-0.94). Model calibration was acceptable in the Lombardy cohort but poor in the Leiden cohort due to the model systematically overpredicting the mortality risk for all patients. The C-statistic of the CURB-65 score was good in the Lombardy cohort (0.80, 95CI: 0.75-0.85) and in the Leiden cohort (0.82, 95CI: 0.76-0.88). The mortality rate in the CURB-65 development cohort was much lower than the mortality rate in the Lombardy cohort. A similar but less pronounced trend was found for patients in the Leiden cohort. CONCLUSION: Although performances did not differ greatly, the 4C mortality score showed the best performance. However, because of quickly changing circumstances, model recalibration may be necessary before using the 4C mortality score.


Subject(s)
COVID-19 , Adult , Hospital Mortality , Humans , Prognosis , Prospective Studies , Retrospective Studies , Risk Factors , SARS-CoV-2
4.
J Thromb Haemost ; 20(7): 1515-1517, 2022 Jul.
Article in English | MEDLINE | ID: covidwho-1927615
5.
Intern Emerg Med ; 2022 Jun 26.
Article in English | MEDLINE | ID: covidwho-1906505

ABSTRACT

Despite vaccination programs, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection remains a public health problem. Identifying key prognostic determinants of severity of the disease may help better focus health resources. The negative prognostic role for metabolic and hepatic alterations is established; however, the interplay among different metabolic comorbidities and their interconnections with the liver have never been explored.The objective of this study is to evaluate the impact of liver alterations in addition to metabolic comorbidities as a predictor of SARS-CoV-2 severity. 382 SARS-CoV-2 patients were enrolled. Severe SARS-CoV-2 was diagnosed according to international consensus. Transaminases > 2 times the upper limit of normality (2ULN), hepatic steatosis (by ultrasound and/or computed tomography in 133 patients), and FIB-4 defined liver alterations. All data were collected on admission. The results are severe SARS-CoV-2 infection in 156 (41%) patients (mean age 65 ± 17; 60%males). Prevalence of obesity was 25%; diabetes, 17%; hypertension, 44%; dyslipidaemia, 29%; with 13% of the cohort with ≥ 3 metabolic alterations. Seventy patients (18%) had transaminases > 2ULN, 82 (62%) steatosis; 199 (54%) had FIB-4 < 1.45 and 45 (12%) > 3.25. At multivariable analysis, ≥ 3 metabolic comorbidities (OR 4.1, CI 95% 1.8-9.1) and transaminases > 2ULN (OR 2.6, CI 95% 1.3-6.7) were independently associated with severe SARS-CoV-2. FIB-4 < 1.45 was a protective factor (OR 0.42, CI 95% 0.23-0.76). Hepatic steatosis had no impact on disease course. The presence of metabolic alterations is associated with severe SARS-CoV-2 infection, and the higher the number of coexisting comorbidities, the higher the risk of severe disease. Normal FIB-4 values are inversely associated with advanced SARS-CoV-2 regardless of metabolic comorbidities, speculating on use of these values to stratify the risk of severe infection.

6.
Rheumatol Ther ; 9(4): 1213-1219, 2022 Aug.
Article in English | MEDLINE | ID: covidwho-1889112

ABSTRACT

Thrombocytopenia is a common feature of antiphospholipid syndrome (APS) and rarely requires treatment. Here we present the case of a 71-year-old man hospitalized for severe immune thrombocytopenia (ITP) secondary to APS and concomitant SARS-CoV-2 infection. The patient was successfully treated with systemic corticosteroids, intravenous immunoglobulins, and plasma exchange (PEX). Few data are published on the use of plasma exchange in the treatment of thrombocytopenia in non-catastrophic APS. In the setting of acute infection when immunosuppressive therapies might be contraindicated, plasma exchange may be considered an effective therapeutic option. SARS-CoV-2 infection may be a trigger for a relapse of immune thrombocytopenia.

7.
Microorganisms ; 10(6)2022 Jun 10.
Article in English | MEDLINE | ID: covidwho-1884281

ABSTRACT

The severity of coronavirus disease 2019 (COVID-19) may be influenced by pre-existing immune responses against endemic coronaviruses, but conflicting data have been reported. We studied 148 patients who were hospitalised because of a confirmed diagnosis of COVID-19, classified mild in 58, moderate in 44, and severe in 46. The controls were 27 healthy subjects. At admission, blood samples were collected for the measurement of biomarkers of disease severity and levels of the IgG against the receptor-binding domain (RBD) of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and pre-existing coronaviruses OC43, HKU1, NL63 and 229E. Higher levels of IgG antibodies against the RBD of pre-existing coronavirus (with the highest significance for anti-HKU1 IgG, p = 0.01) were found in patients with mild disease, compared with those with moderate or severe disease. Multivariable logistic regression confirmed the association of high levels of antibodies to pre-existing coronavirus with mild disease and showed their associations with low levels of the complement activation marker SC5b-9 (p range = 0.007-0.05). High levels of anti-NL63 antibodies were associated with low levels of the coagulation activation marker D-dimer (p = 0.04), while high levels of IgG against 229E were associated with low levels of the endothelial activation marker von Willebrand factor (p = 0.05). Anti-SARS-CoV-2-neutralising activity of plasma positively correlated with anti-SARS-CoV-2 IgG (r = 0.53, p = 0.04) and with anti-HKU1 IgG (r = 0.51, p = 0.05). In hospitalised patients with COVID-19, high levels of antibodies to pre-existing coronaviruses are associated with mild disease, suggesting that their measurement could be useful in predicting the severity of the disease.

8.
PLoS One ; 17(2): e0263705, 2022.
Article in English | MEDLINE | ID: covidwho-1869155

ABSTRACT

The world is experiencing one of the most severe viral outbreaks in the last few years, the pandemic infection by SARS-CoV-2, the causative agent of COVID-19 disease. As of December 10th 2021, the virus has spread worldwide, with a total number of more than 267 million of confirmed cases (four times more in the last year), and more than 5 million deaths. A great effort has been undertaken to molecularly characterize the virus, track the spreading of different variants across the globe with the aim to understand the potential effects in terms of transmission capability and different fatality rates. Here we focus on the genomic diversity and distribution of the virus in the early stages of the pandemic, to better characterize the origin of COVID-19 and to define the geographical and temporal evolution of genetic clades. By performing a comparative analysis of 75401 SARS-CoV-2 reported sequences (as of December 2020), using as reference the first viral sequence reported in Wuhan in December 2019, we described the existence of 26538 genetic variants, the most frequent clustering into four major clades characterized by a specific geographical distribution. Notably, we found the most frequent variant, the previously reported missense p.Asp614Gly in the S protein, as a single mutation in only three patients, whereas in the large majority of cases it occurs in concomitance with three other variants, suggesting a high linkage and that this variant alone might not provide a significant selective advantage to the virus. Moreover, we evaluated the presence and the distribution in our dataset of the mutations characterizing the so called "british variant", identified at the beginning of 2021, and observed that 9 out of 17 are present only in few sequences, but never in linkage with each other, suggesting a synergistic effect in this new viral strain. In summary, this is a large-scale analysis of SARS-CoV-2 deposited sequences, with a particular focus on the geographical and temporal evolution of genetic clades in the early phase of COVID-19 pandemic.


Subject(s)
Genetic Variation , SARS-CoV-2/genetics , COVID-19/virology , Evolution, Molecular , Genome, Viral , Genomics , Haplotypes , Humans , Mutation , Pandemics , Phylogeny , Phylogeography , Spike Glycoprotein, Coronavirus/genetics
9.
EuropePMC; 2022.
Preprint in English | EuropePMC | ID: ppcovidwho-330161

ABSTRACT

Background The coronavirus disease 2019 (COVID-19) presents an urgent threat to global health. Prediction models that accurately estimate mortality risk in hospitalized patients could assist medical staff in treatment and allocating limited resources. Aims To externally validate two promising previously published risk scores that predict in-hospital mortality among hospitalized COVID-19 patients. Methods Two cohorts were available;a cohort of 1028 patients admitted to one of nine hospitals in Lombardy, Italy (the Lombardy cohort) and a cohort of 432 patients admitted to a hospital in Leiden, the Netherlands (the Leiden cohort). The primary endpoint was in-hospital mortality. All patients were adult and tested COVID-19 PCR-positive. Model discrimination and calibration were assessed. Results The C-statistic of the 4C mortality score was good in the Lombardy cohort (0.85, 95CI: 0.82-0.89) and in the Leiden cohort (0.87, 95CI: 0.80-0.94). Model calibration was acceptable in the Lombardy cohort but poor in the Leiden cohort due to the model systematically overpredicting the mortality risk for all patients. The C-statistic of the CURB-65 score was good in the Lombardy cohort (0.80, 95CI: 0.75-0.85) and in the Leiden cohort (0.82, 95CI: 0.76-0.88). The mortality rate in the CURB-65 development cohort was much lower than the mortality rate in the Lombardy cohort. A similar but less pronounced trend was found for patients in the Leiden cohort. Conclusion Although performances did not differ greatly, the 4C mortality score showed the best performance. However, because of quickly changing circumstances, model recalibration may be necessary before using the 4C mortality score.

10.
EuropePMC;
Preprint in English | EuropePMC | ID: ppcovidwho-327436

ABSTRACT

Background The coronavirus disease 2019 (COVID-19) presents an urgent threat to global health. Identification of predictors of poor outcomes will assist medical staff in treatment and allocating limited healthcare resources. Aims The primary aim was to study the value of D-dimer as a predictive marker for in-hospital mortality. Methods This was a cohort study. The study population consisted of hospitalized patients (age >18 years), who were diagnosed with COVID-19 based on real-time PCR at 9 hospitals during the first COVID-19 wave in Lombardy, Italy (Feb-May 2020). The primary endpoint was in-hospital mortality. Information was obtained from patient records. Statistical analyses were performed using a Fine-Gray competing risk survival model. Model discrimination was assessed using Harrell’s C-index and model calibration was assessed using a calibration plot. Results Out of 1049 patients, 501 patients had evaluable data. Of these 501 patients, 96 died. The cumulative incidence of in-hospital mortality within 30 days was 20% (95CI: 16%-23%), and the majority of deaths occurred within the first 10 days. A prediction model containing D-dimer as the only predictor had a C-index of 0.66 (95%CI: 0.61-0.71). Overall calibration of the model was very poor. The addition of D-dimer to a model containing age, sex and co-morbidities as predictors did not lead to any meaningful improvement in either the C-index or the calibration plot. Conclusion The predictive value of D-dimer alone was moderate, and the addition of D-dimer to a simple model containing basic clinical characteristics did not lead to any improvement in model performance.

11.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-307622

ABSTRACT

The world is experiencing one of the most severe viral outbreaks in the last years, the pandemic infection by SARS-COV-2, causative agent of COVID-19 disease. The virus reached over 120 countries, with a total number of 6.5 million infected, and 320000 deaths. A deeper understanding of its genomic diversity is mandatory.We analyzed 21296 SARS-COV-2 reported sequences, defining the existence of recurrent haplotypes and their specific geographical distribution.

12.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-312915

ABSTRACT

BACKGROUND. Aim of the study is to evaluate the incidence of DVT in COVID-19 patients and its correlation with the severity of the disease and with clinical and laboratory findings. METHODS. 234 symptomatic patients with COVID-19, diagnosed according to the World Health Organization guidelines, were included in the study. The severity of the disease was classified as moderate, severe and critical. Doppler ultrasound (DUS) was performed in all patients. DUS findings, clinical, laboratory’s and therapeutic variables were investigated by contingency tables, Pearson chi square test and by Student T test and Fisher's exact test. ROC curve analysis was applied to study significant continuous variables. RESULTS. Overall incidence of DVT was 10.7% (25/234): 1.6% (1/60) among moderate cases, 13.8% (24/174) in severely and critically ill patients. Prolonged bedrest and intensive care unit admission were significantly associated with the presence of DVT (19.7%). Fraction of inspired oxygen, P/F ratio, respiratory rate, heparin administration, D-dimer, IL-6, ferritin and CRP showed correlation with DVT. CONCLUSIONS. DUS may be considered a useful and valid tool for early identification of DVT. In less severely affected patients, DUS as screening of DVT might be unnecessary. High rate of DVT found in severe patients and its correlation with respiratory parameters and some significant laboratory findings suggests that these can be used as a screening tool for patients who should be getting DUS.

13.
Eur J Clin Invest ; 52(5): e13753, 2022 May.
Article in English | MEDLINE | ID: covidwho-1673057

ABSTRACT

BACKGROUND: Biomarkers are used for diagnosis, risk stratification and medical decisions. Copeptin and mid-regional proadrenomedullin (MR-proADM) are markers of stress and endothelial function, respectively, which have been studied in pneumonia, sepsis and septic shock. This study aimed to assess whether copeptin and MR-proADM could predict coronavirus disease 2019 (COVID-19) in-hospital outcomes, that is multi-system complications, length of stay and mortality. METHODS: Copeptin and MR-proADM were assessed at admission in 116 patients hospitalized with COVID-19. Data were retrospectively extracted from an online database. The primary endpoint was in-hospital mortality. The secondary endpoints were in-hospital complications, the composite outcome 'death, or admission to intensive care unit, or in-hospital complications', and length of stay. The predictive power was expressed as area under the receiver operator characteristic curve (AUROC). RESULTS: Copeptin was increased in non-survivors (median 29.7 [interquartile range 13.0-106.2] pmol/L) compared to survivors (10.9 [5.9-25.3] pmol/L, p < 0.01). The AUROC for mortality was 0.71, with a hazard ratio of 3.67 (p < 0.01) for copeptin values > 25.3 pmol/L. MR-proADM differentiated survivors (0.8 [0.6-1.1] nmol/L) from non-survivors (1.5 [1.1-2.8] nmol/L, p < 0.001) and yielded a AUROC of 0.79 and a hazard ratio of 7.02 (p < 0.001) for MR-proADM values > 1.0 nmol/L. Copeptin and MR-proADM predicted sepsis (AUROC 0.95 and 0.96 respectively), acute kidney injury (0.87 and 0.90), the composite outcome (0.69 and 0.75) and length of stay (r = 0.42, p < 0.001, and r = 0.46, p < 0.001). CONCLUSIONS: Admission MR-proADM and copeptin may be implemented for early risk stratification in COVID-19-hospitalized patients to help identify those eligible for closer monitoring and care intensification.


Subject(s)
COVID-19 , Sepsis , Adrenomedullin , Biomarkers , COVID-19/diagnosis , Humans , Prognosis , Prospective Studies , Protein Precursors , Retrospective Studies
14.
Nat Rev Cardiol ; 19(7): 475-495, 2022 07.
Article in English | MEDLINE | ID: covidwho-1632773

ABSTRACT

Coronavirus disease 2019 (COVID-19) predisposes patients to thrombotic and thromboembolic events, owing to excessive inflammation, endothelial cell activation and injury, platelet activation and hypercoagulability. Patients with COVID-19 have a prothrombotic or thrombophilic state, with elevations in the levels of several biomarkers of thrombosis, which are associated with disease severity and prognosis. Although some biomarkers of COVID-19-associated coagulopathy, including high levels of fibrinogen and D-dimer, were recognized early during the pandemic, many new biomarkers of thrombotic risk in COVID-19 have emerged. In this Consensus Statement, we delineate the thrombotic signature of COVID-19 and present the latest biomarkers and platforms to assess the risk of thrombosis in these patients, including markers of platelet activation, platelet aggregation, endothelial cell activation or injury, coagulation and fibrinolysis as well as biomarkers of the newly recognized post-vaccine thrombosis with thrombocytopenia syndrome. We then make consensus recommendations for the clinical use of these biomarkers to inform prognosis, assess disease acuity, and predict thrombotic risk and in-hospital mortality. A thorough understanding of these biomarkers might aid risk stratification and prognostication, guide interventions and provide a platform for future research.


Subject(s)
COVID-19 , Thrombosis , Biomarkers , COVID-19/complications , Humans , Pandemics , SARS-CoV-2 , Thrombosis/diagnosis , Thrombosis/etiology
16.
J Autoimmun ; 124: 102728, 2021 11.
Article in English | MEDLINE | ID: covidwho-1440155

ABSTRACT

Extremely rare reactions characterized by thrombosis and thrombocytopenia have been described in subjects that received ChAdOx1 nCoV-19 vaccination 5-16 days earlier. Although patients with vaccine-induced thrombotic thrombocytopenia (VITT) have high levels of antibodies to platelet factor 4 (PF4)-polyanion complexes, the exact mechanism of the development of thrombosis is still unknown. Here we reported serum studies as well as proteomics and genomics analyses demonstrating a massive complement activation potentially linked to the presence of anti-PF4 antibodies in a patient with severe VITT. At admission, complement activity of the classical and lectin pathways were absent (0% for both) with normal levels of the alternative pathway (73%) in association with elevated levels of the complement activation marker sC5b-9 (630 ng/mL [n.v. 139-462 ng/mL]) and anti-PF4 IgG (1.918 OD [n.v. 0.136-0.300 OD]). The immunoblotting analysis of C2 showed the complete disappearance of its normal band at 110 kDa. Intravenous immunoglobulin treatment allowed to recover complement activity of the classical pathway (91%) and lectin pathway (115%), to reduce levels of sC5b-9 (135 ng/mL) and anti-PF4 IgG (0.681 OD) and to normalize the C2 pattern at immunoblotting. Proteomics and genomics analyses in addition to serum studies showed that the absence of complement activity during VITT was not linked to alterations of the C2 gene but rather to a strong complement activation leading to C2 consumption. Our data in a single patient suggest monitoring complement parameters in other VITT patients considering also the possibility to target complement activation with specific drugs.


Subject(s)
COVID-19 Vaccines/adverse effects , COVID-19/prevention & control , Complement C2 , Complement Membrane Attack Complex , Complement Pathway, Classical , Complement Pathway, Mannose-Binding Lectin , Purpura, Thrombotic Thrombocytopenic , SARS-CoV-2 , Adult , Autoantibodies/blood , COVID-19 Vaccines/administration & dosage , Complement C2/genetics , Complement C2/metabolism , Complement Membrane Attack Complex/genetics , Complement Membrane Attack Complex/metabolism , Complement Pathway, Classical/drug effects , Complement Pathway, Classical/genetics , Complement Pathway, Mannose-Binding Lectin/drug effects , Complement Pathway, Mannose-Binding Lectin/genetics , Female , Humans , Platelet Factor 4/blood , Purpura, Thrombotic Thrombocytopenic/blood , Purpura, Thrombotic Thrombocytopenic/chemically induced , Purpura, Thrombotic Thrombocytopenic/genetics
17.
Vaccines (Basel) ; 9(9)2021 Sep 11.
Article in English | MEDLINE | ID: covidwho-1411056

ABSTRACT

Urticarial eruptions and angioedema are the most common cutaneous reactions in patients undergoing mRNA COVID-19 vaccinations. The vasoactive peptide bradykinin has long been known to be involved in angioedema and recently also in urticaria. Bradykinin is mainly catabolized by angiotensin-converting enzyme (ACE), which is inhibited by ACE inhibitors, a commonly employed class of antihypertensive drugs. We evaluated the risk of developing urticaria/angioedema after inoculation with the BNT162b2 mRNA COVID-19 vaccine in a population of 3586 health care workers. The influences of ACE inhibitors and selected potential confounding variables (sex, age, previous SARS-CoV-2 infection, and allergy history) were evaluated by fitting univariate and multivariable Poisson regression models. The overall cumulative incidence of urticaria/angioedema was 1.8% (65 out of 3586; 95% CI: 1.4-2.3%). Symptoms were mild, and no subject consulted a physician. Subjects taking ACE inhibitors had an adjusted three-fold increased risk of urticaria/angioedema (RR 2.98, 95% CI: 1.12-7.96). When we restricted the analysis to those aged 50 years or more, the adjusted RR was 3.98 (95% CI: 1.44-11.0). In conclusion, our data indicate that subjects taking ACE inhibitors have an increased risk of urticaria/angioedema after vaccination with the BNT162b2 mRNA COVID-19 vaccine. Symptoms are mild and self-limited; however, they should be considered to adequately advise subjects undergoing vaccination.

18.
Microbiol Spectr ; 9(2): e0054921, 2021 10 31.
Article in English | MEDLINE | ID: covidwho-1381170

ABSTRACT

In one year of the coronavirus disease 2019 (COVID-19) pandemic, many studies have described the different metabolic changes occurring in COVID-19 patients, linking these alterations to the disease severity. However, a complete metabolic signature of the most severe cases, especially those with a fatal outcome, is still missing. Our study retrospectively analyzes the metabolome profiles of 75 COVID-19 patients with moderate and severe symptoms admitted to Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico (Lombardy Region, Italy) following SARS-CoV-2 infection between March and April 2020. Italy was the first Western country to experience COVID-19, and the Lombardy Region was the epicenter of the Italian COVID-19 pandemic. This cohort shows a higher mortality rate compared to others; therefore, it represents a unique opportunity to investigate the underlying metabolic profiles of the first COVID-19 patients in Italy and to identify the potential biomarkers related to the disease prognosis and fatal outcome. IMPORTANCE Understanding the metabolic alterations occurring during an infection is a key element for identifying potential indicators of the disease prognosis, which are fundamental for developing efficient diagnostic tools and offering the best therapeutic treatment to the patient. Here, exploiting high-throughput metabolomics data, we identified the first metabolic profile associated with a fatal outcome, not correlated with preexisting clinical conditions or the oxygen demand at the moment of diagnosis. Overall, our results contribute to a better understanding of COVID-19-related metabolic disruption and may represent a useful starting point for the identification of independent prognostic factors to be employed in therapeutic practice.


Subject(s)
Blood Chemical Analysis , COVID-19/epidemiology , COVID-19/mortality , Energy Metabolism/physiology , Metabolome/physiology , Aged , Aged, 80 and over , Biomarkers/blood , Comorbidity , Female , Humans , Italy/epidemiology , Male , Middle Aged , Prognosis , Retrospective Studies , SARS-CoV-2
19.
J Thromb Haemost ; 19(10): 2554-2558, 2021 10.
Article in English | MEDLINE | ID: covidwho-1348160

ABSTRACT

BACKGROUND: Real-world experience with adenoviral vector vaccines against COVID-19 raised some safety concerns. Cases of cerebral vein thrombosis (CVT) associated with thrombocytopenia have been observed after the first dose of the adenoviral vector vaccines CHADOX1 NCOV-19 and AD26.COV2.S. OBJECTIVES: To assess the reporting rate of CVT as adverse drug reaction (ADR) for the COVID-19 vaccines authorized in Europe. PATIENTS AND METHODS: This observational study assessed the CVT reporting rate attributed to four COVID-19 vaccines authorized in Europe, namely Tozinameran (Pfizer-Biontech), CX-024414 (Moderna), CHADOX1 NCOV-19 (AstraZeneca), and AD26.COV2.S (Janssen). Data on thrombotic ADRs reported on EudraVigilance database between January 1, 2021 and July 30, 2021, were collected. ADRs referring to CVT were identified. The reporting rate of CVT was expressed as 1 million individual vaccinated-days with 95% confidence interval. Finally, an observed-to-expected (OE) analysis was performed. RESULTS: The reporting rate of CVT per 1 million person vaccinated-days was 1.92 (95% confidence interval [CI], 1.71-2.12) for Tozinameran, 5.63 (95% CI, 4.74-6.64) for CX-024414, 21.60 (95% CI, 20.16-23.11) for CHADOX1 NCOV-19, and 11.48 (95% CI, 9.57-13.67) for AD26.COV2.S. CVT occurred alongside thrombocytopenia for the four vaccines. The OE ratio was greater than one for all four vaccines, both with the lowest and the highest CVT background incidence. CONCLUSIONS: This report on EudraVigilance data strengthens anecdotal findings on CVT following COVID-19 vaccinations. Although the European Medicines Agency released an alert only for CHADOX1 NCOV-19 and AD26.COV2.S, Tozinameran and CX-024414 also are complicated by CVT, albeit to lesser extent.


Subject(s)
COVID-19 , Drug-Related Side Effects and Adverse Reactions , Thrombosis , Vaccines , COVID-19 Vaccines , Europe , Humans , SARS-CoV-2
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