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2.
Rheumatology international ; 2022.
Article in English | PMC | ID: covidwho-1820920

ABSTRACT

Since the late 1990s, tumor necrosis factor alpha (TNF-α) inhibitors (anti-TNFs) have revolutionized the therapy of immune-mediated inflammatory diseases (IMIDs) affecting the gut, joints, skin and eyes. Although the therapeutic armamentarium in IMIDs is being constantly expanded, anti-TNFs remain the cornerstone of their treatment. During the second decade of their application in clinical practice, a large body of additional knowledge has accumulated regarding various aspects of anti-TNF-α therapy, whereas new indications have been added. Recent experimental studies have shown that anti-TNFs exert their beneficial effects not only by restoring aberrant TNF-mediated immune mechanisms, but also by de-activating pathogenic fibroblast-like mesenchymal cells. Real-world data on millions of patients further confirmed the remarkable efficacy of anti-TNFs. It is now clear that anti-TNFs alter the physical course of inflammatory arthritis and inflammatory bowel disease, leading to inhibition of local and systemic bone loss and to a decline in the number of surgeries for disease-related complications, while anti-TNFs improve morbidity and mortality, acting beneficially also on cardiovascular comorbidities. On the other hand, no new safety signals emerged, whereas anti-TNF-α safety in pregnancy and amid the COVID-19 pandemic was confirmed. The use of biosimilars was associated with cost reductions making anti-TNFs more widely available. Moreover, the current implementation of the "treat-to-target" approach and treatment de-escalation strategies of IMIDs were based on anti-TNFs. An intensive search to discover biomarkers to optimize response to anti-TNF-α treatment is currently ongoing. Finally, selective targeting of TNF-α receptors, new forms of anti-TNFs and combinations with other agents, are being tested in clinical trials and will probably expand the spectrum of TNF-α inhibition as a therapeutic strategy for IMIDs.

3.
Mediterr J Rheumatol ; 31(Suppl 2): 288-294, 2020 Sep.
Article in English | MEDLINE | ID: covidwho-1791347

ABSTRACT

BACKGROUND: The COVID-19 pandemic is associated with emotional distress and significant disruptions in health-care services. These are key players in the development of nocebo phenomena. We aimed to investigate nocebo-prone behaviour in patients with autoimmune rheumatic diseases (ARD) amid the COVID-19 pandemic-associated lockdown. METHODS: Consecutive patients were telephone-interviewed during the COVID-19 pandemic in Greece. Clinical and socioeconomic characteristics (eg, level of education) were recorded. For nocebo behaviour, a four-item validated questionnaire (Q-No, cut-off score>15), was used. Results were compared with pre-COVID-19 Q-No scores collected from patients followed-up in our department. RESULTS: Nocebo behaviour was detected in 51/500 (10.2%) individuals. In patients with nocebo behaviour, use of anti-hypertensives was less common (17.6% vs 31.8%, p=0.04), but a higher level of education was more common (58.8% vs 35.9%, p=0.002), compared with patients with Q-No score ≤15; the latter retained statistical significance in multivariate regression analysis (p=0.009, OR [95%CI]: 2.29, [1.23-4.25]). Total Q-No scores were higher in the COVID-19-period compared to the pre-COVID-19 era [median (range); 12 (4-20) vs 11 (4-20), p=0.02]. Among 78 patients with available Q-No questionnaires in the pre-COVID-19 era, 11 (14.1%) displayed nocebo behaviour, which increased to 16 (20.5%) amid the COVID-19 pandemic. Interim development of nocebo behaviour was also associated with higher educational level (p=0.049, OR: 3.65, 95%CI: 1.005-13.268). CONCLUSION: A considerable proportion of ARD patients manifested nocebo-prone behaviour during the COVID-19 pandemic, which was more common among those with high educational level.

4.
Journal of Clinical Medicine ; 11(7):1810, 2022.
Article in English | MDPI | ID: covidwho-1762282

ABSTRACT

We aimed to search for laboratory predictors of critical COVID-19 in consecutive adults admitted in an academic center between 16 September 2020–20 December 2021. Patients were uniformly treated with low-molecular-weight heparin, and dexamethasone plus remdesivir when SpO2 < 94%. Among consecutive unvaccinated patients without underlying medical conditions (n = 241, 49 year-old median, 71% males), 22 (9.1%) developed critical disease and 2 died (0.8%). White-blood-cell counts, neutrophils, neutrophil-to-lymphocyte ratio, CRP, fibrinogen, ferritin, LDH and γ-GT at admission were each univariably associated with critical disease. ROC-defined cutoffs revealed that CRP > 61.8 mg/L, fibrinogen > 616.5 mg/dL and LDH > 380.5 U/L were each associated with critical disease development, independently of age, sex and days from symptom-onset. A score combining higher-than-cutoff CRP (0/2), LDH (0/1) and fibrinogen (0/1) predicted critical disease (AUC: 0.873, 95% CI: 0.820–0.926). This score performed well in an unselected patient cohort (n = 1228, 100% unvaccinated) predominantly infected by the alpha variant (AUC: 0.718, 95% CI: 0.683–0.753), as well as in a mixed cohort (n = 527, 65% unvaccinated) predominantly infected by the delta variant (AUC: 0.708, 95% CI: 0.656–0.760). Therefore, we propose that a combination of standard biomarkers of acute inflammatory response, cell death and hypercoagulability reflects the severity of COVID-19 per se independently of comorbidities, age and sex, being of value for risk stratification in unselected patients.

5.
Diagnostics (Basel) ; 12(3)2022 Mar 16.
Article in English | MEDLINE | ID: covidwho-1760432

ABSTRACT

Background and Motivation: Cardiovascular disease (CVD) causes the highest mortality globally. With escalating healthcare costs, early non-invasive CVD risk assessment is vital. Conventional methods have shown poor performance compared to more recent and fast-evolving Artificial Intelligence (AI) methods. The proposed study reviews the three most recent paradigms for CVD risk assessment, namely multiclass, multi-label, and ensemble-based methods in (i) office-based and (ii) stress-test laboratories. Methods: A total of 265 CVD-based studies were selected using the preferred reporting items for systematic reviews and meta-analyses (PRISMA) model. Due to its popularity and recent development, the study analyzed the above three paradigms using machine learning (ML) frameworks. We review comprehensively these three methods using attributes, such as architecture, applications, pro-and-cons, scientific validation, clinical evaluation, and AI risk-of-bias (RoB) in the CVD framework. These ML techniques were then extended under mobile and cloud-based infrastructure. Findings: Most popular biomarkers used were office-based, laboratory-based, image-based phenotypes, and medication usage. Surrogate carotid scanning for coronary artery risk prediction had shown promising results. Ground truth (GT) selection for AI-based training along with scientific and clinical validation is very important for CVD stratification to avoid RoB. It was observed that the most popular classification paradigm is multiclass followed by the ensemble, and multi-label. The use of deep learning techniques in CVD risk stratification is in a very early stage of development. Mobile and cloud-based AI technologies are more likely to be the future. Conclusions: AI-based methods for CVD risk assessment are most promising and successful. Choice of GT is most vital in AI-based models to prevent the RoB. The amalgamation of image-based strategies with conventional risk factors provides the highest stability when using the three CVD paradigms in non-cloud and cloud-based frameworks.

6.
Biochim Biophys Acta Mol Basis Dis ; 1868(6): 166393, 2022 Jun 01.
Article in English | MEDLINE | ID: covidwho-1748209

ABSTRACT

Immune senescence in the elderly has been associated with chronic oxidative stress and DNA damage accumulation. Herein we tested the hypothesis that increased endogenous DNA damage and oxidative stress in peripheral blood mononuclear cells of older adults associate with diminished humoral immune response to SARS-CoV-2 vaccination. Increased oxidative stress and DNA double-strand breaks (DSBs) were detected in 9 non-immunocompromised individuals aged 80-96 years compared to 11 adults aged 27-44 years, before, as well as on days 1 and 14 after the first dose, and on day 14 after the second dose of the BNT162B2-mRNA vaccine (all p < 0.05). SARS-CoV-2 vaccination induced a resolvable increase in oxidative stress and DNA damage, but individual DSB-repair efficiency was unaffected by vaccination irrespective of age, confirming vaccination safety. Individual titers of anti-Spike-Receptor Binding Domain (S-RBD)-IgG antibodies, and the neutralizing capacity of circulating anti-SARS-CoV-2 antibodies, measured on day 14 after the second dose in all participants, correlated inversely with the corresponding pre-vaccination endogenous oxidative stress and DSB levels (all p < 0.05). In particular, a strong inverse correlation of individual pre-vaccination DSB levels with both the respective anti-S-RBD-IgG antibodies titers (r = -0.867) and neutralizing capacity of circulating anti-SARS-CoV-2 antibodies (r = -0.983) among the 9 older adults was evident. These findings suggest that humoral responses to SARS-CoV-2 vaccination may be weaker when immune cells are under oxidative and/or genomic stress. Whether such measurements may serve as biomarkers of vaccine efficacy in older adults warrants further studies.


Subject(s)
COVID-19 , Adult , Aged , Aged, 80 and over , COVID-19/prevention & control , COVID-19 Vaccines/adverse effects , DNA Damage , Humans , Leukocytes, Mononuclear , Oxidative Stress , SARS-CoV-2 , Vaccination , Vaccines, Synthetic
8.
Endocrine ; 75(2): 317-327, 2022 02.
Article in English | MEDLINE | ID: covidwho-1639291

ABSTRACT

PURPOSE: The beneficial effect of glucocorticoids in coronavirus disease (COVID-19) is established, but whether adrenal cortisol secretion is impaired in COVID-19 is not fully elucidated. In this case-control study, we investigated the diurnal free bioavailable salivary cortisol secretion in COVID-19 patients. METHODS: Fifty-two consecutive COVID-19 patients-before dexamethasone treatment in cases required-recruited between April 15 to June 15, 2021, (NCT04988269) at Laikon Athens University-Hospital, and 33 healthy age- and sex-matched controls were included. Diurnal salivary cortisol (8 a.m., 12, 6, and 10 p.m.), plasma adrenocorticotropin (ACTH) and aldosterone, and serum interleukin-6 (IL-6) and C-reactive protein (CRP) levels were assessed. Diurnal salivary dehydroepiandrosterone (DHEA) and IL-6 were also assessed in subgroups of patients. RESULTS: Median CRP and IL-6 measurements were about sixfold higher in patients than controls (both p < 0.001) Morning salivary cortisol levels did not differ between the two groups, but patients exhibited higher median levels of evening and nocturnal salivary cortisol compared to controls [0.391 (0.054, 0663) vs. 0.081 (0.054, 0.243) µg/dl, p < 0.001 and 0.183 (0.090, 0.834) vs. 0.054 (0.054, 0.332) µg/dl, p < 0.001, respectively], resulting in higher time-integrated area under the curve (AUC) (4.81 ± 2.46 vs. 2.75 ± 0.810, respectively, p < 0.001). Circulating ACTH, DHEA, and aldosterone levels were similar in patients and controls. Serum IL-6, but not ACTH levels, was strongly correlated with nocturnal cortisol salivary levels (ρ = 0.555, p < 0.001) in patients. CONCLUSIONS: Increased evening and nocturnal but not morning cortisol secretion may occur in even clinically mild COVID-19. In the context of acute viral infection (COVID-19), IL-6 may partially replace ACTH as a stimulus of the glucocorticoid-secreting adrenal zona-fasciculata without influencing the secretion of DHEA and aldosterone. CLINICAL TRIAL REGISTRATION: https://clinicaltrials.gov/ct2/show/NCT04988269?term=yavropoulou&draw=2&rank=3 (NCT04988269).


Subject(s)
COVID-19 , Interleukin-6 , Case-Control Studies , Humans , Hydrocortisone , SARS-CoV-2
9.
Viruses ; 14(1)2021 12 24.
Article in English | MEDLINE | ID: covidwho-1580409

ABSTRACT

Health-Care-Workers (HCWs) are considered at high risk for SARS-CoV-2 infection. We sought to compare rates and severity of Coronavirus disease 2019 (COVID-19) among vaccinated and unvaccinated HCWs conducting a retrospective cohort study in two tertiary Academic Hospitals, namely Laiko and Attikon, in Athens, Greece. Vaccinated by BNT162b2 Pfizer-BioNTech COVID-19 mRNA vaccine and unvaccinated HCWs were included and data were collected between 1 January 2021 and 15 September 2021. Overall, 2921 of 3219 HCWs without a history of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) infection were fully vaccinated during the study period (90.7% at each Hospital). Demographic characteristics were comparable between 102/2921 (3.5%) vaccinated and 88/298 (29.5%) unvaccinated HCWs with COVID-19, although age and occupation differed significantly. None were in need of hospital admission in the vaccinated Group, whereas in the unvaccinated Group 4/88 (4.5%) were hospitalized and one (1.1%) died. Multivariable logistic regression analysis revealed that lack of vaccination was an independent risk factor for COVID-19 with an odds ratio 11.54 (95% CI: 10.75-12.40). Vaccination hesitancy among HCWs resulted to highly increased COVID-19 rates; almost one in three unvaccinated HCWs was SARS-CoV-2 infected during the 9-month period. The absolute need of vaccination of HCWs, including boosting dose, is highlighted. Evidence should be used appropriately to overcome any hesitancy.


Subject(s)
COVID-19/epidemiology , Health Personnel/statistics & numerical data , /statistics & numerical data , Adult , COVID-19/prevention & control , Female , Greece/epidemiology , Humans , Male , Middle Aged , Retrospective Studies , Risk , SARS-CoV-2/immunology , Severity of Illness Index , Tertiary Care Centers , Vaccination/statistics & numerical data
10.
Diagnostics (Basel) ; 11(12)2021 Dec 15.
Article in English | MEDLINE | ID: covidwho-1572404

ABSTRACT

(1) Background: COVID-19 computed tomography (CT) lung segmentation is critical for COVID lung severity diagnosis. Earlier proposed approaches during 2020-2021 were semiautomated or automated but not accurate, user-friendly, and industry-standard benchmarked. The proposed study compared the COVID Lung Image Analysis System, COVLIAS 1.0 (GBTI, Inc., and AtheroPointTM, Roseville, CA, USA, referred to as COVLIAS), against MedSeg, a web-based Artificial Intelligence (AI) segmentation tool, where COVLIAS uses hybrid deep learning (HDL) models for CT lung segmentation. (2) Materials and Methods: The proposed study used 5000 ITALIAN COVID-19 positive CT lung images collected from 72 patients (experimental data) that confirmed the reverse transcription-polymerase chain reaction (RT-PCR) test. Two hybrid AI models from the COVLIAS system, namely, VGG-SegNet (HDL 1) and ResNet-SegNet (HDL 2), were used to segment the CT lungs. As part of the results, we compared both COVLIAS and MedSeg against two manual delineations (MD 1 and MD 2) using (i) Bland-Altman plots, (ii) Correlation coefficient (CC) plots, (iii) Receiver operating characteristic curve, and (iv) Figure of Merit and (v) visual overlays. A cohort of 500 CROATIA COVID-19 positive CT lung images (validation data) was used. A previously trained COVLIAS model was directly applied to the validation data (as part of Unseen-AI) to segment the CT lungs and compare them against MedSeg. (3) Result: For the experimental data, the four CCs between COVLIAS (HDL 1) vs. MD 1, COVLIAS (HDL 1) vs. MD 2, COVLIAS (HDL 2) vs. MD 1, and COVLIAS (HDL 2) vs. MD 2 were 0.96, 0.96, 0.96, and 0.96, respectively. The mean value of the COVLIAS system for the above four readings was 0.96. CC between MedSeg vs. MD 1 and MedSeg vs. MD 2 was 0.98 and 0.98, respectively. Both had a mean value of 0.98. On the validation data, the CC between COVLIAS (HDL 1) vs. MedSeg and COVLIAS (HDL 2) vs. MedSeg was 0.98 and 0.99, respectively. For the experimental data, the difference between the mean values for COVLIAS and MedSeg showed a difference of <2.5%, meeting the standard of equivalence. The average running times for COVLIAS and MedSeg on a single lung CT slice were ~4 s and ~10 s, respectively. (4) Conclusions: The performances of COVLIAS and MedSeg were similar. However, COVLIAS showed improved computing time over MedSeg.

11.
Front Biosci (Landmark Ed) ; 26(11): 1312-1339, 2021 11 30.
Article in English | MEDLINE | ID: covidwho-1552205

ABSTRACT

Background: Atherosclerosis is the primary cause of the cardiovascular disease (CVD). Several risk factors lead to atherosclerosis, and altered nutrition is one among those. Nutrition has been ignored quite often in the process of CVD risk assessment. Altered nutrition along with carotid ultrasound imaging-driven atherosclerotic plaque features can help in understanding and banishing the problems associated with the late diagnosis of CVD. Artificial intelligence (AI) is another promisingly adopted technology for CVD risk assessment and management. Therefore, we hypothesize that the risk of atherosclerotic CVD can be accurately monitored using carotid ultrasound imaging, predicted using AI-based algorithms, and reduced with the help of proper nutrition. Layout: The review presents a pathophysiological link between nutrition and atherosclerosis by gaining a deep insight into the processes involved at each stage of plaque development. After targeting the causes and finding out results by low-cost, user-friendly, ultrasound-based arterial imaging, it is important to (i) stratify the risks and (ii) monitor them by measuring plaque burden and computing risk score as part of the preventive framework. Artificial intelligence (AI)-based strategies are used to provide efficient CVD risk assessments. Finally, the review presents the role of AI for CVD risk assessment during COVID-19. Conclusions: By studying the mechanism of low-density lipoprotein formation, saturated and trans fat, and other dietary components that lead to plaque formation, we demonstrate the use of CVD risk assessment due to nutrition and atherosclerosis disease formation during normal and COVID times. Further, nutrition if included, as a part of the associated risk factors can benefit from atherosclerotic disease progression and its management using AI-based CVD risk assessment.


Subject(s)
Arteries/diagnostic imaging , Atherosclerosis/diagnostic imaging , COVID-19/physiopathology , Cardiovascular Diseases/diagnostic imaging , Nutritional Status , Algorithms , COVID-19/diagnostic imaging , COVID-19/virology , Humans , Risk Factors , SARS-CoV-2/isolation & purification
12.
Vaccines (Basel) ; 9(10)2021 Oct 14.
Article in English | MEDLINE | ID: covidwho-1526864

ABSTRACT

Among healthcare workers (HCWs), SARS-CoV-2 vaccine hesitancy may be linked to a higher susceptibility to nocebo effects, i.e., adverse events (AEs) experienced after medical treatments due to negative expectations. To investigate this hypothesis a cross-sectional survey was performed with a self-completed questionnaire that included a tool (Q-No) for the identification of nocebo-prone individuals. A total of 1309 HCWs (67.2% women; 43.4% physicians; 28.4% nurses; 11.5% administrative staff; 16.6% other personnel) completed the questionnaires, among whom 237 (18.1%) had declined vaccination. Q-No scores were ≥15 in 325 participants (24.8%) suggesting nocebo-prone behavior. In a multivariate logistic regression model with Q-No score, age, gender, and occupation as independent variables, estimated odds ratios (ORs) of vaccination were 0.43 (i.e., less likely, p < 0.001) in participants with Q-No score ≥ 15 vs. Q-No score < 15, 0.58 in females vs. males (p = 0.013), and 4.7 (i.e., more likely) in physicians vs. other HCWs (p < 0.001), independent of age, which was not significantly associated with OR of vaccination. At least one adverse effect (AE) was reported by 67.5% of vaccinees, mostly local pain and flu-like symptoms. In a multivariate logistic regression model, with Q-No score, age, gender, and occupation as independent variables, estimated ORs of AE reporting were 2.0 in females vs. males (p < 0.001) and 1.47 in physicians vs. other HCWs (p = 0.017) independently of age and Q-No score, which were not significantly associated with OR of AE. These findings suggest that nocebo-prone behavior in HCWs is associated with SARS-CoV-2 vaccination hesitancy indicating a potential benefit of a campaign focused on nocebo-prone people.

13.
Ann Rheum Dis ; 2021 Nov 10.
Article in English | MEDLINE | ID: covidwho-1511430

ABSTRACT

OBJECTIVE: Τo report outcomes of breakthrough COVID-19 in comparison with COVID-19 in unvaccinated patients with systemic rheumatic diseases (SRDs). METHODS: Patients with SRD with COVID-19 (vaccinated and unvaccinated) were included by their rheumatologists in a registry operated by the Greek Rheumatology Society in a voluntarily basis. Type, date and doses of SARS-CoV-2 vaccines were recorded, and demographics, type of SRD, concurrent treatment, comorbidities and COVID-19 outcomes (hospitalisation, need for oxygen supplementation and death) were compared between vaccinated and unvaccinated patients. RESULTS: Between 1 March 2020 and 31 August 2021, 195 patients with SRD with COVID-19 were included; 147 unvaccinated and 48 vaccinated with at least one dose of a SARS-CoV-2 vaccine (Pfizer n=38 or AstraZeneca n=10). Among vaccinated patients, 29 developed breakthrough COVID-19 >14 days after the second vaccine dose (fully vaccinated), while 19 between the first and <14 days after the second vaccine dose (partially vaccinated). Despite no differences in demographics, SRD type, treatment or comorbidities between unvaccinated and vaccinated patients, hospitalisation and mortality rates were higher in unvaccinated (29.3% and 4.1%, respectively) compared with partially vaccinated (21% and 0%) or fully vaccinated (10.3% and 0%) patients. CONCLUSIONS: Vaccinated patients with SRD with breakthrough COVID-19 have better outcomes compared with unvaccinated counterparts with similar disease/treatment characteristics.

14.
RMD Open ; 7(3)2021 11.
Article in English | MEDLINE | ID: covidwho-1504941

ABSTRACT

OBJECTIVES: To compare current all-cause mortality rates in rheumatoid arthritis (RA), ankylosing spondylitis (AS), psoriatic arthritis (PsA), systemic lupus erythematosus (SLE) and systemic sclerosis (SSc) versus general population. METHODS: In this population-based, retrospective cohort study, anonymised data on 11 186 586 citizens, including all patients with RA (42 735, 79% female), AS (9707, 43% female), PsA (13 779, 55% female), SLE (10 440, 89% female) and SSc (2277, 88% female), (median age of 64/47/54/53/59 years at study entry, respectively), under prescribed treatment between 2015 and 2019, were extracted from the electronic database covering nearly 99% of the Greek population. RESULTS: After 1:5 (patients:general population) matching for gender/age, we found that survival was worse in SSc, followed by SLE and inflammatory arthritis. Compared with the general population HRs for death increased from the first 3 years to 5 years of observation possibly due to increases in disease duration: RA (from 0.63 to 1.13 (95% CI: 1.05 to 1.22), AS (from 0.62 to 1.01, (95% CI: 0.76 to 1.33)), PsA (from 0.68 to 1.06, (95% CI: 0.88 to 1.28)), SLE (from 1.52 to 1.98, (95% CI: 1.67 to 2.33)) and SSc (from 2.27 to 4.24, (95% CI: 3.19 to 5.63)). In both SLE and SSc mortality was increased in men than women and in patients younger than 50 years. CONCLUSIONS: Survival rates over 5 years in inflammatory arthritis under treatment are currently becoming comparable (AS/PsA) or slightly higher (RA) than those of the general population. However, all-cause mortality is almost twofold and fourfold higher in SLE and SSc, respectively, being even higher for male and younger patients.


Subject(s)
Arthritis, Psoriatic , Arthritis, Rheumatoid , Lupus Erythematosus, Systemic , Rheumatic Diseases , Arthritis, Psoriatic/drug therapy , Female , Humans , Lupus Erythematosus, Systemic/drug therapy , Male , Middle Aged , Retrospective Studies , Rheumatic Diseases/drug therapy
15.
Rheumatol Int ; 42(1): 31-39, 2022 01.
Article in English | MEDLINE | ID: covidwho-1503952

ABSTRACT

OBJECTIVE: To describe the rate and type of adverse effects (AEs) and the frequency of disease flares after COVID-19 vaccination and to assess the reasons for vaccination hesitancy (non-vaccination) in SRD patients. METHODS: Telephone interviews were conducted of SRD patients consecutively enrolled (15/06/2021-1/7/2021). Participants were asked about the type of AEs and disease flare after vaccination. Reasons for vaccination hesitancy were recorded. Univariate and mutivariable analyses examined associations of demographic, clinical and other features, with occurrence of AEs, disease flare and non-vaccination. For the latter, association with negative vaccination behaviour (not influenza vaccinated for the last 2 years) and nocebo-prone behaviour (denoting AEs attributed to negative expectations [Q-No questionnaire]) was also tested. RESULTS: 561 out of 580 contacted patients were included in the study. 441/561 (78.6%) patients were vaccinated [90% (Pfizer, Moderna), 10% (Astra-Zeneca)]. AEs were reported by 148/441 (33.6%), with rates being comparable between the three vaccines. AEs were more common in females and those with chronic obstructive pulmonary disease [OR, 95% CI; females: 2.23 (1.30-3.83); COPD: 3.31 (1.24-8.83)]. Disease flare was reported in 9/441 (2%) patients. For those unvaccinated, fear that the vaccine would be harmful (53.3%), could cause disease flare (24.2%) and/or could cause thrombosis (21.7%) were the main reasons to do so. Multivariable analysis identified as independent variables for non-vaccination: nocebo-prone behaviour (OR; 95% CI, 3.88; 1.76-8.55), negative vaccination behaviour (6.56; 3.21-13.42) and previous COVID-19 infection (2.83; 1.13-7.05). Higher educational status was protective (0.49; 0.26-0.92). CONCLUSION: No new safety signals for COVID-19 vaccination were observed. Vaccination campaign should target SRD patients with nocebo-prone and negative influenza vaccination behaviour.


Subject(s)
COVID-19 Vaccines/therapeutic use , COVID-19/prevention & control , Rheumatic Diseases/immunology , Adult , Aged , COVID-19/immunology , Cross-Sectional Studies , Female , Humans , Male , Middle Aged , Nocebo Effect , Vaccination
16.
Diagnostics (Basel) ; 11(11)2021 Nov 01.
Article in English | MEDLINE | ID: covidwho-1488513

ABSTRACT

Background: For COVID-19 lung severity, segmentation of lungs on computed tomography (CT) is the first crucial step. Current deep learning (DL)-based Artificial Intelligence (AI) models have a bias in the training stage of segmentation because only one set of ground truth (GT) annotations are evaluated. We propose a robust and stable inter-variability analysis of CT lung segmentation in COVID-19 to avoid the effect of bias. Methodology: The proposed inter-variability study consists of two GT tracers for lung segmentation on chest CT. Three AI models, PSP Net, VGG-SegNet, and ResNet-SegNet, were trained using GT annotations. We hypothesized that if AI models are trained on the GT tracings from multiple experience levels, and if the AI performance on the test data between these AI models is within the 5% range, one can consider such an AI model robust and unbiased. The K5 protocol (training to testing: 80%:20%) was adapted. Ten kinds of metrics were used for performance evaluation. Results: The database consisted of 5000 CT chest images from 72 COVID-19-infected patients. By computing the coefficient of correlations (CC) between the output of the two AI models trained corresponding to the two GT tracers, computing their differences in their CC, and repeating the process for all three AI-models, we show the differences as 0%, 0.51%, and 2.04% (all < 5%), thereby validating the hypothesis. The performance was comparable; however, it had the following order: ResNet-SegNet > PSP Net > VGG-SegNet. Conclusions: The AI models were clinically robust and stable during the inter-variability analysis on the CT lung segmentation on COVID-19 patients.

17.
Front Immunol ; 12: 746203, 2021.
Article in English | MEDLINE | ID: covidwho-1477828

ABSTRACT

The reasons behind the clinical variability of SARS-CoV-2 infection, ranging from asymptomatic infection to lethal disease, are still unclear. We performed genome-wide transcriptional whole-blood RNA sequencing, bioinformatics analysis and PCR validation to test the hypothesis that immune response-related gene signatures reflecting baseline may differ between healthy individuals, with an equally robust antibody response, who experienced an entirely asymptomatic (n=17) versus clinical SARS-CoV-2 infection (n=15) in the past months (mean of 14 weeks). Among 12.789 protein-coding genes analysed, we identified six and nine genes with significantly decreased or increased expression, respectively, in those with prior asymptomatic infection relatively to those with clinical infection. All six genes with decreased expression (IFIT3, IFI44L, RSAD2, FOLR3, PI3, ALOX15), are involved in innate immune response while the first two are interferon-induced proteins. Among genes with increased expression six are involved in immune response (GZMH, CLEC1B, CLEC12A), viral mRNA translation (GCAT), energy metabolism (CACNA2D2) and oxidative stress response (ENC1). Notably, 8/15 differentially expressed genes are regulated by interferons. Our results suggest that subtle differences at baseline expression of innate immunity-related genes may be associated with an asymptomatic disease course in SARS-CoV-2 infection. Whether a certain gene signature predicts, or not, those who will develop a more efficient immune response upon exposure to SARS-CoV-2, with implications for prioritization for vaccination, warrant further study.


Subject(s)
Antibodies, Viral/blood , Asymptomatic Infections , Immunity, Innate/genetics , SARS-CoV-2/immunology , Transcriptome/genetics , Adult , COVID-19/pathology , Female , Gene Expression Profiling , Humans , Immunity, Innate/immunology , Male , RNA, Messenger/genetics , Sequence Analysis, RNA , Severity of Illness Index
18.
Diagnostics (Basel) ; 11(8)2021 Aug 04.
Article in English | MEDLINE | ID: covidwho-1341653

ABSTRACT

BACKGROUND: COVID-19 lung segmentation using Computed Tomography (CT) scans is important for the diagnosis of lung severity. The process of automated lung segmentation is challenging due to (a) CT radiation dosage and (b) ground-glass opacities caused by COVID-19. The lung segmentation methodologies proposed in 2020 were semi- or automated but not reliable, accurate, and user-friendly. The proposed study presents a COVID Lung Image Analysis System (COVLIAS 1.0, AtheroPoint™, Roseville, CA, USA) consisting of hybrid deep learning (HDL) models for lung segmentation. METHODOLOGY: The COVLIAS 1.0 consists of three methods based on solo deep learning (SDL) or hybrid deep learning (HDL). SegNet is proposed in the SDL category while VGG-SegNet and ResNet-SegNet are designed under the HDL paradigm. The three proposed AI approaches were benchmarked against the National Institute of Health (NIH)-based conventional segmentation model using fuzzy-connectedness. A cross-validation protocol with a 40:60 ratio between training and testing was designed, with 10% validation data. The ground truth (GT) was manually traced by a radiologist trained personnel. For performance evaluation, nine different criteria were selected to perform the evaluation of SDL or HDL lung segmentation regions and lungs long axis against GT. RESULTS: Using the database of 5000 chest CT images (from 72 patients), COVLIAS 1.0 yielded AUC of ~0.96, ~0.97, ~0.98, and ~0.96 (p-value < 0.001), respectively within 5% range of GT area, for SegNet, VGG-SegNet, ResNet-SegNet, and NIH. The mean Figure of Merit using four models (left and right lung) was above 94%. On benchmarking against the National Institute of Health (NIH) segmentation method, the proposed model demonstrated a 58% and 44% improvement in ResNet-SegNet, 52% and 36% improvement in VGG-SegNet for lung area, and lung long axis, respectively. The PE statistics performance was in the following order: ResNet-SegNet > VGG-SegNet > NIH > SegNet. The HDL runs in <1 s on test data per image. CONCLUSIONS: The COVLIAS 1.0 system can be applied in real-time for radiology-based clinical settings.

20.
Clin Immunol ; 229: 108765, 2021 08.
Article in English | MEDLINE | ID: covidwho-1252592

ABSTRACT

Whether and how an acute immune challenge may affect DNA Damage Response (DDR) is unknown. By studying vaccinations against Influenza and SARS-CoV-2 (mRNA-based) we found acute increases of type-I interferon-inducible gene expression, oxidative stress and DNA damage accumulation in blood mononuclear cells of 9 healthy controls, coupled with effective anti-SARS-CoV-2 neutralizing antibody production in all. Increased DNA damage after SARS-CoV-2 vaccine, partly due to increased oxidative stress, was transient, whereas the inherent DNA repair capacity was found intact. In contrast, in 26 patients with Systemic Lupus Erythematosus, who served as controls in the context of chronic immune activation, we validated increased DNA damage accumulation, increased type-I interferon-inducible gene expression and induction of oxidative stress, however aberrant DDR was associated with deficiencies in nucleotide excision repair pathways. These results indicate that acute immune challenge can indeed activate DDR pathways, whereas, contrary to chronic immune challenge, successful repair of DNA lesions occurs.


Subject(s)
Antibodies, Neutralizing/physiology , COVID-19 Vaccines/immunology , COVID-19/prevention & control , DNA Damage , Lupus Erythematosus, Systemic/immunology , SARS-CoV-2/immunology , Adolescent , Adult , Aged , COVID-19/pathology , Case-Control Studies , Female , Gene Expression Regulation/immunology , Humans , Interferon Type I/metabolism , Male , Middle Aged , Oxidative Stress , Vaccines, Synthetic/immunology , Young Adult
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