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Background: Severe COVID-19 and obesity are characterized by higher inflammation. We aimed to examine early inflammatory patterns in people with (Ob) and without (NOb) obesity and COVID-19 and how they relate to COVID-19 disease severity Methods: Ob (BMI >30 Kg/m2) and NOb with COVID-19 matched for age, sex and WHO disease severity provided blood early after diagnosis. Immunoassays measured 57 plasma biomarkers reflecting innate immune and endothelial activation, systemic inflammation, coagulation, metabolism and microbial translocation (Fig 1). Between-group differences were assessed by Mann- Whitney. Associations between subsequent maximal COVID-19 severity (mild vs moderate/severe/critical) and biomarkers were explored by logistic regression adjusted for age, sex, hypertension (HTN) and diabetes (DM). Data are median pg/mL [IQR] or n [%] unless stated Results: Of 100 subjects (50 Ob and 50 Nob) presenting between April 2020 and March 2021, characteristics (Ob vs Nob) included: age 65 [23-91] vs 65 [21-95];female sex 27 (48%) vs 28 (56%);BMI 33.7 [30.0-71.8] vs 23.3 [15.3-25.9];disease severity mild 22 [48%] vs 23 [46%], moderate 15 [30%] vs 13 [26%], severe 6 [12%] vs 7 [14%];HTN 30 (60%) vs 17 (34%);DM 19 [38%] vs 6 [12%];days from symptom onset 7 [2-17] vs 8 [1-15];vaccinated 3 (6%) vs 0 (0%). Compared to NOb, Ob had higher IFN-alpha (1.8 [0.6;11] vs 0.9 [0.1;4.7]), CRP (10 mAU/mL [9.6;10.2] vs 9.7 [7.2;10]), IL-1RA (197 [122;399] vs 138 [88;253]), IL-4 (288 AU/mL [161;424] vs 205 [82;333]), vWF (252 [166;383] vs 163 [96;318]), Zonulin (114 ng/mL [77;131] vs 57 [18;106]), Resistin (956 [569;1153] vs 727 [712;1525]), Leptin (3482 [1513;5738] vs 848 [249;2114]), and lower Adiponectin (1.12 mg/L [0.09;1.5] vs 1.5 [1.18;1.93]), all p< 0.05. In both groups higher, proinflammatory IL-18 and lower levels of antiinflammatory CCL22 and IL-5 were associated with higher odds of disease severity, and lower E-selectin with higher disease severity only in Ob. However, in NOb higher type 3 interferons (IL-28A), macrophage activation (sCD163, CCL3) and vascular inflammation markers (ICAM-1, VCAM-1), along with higher S100B, GM-CSF and leptin were also associated with disease severity, a pattern not observed in Ob (Fig 1) Conclusion(s): Although Ob had higher overall levels of inflammation than NOb, few biomarkers predicted subsequent COVID-19 severity in Ob. These differential inflammatory patterns suggest dysregulated immune responses in Ob with COVID-19. (Figure Presented).
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Background: Better understanding of host inflammatory changes that precede development of severe COVID-19 could improve delivery of available antiviral and immunomodulatory therapies, and provide insights for the development of new therapies. Method(s): In plasma from individuals with COVID-19, sampled <=10 days from symptom onset from the All-Ireland Infectious Diseases Cohort study, we measured 61 biomarkers, including markers of innate immune and T cell activation, coagulation, tissue repair, lung injury, and immune regulation. We used principal component analysis (PCA) and k-means clustering to derive biomarker clusters, and univariate and multivariate ordinal logistic regression to explore association between cluster membership and maximal disease severity, adjusting for risk factors for severe COVID-19, including age, sex, ethnicity, BMI, hypertension and diabetes. Result(s): From March 2020-April 2021, we included 312 individuals, (median (IQR) age 62 (48-77) years, 7 (4-9) days from symptom onset, 54% male) in the analysis. PCA and clustering derived 4 clusters. Compared to cluster 1, clusters 2-4 were significantly older and of higher BMI but there were no significant differences in sex or ethnicity. Cluster 1 had low levels of inflammation, cluster 2 had higher levels of markers of tissue repair and endothelial activation (EGF, VEGF, PDGF, TGFalpha, serpin E1 and p-selectin). Cluster 3 and 4 were both characterised by higher overall inflammation, but compared to cluster 4, cluster 3 had downregulation of growth factors, markers of endothelial activation, and immune regulation (IL10, PDL1), but higher alveolar epithelial injury markers (RAGE, ST2). In univariate analysis, compared to cluster 1, cluster 3 had the highest odds of severe disease (OR (95% CI) 9.02 (4.62-18.31), followed by cluster 4: 5.59 (2.75-11.72) then cluster 2: 4.5 (2.38-8.81), all p < 0.05). Cluster 3 remained most strongly associated with severe disease in fully adjusted analyses;cluster 3: OR(95% CI) 5.99 (2.69-13.35), cluster 2: 3.14 (1.54-6.42), cluster 4: 3.13 (1.36-7.19), all p< 0.05). Conclusion(s): Distinct early inflammatory profiles predicted maximal disease severity independent of known risk factors for severe COVID-19. A cluster characterised by downregulation of growth factor and endothelial markers and early evidence of alveolar injury was associated with highest risk of developing severe COVID19. Whether this reflects a dysregulated inflammatory response that could improve targeted treatment requires further study. Heatmap of biomarker derived clusters and forest plot of association between clusters and disease severity. A: Heatmap demonstrating differences in biomarkers between clusters B: Forest plot demonstrating odds ratio of specific clusters for progressing to moderate or severe disease (reference Cluster 1), calculated using ordinal logistic regression. Odds ratio (95% CI) presented as unadjusted and fully adjusted (for age, sex, ethnicity, BMI, hypertension, diabetes, immunosuppression, smoking and baseline anticoagulant use). Maximal disease severity graded per the WHO severity scale.
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Background. Which components of the immune response to SARS-CoV-2 vaccination best protect against subsequent infection remains unclear. We explored SARS-CoV-2 specific antibody and B-cell responses post 3rd dose vaccine and their relationship to subsequent SARS-CoV-2 infection. Methods. In a multicentre prospective cohort, adult subjects provided samples before and 14 days (d14) post 3rd dose vaccine with Pfizer-BioNTech 162b2. At 18-22 weeks post vaccine, subjects self-reported SARS-CoV-2 infection (confirmed by PCR or antigen test). We used electrochemiluminescence assays to quantify antibodies to SARS-CoV-2 spike subunit 1 (S1), subunit 2 (S2) and receptor-binding domain (RBD) in plasma (reported inWHOIU/mL). In a subset of subjects, we assessed SARS-CoV-2 specific differentiated B-cell (plasma cell) and memory B-cell responses from peripheral blood mononuclear cells. Unstimulated plasma cells, and memory B cells stimulated with R848 and IL2, were seeded on plates coated with RBD or full Spike antigen and antigen-specific responses measured by ELISpot (Mabtech ELISpot, Sweden). We compared between group differences by Wilcoxon signed rank or Mann-Whitney tests. Data are median [IQR] unless specified. Results. Of 133 subjects (age 43 [32-50], 81.2% female (table 1), 77 subjects in the B-cell subgroup (table 2)), 47 (35.3%) reported SARS-CoV-2 infection post 3rd vaccine. Antibody titres, plasma cell and memory B-cell responses all increased significantly at d14 post 3rd vaccine (Table 1 & 2, all P< 0.001). Although d14 antibody titres did not differ in those with and without subsequent infection (table 1), those reporting subsequent infection had significantly lower d14 RBD-specific plasma cells and a lower proportion of RBD-specific memory B-cells (Figure 1a-b, both P< 0.05). Similar results were observed with full-spike-specific memory B-cell responses (Figure 1d). The differences persisted when the non-infected group was restricted only to those reporting a confirmed close contact (n=26). Conclusion. Infection following 3rd dose vaccine is associated with lower d14 circulating and memory B cell responses, but not antibody titres, suggesting B-cell responses better predict protection against subsequent SARS-CoV-2 infection.
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Background. Quantifying neutralising capacity of circulating SARS-COV-2 antibodies is critical in evaluating protective humoral immune responses generated postinfection/post-vaccination. Here we describe a novel medium-throughput flow cytometry based micro-neutralisation assay to evaluate Neutralising Antibody (NAb) responses against live SARS-CoV-2 Wild Type (D641G) and Variants of Concern (VoC) in convalescent/vaccinated populations. Methods. Micro-Neutralisation assay (Micro-NT) was performed in 96-well plates using clinical isolate 2019-nCoV/Italy-INMI1, D641G (SARS-CoV-2/human/ IRL/AIIDV1446/2020) and/or VOCs Beta (SARS-CoV-2/human/IRL/AIIDV1752/ 2021) and Omicron (SARS-Cov-2/human/IRL/AIIDV2326/2021). Plasma samples (All Ireland Infectious Diseases (AIID) Cohort) were serially diluted (8 points, halflog) from 1/20 and pre-incubated with SARS-CoV-2 (1h, 37degreeC). Virus-plasma mixture were added onto VERO E6/VERO-E6 TMPRSS2 cells for 18h. Percentage infected cells was analysed by automated flow cytometry following trypsinisation,fixation and SARS-CoV-2 Nucleoprotein intracellular staining. Half-maximal Neutralisation Titres (NT50) was determined using four-parameter logistic regression. Our assay was compared to Plaque Reduction Neutralisation Test (PRNT) and validated against WHO anti-SARS-CoV-2 Immunoglobulin Standards. Results. Using WHO Standards with low, medium or high anti-SARS-CoV-2 IgG, both Micro-NT and PRNT achieved comparable NT50 values (Table 1). Micro-NT was found to be highly reproducible (inter-assay CV of 11.39%). Screening 190 convalescent samples and 11 COVID-19 naive controls (AIID cohort) we achieved an assay sensitivity of 90% and specificity of 81%. We demonstrated that Micro-NT has broad dynamic range differentiating NT50s < 1/20 to > 1/5000 (Figure 1). We could also characterise immune-escape VoC, observing up to 10-fold reduction in NT50 against Beta (Figure 2). Table 1: NT50s of Low, Medium and High Titre Anti-SARS-CoV-2 IgG Standards measured against Live SARS-CoV-2 using PRNT and Micro-NT Neutralising Capacity of low, medium and high-titre anti-SARS-CoV-2 IgG (WHO, International Standards) against live SARS-CoV-2 (2019-nCoV/Italy-INMI1) measured using PRNT and Micro-NT Assays on Vero E6 cells, as well as the potency of NAbs in each sample in International Units (IU/ml) as determined by the WHO. Figure 1: Dynamic Range of Micro-NT Micro-NT has a broad Dynamic Range, distinguishing low (A), medium (B) and high (C) neutralising plasma samples against live SARS-CoV-2 (2019-nCoV/Italy-INMI1) from a cohort of COVID-19 convalescent individuals (AIID cohort), as well as negative samples from COVID-19 naive samples (D). Graphs show 3 representative samples of each NT50 range. (E) shows the population distribution of 190 Convalescent plasma samples as measured by Micro-NT on Vero E6 cells. Figure 2: Reduced Neutralisation Capacities measured against SARS-CoV-2 VoC using Micro-NT Low (A), Medium (B) and High (C) anti-SARS-CoV-2 IgG (WHO Standards) show different neutralising capacities against WT (D614G) SARS-CoV-2 and variants Beta and Omicron, measured using Micro-NT on Vero-E6-TMPRSS2 cells. Conclusion. Our flow-cytometry-based Micro-NT is a robust and reliable assay to quantify NAb titres, an important evaluation endpoint in clinical trials. It has higher throughput (96 well format versus 12 well) and reduced infection time (18h vs 48-96h) compared to the gold standard PRNT.
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Background. A wide array of assays to detect the serologic response to SARS-CoV-2 have been developed since the emergence of the pandemic. The majority of these are either qualitative or semi-quantitative, detect antibodies against one antigenic target, and are not adaptable to new antigens. Methods. We developed a new, multiplex immunoassay to detect antibodies against the receptor binding domain, S1 and S2 spike subunits and nucleocapsid (N) antigens of SARS-CoV-2 (the CEPHR SARS-CoV-2 Serology Assay). This assay uses electrochemiluminescence technology which allows for a broad dynamic range, and a linker format which allows for the addition of new antigenic targets. We tested this assay on a series of biobanked samples and validated its performance against the Abbott SARS-CoV-2 IgG and Abbott SARS-CoV-2 IgG II assays, and the MesoScale Diagnostics V-PLEX SARS-CoV-2 Panel 2 Kit. Results. Participant demographics are shown in Table 1. The mean (standard deviation (SD)) intra-assay (within plate) coefficient of variation (CV) of 80 plasma samples run on the same plate was 3.9% (2.9) for N, 3.8% (6.2) for RBD, 3.8% (5.9) for S1 and 3.9% (5.3) for S2. The mean (SD) inter-assay CV derived from 5 samples run across 3 days by two different operators was 11% (6.5) for N, 13% (5.7) for RBD, 14% (8.9) for S1 and 13% (5.1) for S2. In the convalescent group (n=193), overall sensitivity for each assay was;RBD 82% (95% CI 76-87), S1 86% (81-91%), S2 88% (83 - 92%) and N 72% (64 - 78%). Sensitivity improved when analysis included only individuals who were sampled more than 14 days from onset of symptoms (n=166), RBD 87% (81 - 95%), S1 91% (85 - 95%), S2 91% (85 - 95%) but not for the N-target (73% (66-80%)). In vaccinated individuals (n = 58), 100% (94-100%) had both detectable RBD and S1 antibodies. Overall specificity was 96% (87-99%) for RBD, 90% (78-97%) for S1, 94% (84-99%) for S2 and 90% (78-97%) for N. There was excellent correlation between the Abbott IgG II and both CEPHR anti-RBD IgG (rho 0.91) and CEPHR anti-S1 IgG (rho 0.9, both p < 0.001, Figure 1.) and the V-PLEX full spike and both CEPHR RBD IgG (rho 0.83) and S1 IgG (rho 0.82, both p < 0.001, Figure 4). Conclusion. The CEPHR SARS-CoV-2 Serology Assay is a robust, customisable, multiplex serologic assay for the detection of several different IgG specific to SARS-CoV-2.
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Aims To describe readmissions of hospitalised patients with COVID-19, define predictors of readmission and explore the long term outcomes using the SF-12 score compared to patients who were not readmitted and those not hospitalised. Methods A single centre retrospective in North Inner-City Dublin. Recruitment was done through a COVID follow up clinic. Predictors of readmission and SF-12 scores at two timepoints post follow up at median 3 months and 12 months. Results Seventy (45%) participants were admitted, with a median age of 49.5 years (IQR 41.3-56.9), 36(51%) of whom were female. Unscheduled readmissions at ≤30 days in COVID-19 patients were 9(12.9%) and length of stay was four days (IQR 2-5). Readmissions were due to ongoing symptoms(n=9(64.3%)) or new complications(n=5(35.7%)). Mechanical ventilation and having symptoms of nausea and vomiting on index admission were predictive of readmission. (p=0.002). SF-12 scores at one year of readmitted patients were not different to patients who were never admitted at median one year follow up, p=.089. Conclusions Most readmissions were of short duration. Early follow up of patients post MV or who had nausea and vomiting on index admission should be prioritised. Wellbeing of readmitted patients was not different to those never hospitalised, at one year.
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COVID-19 , Adult , Female , Humans , Male , Middle Aged , Nausea , Patient Readmission , Retrospective Studies , Risk Factors , VomitingABSTRACT
Background: Although presence of SARS-CoV-2 neutralising antibodies can provide protection against development of COVID-19, how reflective circulating anti-SARS-CoV-2 antibody levels are of underlying neutralising capacity, and whether a threshold exists to predict sufficient neutralising capacity remains unclear. Methods: In plasma from individuals with PCR-confirmed COVID-19 recruited to the All Ireland Infectious Diseases Cohort Study, we measured IgG concentrations against RBD, Spike protein sub-unit 1 and 2 (S1, S2) and Nucleocapsid (NC) using multiplex electrochemiluminescence (normalised to World Health Organisation reference serum as IU/mL). Neutralising capacity was measured against live SARS-CoV-2 virus (clinical isolate 2019-nCoV/Italy-INMI1) by determining the maximum plasma dilution required to maintain 50% inhibition of infection of Vero E6 cells (50% Neutralisation Titre (NT50)), by flow cytometry-based micro-neutralisation assay. Given that the Beta SARS-CoV-2 variant of concern (VOC) reduces neutralising activity up to six fold, we estimated a NT50 of 1:1000 against wild type SARS-CoV-2 would maintain neutralising activity against VOC. We used Spearman correlation and linear regression to model relationships between NT50 and IgG concentrations. Data are presented as median (IQR) unless specified. Results: In 190 individuals (age 50 (40-64) years, 55% female, time from symptom onset 98 (35-179) days), NT50 most highly correlated with anti-RBD IgG (Rho 0.81 p<0.001, Fig 1a) compared with other IgG classes (S1;Rho 0.8, S2;0.73, NC;0.72, all p<0.001). Median RBD titre was 246 (71-662) but trended lower over time, with a median of 319 (61-1012) IU/ml at 0-90 days, 244 (86-523) IU/ml at 90-180 days and 157 (80-364) IU/ml at >180 days post symptom onset respectively (p=0.08, Fig 1b). RBD IgG titres of 476 IU/ml corresponded to a NT50 of 1:1000. Overall, RBD ≥476 IU/ml predicted NT50 ≥1:1000 with a sensitivity of 77 (95% CI 65-87)% and specificity 89 (95% CI 82-93)%. This improved in an analysis restricted to convalescent samples (>30 days post symptom onset, n=148), with a sensitivity 88% (95% CI 74-96%) and specificity 90% (95%CI 82-95%) respectively. Conclusion: In convalescent plasma, RBD IgG titres ≥476IU/mL is sensitive and specific for predicting robust underlying neutralising capacity. Further research is required to validate these findings in other cohorts and confirm these thresholds in post-vaccinated individuals.
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Background: Coronavirus disease 2019 (COVID19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has varied clinical presentations from mild subclinical to severe disease with high mortality. Our aim was to determine whether examining immune-related gene expression early in infection could predict progression to severe disease. Methods: In subjects of the All Ireland Infectious Diseases Cohort study, we analysed expression of 579 genes with the NanoString nCounter Immunology panel in peripheral blood mononuclear cells in those with confirmed SARS-CoV-2 infection collected within 5 days of symptom onset and matched SARS-CoV-2 negative controls with respiratory infection. Subsequent maximum COVID19 disease severity was classified as mild or severe. Read counts were normalized using panel housekeeping genes. Expression changes in severity groups were estimated against control baseline. Results: Between April and July of 2020, we recruited 120 subjects, 62 with COVID19 and 58 controls, with average age 59 y.o. (IQR 34-88), 66% males and 69% Caucasian ethnicity. Maximal disease severity was used to separate COVID19 cases into mild (n=31) and severe (n=31). We identified 20 significantly deregulated genes between those with COVID19 and controls (;log2 fold;>0.5, p<0.05, Benjamin-Yekutieli p-adjustment). Function of 12 of these genes related to cytokine signaling, 9 upregulated genes to type I interferon signaling (MX1, IRF7, IFITM1, IFI35, STAT2, IRF4, PML, BST2, STAT1), while 7 downregulated genes mapped to innate immune function (IRF7, ICAM2, SERPING1, IFI16, BST2, FCER1A, PTK2). Expression in the severe group showed downregulation of FCER1A (innate immunity regulation), IL1B and TNF (inflammatory cytokines), and PTGS2 (inflammatory mediator) and greater upregulation of TNFSF4 (cytokine signaling) and PTK2 (innate immunity). Mild cases presented higher upregulation of IFIT2 (type I interferon signaling). Conclusion: Observed early downregulation of regulators and mediators of inflammation in those who developed severe COVID19, suggested dysregulation of inflammation. Specifically, IFIT2 upregulation in mild cases and FCER1A downregulation in severe cases, points to early differences in host responses centered on deregulation of the interferon and inflammation responses. Whether these patterns reflect delayed interferon involvement in pathways to control the infection and contribute to pathological inflammation and cytokine storms observed in severe COVID19 requires further research.
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Background: About 10-35% of people with COVID-19 merit medical care within 3 weeks of infection. However, the prevalence of ongoing care needs among individuals experiencing severe COVID-19 illness is unclear. Research question: What is the prevalence of ongoing care needs among severe COVID-19 patients? Methods: This pilot study applied a cross-sectional design whereby data was collected from adult patients attending a post-COVID-19 follow-up clinic at the Mater Misericordiae University Hospital, Dublin, Ireland, 3-6 months after their initial presentation at the clinic. Participants completed questionnaires documenting their demographics, medical histories, hospital admissions/re-admissions where applicable, and where relevant, primary care service use following hospital discharge. Analyses were conducted using descriptive/inferential statistics. Results: Participants' (n=153) median age =43.5 (IQR =30.9-52.1). There were 105 females (68.6%) and 48 males (31.4%). Various medical histories were reported among participants. 67 (43.2%) reported being admitted to the hospital for COVID-19. Older individuals, males, ICU admissions, and re-admissions were common among hospital attendees. Of the hospital attendees, 16 (24%, 95% CI =13.7-34.2%) and 26 (39%, 95% CI =27.3-50.7%) attended general practices within seven and 30 days of hospital discharge. Older adults (median age =49.8 years), people with pre-existing medical conditions, and individuals admitted to ICU/readmitted to hospital were common among general practice attendees. Conclusion: Persistent health issues appear to be common among patients who experienced severe COVID-19 illness. Older adults, people with pre-existing health problems, and individuals who received ICU and/or re-admission care may have greater long-term care needs requiring attention.
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Background : COVID-19 confers an increased risk of thrombosis however the mechanisms underlying this coagulopathy and the optimal approach to thromboprophylaxis are unknown. Thrombotic risk is likely greatest among patients with severe COVID-19 requiring critical organ support however patients with moderate disease may be at risk and might also benefit from intensified thromboprophylaxis. Aims : To characterise plasma thrombin generation (TG) in patients with COVID-19 of moderate severity, treated with pharmacological thromboprophylaxis. Methods : Blood was collected from individuals admitted to hospital with COVID-19 of moderate severity (not requiring critical care support) and a group of age-matched patients admitted with infective/ inflammatory illness (negative for COVID-19). All subjects received standard dose low molecular weight heparin (LMWH) thromboprophylaxis with samples taken at time of predicted trough levels (confirmed by measuring anti-FXa activity). TG in platelet-poor plasma was determined by calibrated automated thrombography in the presence/absence of tissue factor (TF) (ppp-LOW reagent, 1 pM TF & 4 μM phospholipid;MP-reagent, 4 μM phospholipid;Thrombinoscope BV™). Results : Fourteen COVID-19 positive subjects and 11 hospitalised COVID-19 negative controls were recruited. Mean trough plasma anti-Xa activity was similar in both groups (0.06 vs 0.04 IU/mL;P = 0.2). In the presence of TF, mean endogenous thrombin potential was significantly higher in the COVID group in comparison to controls (1929 ± 119.7 vs 1528 ± 138.9 nM∗min;P = 0.02). Peak thrombin was also higher in COVID-19 (267.3 ± 22.2 vs 208.6 ± 17.8 nM;P = 0.06). Despite increased TG overall, lagtime to TG was significantly prolonged in COVID-19 (8.1 ± 0.5 vs 6.2 ± 0.5 mins;P = 0.02). No difference in any parameter of TG was observed between groups in the absence of TF. Conclusions : Despite pharmacological thromboprophylaxis plasma TG is enhanced in COVID-19. The underlying mechanisms remain to be elucidated. Specific clinical implications of increased TG despite pharmacological thromboprophylaxis have yet to be determined although clinical trials evaluating intensified anticoagulant regimens in a similar population are ongoing.
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Background : Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has affected over 100 million globally to date. Although high rates of venous thromboembolism and evidence of COVID-19-induced endothelial dysfunction have been reported, the precise aetiology of the increased thrombotic risk associated with COVID-19 infection remains to be fully elucidated. Several studies to date suggest a role for platelets in COVID-19-associated thrombosis. Aims : To assess the impact of COVID-19 on platelet activity and to characterise the proteome of the platelet releasate from COVID-19 patients, compared with healthy controls. Methods : Ethical approval was granted by the Institutional Review Board of the Mater Misericordiae University Hospital. Haematologic parameters of patients with severe COVID-19 disease (requiring intensive care;n = 34), with non-severe disease (not requiring intensive care;n = 20) and in general medical in-patients without COVID-19 ( n = 20) were assessed. Platelet function and activity were evaluated by secretion and platelet marker analysis ( n = 6 each cohort). The proteome of the platelet releasate was assessed using label-free mass spectrometry. Results : We demonstrated agonist-induced ADP release was 30-to-90 fold higher in COVID-19 patients compared with hospitalized controls (Fig. 1) and circulating levels of platelet-factor 4 (PF4), soluble P-selectin (sP-selectin) and thrombopoietin (TPO) were also significantly elevated in COVID-19. This study shows that COVID-19 patients possess hyperactive circulating platelets combined with a decreased activation threshold. Mass spectrometry analysis identified over 400 proteins from the releasate of COVID-19 patients and controls, including a multitude of inflammatory, vasoactive and vesicular proteins. The release of a subset of highly-relevant platelet proteins was modified based on the severity of COVID-19 infection. controls (Fig. 1) and circulating levels of platelet-factor 4 (PF4), soluble P-selectin (sP-selectin) and thrombopoietin (TPO) were also significantly elevated in COVID-19. This study shows that COVID-19 patients possess hyperactive circulating platelets combined with a decreased activation threshold. Mass spectrometry analysis identified over 400 proteins from the releasate of COVID-19 patients and controls, including a multitude of inflammatory, vasoactive and vesicular proteins. The release of a subset of highly-relevant platelet proteins was modified based on the severity of COVID-19 infection.
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Introduction: The COVID-19 pandemic has brought the decision-making process regarding cardiopulmonary resuscitation into focus. This study aims to analyse Do-Not-Attempt CPR (DNACPR) documentation in older hospitalised patients before and during the COVID-19 pandemic. Methods: This was a retrospective repeated cross-sectional study. Data including comorbidities and resuscitation status was collected on 300 patients with COVID-19 hospitalised from March 1st toMay 31 s t 2020. DNACPR documentation rates in patients aged ≥65 years with a diagnosis of COVID-19 were compared to those without COVID- 19 admitted during the same period. Pre-COVID-19 pandemic DNACPR documentation rates were also examined. Factors associated with DNACPR order instatement during the first wave of the COVID-19 pandemic were identified. Results: Of 300 COVID-19-positive patients, 28% had a DNACPR order documented during their admission. 50% of DNAR orders were recorded within 24 hours of a positive swab result for SARS-CoV-2. Of 131 patients aged 65 years or over within the cohort admitted with COVID-19, 60.3% had a DNACPR order compared to 25.4% of 130 patients ≥65 without COVID-19 (p<0.0001). During a comparable time period prepandemic, 15.4% of 130 older patients had a DNACPR order in place (p<0.0001). Independent associations with DNACPR order documentation included increasing age (Odds Ratio [O.R.] 1.12;95% CI 1.05-1.21);nursing home resident status (O.R. 3.57;95% CI 1.02-12.50);frailty (O.R. 3.34;95% CI 1.16-9.61) and chronic renal impairment (O.R. 5.49;1.34-22.47). The case-fatality-rate of older patients with COVID-19 was 29.8% versus 5.4% without COVID-19. Of older COVID-19-positive patients, 39.2% were referred to palliative care services and 70.2% survived. Conclusion: The COVID-19 pandemic has prompted more widespread and earlier decision-making regarding resuscitation status. Although case-fatality-rates were higher for older hospitalised patients with COVID-19, many older patients survived the illness. Advance care planning should be prioritised in all patients and should remain clinical practice despite the pandemic.
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Background: Although reports suggest that most individuals with COVID-19 infection develop detectable antibodies post infection, the kinetics, durability, and relative differences between IgM and IgG responses remain poorly understood beyond the first few weeks after symptom onset. Methods: Within a large, well-phenotyped, diverse, prospective cohort of subjects with and without SARS-CoV-2 PCR-confirmed infection and historical controls derived from cohorts with high prevalence of viral coinfections and samples taken during prior flu seasons, we measured SARS-CoV-2 serological responses (both IgG and IgM) using three commercially available assays. We calculated sensitivity and specificity, relationship with disease severity and mapped the kinetics of antibody seropositivity and antibody levels over time using generalised additive models. Results: We analysed 1,001 samples (327 confirmed SARS-CoV-2, of whom 30% developed severe disease) from 752 subjects spanning a period of 90 days from symptom onset. Overall sensitivity was lower (44.1-47.1%) early (<10 days) after symptom onset but increased to >80% after 10 days. IgM positivity increased earlier than IgG-targeted assay but positivity peaked between day 32 and 38 post onset of symptoms and declined thereafter, a dynamic that was confirmed when antibody levels were analysed and was more rapid with IgM. Early (<10 days) IgM but not IgG levels were significantly higher in those who subsequently developed severe disease (signal / cut-off 4.20 (0.75-17.93) versus 1.07 (0.21-5.46), P=0.048). Conclusion: This study suggests that post-infectious antibody responses in those with confirmed COVID-19 infection begin to decline relatively early post infection and suggests a potential role for higher IgM levels early in infection predicting subsequent disease severity.
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Background: The COVID19 pandemic has necessitated innovative ways to provide safe healthcare remotely for large numbers of infected patients. We implemented a COVID Virtual Clinic (CVC) in a tertiary referral centre allowing such patients to be monitored in the community. This study describes the CVC's remote monitoring experience and explores the predictors of need for specialist intervention. Methods: We included all patients enrolled in the CVC at the Mater Misericordiae University Hospital, Dublin between March 1st and June 1st 2020. Patients received a Bluetooth-enabled pulse oximeter and smartphone application (Patient-M-Power®) and uploaded twice-daily SpO2 readings, heart rate and dyspnoea score (1-10). A team of 2-14 healthcare providers monitored results. Abnormal or absent data triggered calls from the CVC, with assessments and/or admission as required. We collected data on demographics, calls received from/made to patients, outcomes and readmissions. Descriptive analysis of the CVC was performed as well as simple logistic regression to explore factors associated with the likelihood of readmission. Results: 502 patients were included (179 (36.4%) male, median age 39 (IQR 50-3) years, 360 (73.2%) staff). Outcomes are illustrated in Figure 1. Median time in CVC was 12 days (IQR 13-10). 1902 calls were made to patients by CVC staff prompted by abnormal data: dyspnoea (41 patients, 8.2%), low SpO2 (133, 26.5%), tachycardia, (99, 19.7%), technical issues (81, 16.1%), absent results (255, 50.1%). This resulted in 45 (9%) patients requiring re-assessment and 42 (8.4%) being readmitted. Of those readmitted, 3 (7%) required critical care admission. Median length of stay was 2 (IQR 6.75-1) days. Those readmitted were more likely to be older (odds ratio [OR] per year older 1.03 (1.01, 1.05), P=0.0050, have an abnormal SpO2 (<94%, OR 5.43 [2.93, 11.1], P<0.001), a high dyspnoea score (>7, OR 4.33 (2.04, 9.3), P<0.001) and be staff (OR 6.08 (3.11, 11.87), P<0.001). Neither gender nor abnormal HR were associated with higher likelihood of readmission. 22.2% of presenting patients were hypoxic in the absence of dyspnoea, of which 70% required admission and one patient required intensive care. Conclusion: We describe the largest remotely monitored cohort of COVID19 patients to date. The low frequency of readmissions and value of SpO2 monitoring and dyspnoea scores as predictors of readmission highlights the value of this model in providing safe care whilst minimising unnecessary admissions.
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AIM: To report an audit of the evaluation of suspected, unconfirmed cases of COVID-19 including chest computed tomography (CT), as compared to World Health Organization recommendations. METHODS: A clinical audit was undertaken examining the evaluation of patients with suspected COVID-19 with negative SARS-CoV-2 reverse transcriptase polymerase chain reaction (RT-PCR) results, with comparison to WHO recommendations. A retrospective chart review was undertaken for 90 patients examining investigations, in particular CT, used to clarify the diagnosis. RESULTS: Ninety patients underwent additional investigation. Seventy-five per cent adherence to WHO recommendations was observed. Fifty-two men (57.78%) and 38 (42.22%) women were investigated, with a median age of 69 years (range 20-96 years). Seventy-nine chest CT examinations demonstrated positive, indeterminate, and negative rates for COVID-19 of 3.79%, 24.1%, and 72.15% respectively. Three patients had discordant swab results with initially negative and subsequently positive results for SARS-CoV-2, resulting in false-negative rates of 5.1% for those retested. Combining discordant RT-PCR swab results, positive radiology, and patients treated as COVID-19-positive due to indeterminate radiology and highly consistent symptoms, resulted in a false-negative rate for initial SARS-CoV-2 RT-PCR swabs of 16.67%. CONCLUSION: Seventy-five per cent compliance with relevant WHO guidance and a false-negative rate for initial swabs of 16.67% was demonstrated. Further evidence is needed to fully determine the utility of chest CT in the diagnosis of COVID-19 in the context of initial false-negative RT-PCR results.