Background:Cardiovascular disease (CVD) prediction models for persons living with HIV (PLWH) depend on traditional CVD risk factors, but these underestimate true risk. We aimed to identify proteins and genetic variants and create proteo-genomic risk scores for CVD in PLWH. Methods:We analyzed genetic and protein data from participants involved in trials for PLWH. We used state-of-the-art statistical methods for data integration, identified correlated signatures, and developed a protein score (PS) and a genetic score (GS) to predict CVD. We conducted functional enrichment analysis to explore biological functions of signatures identified in relation to CVD. Results:A panel of 14 proteins and a set of 15 genetic variants were found to be better at distinguishing between CVD cases and controls than individual proteins or genetic variants. The PS or GS was each independently associated with a higher risk of CVD (OR for PS: 2.36, CI: 1.78-3.19; OR for GS: 4.59, CI: 3.21-6.80). Combining CVD-, HIV-related factors, genetics, and protein scores resulted in the most powerful discrimination with an AUC of 0.86 (CI: 0.82-0.90). Having a PS in the top 25% compared to the bottom 75% resulted in a 3.9 times higher risk of CVD. Having a GS in the top 25% compared to the bottom 75% resulted in a 7.3 times higher risk of CVD. For individuals with both PS and GS in the top 25% compared to others, the risk of CVD was 7.9 times higher. Functional enrichment analysis showed an upregulation of the cytokine tumor necrosis factor (TNF) and strong enrichment for inflammation related pathways such as the pathogen induced cytokine storm. Conclusions:A panel of protein biomarkers, some new (IGFBP7, HGF) and some previously known in PLWH (CLEC6A), could help identify PLWH at higher risk of developing CVD. If confirmed, these scores could be used with CVD and HIV-related factors to identify PLWH at risk for CVD who would benefit from proactive risk reduction strategies.

OBJECTIVES:To report long-term clinical efficacy, safety, pharmacokinetics, immunogenicity and seroneutralization results of AZD7442 (monoclonal antibodies tixagevimab-cilgavimab) in patients hospitalized with COVID-19. METHODS:In this phase 3, double-blind, randomized, multicentre trial, hospitalized adults with PCR-confirmed SARS-CoV-2 infection were randomly assigned 1:1 to receive AZD7442 or placebo, and followed-up until day 456, with repeated blood sample collections until day 365. Clinical endpoints included clinical status, mortality, rehospitalization, SARS-CoV-2 reinfection, and adverse events. Antidrug antibodies and serum drug concentrations were measured. Analyses were performed on the modified intention-to-treat (mITT) populations, defined as participants who actually received the intervention. RESULTS:Between April 28, 2021, and June 23, 2022, 237 participants were randomly assigned to AZD7442 (n = 127) or placebo (n = 110), and 123 participants actually received AZD7442. Participants were infected with pre-Omicron variants in 58.8% (133/226) of cases, versus 33.2% (75/226) of Omicron BA1, BA2, or BA5, and 8% (18/226) missing data. There was no significant difference in the distribution of the 7-point ordinal scale between the AZD7442 and placebo groups, either on day 15 (primary endpoint) (OR = 0.93 [0.54-1.61], p 0.81), or any other time point. Significantly more rehospitalizations occurred between discharge and day 456 among participants who received AZD7442 in the global mITT population (OR = 2.04 [1.03-4.05], p 0.04), but not in the antigen-positive mITT population (OR = 1.78 [0.80-3.94], p 0.15). No significant differences were observed in mortality, SARS-CoV-2 reinfection, or adverse events. In the AZD7442 group, 12 of 87 participants (13.8%) had treatment-emergent antidrug antibodies versus 5 of 69 (7.2%) in the placebo group (OR = 2.02 [0.66-6.14], p 0.21). Serum drug concentrations were detectable up to day 365 for all sampled participants (35/35). Neutralizing antibody titres were significantly higher in the AZD7442 group up to day 180. CONCLUSIONS:AZD7442 did not demonstrate any clinical benefit and was safe up to 15 months. This study also provides valuable data on the pharmacokinetics, immunogenicity, and neutralizing activity of AZD7442 in patients hospitalized with COVID-19.

OBJECTIVE:Since the emergence of SARS-CoV-2, an increasing number of people report long-term physical and psychological impairments. Research on the immunological sequalae of long COVID (LC) is growing, though its relationship with mental health remains underexplored. We investigated the psychological impairments associated with LC, identified related psychological symptom clusters, and their relationship with physical symptoms and pandemic-related variables. METHODS:This is a cross-sectional descriptive study using an online questionnaire (September 2020 to December 2022) in German and French to assess depression, anxiety, fatigue, stress, and somatic symptoms. Clusters were identified using hierarchical and machine learning techniques (Kmeans and AffinityPropagation) and compared based on LC symptoms, past physical and mental health, substance use, COVID-19 variants, and family dynamics. RESULTS:Among 1218 LC participants (78.7% female), 4 clusters were identified using AffinityPropagation: (1) low anxiety, depression, and somatoform symptoms, (2) low anxiety and depression but moderate somatoform symptoms, (3) high anxiety and depression with high somatoform symptoms, and (4) high anxiety and depression with moderate somatoform symptoms. Cluster 3 reported the most severe physical and neurological symptoms, the largest life impact (including relationship deterioration and professional difficulties), and the highest prevalence of past mental disorders (depression and post-traumatic stress disorder). Cluster 1 reported the least symptoms. CONCLUSIONS:LC significantly impacts mental health, particularly through increased anxiety, depression, and somatoform symptoms, especially in patients with severe LC physical symptoms. Psychological interventions targeting distinct symptom clusters may improve both mental and physical outcomes. Early mental health screening and tailored interventions are recommended for LC assessment and treatment.

Background Tixagevimab and cilgavimab (AZD7442) are two monoclonal antibodies developed by AstraZeneca for the pre-exposure prophylaxis and treatment of patients infected by SARS-CoV-2. Its effectiveness and safety in patients hospitalized with COVID-19 was not known at the outset of this trial.Methods DisCoVeRy is a phase 3, adaptive, multicentre, randomized, controlled trial conducted in 63 sites in Europe. Participants were randomly assigned (1:1) to receive placebo or tixagevimab-cilgavimab in addition to standard of care. The primary outcome was the clinical status at day 15 measured by the WHO seven-point ordinal scale. Several clinical, virological, immunological and safety endpoints were also assessed.Findings Due to slow enrolment, recruitment was stopped on July 1st, 2022. The antigen positive modified intention-to-treat population (mITT) was composed of 173 participants randomized to tixagevimab-cilgavimab (N = 91) or placebo (N = 82), 91.9% (159/173) with supplementary oxygen, and 47.4% (82/173) previously vaccinated at inclusion. There was no significant difference in the distribution of the WHO ordinal scale at day 15 between the two groups (odds ratio (OR) 0.93, 95%CI [0.54-1.61]; p = 0.81) nor in any clinical, virological or safety secondary endpoints. In the global mITT (N = 226), neutralization antibody titers were significantly higher in the tixagevimab-cilgavimab group/patients compared to placebo at day 3 (Least-squares mean differences (LSMD) 1.44, 95% Confidence interval (CI) [1.20-1.68]; p < 10−23) and day 8 (LSMD 0.91, 95%CI [0.64-1.18]; p < 10−8) and it was most important for patients infected with a pre-omicron variant, both at day 3 (LSMD 1.94, 95% CI [1.67-2.20], p < 10−25) and day 8 (LSMD 1.17, 95% CI [0.87-1.47], p < 10−9), with a significant interaction (p < 10−7 and p = 0.01 at days 3 and 8, respectively).Interpretation There were no significant differences between tixagevimab-cilgavimab and placebo in clinical endpoints, however the trial lacked power compared to prespecified calculations. Tixagevimab-cilgavimab was well tolerated, with low rates of treatment related events.Funding Trial registration: [ClinicalTrials.gov][1] [NCT04315948][2]. Registered on 13 March 2020 updated on 22 April 2021.### Competing Interest StatementM.H. reports grants from The Belgian Center for Knowledge (KCE), the Fonds Erasme-COVID-Université Libre de Bruxelles and the EU-Horizon program, for the submitted work; and has received support for attending meetings from Pfizer; support for participation on an advisory board for therapeutics on COVID-19; and support for leadership for the Belgian guidelines on therapeutics for COVID-19 and acting as a treasurer for the Belgian Society of Clinical Microbiology and Infectious Diseases. R.G. reports consulting fees from Celgene, Novartis, Roche, Bristol Myers Squibb, Takeda, Abbvie, AstraZeneca, Janssen, Merck Sharp & Dohme, Merck, Gilead, and Daiichi Sankvo; lecture fees from Celgene, Roche, Merck, Takeda, AstraZeneca, Novartis, Amgen, Bristol Myers Squibb, Merck Sharp & Dohme, Sandoz, Abbvie, Gilead, and Daiichi Sankvo; support for attending meetings from Roche, Amgen, Janssen, AstraZeneca, Novartis, Merck Sharp & Dohme, Celgene, Gilead, Bristol Myers Squibb, Abbvie, and Daiichi Sankvo; participation in a Data Safety and Monitoring Board for Celgene, Novartis, Roche, Bristol Myers Squibb, Takeda, Abbvie, AstraZeneca, Janssen, Merck Sharp & Dohme, Merck, Gilead, and Daiichi Sankyo; research grants from Celgene, Roche, Merck, Takeda, AstraZeneca, Novartis, Amgen, Bristol Myers Squibb, Merck Sharp & Dohme, Sandoz, Abbvie, Gilead, and Daiichi Sankyo. J.-A.P. reports consulting fees from Pfizer, Merck Sharp & Dohme, and Janssen-Cilag; lecture fees from Pfizer; and support for attending meetings from Pfizer. D.C. reports grants and lecture fees from Janssen and lecture fees from Gilead, outside the submitted work. C.B. reports participation in a Data Safety and Monitoring Board for 4Living Biotech; and consulting fees from Da Volterra and Mylan Pharmaceuticals, outside the submitted work. F.M. reports grants and consulting fees from Da Volterra, grants from Sanofi, and consulting fees from Ipsen, outside the submitted work. All other authors declare no competing interests.### Clinical TrialNCT04315948### Funding StatementThis work received funding from several sources: the European Commission (EU-Response, Grant 101015736), the DIM One Health Ile-de-France (R20117HD) and Astra-Zeneca. We thank all participants who consented to enroll in the trial, as well as all study and site staff whose indispensable assistance made the conduct of the DisCoVeRy trial possible (all listed in the appendix, pp 27-36)### Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesThe details of the IRB/oversight body that provided approval or exemption for the research described are given below:Ethics committee of the BASG (Bundesamt fur Sicherheit im Gesundheitswesen), Austria, gave ethical approval for this work. Ethics committee of the FAMHP (Federal Agency for Medicines and Health Products), Belgium, gave ethical approval for this work. Ethics committee of the SUKL (Statni Ustav Pro Kontrolu Leciv), Czech Republic, gave ethical approval for this work. Ethics committee of the ANSM (Agence nationale de securite du medicament et des produits de sante), France, gave ethical approval for this work. Ethics committee of the National Organization for Medicines, Greece, gave ethical approval for this work. Ethics committee of the National Institute of Pharmacy and Nutrition (OGYEI), Hungary, gave ethical approval for this work. Ethics committee of the HPRA (Health Products Regulatory Authority), Ireland, gave ethical approval for this work. Ethics committee of the CNER (Comite National d Ethique de Recherche, ministere de la sante), Luxembourg, gave ethical approval for this work. Ethics committee of the NOMA (Norwegian Medical Products Agency), Norway, gave ethical approval for this work. Ethics committee of the Komisja Bioetyczna Przy Uniwersytecie Medycznym W Lodzi, Poland, gave ethical approval for this work. Ethics committee of the Infarmed (National Authority of Medicines and Health Products), Portugal, gave ethical approval for this work. Ethics committee of the SULK (Statni ustav pro kontrolu leciv), Slovakia, gave ethical approval for this work. Ethics committee of the AEMPS (Agencia Espanola de Medicamentos y Productos Sanitarios), Spain, gave ethical approval for this work. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).YesI have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable.YesWith publication, deidentified, individual participant data that underlie this Article, along with a data dictionary describing variables in the dataset, will be made available to researchers whose proposed purpose of use is approved by the DisCoVeRy Steering Committee. To request the dataset, please address directly to the corresponding author (florence.ader@chu-lyon.fr) or to the sponsor's representative (helene.esperou{at}inserm.fr) to obtain a data access form. All requests will be evaluated by the Trial Management Team and the DisCoVeRy Steering Committee. For accepted requests, data will be shared after signing a data transfer agreement with the study sponsor. Data will be shared directly or through access on the INSERM repository. Related documents, such as the study protocol, statistical analysis plan, and informed consent form, will be made available (with publication) on request to the corresponding author or to the sponsor's representative. The data will be open access for the informed consent form, protocol, and statistical analysis plan. [1]: http://ClinicalTrials.gov [2]: /lookup/external-ref?link_type=CLINTRIALGOV&access_num=NCT04315948&atom=%2Fmedrxiv%2Fearly%2F2024%2F02%2F24%2F2024.02.23.24302586.atom

BACKGROUND:We aimed to evaluate the cardiac adverse events (AEs) in hospitalized patients with coronavirus disease 2019 (COVID-19) who received remdesivir plus standard of care (SoC) compared with SoC alone (control), as an association was noted in some cohort studies and disproportionality analyses of safety databases. METHODS:This post hoc safety analysis is based on data from the multicenter, randomized, open-label, controlled DisCoVeRy trial in hospitalized patients with COVID-19. Any first AE that occurred between randomization and day 29 in the modified intention-to-treat (mITT) population randomized to either remdesivir or control group was considered. Analysis was performed using Kaplan-Meier survival curves, and Kaplan-Meier estimates were calculated for event rates. RESULTS:Cardiac AEs were reported in 46 (11.2%) of 410 and 48 (11.3%) of 423 patients in the mITT population (n = 833) enrolled in the remdesivir and control groups, respectively. The difference between both groups was not significant (hazard ratio [HR], 1.0; 95% confidence interval [CI], .7-1.5; P = .98), even when serious and nonserious cardiac AEs were evaluated separately. The majority of reports in both groups were of arrhythmic nature (remdesivir, 84.8%; control, 83.3%) and were associated with a favorable outcome. There was no significant difference between the two groups in the occurrence of cardiac AE subclasses, including arrhythmic events (HR, 1.1; 95% CI, .7-1.7; P = .68). CONCLUSIONS:Remdesivir treatment was not associated with an increased risk of cardiac AEs compared with control in patients hospitalized with moderate or severe COVID-19. These results are consistent with other randomized, controlled trials and meta-analyses. Clinical Trials Registration. NCT04315948; EudraCT 2020-000936-23.

The current COVID-19 pandemic was an exceptional health situation, including for drug use. As there was no known effective drug for COVID-19 at the beginning of the pandemic, different drug candidates were proposed. In this article, we present the challenges for an academic Safety Department to manage the global safety of a European trial during the pandemic. The National Institute for Health and Medical Research (Inserm) conducted a European multicenter, open-label, randomized, controlled trial involving three repurposed and one-in development drugs (lopinavir/ritonavir, IFN-β1a, hydroxychloroquine, and remdesivir) in adults hospitalized with COVID-19. From 25 March 2020 to 29 May 2020, the Inserm Safety Department had to manage 585 Serious Adverse Events (SAEs) initial notification and 396 follow-up reports. The Inserm Safety Department's staff was mobilized to manage these SAEs and to report Expedited safety reports to the competent authorities within the legal timeframes. More than 500 queries were sent to the investigators due to a lack of or incoherent information on SAE forms. At the same time, the investigators were overwhelmed by the management of patients suffering from COVID-19 infection. These particular conditions of missing data and lack of accurate description of adverse events made evaluation of the SAEs very difficult, particularly the assessment of the causal role of each investigational medicinal product. In parallel, working difficulties were accentuated by the national lockdown, frequent IT tool dysfunctions, delayed implementation of monitoring and the absence of automatic alerts for SAE form modification. Although COVID-19 is a confounding factor per se, the delay in and quality of SAE form completion and the real-time medical analysis by the Inserm Safety Department were major issues in the quick identification of potential safety signals. To conduct a high-quality clinical trial and ensure patient safety, all stakeholders must take their roles and responsibilities.

BACKGROUND For people with HIV and CD4+ counts >500 cells/mm3, early initiation of antiretroviral therapy (ART) reduces serious AIDS and serious non-AIDS (SNA) risk compared with deferral of treatment until CD4+ counts are <350 cells/mm3. Whether excess risk of AIDS and SNA persists once ART is initiated for those who defer treatment is uncertain. METHODS The Strategic Timing of AntiRetroviral Treatment (START) trial, as previously reported, randomly assigned 4684 ART-naive HIV-positive adults with CD4+ counts .500 cells/mm3 to immediate treatment initiation after random assignment (n = 2325) or deferred treatment (n= 2359). In 2015, a 57% lower risk of the primary end point (AIDS, SNA, or death) for the immediate group was reported, and the deferred group was offered ART. This article reports the follow-up that continued to December 31, 2021. Cox proportional-hazards models were used to compare hazard ratios for the primary end point from randomization through December 31, 2015, versus January 1, 2016, through December 31, 2021. RESULTS Through December 31, 2015, approximately 7 months after the cutoff date from the previous report, the median CD4+ count was 648 and 460 cells/mm3 in the immediate and deferred groups, respectively, at treatment initiation. The percentage of follow-up time spent taking ART was 95% and 36% for the immediate and deferred groups, respectively, and the time-averaged CD4+ difference was 199 cells/mm3. After January 1, 2016, the percentage of follow-up time on treatment was 97.2% and 94.1% for the immediate and deferred groups, respectively, and the CD4+ count difference was 155 cells/mm3. After January 1, 2016, a total of 89 immediate and 113 deferred group participants experienced a primary end point (hazard ratio of 0.79 [95% confidence interval, 0.60 to 1.04] versus hazard ratio of 0.47 [95% confidence interval, 0.34 to 0.65; P<0.001]) before 2016 (P=0.02 for hazard ratio difference). CONCLUSIONS Among adults with CD4+ counts >500 cells/mm3, excess risk of AIDS and SNA associated with delaying treatment initiation was diminished after ART initiation, but persistent excess risk remained. (Funded by the National Institute of Allergy and Infectious Diseases and others.).

The role of antiviral treatment in coronavirus disease 2019 hospitalized patients is controversial. To address this question, we analyzed simultaneously nasopharyngeal viral load and the National Early Warning Score 2 (NEWS-2) using an effect compartment model to relate viral dynamics and the evolution of clinical severity. The model is applied to 664 hospitalized patients included in the DisCoVeRy trial (NCT04315948; EudraCT 2020-000936-23) randomly assigned to either standard of care (SoC) or SoC + remdesivir. Then we use the model to simulate the impact of antiviral treatments on the time to clinical improvement, defined by a NEWS-2 score lower than 3 (in patients with NEWS-2 <7 at hospitalization) or 5 (in patients with NEWS-2 ≥7 at hospitalization), distinguishing between patients with low or high viral load at hospitalization. The model can fit well the different observed patients trajectories, showing that clinical evolution is associated with viral dynamics, albeit with large interindividual variability. Remdesivir antiviral activity was 22% and 78% in patients with low or high viral loads, respectively, which is not sufficient to generate a meaningful effect on NEWS-2. However, simulations predicted that antiviral activity greater than 99% could reduce by 2 days the time to clinical improvement in patients with high viral load, irrespective of the NEWS-2 score at hospitalization, whereas no meaningful effect was predicted in patients with low viral loads. Our results demonstrate that time to clinical improvement is associated with time to viral clearance and that highly effective antiviral drugs could hasten clinical improvement in hospitalized patients with high viral loads.

SARS-CoV-2 infection and/or vaccination elicit a broad range of neutralizing antibody responses against the different variants of concern (VOC). We established a new variant-adapted surrogate virus neutralization test (sVNT) and assessed the neutralization activity against the ancestral B.1 (WT) and VOC Delta, Omicron BA.1, BA.2, and BA.5. Analytical performances were compared against the respective VOC to the reference virus neutralization test (VNT) and two CE-IVD labeled kits using three different cohorts collected during the COVID-19 waves. Correlation analyses showed moderate to strong correlation for Omicron sub-variants (Spearman’s r = 0.7081 for BA.1, r = 0.7205 for BA.2, and r = 0.6042 for BA.5), and for WT (r = 0.8458) and Delta-sVNT (r = 0.8158), respectively. Comparison of the WT-sVNT performance with two CE-IVD kits, the “Icosagen SARS-CoV-2 Neutralizing Antibody ELISA kit” and the “Genscript cPass, kit” revealed an overall good correlation ranging from 0.8673 to −0.8773 and a midway profile between both commercial kits with 87.76% sensitivity and 90.48% clinical specificity. The BA.2-sVNT performance was similar to the BA.2 Genscript test. Finally, a correlation analysis revealed a strong association (r = 0.8583) between BA.5-sVNT and VNT sVNT using a double-vaccinated cohort (n = 100) and an Omicron-breakthrough infection cohort (n = 91). In conclusion, the sVNT allows for the efficient prediction of immune protection against the various VOCs.

Since the emergence of SARS-CoV-2 Omicron BA.1 and BA.2, several Omicron sublineages have emerged, supplanting their predecessors. Here we compared the neutralization of Omicron sublineages BA.1, BA.2, BA.4 and BA.5 by human sera collected from individuals who were infected with the ancestral B.1 (D614G) strain, who were vaccinated (3 doses) or with breakthrough infection with pre-Omicron strains (Gamma or Delta). All Omicron sublineages exhibited extensive escape from all sera when compared to the ancestral B.1 strain and to Delta, albeit to different levels depending on the origin of the sera. Convalescent sera were unable to neutralize BA.1, and partly neutralized BA.2, BA.4 and BA.5. Vaccinee sera partly neutralized BA.2, but BA.1, BA.4 and BA.5 evaded neutralizing antibodies (NAb). Some breakthrough infections (BTI) sera were non-neutralizing. Neutralizing BTI sera had similar neutralizing ability against all Omicron sublineages. Despite similar levels of anti-Spike and anti-Receptor Binding Domain (RBD) antibodies in all groups, BTI sera had the highest cross-neutralizing ability against all Omicron sublineages and convalescent sera were the least neutralizing. Antibody avidity inferred from the NT50:antibody titer ratio was highest in sera from BTI patients, underscoring qualitative differences in antibodies elicited by infection or vaccination. Together, these findings highlight the importance of vaccination to trigger highly cross-reactive antibodies that neutralize phylogenetically and antigenically distant strains, and suggest that immune imprinting by first generation vaccines may restrict, but not abolish, cross-neutralization.

Background Cardiovascular disease risk prediction models underestimate CVD risk in people living with HIV (PLWH). Our goal is to derive a risk score based on protein biomarkers that could be used to predict CVD in PLWH. Methods and Results In a matched case–control study, we analyzed normalized protein expression data for participants enrolled in 1 of 4 trials conducted by INSIGHT (International Network for Strategic Initiatives in Global HIV Trials). We used dimension reduction, variable selection and resampling methods, and multivariable conditional logistic regression models to determine candidate protein biomarkers and to generate a protein score for predicting CVD in PLWH. We internally validated our findings using bootstrap. A protein score that was derived from 8 proteins (including HGF [hepatocyte growth factor] and interleukin‐6) was found to be associated with an increased risk of CVD after adjustment for CVD and HIV factors (odds ratio: 2.17 [95% CI: 1.58–2.99]). The protein score improved CVD prediction when compared with predicting CVD risk using the individual proteins that comprised the protein score. Individuals with a protein score above the median score were 3.10 (95% CI, 1.83–5.41) times more likely to develop CVD than those with a protein score below the median score. Conclusions A panel of blood biomarkers may help identify PLWH at a high risk for developing CVD. If validated, such a score could be used in conjunction with established factors to identify CVD at‐risk individuals who might benefit from aggressive risk reduction, ultimately shedding light on CVD pathogenesis in PLWH.

Objectives We evaluated the clinical, virological and safety outcomes of lopinavir/ritonavir, lopinavir/ritonavir-interferon (IFN)-beta-1a, hydroxychloroquine or remdesivir in comparison to standard of care (control) in COVID-19 inpatients requiring oxygen and/or ventilatory support. While preliminary results were previously published, we present here the final results, following completion of the data monitoring. Methods We conducted a phase 3 multi-centre open-label, randomized 1:1:1:1:1, adaptive, controlled trial (DisCoVeRy), add-on trial to Solidarity (NCT04315948, EudraCT2020-000936-23). The primary outcome was the clinical status at day 15, measured by the WHO 7-point ordinal scale. Secondary outcomes included SARS-CoV-2 quantification in respiratory specimens, pharmacokinetic and safety analyses. We report the results for the lopinavir/ritonavir-containing arms and for the hydroxychloroquine arm, which were stopped prematurely. Results The intention-to-treat population included 593 participants (lopinavir/ritonavir, n=147; lopinavir/ritonavir-IFN-beta-1a, n=147; hydroxychloroquine, n=150; control, n=149), among whom 421 (71.0%) were male, the median age was 64 years (IQR, 54-71) and 214 (36.1%) had a severe disease. The day 15 clinical status was not improved with investigational treatments: lopinavir/ritonavir versus control, adjusted odds ratio (aOR) 0.82, (95% confidence interval [CI] 0.54-1.25, P=0.36); lopinavir/ritonavir-IFN-beta-1a versus control, aOR 0.69 (95%CI 0.45-1.05, P=0.08); hydroxychloroquine versus control, aOR 0.94 (95%CI 0.62-1.41, P=0.76). No significant effect of investigational treatment was observed on SARS-CoV-2 clearance. Trough plasma concentrations of lopinavir and ritonavir were higher than those expected, while those of hydroxychloroquine were those expected with the dosing regimen. The occurrence of Serious Adverse Events was significantly higher in participants allocated to the lopinavir/ritonavir-containing arms. Conclusion In adults hospitalized for COVID-19, lopinavir/ritonavir, lopinavir/ritonavir-IFN-beta-1a and hydroxychloroquine did not improve the clinical status at day 15, nor SARS-CoV-2 clearance in respiratory tract specimens.

BACKGROUND:The antiviral efficacy of remdesivir in COVID-19 hospitalized patients remains controversial. OBJECTIVES:To estimate the effect of remdesivir in blocking viral replication. METHODS:We analysed nasopharyngeal normalized viral loads from 665 hospitalized patients included in the DisCoVeRy trial (NCT04315948; EudraCT 2020-000936-23), randomized to either standard of care (SoC) or SoC + remdesivir. We used a mathematical model to reconstruct viral kinetic profiles and estimate the antiviral efficacy of remdesivir in blocking viral replication. Additional analyses were conducted stratified on time of treatment initiation (≤7 or >7 days since symptom onset) or viral load at randomization (< or ≥3.5 log10 copies/104 cells). RESULTS:In our model, remdesivir reduced viral production by infected cells by 2-fold on average (95% CI: 1.5-3.2-fold). Model-based simulations predict that remdesivir reduced time to viral clearance by 0.7 days compared with SoC, with large inter-individual variabilities (IQR: 0.0-1.3 days). Remdesivir had a larger impact in patients with high viral load at randomization, reducing viral production by 5-fold on average (95% CI: 2.8-25-fold) and the median time to viral clearance by 2.4 days (IQR: 0.9-4.5 days). CONCLUSIONS:Remdesivir halved viral production, leading to a median reduction of 0.7 days in the time to viral clearance compared with SoC. The efficacy was larger in patients with high viral load at randomization.

SARS-CoV-2 variants raise concern because of their high transmissibility and their ability to evade neutralizing antibodies elicited by prior infection or by vaccination. Here, we compared the neutralizing abilities of sera from 70 unvaccinated COVID-19 patients infected before the emergence of variants of concern (VOCs) and of 16 vaccine breakthrough infection (BTI) cases infected with Gamma or Delta against the ancestral B.1 strain, the Gamma, Delta and Omicron BA.1 VOCs using live virus. We further determined antibody levels against the Nucleocapsid (N) and full Spike proteins, the receptor-binding domain (RBD) and the N-terminal domain (NTD) of the Spike protein. Convalescent sera featured considerable variability in the neutralization of B.1 and in the cross-neutralization of different strains. Their neutralizing capacity moderately correlated with antibody levels against the Spike protein and the RBD. All but one convalescent serum failed to neutralize Omicron BA.1. Overall, convalescent sera from patients with moderate disease had higher antibody levels and displayed a higher neutralizing ability against all strains than patients with mild or severe forms of the disease. The sera from BTI cases fell into one of two categories: half the sera had a high neutralizing activity against the ancestral B.1 strain as well as against the infecting strain, while the other half had no or a very low neutralizing activity against all strains. Although antibody levels against the spike protein and the RBD were lower in BTI sera than in unvaccinated convalescent sera, most neutralizing sera also retained partial neutralizing activity against Omicron BA.1, suggestive of a better cross-neutralization and higher affinity of vaccine-elicited antibodies over virus-induced antibodies. Accordingly, the IC50: antibody level ratios were comparable for BTI and convalescent sera, but remained lower in the neutralizing convalescent sera from patients with moderate disease than in BTI sera. The neutralizing activity of BTI sera was strongly correlated with antibodies against the Spike protein and the RBD. Together, these findings highlight qualitative differences in antibody responses elicited by infection in vaccinated and unvaccinated individuals. They further indicate that breakthrough infection with a pre-Omicron variant boosts immunity and induces cross-neutralizing antibodies against different strains, including Omicron BA.1.

BackgroundThe Solidarity trial among COVID-19 inpatients has previously reported interim mortality analyses for four repurposed antiviral drugs. Lopinavir, hydroxychloroquine, and interferon (IFN)-β1a were discontinued for futility but randomisation to remdesivir continued. Here, we report the final results of Solidarity and meta-analyses of mortality in all relevant trials to date.MethodsSolidarity enrolled consenting adults (aged ≥18 years) recently hospitalised with, in the view of their doctor, definite COVID-19 and no contraindication to any of the study drugs, regardless of any other patient characteristics. Participants were randomly allocated, in equal proportions between the locally available options, to receive whichever of the four study drugs (lopinavir, hydroxychloroquine, IFN-β1a, or remdesivir) were locally available at that time or no study drug (controls). All patients also received the local standard of care. No placebos were given. The protocol-specified primary endpoint was in-hospital mortality, subdivided by disease severity. Secondary endpoints were progression to ventilation if not already ventilated, and time-to-discharge from hospital. Final log-rank and Kaplan-Meier analyses are presented for remdesivir, and are appended for all four study drugs. Meta-analyses give weighted averages of the mortality findings in this and all other randomised trials of these drugs among hospital inpatients. Solidarity is registered with ISRCTN, ISRCTN83971151, and ClinicalTrials.gov, NCT04315948.FindingsBetween March 22, 2020, and Jan 29, 2021, 14 304 potentially eligible patients were recruited from 454 hospitals in 35 countries in all six WHO regions. After the exclusion of 83 (0·6%) patients with a refuted COVID-19 diagnosis or encrypted consent not entered into the database, Solidarity enrolled 14 221 patients, including 8275 randomly allocated (1:1) either to remdesivir (ten daily infusions, unless discharged earlier) or to its control (allocated no study drug although remdesivir was locally available). Compliance was high in both groups. Overall, 602 (14·5%) of 4146 patients assigned to remdesivir died versus 643 (15·6%) of 4129 assigned to control (mortality rate ratio [RR] 0·91 [95% CI 0·82–1·02], p=0·12). Of those already ventilated, 151 (42·1%) of 359 assigned to remdesivir died versus 134 (38·6%) of 347 assigned to control (RR 1·13 [0·89–1·42], p=0·32). Of those not ventilated but on oxygen, 14·6% assigned to remdesivir died versus 16·3% assigned to control (RR 0·87 [0·76–0·99], p=0·03). Of 1730 not on oxygen initially, 2·9% assigned to remdesivir died versus 3·8% assigned to control (RR 0·76 [0·46–1·28], p=0·30). Combining all those not ventilated initially, 11·9% assigned to remdesivir died versus 13·5% assigned to control (RR 0·86 [0·76–0·98], p=0·02) and 14·1% versus 15·7% progressed to ventilation (RR 0·88 [0·77–1·00], p=0·04). The non-prespecified composite outcome of death or progression to ventilation occurred in 19·6% assigned to remdesivir versus 22·5% assigned to control (RR 0·84 [0·75–0·93], p=0·001). Allocation to daily remdesivir infusions (vs open-label control) delayed discharge by about 1 day during the 10-day treatment period. A meta-analysis of mortality in all randomised trials of remdesivir versus no remdesivir yielded similar findings.InterpretationRemdesivir has no significant effect on patients with COVID-19 who are already being ventilated. Among other hospitalised patients, it has a small effect against death or progression to ventilation (or both).FundingWHO.

Background: Weight gain is becoming increasingly prevalent amongst people with HIV (PWH) receiving contemporary antiretroviral treatment. We investigated BMI changes and clinical impact in a large prospective observational study. Methods: PWH aged ≥18 years were included who started a new antiretroviral (baseline) during 2010–2019 with baseline and ≥1 follow-up BMI assessment available. Rates of clinical outcomes (cardiovascular disease [CVD], malignancies, diabetes mellitus [DM] and all-cause mortality) were analysed using Poisson regression to assess effect of time-updated BMI changes (>1 kg/m2 decrease, ±1 kg/m2 stable, >1 kg/m2 increase), lagged by 1-year to reduce reverse causality. Analyses were adjusted for baseline BMI plus key confounders including antiretroviral exposure. Results: 6721 PWH were included; 72.3% were male, median age 48 years (interquartile range [IQR] 40–55). At baseline, 8.4% were antiretroviral-naive, and 5.0% were underweight, 59.7% healthy weight, 27.5% overweight, and 7.8% were living with obesity. There was an 8.2% increase in proportion of overweight and 4.8% in obesity over the study period (median follow-up 4.4 years [IQR 2.6–6.7]). 100 CVDs, 149 malignancies, 144 DMs, and 257 deaths were observed with incidence rates 4.4, 6.8, 6.6, 10.6 per 1000 person-years of follow-up, respectively. Compared to stable BMI, >1 kg/m2 increase was associated with increased risk of DM (adjusted incidence rate ratio [IRR]: 1.96, 95% confidence interval [CI]: 1.36–2.80) and >1 kg/m2 decrease with increased risk of death (adjusted IRR: 2.33, 95% CI: 1.73–3.13). No significant associations were observed between BMI changes and CVD or malignancies. Conclusions: A BMI increase was associated with DM and a decrease associated with death.

Abstract Introduction Data on safety and effectiveness of RPV from the real-world setting as well as comparisons with other NNRTIs such as efavirenz (EFV) remain scarce. Methods Participants of EuroSIDA were included if they had started a RPV- or an EFV-containing regimen over November 2011-December 2017. Statistical testing was conducted using non-parametric Mann–Whitney U test and Chi-square test. A logistic regression model was used to compare participants’ characteristics by treatment group. Kaplan–Meier analysis was used to estimate the cumulative risk of virological failure (VF, two consecutive values > 50 copies/mL). Results 1,355 PLWH who started a RPV-based regimen (11% ART-naïve), as well as 333 initiating an EFV-containing regimen were included. Participants who started RPV differed from those starting EFV for demographics (age, geographical region) and immune-virological profiles (CD4 count, HIV RNA). The cumulative risk of VF for the RPV-based group was 4.5% (95% CI 3.3–5.7%) by 2 years from starting treatment (71 total VF events). Five out of 15 (33%) with resistance data available in the RPV group showed resistance-associated mutations vs. 3/13 (23%) among those in the EFV group. Discontinuations due to intolerance/toxicity were reported for 73 (15%) of RPV- vs. 45 (30%) of EFV-treated participants (p = 0.0001). The main difference was for toxicity of central nervous system (CNS, 3% vs. 22%, p < 0.001). Conclusion Our estimates of VF > 50 copies/mL and resistance in participants treated with RPV were similar to those reported by other studies. RPV safety profile was favourable with less frequent discontinuation due to toxicity than EFV (especially for CNS).

Abstract Background “Long COVID” is characterized by a variety of symptoms and an important burden for affected people. Our objective was to describe long COVID symptomatology according to initial coronavirus disease 2019 (COVID-19) severity. Methods Predi-COVID cohort study participants, recruited at the time of acute COVID-19 infection, completed a detailed 12-month symptom and quality of life questionnaire. Frequencies and co-occurrences of symptoms were assessed. Results Among the 289 participants who fully completed the 12-month questionnaire, 59.5% reported at least 1 symptom, with a median of 6 symptoms. Participants with an initial moderate or severe acute illness declared more frequently 1 or more symptoms (82.6% vs 38.6%, P < .001) and had on average 6.8 more symptoms (95% confidence interval, 4.18–9.38) than initially asymptomatic participants who developed symptoms after the acute infection. Overall, 12.5% of the participants could not envisage coping with their symptoms in the long term. Frequently reported symptoms, such as neurological and cardiovascular symptoms, but also less frequent ones such as gastrointestinal symptoms, tended to cluster. Conclusions Frequencies and burden of symptoms present 12 months after acute COVID-19 infection increased with the severity of the acute illness. Long COVID likely consists of multiple subcategories rather than a single entity. This work will contribute to the better understanding of long COVID and to the definition of precision health strategies. Clinical Trials Registration NCT04380987.