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Enregistrement W3168033977 · doi:10.1016/s2666-5247(21)00114-2

Combining immunomodulators and antivirals for COVID-19

2021· letter· en· W3168033977 sur OpenAlexaff
Luke Y. C. Chen, Tien T T Quach

Notice bibliographique

RevueThe Lancet Microbe · 2021
Typeletter
Langueen
DomaineMedicine
ThématiqueCOVID-19 Clinical Research Studies
Établissements canadiensUniversity of British Columbia
Organismes subventionnairesnon disponible
Mots-clésCytokine stormCoronavirus disease 2019 (COVID-19)InterferonScopusCytokine release syndromeImmunologyViral loadSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Immune systemMedicineCytokineDiseaseVirusVirologyBiologyMEDLINEInternal medicineInfectious disease (medical specialty)

Résumé

récupéré en direct d'OpenAlex

We read with interest the Comment by Jesus Bermejo-Martin and colleagues1Bermejo-Martin JF Almansa R Tedim AP et al.Mounting evidence of impaired viral control in severe COVID-19.Lancet Microbe. 2021; (published online April 15.)https://doi.org/10.1016/S2666-5247(21)00084-7Summary Full Text Full Text PDF PubMed Scopus (7) Google Scholar on impaired viral control in severe COVID-19. They highlight the importance of ongoing research on plasma viral load monitoring and antiviral therapies, and we agree with these points. However, three concepts in their Comment regarding host inflammatory responses and immunomodulatory therapy require clarification or rebuttal. First, the simple biphasic model of viral invasion followed by uncontrolled inflammation, which Bermejo-Martin and colleagues oppose, is already obsolete. SARS-CoV-2 elicits highly heterogeneous host responses ranging from mild illness in most people, to severe disease and critical illness in 2–10% of those infected.2Chen LY Biggs CM Jamal S et al.Soluble interleukin-6 receptor in COVID cytokine storm syndrome.Cell Rep Med. 2021; (published online April 19.)https://doi.org/10.1016/j.xcrm.2021.100269Summary Full Text Full Text PDF Scopus (35) Google Scholar Much of this heterogaeneity is due to differences in immune responses to the virus. Severe disease is characterised by a defective type I or III interferon response followed by persistent, maladaptive hypercytokinemia, termed COVID-19 cytokine storm syndrome.3Galani I-E Rovina N Lampropoulou V et al.Untuned antiviral immunity in COVID-19 revealed by temporal type I/III interferon patterns and flu comparison.Nature Immunol. 2021; 22: 32-40Crossref PubMed Scopus (290) Google Scholar, 4Chen LYC Quach TTT COVID-19 cytokine storm syndrome: a threshold concept.Lancet Microbe. 2021; 2: e49-e50Summary Full Text Full Text PDF PubMed Scopus (50) Google Scholar The cytokine system most implicated in prognosis and treatment is the interleukin (IL)-6-soluble IL-6 receptor axis.2Chen LY Biggs CM Jamal S et al.Soluble interleukin-6 receptor in COVID cytokine storm syndrome.Cell Rep Med. 2021; (published online April 19.)https://doi.org/10.1016/j.xcrm.2021.100269Summary Full Text Full Text PDF Scopus (35) Google Scholar Second, the authors rightly caution against overly reductive models of COVID-19; unfortunately, this advice is immediately followed by the rather reductive statement that COVID-19 is “a viral disease, not an autoimmune one”.1Bermejo-Martin JF Almansa R Tedim AP et al.Mounting evidence of impaired viral control in severe COVID-19.Lancet Microbe. 2021; (published online April 15.)https://doi.org/10.1016/S2666-5247(21)00084-7Summary Full Text Full Text PDF PubMed Scopus (7) Google Scholar 10% of patients with severe disease have autoantibodies against type I interferons;5Bastard P Rosen LB Zhang Q et al.Autoantibodies against type I IFNs in patients with life-threatening COVID-19.Science. 2020; 370eabd4585Crossref PubMed Scopus (1565) Google Scholar even so, no clinicians seriously consider COVID-19 an autoimmune disease in the same vein as, say, rheumatoid arthritis. A more useful parallel is viral haemophagocytic lymphohistiocytosis, which is characterised by an excessive, deleterious host immune response to various viral infections. Epstein-Barr virus haemophagocytic lymphohistiocytosis has a much worse prognosis than cytomegalovirus haemophagocytic lymphohistiocytosis. One factor that explains this difference is the existence of effective antiviral therapies against cytomegalovirus, which are used in addition to immunosuppressive therapy, whereas there are no such antiviral therapies for Epstein-Barr virus haemophagocytic lymphohistiocytosis. A combined immunomodulatory and antiviral approach would likewise be ideal in COVID-19. Finally, investigating the pathological immune activation of COVID-19 does not detract from antiviral research. The main domains of trials have included antivirals (eg, lopinavir or remdesivir), immunomodulation (eg, corticosteroids or tocilizumab), and immunoglobulins (eg, convalescent plasma). Only the immunomodulation domain has currently improved mortality (appendix). We have noted that pathological immune activation can be a troublesome, transformative, threshold concept.4Chen LYC Quach TTT COVID-19 cytokine storm syndrome: a threshold concept.Lancet Microbe. 2021; 2: e49-e50Summary Full Text Full Text PDF PubMed Scopus (50) Google Scholar This threshold concept has practical, real world benefits. Any debate pitting immunomodulation against antiviral therapy is counterproductive. Corticosteroids and IL-6 inhibitors save lives; finding effective antivirals to complement them would be a welcome development. We declare no competing interests. Download .pdf (.16 MB) Help with pdf files Supplementary appendix Mounting evidence of impaired viral control in severe COVID-19Substantial gaps in knowledge regarding the evolution and pathogenesis of COVID-19 remain after 1 year of the SARS-CoV-2 pandemic. At the start of the pandemic, a biphasic model to explain the physiopathology of COVID-19 became popular. This model divided the disease course into an initial viral response phase, followed by the inflammatory response phase.1,2 In the inflammatory response phase, the virus is thought to have a minor role, and host inflammatory responses are the predominant mediators of pathophysiology, by triggering tissue damage leading to acute respiratory distress syndrome. Full-Text PDF Open AccessCombining immunomodulators and antivirals for COVID-19 – Authors' replyWe thank Luke Chen and Tien Quach for their interest on our Comment. We could not agree more with the title of their reply letter, combining immunomodulators and antivirals for COVID-19, which is consistent with the conclusion of our Comment: “the available evidence would support combined strategies to simultaneously control viral replication and deleterious inflammation, based on specific indicators or biomarkers of both pathophysiological processes”.1 Our conclusion already proposed using biological indicators to guide anti-inflammatory and antiviral therapies in COVID-19, which converges with the so-called threshold concept of pathological immune activation raised by Chen and Quach. Full-Text PDF Open Access

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,007
score de la tête « metaresearch » (Gemma)0,024
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Commentaire · Signal consensuel: Commentaire
Score de désaccord entre enseignants0,016
Score d'incertitude au seuil0,038

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0070,024
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0020,002
Bibliométrie0,0010,001
Études des sciences et des technologies0,0020,003
Communication savante0,0030,007
Science ouverte0,0030,002
Intégrité de la recherche0,0160,030
Charge utile insuffisante (le modèle a refusé de juger)0,0060,006

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,127
Tête enseignante GPT0,432
Écart entre enseignants0,304 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreCommentaire

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations5
Publié2021
Routes d'admission1
Résumé présentoui

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