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Enregistrement W4229055092 · doi:10.1002/wps.20983

Repurposing fluvoxamine, and other psychiatric medications, for <scp>COVID</scp>‐19 and other conditions

2022· letter· en· W4229055092 sur OpenAlexaboutno aff
Eric J. Lenze, Angela M. Reiersen, Paramala Santosh

Notice bibliographique

RevueWorld Psychiatry · 2022
Typeletter
Langueen
DomaineBiochemistry, Genetics and Molecular Biology
ThématiquePharmacological Receptor Mechanisms and Effects
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésFluvoxamineMedicineRepurposingPlaceboRandomized controlled trialExacerbationPsychiatryFluoxetineInternal medicinePharmacologyAlternative medicine

Résumé

récupéré en direct d'OpenAlex

Early in the COVID-19 pandemic, repurposing some already-approved drugs was proposed for reducing the morbidity and mortality risk of those who were infected. For example, the UK RECOVERY trial demonstrated the benefits of dexamethasone for severe respiratory illness, leading to its widespread adoption by mid-2020. Many psychiatric drugs have antiviral and immune modulatory effects, and are candidates for repurposing for COVID-19 and other non-psychiatric conditions. Fluvoxamine is a potent activator of the sigma-1 receptor (S1R), dampening cellular stress responses and leading to anti-inflammatory effects1. In 2020, we conducted a randomized placebo-controlled trial which demonstrated that fluvoxamine prevented clinical deterioration from COVID-192. These findings were replicated in a larger study, the TOGETHER trial, which randomized 1,497 patients to fluvoxamine 100 mg twice daily or placebo for 10 days. The trial found a 32% reduction in risk for severe disease progression with fluvoxamine. Among patients who were compliant with their treatment regimen, taking at least 80% of their pills, there was a 66% reduction in risk for hospitalization with fluvoxamine, and only one death in the fluvoxamine group compared to 12 in the placebo group3. Fluvoxamine has now been recommended for use by several organizations, including the Ontario province in Canada. Two ongoing trials are testing fluvoxamine at a lower dose of 50 mg twice daily: the ACTIV-6 trial and the COVID OUT trial. Based on this growing scientific evidence, as well as its safety profile and availability, we believe that fluvoxamine should be used in COVID-19 for outpatients at high risk for morbidity and mortality from complications of the infection. The recommended dose is 100 mg twice daily for 10-15 days, which can be adjusted based on tolerability. No laboratory monitoring is needed, but co-prescribed drugs should be evaluated for potential interactions, because of fluvoxamine’s inhibition of cytochromes P450 (CYP) 1A2 and 2C19. Patients taking theophylline, clozapine, olanzapine and tizanidine, which are CYP1A2 substrates, should not be administered fluvoxamine in most cases. Caffeine, a CYP­1A2 substrate, should be eliminated or greatly reduced during fluvoxamine treatment. Also, for patients already taking a serotonin reuptake inhibitor (SSRI) or a serotonin-norepinephrine reuptake inhibitor (SNRI), we would discourage adding fluvoxamine or switching to it for COVID-19 treatment. Other potential mechanisms have been suggested for the effects of SSRIs, beyond fluvoxamine alone, including inhibition of hypercoagulable states or excess serotonin release by platelets, and functional inhibition of acid sphingomyelinase, leading to inhibition of entry and propagation of SARS-CoV-2 into cells1. For example, a study of adults hospitalized for severe COVID-19 found that those who were taking a medication which was a functional inhibitor of acid sphingomyelinase (including all SSRIs) were less likely to be intubated or die4. A study of psychiatric inpatients in New York state during the first wave of the pandemic in 2020 found that SSRIs and SNRIs, and specifically fluoxetine, showed a protective effect against COVID-19 infection5. Also, a study of 83,584 patients found that those who were taking SSRIs, and in particular those who were on fluoxetine or fluvoxamine, had a reduced mortality6. Given the time and costs of conducting large randomized con­trolled trials, it is tempting to use the data from these observational studies as sufficient evidence for drug repurposing. Yet, observational studies are known to suffer from biases, including confounding by indication. Although techniques exist to reduce these biases, it remains controversial to assert a drug’s benefit for a new indication based purely on observational data. For example, a drug or drug class might appear to be protective against COVID-19, yet be a proxy for some other patient characteristic or behavior (e.g., social isolation because of depression). Thus, promising observational study findings will still require corroboration in randomized trials, and accomplishments such as the UK RECOVERY trial show that rapid clinical innovations are possi­ble. SSRIs and other antidepressants might also help with the long­er-term neuropsychiatric manifestations of COVID-19. “Neuro­psychiatric long COVID” refers to the fact that cognitive and psy­chiatric symptoms are a large proportion of the constellation of post-acute COVID-19 symptoms that are either chronic or intermittent, and are bothersome, painful and disabling. For example, the Patient-Led Research Collaborative assessed the prevalence of symptoms in 3,762 persons over 7 months post-COVID7. They found a preponderance of neuropsychiatric symptoms, particularly memory and cognitive dysfunction, which were experienced by over 85% of respondents, with negative impacts on daily functioning. Other common neuropsychiatric symptoms were insomnia, anxiety, depression, and occasionally hallucinations (olfactory and other). The etiological factors involved in neuropsychiatric long COVID may include persistent SARS-CoV-2 infection and a prolonged hyper-inflammatory state, compounded by psychosocial stress. Unfortunately, there is little research to-date on the treatment of neuropsychiatric long COVID. One recent report in post-COVID depressive illness8 found that 55/60 (92%) patients showed a clinical response after 4 weeks of SSRI treatment. This strong antidepressant benefit was seen irrespective of gender, previous psychiatric history, and SSRI type. The authors speculated that this rapid response to SSRIs could be due to their direct action on neuroinflammation, in addition to their typical antidepressant mechanisms (which remain unclear). This was a single-site, open-label study, and more research is needed regarding the efficacy of various treatments. But this study also shows an important role for psychiatrists in managing, and supervising, the long-term neuropsychiatric effects of COVID-19. With the pandemic continuing to evolve, it will be critical to keep on answering key questions about the role of SSRIs in the treatment of acute COVID-19 illness. What is the best dose and timing of fluvoxamine, and how effective is it in combination with other treatments against COVID-19 (such as monoclonal antibodies)? Is fluoxetine, which has lower S1R affinity compared to fluvoxamine but has shown promise in preclinical and observational studies, also an effective treatment, considering that it is more widely available and easier to use? And what are the best treatments for neuropsychiatric manifestations of long COVID, and in which patients? Given that many psychotropics are now appreciated to have widespread molecular, cellular and physiological effects, in­cluding anti-inflammatory, neuroprotective and cardioprotective, and antiproliferative, we can expect that lessons learned in testing these medications for COVID-19 will be important for other drug repurposing efforts, ranging from infectious and inflammatory diseases, to neurodegenerative diseases such as Alzheimer’s disease, and cancer9.

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict)
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 enseignants0,419
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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 Opus0,015
Tête enseignante GPT0,300
Écart entre enseignants0,285 · 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 tête enseignante, pas un consensus.

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

Citations10
Publié2022
Routes d'admission1
Résumé présentoui

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