Repurposing fluvoxamine, and other psychiatric medications, for <scp>COVID</scp>‐19 and other conditions
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".