What we have learned from the COVID-19 pandemic: Time to think outside the box, maybe far outside

Post-COVID-19 neuropsychiatric manifestations: a suggested therapeutic approach to 'long COVID' with azithromycin

The devastating effects of the coronavirus disease (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) may not end when the acute illness has terminated. A subset of COVID-19 patients may have symptoms that persist for months. This condition has been described as 'long COVID'. From a historical perspective, it has been recognized that serious long-term neurological sequelae have been associated with RNA viruses such as influenza viruses and coronaviruses. A potential intervention for early post-COVID-19 neuropsychiatric impairment may be the commonly employed, readily available, reasonably priced macrolide antibiotic, azithromycin. We have observed a favourable clinical response with azithromycin in three patients with neurological symptoms associated with long COVID-19. We recommend considering formal clinical trials using azithromycin for patients with post-COVID-19 infection neurological changes including 'COVID fog' or the more severe neurological symptoms that may later develop.

Limitations of randomized, controlled, double-blinded studies in determining safety and effectiveness of treatments

Randomized, controlled, double-blinded studies, in which treated subjects are randomly selected from the same pool as controlled (untreated) ones and neither the caregiver nor the patient knows which is which, are widely accepted as the gold standard of experimental medicine. There are well-documented advantages of such studies. There are, however, significant limitations of them as well of which it is important to be aware. Notably, physicians who rely on experience and on what they were taught in medical school and post-graduate training are not necessarily wrong when this information runs contrary to the results of such studies. Some limitations of them are widely known and taught, such as inadequate sample size, failure of proper randomization, et cetera; others are less well-known. We shall focus on the latter.