Revista de comunicaciones de atención médica Acceso abierto

Abstracto

Commentary on “Statistical Analysis Methods Applied to Early Outpatient COVID-19 Treatment Case Series Data” by Gkioulekas, Mccullough and Zelenko”: A Return Back to the Future

Marc Rendell*

Context: This commentary deals with the article “Statistical analysis methods applied to early outpatient COVID-19 treatment case series data” by Gkioulekas, McCullough and the late Dr. Vladimir Zelenko, published in COVID in August, 2022. Although highly mathematical, the work is readily understandable as a framework to extract valid information from case series data, outside the randomized, placebo, controlled clinical trial ordained approach.

Objective: The gist of the approach is to recognize probable benefit when results of treatment show a large magnitude of difference with those obtained in the wider population derived lower bounds for mortality. The particular application of the mathematical construct was to the use of empirical treatments, notably the Zelenko and Mc- Cullough protocols, in patients with early phase SARS-Cov-2 infections. Yet, the formalism is quite generally applicable to data obtained from case series in conditions where the safety of interventions is well known historically.

Conclusion: The mathematical formulation proposed is very well suited to the large population studies which have essentially superseded randomized control trials in evaluation of current COVID-19 prevention and treatment modalities.