Abstract Machine learning is increasingly used in mental health research and has the
potential to advance our understanding of how to characterize, predict, and treat mental …

The pleiotropic cytokine interleukin-6 (IL-6) has been implicated in the pathogenesis of
COVID-19, but uncertainty remains about the potential benefits and harms of targeting IL-6 …

Quantifying the effect of a treatment on a clinical outcome—causal inference—requires the
comparison of outcomes under different courses of action. For example, to quantify the effect …

Importance Mediation analyses of randomized trials and observational studies can generate
evidence about the mechanisms by which interventions and exposures may influence health …

Importance Therapies that improve survival in critically ill patients with coronavirus disease
2019 (COVID-19) are needed. Tocilizumab, a monoclonal antibody against the interleukin 6 …

Observational studies are commonly used to evaluate the association between a risk factor
or “exposure” and the time that elapses until an outcome of interest occurs (eg, smoking …

Purpose Limited data are available on venovenous extracorporeal membrane oxygenation
(ECMO) in patients with severe hypoxemic respiratory failure from coronavirus disease 2019 …

Selection bias remains a subject of controversy. Existing definitions of selection bias are
ambiguous. To improve communication and the conduct of epidemiologic research focused …

We make only one point in this article. Every quantitative study must be able to answer the
question: what is your estimand? The estimand is the target quantity—the purpose of the …

The increasing availability of large healthcare databases is fueling an intense debate on
whether real-world data should play a role in the assessment of the benefit–risk of medical …