These results should be interpreted with caution, because most of these data come from observational, retrospective studies, which are subject to numerous biases and sometimes control poorly for confounders, despite the use of various statistical tools, such as logistic regression [51] . It is clear that analyses should not include only admission data. For example, in a welldefined patient population, such as after cardiac surgery, patients who develop gastrointestinal bleeding and require a blood transfusion have a worse prognosis, which is not necessarily the result of the blood transfusion. It is of paramount importance that all risks factors are taken into account. Ruttinger et al. [52] illustrated this point very well. In a series of more than 3,000 surgical patients, these authors showed by using a limited multivariable analysis that transfusions were associated with a worse outcome, but a more complete analysis cancelled out this statistical observation.