In this manuscript we use realistic data to conduct a network meta-analysis using a Bayesian approach to analysis. The purpose of this manuscript is to explain, in lay terms, how to interpret the output of such an analysis. Many readers are familiar with the forest plot as an approach to presenting the results of a pairwise meta-analysis. However when presented with the results of network meta-analysis, which often does not include the forest plot, the output and results can be difficult to understand. Further, one of the advantages of Bayesian network meta-analyses is in the novel outputs such as treatment rankings and the probability distributions are more commonly presented for network meta-analysis. Our goal here is to provide a tutorial for how to read the outcome of network meta-analysis rather than how to conduct or assess the risk of bias in a network meta-analysis.

Natural zeolites have traditionally been used as supplements in animal nutrition with positive effects in terms of either faster growth or reduced incidence of diseases and death. The discovery that natural zeolites may act as drugs or coadjutants in pharmaceutical preparations has greatly enlarged the field of their applications in many sectors of biology and medicine, opening unexpected horizons for either basic or applied research. This review updates the state of the art of research in this sector, focusing on clinoptilolite-rich materials, with two main purposes: (1) trying to rationalize this subject, which is extremely variable and heterogeneous, and (2) raising doubts about unsuitable uses of natural zeolites in the light of their known properties and expected behaviour.