Oral care interventions (OCI) have been recognized as favorably impacting the risk and course of ventilator-associated pneumonia (VAP) in critically ill patients.  A range of preventive strategies have been suggested that include the use of topical (rinse) formulations of antimicrobial agents, such as chlorhexidine (CHX) and povidone iodine (PI), and/or mechanical cleansing by healthcare providers. [1–4] Debate persists as to which tactic is most clinically- and cost-effective. A number of randomized trials (RCTs) have been completed to address this uncertainty.  In almost all cases, these RCTs have used a standard clinical trial pairwise design in which a placebo or best care was compared to a test agent or regimen. While this approach provides snapshot outcomes for a specific intervention, it lacks the ability to hierarchically assess or rank the efficacy of each in the context of all of the interventions studied.
To address this deficiency, we explored the utility of a novel approach in which network meta-analysis (NMA) was applied to a previously published comprehensive pairwise meta-analysis (PMA).  NMA, also known as multiple treatment comparison or mixed treatment comparison, is a method of generalization of conventional pairwise meta-analysis whereby the network statistically combines direct and indirect evidence from trials  to yield inter-study intervention comparisons. In addition, NMA expresses relative effectiveness of interventions among all trials and then rank orders them. We explored the utility of NMA as a means of comparing different OCIs with the objective of identifying those most effective for mitigating VAP in critically ill patients.
Concepts Of Network Meta-analysis
For clinical trials, conventional PMA typically focus on pairwise comparisons of an active treatment vs. a placebo or usual care with the objective of assessing superiority of the test agent vs. a control. If the investigation seeks to compare multiple active agents simultaneously, the sample size must increase leading to extended accrual times, extraordinary expense and efficacy assessment challenges.
In contrast NMA utilizes a multiple comparison methodology which enables the interventions of one trial to be contrasted with the active interventions of other trials, while maintaining the internal randomization of the direct and indirect comparisons. [figure 1]. For example, when two active OCIs like chlorhexidine ( CHX) and Toothbrushing (Tb) are independently compared for efficacy against a saline control in two different trials then randomised comparison in the trial 1, CHX and saline provides a direct estimate of the treatment effects of CHX and Saline, measured on the scale as log odds ratio. We then denote this approach as θ CHX Saline direct. Trial 2, provide information on the direct comparison between treatment Tb and Saline, denoted by θ Tb Saline direct. Then NMA provide indirect evidence for the comparison of CHX and Tb from the treatment difference CHX and Saline and Tb and Saline as follows:
θ CHX Tb indirect = θ CHX Saline direct - θ Tb Saline direct and the variance of this association is given by the Var (θ CHX Tbindirect) = Var(θ CHX Saline direct ) + Var (θ Tb Saline direct ). So as to have the NMA combination for the direct and indirect comparisons, we are assuming that the trial 1 and 2 are independent, the underlying effects are consistent and any differences in the data are due to random error. The NMA now has a consequent network having its integer of total treatments, designs (a design refers to each combination of treatment), pairwise comparisons and its subsequent statistical inferences of all the included studies.