Note: This clinical practice guideline (CPG) on UGIB was developed under the direction of Drs. Alan N. Barkun and Marc Bardou, in accordance with the policies and procedures of the CAG and under the direction of CAG Clinical Affairs. It has been reviewed by the CAG Clinical Affairs Committee and the CAG Board of Directors. The CPG was developed after a thorough consideration of the medical literature and the best available evidence and clinical experience. It represents the consensus of a Canadian and international panel comprising experts on this topic. The CPG aims to provide a reasonable and practical approach to care for specialists and allied health professionals who are charged with providing optimal care to patients and their families, and it may be subject to change as scientific knowledge and technology advance and as practice patterns evolve.

Patients with LGIB have a high burden of comorbidity and frequent antiplatelet or anticoagulant use. Red cell transfusion was common but most patients were not shocked and required no endoscopic, radiological or surgical treatment. Nearly half were not investigated. In-hospital mortality was related to comorbidity, not severe haemorrhage.

BackgroundAdjustment for prognostic covariates can lead to increased power in the analysis of randomized trials. However, adjusted analyses are not often performed in practice.MethodsWe used simulation to examine the impact of covariate adjustment on 12 outcomes from 8 studies across a range of therapeutic areas. We assessed (1) how large an increase in power can be expected in practice; and (2) the impact of adjustment for covariates that are not prognostic.ResultsAdjustment for known prognostic covariates led to large increases in power for most outcomes. When power was set to 80% based on an unadjusted analysis, covariate adjustment led to a median increase in power to 92.6% across the 12 outcomes (range 80.6 to 99.4%). Power was increased to over 85% for 8 of 12 outcomes, and to over 95% for 5 of 12 outcomes. Conversely, the largest decrease in power from adjustment for covariates that were not prognostic was from 80% to 78.5%.ConclusionsAdjustment for known prognostic covariates can lead to substantial increases in power, and should be routinely incorporated into the analysis of randomized trials. The potential benefits of adjusting for a small number of possibly prognostic covariates in trials with moderate or large sample sizes far outweigh the risks of doing so, and so should also be considered.

The RHI is a new histopathological index with favourable operating properties.