PubMed · 15520909
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A M Kassem. 2004. Gastrointestinal bleeding.. https://doi.org/10.1055/s-2004-825966
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Gastrointestinal bleeding is a frequent and severe complication of portal hypertension. The most frequent cause of the bleeding is variceal rupture. Despite improvements in prognosis after variceal bleeding over the past two decades, the 6-week mortality rate remains high, ranging from 15 to 30%. Patients die from uncontrolled bleeding, early rebleeding, infection, or renal failure within the first weeks of a bleeding episode. Poor hepatic function, severe portal hypertension with a hepatic venous pressure gradient (HVPG) >20 mmHg, and active bleeding at endoscopy are independently associated with poor prognosis. First-line treatment includes resuscitation, prophylactic antibiotic therapy, the combined use of vasoactive drugs (started as soon as possible), and an endoscopic procedure. Reconstitution of blood volume should be done cautiously to maintain the haematocrit between 25 and 30%. Terlipressin, somatostatin, or octreotide can be used, and drug therapy is maintained from 48 h to 5 days. Ligation is the endoscopic treatment of choice in bleeding oesophageal varices; in gastric varices, obturation with cyanoacrylate is preferable. Uncontrolled bleeding should be an indication for a salvage transjugular portosystemic shunt (TIPS). In patients with Child-Pugh score A, shunt surgery might be an alternative to TIPS. Trials are currently ongoing into the precise indications of early TIPS in selected patients with an HVPG >20 mmHg, and into the usefulness of administration of recombinant activated factor VII when there is an active bleeding at endoscopy.
Perhaps the greatest threat to the validity of a meta-analysis is the possibility of publication bias, where studies that are interesting or statistically significant are more likely to be published than those with less encouraging results. In particular, there is the concern that this bias might be 'one-sided', where studies indicating that the treatment is beneficial have a greater probability of publication. The impact that this type of bias has on the estimate of treatment effect has received a great deal of attention but this also has implications for estimates of between-study variance. Using step functions to model the bias it can be demonstrated that it is impossible to make generalizations concerning how we should revise estimates of between-study variance when presented with the possibility of publication bias. To determine this, assumptions must be made concerning the form that the bias takes, which is unknown in practice.