Outcomes after radical prostatectomy and cystectomy are on average likely to be better if these procedures are performed by and at high volume providers. For radical nephrectomy the evidence is unclear. The impact of volume based policies (increasing volume to improve outcomes) depends on the extent to which "practice makes perfect" explains the observed results. Further studies should explicitly address selective referral and confounding as alternative explanations. Longitudinal studies should be performed to evaluate the impact of volume based policies.

A model that can accurately predict post -liver transplant mortality would be useful for clinical decision making, would help to provide patients with prognostic information, and would facilitate fair comparisons of surgical performance between transplant units. A systematic review of the literature was carried out to assess the quality of the studies that developed and validated prognostic models for mortality after liver transplantation and to validate existing models in a large data set of patients transplanted in the United Kingdom (UK) and Ireland between March 1994 and September 2003. Five prognostic model papers were identified. The quality of the development and validation of all prognostic models was suboptimal according to an explicit assessment tool of the internal, external, and statistical validity, model evaluation, and practicality. The discriminatory ability of the identified models in the UK and Ireland data set was poor (area under the receiver operating characteristic curve always smaller than 0.7 for adult populations). Due to the poor quality of the reporting, the methodology used for the development of the model could not always be determined. In conclusion, these findings demonstrate that currently available prognostic models of mortality after liver transplantation can have only a limited role in clinical practice, audit, and research. D eveloping a prognostic model that can accurately predict mortality of patients after liver transplantation has been the focus of much research. Such models are important for many reasons. First, it can be used to identify patients with end-stage liver disease who may benefit from liver transplantation. Second, prediction of mortality after liver transplantation can provide patients with information about their prognosis that will support informed decision making about their treatment. Third, prognostic information is an essential component of the construction of risk-adjusted comparisons of outcomes between transplant units.It has been shown that the model for end-stage liver disease (MELD) score is an accurate predictor of survival of patients without transplantation. 1 However, the MELD score is a poor predictor of survival after transplantation. 2 It has been claimed that prognostic models that specifically aim to predict post -liver transplant mortality on the basis of clinical information that is available before transplantation will always fail to perform adequately. The reasoning is that outcomes after liver transplantation may depend on unpredictable events that occur during the perioperative period rather than on the severity of the liver disease and comorbid conditions. A first step to verifying this claim is to evaluate existing prognostic models for mortality after liver transplantation. In light of this, a systematic review of the literature was carried out (1) to assess the quality of the studies that developed and described prognostic models, (2) to validate existing models on a United Kingdom (UK) and Ireland data set, and (3) to establish...

Calcium-channel blockers and beta-blockers are effective in reducing postoperative atrial tachyarrhythmia. The use of these medications should be individualized, and possible adverse events of beta-blockers should be taken into account. Randomized clinical trials do not support the use of digitalis in general thoracic surgery. The value of magnesium as a supplement to a main prophylactic regimen should be explored.