ABSTRACT
Risk identification should allow the clinician to develop the optimal treatment strategy for the patient and to provide better informed consent. From a scientific point, evaluation of comorbidity is important in healthcare outcomes research because variation in baseline patient characteristics may significantly contribute to differences in outcome.1,2 Clinical reports that evaluate revascularization procedures, particularly those that compare different treatment methods, may be difficult to interpret when differences in factors that can affect complication rate and outcome are not identified and characterized. The completeness and reliability of data concerning comorbidity and therefore the risk of any intervention affect the validity of risk adjustment models and the accuracy of comparisons between different patient cohorts. However, it should also be stressed that risk factors that affect periinterventional morbidity and mortality rates are not identical with those that relate to patency.
