• Sarah Barnett and Suneetha Ramani Moonesinghe.
• Centre for Anaesthesia, 3rd Floor Maples Link Corridor, University College London Hospital, 235 Euston Road, London, UK. sarahfbarnett@googlemail.com
• Postgrad Med J. 2011 Aug 1; 87 (1030): 535-41.

AbstractPerioperative morbidity is associated with reduced long term survival. Comorbid disease, cardiovascular illness, and functional capacity can predispose patients to adverse surgical outcomes. Accurate risk stratification would facilitate informed patient consent and identify those individuals who may benefit from specific perioperative interventions. The ideal clinical risk scoring system would be objective, accurate, economical, simple to perform, based entirely on information available preoperatively, and suitable for patients undergoing both elective and emergency surgery. The POSSUM (Physiological and Operative Severity Score for the enUmeration of Mortality and Morbidity) scoring systems are the most widely validated perioperative risk predictors currently utilised; however, their inclusion of intra- and postoperative variables precludes validation for preoperative risk prediction. The Charlson Index has the advantage of consisting exclusively of preoperative variables; however, its validity varies in different patient cohorts. Risk models predicting cardiac morbidity have been extensively studied, despite the relatively uncommon occurrence of postoperative cardiac events. Probably the most widely used cardiac risk score is the Lee Revised Cardiac Risk Index, although it has limited validity in some patient populations and for non-cardiac outcomes. Bespoke clinical scoring systems responding to dynamic changes in population characteristics over time, such as those developed by the American College of Surgeons National Surgical Quality Improvement Program, are more precise, but require considerable resources to implement. The combination of objective clinical variables with information from novel techniques such as cardiopulmonary exercise testing and biomarker assays, may improve the predictive precision of clinical risk scores used to guide perioperative management.

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