Article Text

other Versions

Clinical risk scores to guide perioperative management
  1. Sarah Barnett1,
  2. Suneetha Ramani Moonesinghe2
  1. 1Centre for Anaesthesia, University College London Hospital, London, UK
  2. 2Surgical Outcomes Research Centre (SOuRCe) UCL/UCLH Joint Comprehensive Biomedical Research Centre, Department of Anaesthetics, University College London Hospital, London, UK
  1. Correspondence to Dr Sarah Barnett, Centre for Anaesthesia, 3rd Floor Maples Link Corridor, University College London Hospital, 235 Euston Road, London NW1 2BU, UK; sarahfbarnett{at}


Perioperative 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.

  • Perioperative
  • scoring systems
  • risk stratification
  • surgery
  • adult anaesthesia
  • adult surgery

Statistics from


  • Competing interests SRM works within the University College London/University College London Hospitals' Joint Comprehensive Biomedical Research Centre, which received a proportion of funding from the UK Department of Health's National Institute for Health Research Biomedical Research Centres' funding scheme.

  • Provenance and peer review Commissioned; externally peer reviewed.

Request Permissions

If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.

Linked Articles