A Review of Risk Scoring Systems Utilised in Patients Undergoing Gastrointestinal Surgery
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Adequate stratification and scoring of risk is essential to optimise clinical practice; the ability to predict operative mortality and morbidity is important. This review aims to outline the essential elements of available risk scoring systems in patients undergoing gastrointestinal surgery and their differences in order to enable effective utilisation.
The English literature was searched over the last 50 years to provide an overview of systems pertaining to the adult surgical patient.
Scoring systems can provide objectivity and mortality prediction enabling communication and understanding of severity of illness. Incorporating subjective factors within scoring systems can allow clinicians to apply their experience and understanding of the situation to an individual but are not reproducible. Limitations relating to obtaining variables, calculating predicted mortality and applicability were present in most systems. Over time scoring systems have become out-dated which may reflect continuing improvement in care. APACHE II shows the importance of reproducibility and comparability particularly when assessing critically ill patients. Both NSQIP in the USA and P-POSSUM in the UK seem to have many benefits which derive from their comprehensive dataset. The “Surgical Apgar” score offers relatively objective criteria which contrasts against the subjective nature of the ASA score.
P-POSSUM and NSQIP are comprehensive but are difficult to calculate. In the search for a simple and easy to calculate score, the “Surgical Apgar” score may be a potential answer. However, more studies need to be performed before it becomes as widely taken up as APACHE II, NSQIP and P-POSSUM.
KeywordsCritical illness Critical care Surgery Risk assessment Peri-operative care Prognosis High dependency unit Scoring systems
Acute Physiology and Chronic Health Evaluation
American Society of Anaesthesiologists
Alert/Voice/Pain/Unresponsive (conscious level)
British United Provident Association
Cardiac Risk Index Assessment
Intensive Care Unit
Estimation of Physiologic Ability and Stress
Glasgow Coma Scale
High Dependency Unit
Intensive Care National Audit and Research Centre
Mortality Prediction Model
National Surgical Quality Improvement Programme
Physiological and Operative Severity Score for EnUmeration of Mortality and Morbidity
Surgical Mortality Score
Surgical Risk Score
Simplified Acute Physiology Score
Arterial Oxygen Saturations
Special thanks to Dr Jules Barwell, Senior Lecturer and Honorary Consultant in Genetics, Leicester and Dr Barry Phillips, Consultant Intensivist, Eastbourne for their support and suggestions having reviewed the paper.
- 1.National Institute for Health and Clinical Excellence. Acutely ill patients in hospital: recognition of and response to acute illness in adults in hospital. London: National Institute for Health and Clinical Excellence; 2007.Google Scholar
- 23.Beck DH, Taylor BL, Millar B, Smith GB. Prediction of outcome from intensive care: a prospective cohort study comparing Acute Physiology and Chronic Health Evaluation II and III prognostic systems in a United Kingdom intensive care unit. Crit Care Med. 1997;25(1):9–15. doi: 10.1097/00003246-199701000-00006.CrossRefPubMedGoogle Scholar
- 29.Metnitz PG, Valentin A, Vesely H, Alberti C, Lang T, Lenz K, et al. Hiesmayr M. Prognostic performance and customization of the SAPS II: results of a multicenter Austrian study. Simplified Acute Physiology Score. Intensive Care Med. 1999;25(2):192–197. doi: 10.1007/s001340050815.CrossRefPubMedGoogle Scholar
- 31.Moreno RP, Metnitz PG, Almeida E, Jordan B, Bauer P, Campos RA, et al. SAPS 3--From evaluation of the patient to evaluation of the intensive care unit. Part 2: Development of a prognostic model for hospital mortality at ICU admission. Intensive Care Med. 2005;31(10):1345–1355. doi: 10.1007/s00134-005-2763-5.CrossRefPubMedGoogle Scholar
- 44.Vather R, Zargar-Shoshtari K, Adegbola S, Hill AG. Comparison of the possum, P-POSSUM and Cr-POSSUM scoring systems as predictors of post-operative mortality in patients undergoing major colorectal surgery. ANZ J Surg. 2006;76(9):812–816. doi: 10.1111/j.1445-2197.2006.03875.x.CrossRefPubMedGoogle Scholar
- 46.Prytherch DR, Whiteley MS, Higgins B, Weaver PC, Prout WG, Powell SJ. POSSUM and Portsmouth POSSUM for predicting mortality. Physiological and Operative Severity Score for the enUmeration of Mortality and morbidity. Br J Surg. 1998;85(9):1217–1220. doi: 10.1046/j.1365-2168.1998.00840.x.CrossRefPubMedGoogle Scholar
- 47.Haga Y, Ikei S, Wada Y, Takeuchi H, Sameshima H, Kimura O, et al. Evaluation of an Estimation of Physiologic Ability and Surgical Stress (E-PASS) scoring system to predict post-operative risk: a multicenter prospective study. Surg Today. 2001;31(7):569–574. doi: 10.1007/s005950170088.CrossRefPubMedGoogle Scholar
- 49.Oka Y, Nishijima J, Oku K, Azuma T, Inada K, Miyazaki S, et al. Usefulness of an estimation of physiologic ability and surgical stress (E-PASS) scoring system to predict the incidence of post-operative complications in gastrointestinal surgery. World J Surg. 2005;29(8):1029–1033. doi: 10.1007/s00268-005-7719-y.CrossRefPubMedGoogle Scholar
- 50.Khuri SF, Daley J, Henderson W, Hur K, Gibbs JO, Barbour G, et al. Risk adjustment of the post-operative mortality rate for the comparative assessment of the quality of surgical care: results of the National Veterans Affairs Surgical Risk Study. J Am Coll Surg. 1997;185(4):315–327.PubMedGoogle Scholar