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Accuracy of the Surgeons’ Clinical Prediction of Perioperative Complications Using a Visual Analog Scale

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Abstract

Background

The ability to predict who will develop perioperative complications remains difficult because the etiology of adverse events is multifactorial. This study examines the preoperative and postoperative ability of the surgeon to predict complications and assesses the significance of a change in prediction.

Methods

This was a prospective study of 1013 patients. The surgeon assessed the risk of a major complication on a 100-mm visual analog scale (VAS) immediately before and after surgery. When the VAS score was changed, the surgeon was asked to document why. Patients were assessed up to 30 days postoperatively.

Results

Surgeons made a meaningful preoperative prediction of major complications (median score = 27mm vs. 19mm, p < 0.01), with an area under the receiver operating characteristic curve of 0.74 for mortality, 0.67 for major complications, and 0.63 for all complications. A change in the VAS score postoperatively was due to technical reasons in 74% of stated cases. An increased VAS score identified significantly more complications, but the improvement in the discrimination was small. When included in a multivariate model for predicting postoperative complications, the surgeon’s VAS score functioned as an independent predictive variable and improved the predictive ability, goodness of fit, and discrimination of the model.

Conclusions

Clinical assessment of risk by the surgeon using a VAS score independently improves the prediction of perioperative complications. Including the unique contribution of the surgeon’s clinical assessment should be considered in models designed to predict the risk of surgery.

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References

  1. Adab P, Rouse AM, Mohammed MA, et al. (2002) Performance league tables: the NHS deserves better. Br Med J 324:95–98

    Article  Google Scholar 

  2. Pettigrew RA, Hill GL (1986) Indicators of surgical risk and clinical judgement. Br J Surg 73:47–51

    Article  PubMed  CAS  Google Scholar 

  3. Copeland GP (2002) The POSSUM system of surgical audit. Arch Surg 137(1):15–20

    Article  PubMed  Google Scholar 

  4. Copeland GP, Jones D, Walters M (1991) POSSUM: a scoring system for surgical audit. Br J Surg 78:356–369

    Article  Google Scholar 

  5. Knaus WA (2002) APACHE 1978–2001: The development of a quality assurance system based on prognosis: Milestones and personal reflections. Arch Surg 137:37–42

    Article  PubMed  Google Scholar 

  6. Knaus WA, Draper EA, Wagner DP, et al. (1985) APACHE II: a severity of disease classification system. Crit Care Med 13:818–829

    Article  PubMed  CAS  Google Scholar 

  7. Sutton R, Bann S, Brooks M, et al. (2002) Surgical Risk Scale as an improved tool for risk-adjusted analysis in comparative surgical audit. Br J Surg 89(6):763–768

    Article  PubMed  CAS  Google Scholar 

  8. Pillai SB, van Rij AM, Williams S, et al. (1999) Complexity and risk adjusted models for measuring surgical outcome. Br J Surg 86:1567–1572

    Article  PubMed  CAS  Google Scholar 

  9. Daley J, Khuri SF, Henderson W, et al. (1997) Risk adjustment of the postoperative morbidity rate for the comparative assessment of the quality of surgical care: results of the National Veterans Affairs Surgical Risk Study. J Am Coll Surg 185(4):328–340

    PubMed  CAS  Google Scholar 

  10. Khuri SF, Daley J, Henderson W, et al. (1997) Risk adjustment of the postoperative 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 185:315–327

    PubMed  CAS  Google Scholar 

  11. Tekkis PP, Poloniecki JD, Thompson MR, et al. (2002) ACPGBI colorectal cancer study 2002. Part B: Risk adjusted outcomes. The ACPGBI colorectal cancer model. London, Association of Coloproctology of Great Britain and Ireland

  12. Klotz HP, Candinas D, Platz A, et al. (1996) Preoperative risk assessment in elective general surgery. Br J Surg 83:1788–1791

    Article  PubMed  CAS  Google Scholar 

  13. Ondrula DP, Nelson RL, Prasad ML, et al. (1992) Multifactorial Index of Preoperative Risk Factors in colon resections. Dis Colon Rectum 35:117–122

    Article  PubMed  CAS  Google Scholar 

  14. Al-Ruzzeh SI, Asimakopoulos G, Ambler G, et al. (2003) Validation of four different risk stratification systems in patients undergoing off-pump coronary artery bypass surgery: a UK multicentre analysis of 2223 patients. Heart 89(4):432–435

    Article  PubMed  CAS  Google Scholar 

  15. Jones DR, Copeland GP, de Cossart L (1992) Comparison of POSSUM with APACHE II for prediction of outcome from a surgical high dependency unit. Br J Surg 79:1293–1296

    Article  PubMed  CAS  Google Scholar 

  16. Martin IG, Kempthorne AE, Connolly A (2002) Assessing patients for general surgical procedures: how well can we predict outcomes? ANZ J Surg 72(Suppl 1):A24

    Google Scholar 

  17. Pettigrew RA, Burns HJG, Carter DC (1987) Evaluating surgical risk: the importance of technical factors in determining outcome. Br J Surg 74:791–794

    Article  PubMed  CAS  Google Scholar 

  18. Russell RCG (1987) Surgical technique. Br J Surg 74:763–764

    Article  PubMed  CAS  Google Scholar 

  19. Ouriel K, Geary K, Green RM, et al. (1990) Factors determining survival after ruptured aortic aneurysm: The hospital, the surgeon, and the patient. J Vasc Surg 11:493–496

    Article  PubMed  CAS  Google Scholar 

  20. Bancewicz J (1990) Cancer of the oesophagus. Find a good surgeon. Br J Surg 300:3–4

    CAS  Google Scholar 

  21. Callahan MA, Christos PJ, Gold HT, et al. (2003) Influence of surgical subspecialty training on in-hospital mortality for colectomy patients. Ann Surg 238(4):629–639

    PubMed  Google Scholar 

  22. Halm EA, Lee C, Chassin MR (2002) Is volume related to outcome in health care? A systematic review and methodologic critique of the literature. Ann Intern Med 137:511–520

    PubMed  Google Scholar 

  23. Ingemar I (2003) The volume-outcome relationship in cancer surgery: a hard sell. Ann Surg 238(6):777–781

    Article  Google Scholar 

  24. Woodfield JC, van Rij AM, Pettigrew RA, et al. (2003) A comparison of the prophylactic efficacy of ceftriaxone and cefotaxime in abdominal surgery. Am J Surg 185:45–49

    Article  PubMed  CAS  Google Scholar 

  25. Department of Surgery Clinical Audit Research Unit (1996) The Otago Audit System: Codes for Surgical Audit (General/Vascular) 1996 Revision. Dunedin, New Zealand, University of Otago

    Google Scholar 

  26. Arvidsson S, Ouchterlony J, Sjostedt L, et al. (1996) Predicting postoperative adverse events. Clinical efficiency of four general classification systems. The project perioperative risk. Acta Anaesthesiol Scand 40:783–791

    Article  PubMed  CAS  Google Scholar 

  27. Hartley MN, Sagar PM (1994) The surgeons gut feeling as a predictor of postoperative outcome. Ann R Coll Surg Engl 76(Suppl 6):277–278

    PubMed  CAS  Google Scholar 

  28. Markus PM, Martell I, Leister O, et al. (2005) Predicting postoperative morbidity by clinical assessment. Br J Surg 92:101–106

    Article  PubMed  CAS  Google Scholar 

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Authors and Affiliations

  1. Department of Surgery, University of Otago, Dunedin, New Zealand

    John C. Woodfield, Ross A. Pettigrew, Michael Landmann & Andre M. van Rij

  2. Department of Surgery, University of Auckland, Auckland, New Zealand

    Lindsay D. Plank

  3. Department of Surgery, University of Otago Medical School, P. O. Box 913, Dunedin, New Zealand

    Andre M. van Rij

Authors
  1. John C. Woodfield
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  2. Ross A. Pettigrew
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  3. Lindsay D. Plank
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  4. Michael Landmann
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  5. Andre M. van Rij
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Corresponding author

Correspondence to Andre M. van Rij.

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Woodfield, J.C., Pettigrew, R.A., Plank, L.D. et al. Accuracy of the Surgeons’ Clinical Prediction of Perioperative Complications Using a Visual Analog Scale. World J Surg 31, 1912–1920 (2007). https://doi.org/10.1007/s00268-007-9178-0

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  • DOI: https://doi.org/10.1007/s00268-007-9178-0

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