Accuracy of the surgeons' clinical prediction of perioperative complications using a visual analog scale.
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 = 27 mm vs. 19 mm, 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.
Department of Surgery, University of Otago, Dunedin, New Zealand.
John C
JC
Woodfield
Ross A
RA
Pettigrew
Lindsay D
LD
Plank
Michael
M
Landmann
Andre M
AM
van Rij
D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D019540:Area Under Curve; D002648:Child; D003657:Decision Making; D005260:Female; D006305:Health Status Indicators; D006801:Humans; D008297:Male; D008875:Middle Aged; D017063:Outcome Assessment, Health Care / Q000379:methods*; D010147:Pain Measurement; D011183:Postoperative Complications / Q000453:epidemiology*; D011446:Prospective Studies; D012372:ROC Curve; D018570:Risk Assessment / Q000379:methods