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...
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Published in | World journal of surgery Vol. 31; no. 10; pp. 1912 - n/a |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
New York
Springer‐Verlag
01.10.2007
Springer Springer Nature B.V |
Subjects | |
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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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AbstractList | 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. BackgroundThe 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.MethodsThis 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.ResultsSurgeons 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.ConclusionsClinical 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. |
Author | Pettigrew, Ross A. Rij, Andre M. Plank, Lindsay D. Woodfield, John C. Landmann, Michael |
Author_xml | – sequence: 1 givenname: John C. surname: Woodfield fullname: Woodfield, John C. organization: University of Otago – sequence: 2 givenname: Ross A. surname: Pettigrew fullname: Pettigrew, Ross A. organization: University of Otago – sequence: 3 givenname: Lindsay D. surname: Plank fullname: Plank, Lindsay D. organization: University of Auckland – sequence: 4 givenname: Michael surname: Landmann fullname: Landmann, Michael organization: University of Otago – sequence: 5 givenname: Andre M. surname: Rij fullname: Rij, Andre M. email: Andre.vanRij@stonebow.otago.ac.nz organization: University of Otago Medical School |
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Keywords | Medicine Perioperative Accuracy Treatment Evaluation scale Analog Surgery Prediction Complication Predictive factor Surgeon |
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The ability to predict who will develop perioperative complications remains difficult because the etiology of adverse events is multifactorial. This... The ability to predict who will develop perioperative complications remains difficult because the etiology of adverse events is multifactorial. This study... Abstract Background The ability to predict who will develop perioperative complications remains difficult because the etiology of adverse events is... BackgroundThe ability to predict who will develop perioperative complications remains difficult because the etiology of adverse events is multifactorial. This... |
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SubjectTerms | Adolescent Adult Aged Aged, 80 and over Area Under Curve Biological and medical sciences Child Complications Decision Making Etiology Female General aspects Goodness of fit Health participants Health Status Indicators Humans Major Complication Major Complication Rate Male Medical sciences Middle Aged Outcome Assessment, Health Care - methods Pain Measurement Patients Postoperative Postoperative Complications - epidemiology Predictions Prognostic Variable Prospective Studies Public health. Hygiene Public health. Hygiene-occupational medicine Risk assessment Risk Assessment - methods ROC Curve Surgeons Surgery Visual Analog Scale Visual Analog Scale Score Visual discrimination |
Title | Accuracy of the Surgeons’ Clinical Prediction of Perioperative Complications Using a Visual Analog Scale |
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