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 inWorld journal of surgery Vol. 31; no. 10; pp. 1912 - n/a
Main Authors Woodfield, John C., Pettigrew, Ross A., Plank, Lindsay D., Landmann, Michael, Rij, Andre M.
Format Journal Article
LanguageEnglish
Published New York Springer‐Verlag 01.10.2007
Springer
Springer Nature B.V
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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.
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
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Issue 10
Keywords Medicine
Perioperative
Accuracy
Treatment
Evaluation scale
Analog
Surgery
Prediction
Complication
Predictive factor
Surgeon
Language English
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SSID ssj0017606
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Snippet Background 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...
SourceID proquest
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pubmed
pascalfrancis
wiley
SourceType Aggregation Database
Index Database
Publisher
StartPage 1912
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
URI https://onlinelibrary.wiley.com/doi/abs/10.1007%2Fs00268-007-9178-0
https://www.ncbi.nlm.nih.gov/pubmed/17674096
https://www.proquest.com/docview/219966550
https://www.proquest.com/docview/2664669000
Volume 31
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