BACKGROUND: Selection of patients with the highest probability for therapeutic ERCP remains an important task in a clinical workup of patients with suspected choledocholithiasis (CDL). OBJECTIVE: To determine whether an artificial neural network (ANN) model can improve the accuracy of selecting patients with a high probability of undergoing therapeutic ERCP among those with strong clinical suspicion of CDL and to compare it with our previously reported prediction model. DESIGN: Prospective, observational study. SETTING: Single, tertiary-care endoscopy center. PATIENTS: Between January 2010 and September 2012, we prospectively recruited 291 consecutive patients who underwent ERCP after being referred to our center with firm suspicion for CDL. INTERVENTIONS: Predictive scores for CDL based on a multivariate logistic regression model and ANN model. MAIN OUTCOME MEASUREMENTS: The presence of common bile duct stones confirmed by ERCP. RESULTS: There were 80.4% of patients with positive findings on ERCP. The area under the receiver-operating characteristic curve for our previously established multivariate logistic regression model was 0.787 (95% CI, 0.720-0.854; P < .001), whereas area under the curve for the ANN model was 0.884 (95% CI, 0.831-0.938; P < .001). The ANN model correctly classified 92.3% of patients with positive findings on ERCP and 69.6% patients with negative findings on ERCP. LIMITATIONS: Only those variables believed to be related to the outcome of interest were included. The majority of patients in our sample had positive findings on ERCP. CONCLUSIONS: An ANN model has better discriminant ability and accuracy than a multivariate logistic regression model in selecting patients for therapeutic ERCP.
BACKGROUND: Selection of patients with the highest probability for therapeutic ERCP remains an important task in a clinical workup of patients with suspected choledocholithiasis (CDL). OBJECTIVE: To determine whether an artificial neural network (ANN) model can improve the accuracy of selecting patients with a high probability of undergoing therapeutic ERCP among those with strong clinical suspicion of CDL and to compare it with our previously reported prediction model. DESIGN: Prospective, observational study. SETTING: Single, tertiary-care endoscopy center. PATIENTS: Between January 2010 and September 2012, we prospectively recruited 291 consecutive patients who underwent ERCP after being referred to our center with firm suspicion for CDL. INTERVENTIONS: Predictive scores for CDL based on a multivariate logistic regression model and ANN model. MAIN OUTCOME MEASUREMENTS: The presence of common bile duct stones confirmed by ERCP. RESULTS: There were 80.4% of patients with positive findings on ERCP. The area under the receiver-operating characteristic curve for our previously established multivariate logistic regression model was 0.787 (95% CI, 0.720-0.854; P < .001), whereas area under the curve for the ANN model was 0.884 (95% CI, 0.831-0.938; P < .001). The ANN model correctly classified 92.3% of patients with positive findings on ERCP and 69.6% patients with negative findings on ERCP. LIMITATIONS: Only those variables believed to be related to the outcome of interest were included. The majority of patients in our sample had positive findings on ERCP. CONCLUSIONS: An ANN model has better discriminant ability and accuracy than a multivariate logistic regression model in selecting patients for therapeutic ERCP.
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