title: Prediction of unexpected emergency room visit after extracorporeal shock wave lithotripsy for urolithiasis - an application of artificial neural network in hospital information system.
abstract: Extracorporeal shock wave lithotripsy (ESWL) for urolithiasis was developed for more than 30 years. It benefited most patients suffering from acute renal colic. The ESWL may be performed at outpatient based in most hospital in Taiwan. But the post-ESWL emergency room (ER) visits will be a painful experience for patient and the urologist,especially those patients visited ER immediately on the same day of ESWL. Though most guidelines for ESWL suggest the larger stone burden, the higher risk for post-ESWL ER visits,there are about 10% patients will come back to ER due to renal colic post-operatively. We use artificial neural network(ANN) to predict the post-ESWL ER visit for patient with urolithiasis. The result disclosed high sensitivity and specificity of prediction. In conclusion, it will decrease the rate of post-ER visit rate and patients' suffer by using ANN to predict the post-ESWL ER visits.
authors.affiliation: Division of Urology, Department of Surgery, Buddhist Tzu Chi General Hospital, Taipei Branch, Taipei, Taiwan.
authors.forename: Chi-Cheng
authors.initials: CC
authors.lastname: Sun
authors.forename: Polun
authors.initials: P
authors.lastname: Chang
mesh_terms: D003085:Colic / Q000209:etiology; D004636:Emergency Service, Hospital / Q000706:statistics & numerical data*; D006751:Hospital Information Systems; D006801:Humans; D007674:Kidney Diseases / Q000209:etiology; D008096:Lithotripsy / Q000009:adverse effects*; D016571:Neural Networks, Computer; D012307:Risk Factors; D052878:Urolithiasis / Q000628:therapy*