BACKGROUND & AIMS: Reducing rapid readmission of patients after discharge could improve quality of treatment and reduce costs. Little is known about clinical predictors of early readmission for acute pancreatitis (AP). We developed a strategy to identify and stratify patients with AP at risk for readmission within 30 days of discharge. METHODS: We derived and validated a model in a cohort of patients hospitalized with AP from June 2005-October 2009. Early readmission was defined as admission to the hospital or reevaluation in the emergency department within 30 days of discharge. The cohort was divided into a derivation cohort (admitted June 2005-December 2007, n = 248) and a validation cohort (admitted January 2008-October 2009, n = 198). A weighted scoring system was developed using logistic regression for the prediction of early readmission. Accuracy was assessed by area under the receiver-operator characteristic (ROC) curve analysis. RESULTS: Of the total patients, 21% (92/446) had early readmission. Multivariable analysis identified the following discharge characteristics as independent risk factors for early readmission: gastrointestinal symptoms, eating less than a solid diet, pancreatic necrosis, treatment with antibiotics, and pain (P < .05). Weighted risk scores stratified patients into groups of low, moderate, and high risk for early readmission: 4%, 15%, and 87%, respectively, in the derivation cohort and 5%, 18%, and 68%, respectively, in the validation cohort. Area under the ROC curve demonstrated an accurate prediction (c-statistic = 0.83). CONCLUSIONS: We created a scoring system that accurately predicts which patients with AP have high and low risk of readmission within 30 days of discharge.
BACKGROUND & AIMS: Reducing rapid readmission of patients after discharge could improve quality of treatment and reduce costs. Little is known about clinical predictors of early readmission for acute pancreatitis (AP). We developed a strategy to identify and stratify patients with AP at risk for readmission within 30 days of discharge. METHODS: We derived and validated a model in a cohort of patients hospitalized with AP from June 2005-October 2009. Early readmission was defined as admission to the hospital or reevaluation in the emergency department within 30 days of discharge. The cohort was divided into a derivation cohort (admitted June 2005-December 2007, n = 248) and a validation cohort (admitted January 2008-October 2009, n = 198). A weighted scoring system was developed using logistic regression for the prediction of early readmission. Accuracy was assessed by area under the receiver-operator characteristic (ROC) curve analysis. RESULTS: Of the total patients, 21% (92/446) had early readmission. Multivariable analysis identified the following discharge characteristics as independent risk factors for early readmission: gastrointestinal symptoms, eating less than a solid diet, pancreatic necrosis, treatment with antibiotics, and pain (P < .05). Weighted risk scores stratified patients into groups of low, moderate, and high risk for early readmission: 4%, 15%, and 87%, respectively, in the derivation cohort and 5%, 18%, and 68%, respectively, in the validation cohort. Area under the ROC curve demonstrated an accurate prediction (c-statistic = 0.83). CONCLUSIONS: We created a scoring system that accurately predicts which patients with AP have high and low risk of readmission within 30 days of discharge.
Authors: Jose Serrano; Dana K Andersen; Christopher E Forsmark; Stephen J Pandol; Ziding Feng; Sudhir Srivastava; Jo Ann S Rinaudo Journal: Pancreas Date: 2018 Nov/Dec Impact factor: 3.327
Authors: James Buxbaum; Michael Quezada; Bradford Chong; Nikhil Gupta; Chung Yao Yu; Christianne Lane; Ben Da; Kenneth Leung; Ira Shulman; Stephen Pandol; Bechien Wu Journal: Am J Gastroenterol Date: 2018-03-15 Impact factor: 10.864
Authors: Thomas K Maatman; Sarakshi Mahajan; Alexandra M Roch; Kyle A Lewellen; Mark A Heimberger; Cameron L Colgate; Eugene P Ceppa; Michael G House; Attila Nakeeb; C Max Schmidt; Nicholas J Zyromski Journal: J Gastrointest Surg Date: 2019-01-31 Impact factor: 3.452
Authors: Pedro Palacios Argueta; Miguel Salazar; Ishaan Vohra; Juan E Corral; Frank J Lukens; John J Vargo; Prabhleen Chahal; C Roberto Simons-Linares Journal: Dig Dis Sci Date: 2021-01-19 Impact factor: 3.199