Flora K Szabo1, Lindsey Hornung2, Judy-April Oparaji3, Rabea Alhosh4, Sohail Z Husain3, Quin Y Liu4, Joseph Palermo1, Tom K Lin1, Jaimie D Nathan5, Daniel J Podberesky6, Mark Lowe3, Lin Fei7, Maisam Abu-El-Haija8. 1. Division of Gastroenterology Hepatology and Nutrition; Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA. 2. Division of Biostatistics and Epidemiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA. 3. Division of Gastroenterology Hepatology and Nutrition, Children's Hospital of Pittsburgh of UPMC, Pittsburgh, PA, USA. 4. Division of Gastroenterology Hepatology and Nutrition, Children's Hospital Los Angeles, Los Angeles, CA, USA. 5. Division of Pediatric General and Thoracic Surgery, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA. 6. Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA; Department of Radiology, Nemours Children's Hospital, Orlando, FL, USA. 7. Division of Gastroenterology Hepatology and Nutrition; Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA; Division of Biostatistics and Epidemiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA. 8. Division of Gastroenterology Hepatology and Nutrition; Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA. Electronic address: maisam.haija@cchmc.org.
Abstract
BACKGROUND/ OBJECTIVES: Approximately 15-20% of pediatric patients with acute pancreatitis (AP) develop severe disease. Severity scoring tools were developed for adult patients, but have limitations when applied in children. We aimed to identify early predictors of severe acute pancreatitis (SAP) on hospital admission for early risk stratification of patients. METHODS: Retrospective review of AP admissions was conducted. The derivation cohort included cases at Cincinnati Children's Hospital Medical Center (CCHMC) between 2009 and 2013. Clinical data collected during the first 24 h of admission were analyzed and a predictive model was derived through statistical analysis. The performance of the model was evaluated in a validation cohort from 2 more institutions other than CCHMC. RESULTS: In the derivation cohort 19% of the 284 admissions were SAP. A generalized linear mixed effect model analysis revealed that lipase, albumin and white blood count (WBC) play a role in the development of SAP (area under the receiver operating curve (AUROC 0.76)). In the validation cohort of 165 AP cases, SAP ranged from 8 to 20% at the three institutions. Performance of the model in this cohort was comparable to the derivation model (AUROC 0.77). There were 369 encounters in the combined derivation and validation pool (AUROC 0.76). CONCLUSIONS: The prognostic severity tool with 3 variables (lipase, albumin, and WBC) obtained within 24 h of admission can be applied to predict SAP in pediatric patients.
BACKGROUND/ OBJECTIVES: Approximately 15-20% of pediatric patients with acute pancreatitis (AP) develop severe disease. Severity scoring tools were developed for adult patients, but have limitations when applied in children. We aimed to identify early predictors of severe acute pancreatitis (SAP) on hospital admission for early risk stratification of patients. METHODS: Retrospective review of AP admissions was conducted. The derivation cohort included cases at Cincinnati Children's Hospital Medical Center (CCHMC) between 2009 and 2013. Clinical data collected during the first 24 h of admission were analyzed and a predictive model was derived through statistical analysis. The performance of the model was evaluated in a validation cohort from 2 more institutions other than CCHMC. RESULTS: In the derivation cohort 19% of the 284 admissions were SAP. A generalized linear mixed effect model analysis revealed that lipase, albumin and white blood count (WBC) play a role in the development of SAP (area under the receiver operating curve (AUROC 0.76)). In the validation cohort of 165 AP cases, SAP ranged from 8 to 20% at the three institutions. Performance of the model in this cohort was comparable to the derivation model (AUROC 0.77). There were 369 encounters in the combined derivation and validation pool (AUROC 0.76). CONCLUSIONS: The prognostic severity tool with 3 variables (lipase, albumin, and WBC) obtained within 24 h of admission can be applied to predict SAP in pediatric patients.
Authors: Maisam Abu-El-Haija; Soma Kumar; Jose Antonio Quiros; Keshawadhana Balakrishnan; Bradley Barth; Samuel Bitton; John F Eisses; Elsie Jazmin Foglio; Victor Fox; Denease Francis; Alvin Jay Freeman; Tanja Gonska; Amit S Grover; Sohail Z Husain; Rakesh Kumar; Sameer Lapsia; Tom Lin; Quin Y Liu; Asim Maqbool; Zachary M Sellers; Flora Szabo; Aliye Uc; Steven L Werlin; Veronique D Morinville Journal: J Pediatr Gastroenterol Nutr Date: 2018-01 Impact factor: 2.839
Authors: Maisam Abu-El-Haija; Anna S Gukovskaya; Dana K Andersen; Timothy B Gardner; Peter Hegyi; Stephen J Pandol; Georgios I Papachristou; Ashok K Saluja; Vikesh K Singh; Aliye Uc; Bechien U Wu Journal: Pancreas Date: 2018 Nov/Dec Impact factor: 3.327
Authors: Abdul R Shahein; J Antonio Quiros; Ricardo A Arbizu; Candi Jump; Steven D Lauzon; Susan S Baker Journal: Pediatr Gastroenterol Hepatol Nutr Date: 2020-07-03
Authors: David S Vitale; Patrick Lahni; Lindsey Hornung; Tyler Thompson; Peter R Farrell; Tom K Lin; Jaimie D Nathan; Hector R Wong; Maisam Abu-El-Haija Journal: PLoS One Date: 2022-02-14 Impact factor: 3.240
Authors: Peter R Farrell; Lindsey Hornung; Peter Farmer; Angelica W DesPain; Esther Kim; Ryan Pearman; Beemnet Neway; Ashley Serrette; Sona Sehgal; James E Heubi; Tom K Lin; Jaimie D Nathan; David S Vitale; Maisam Abu-El-Haija Journal: J Pediatr Gastroenterol Nutr Date: 2020-10 Impact factor: 3.288