Cargando…

Who’s at Risk? A Prognostic Model for Severity Prediction in Pediatric Acute Pancreatitis

OBJECTIVES: The aim of the study was to validate and optimize a severity prediction model for acute pancreatitis (AP) and to examine blood urea nitrogen (BUN) level changes from admission as a severity predictor. STUDY DESIGN: Patients from 2 hospitals were included for the validation model (Childre...

Descripción completa

Detalles Bibliográficos
Autores principales: Farrell, Peter R., Hornung, Lindsey, Farmer, Peter, DesPain, Angelica W., Kim, Esther, Pearman, Ryan, Neway, Beemnet, Serrette, Ashley, Sehgal, Sona, Heubi, James E., Lin, Tom K., Nathan, Jaimie D., Vitale, David S., Abu-El-Haija, Maisam
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8020899/
https://www.ncbi.nlm.nih.gov/pubmed/32541203
http://dx.doi.org/10.1097/MPG.0000000000002807
_version_ 1783674646070034432
author Farrell, Peter R.
Hornung, Lindsey
Farmer, Peter
DesPain, Angelica W.
Kim, Esther
Pearman, Ryan
Neway, Beemnet
Serrette, Ashley
Sehgal, Sona
Heubi, James E.
Lin, Tom K.
Nathan, Jaimie D.
Vitale, David S.
Abu-El-Haija, Maisam
author_facet Farrell, Peter R.
Hornung, Lindsey
Farmer, Peter
DesPain, Angelica W.
Kim, Esther
Pearman, Ryan
Neway, Beemnet
Serrette, Ashley
Sehgal, Sona
Heubi, James E.
Lin, Tom K.
Nathan, Jaimie D.
Vitale, David S.
Abu-El-Haija, Maisam
author_sort Farrell, Peter R.
collection PubMed
description OBJECTIVES: The aim of the study was to validate and optimize a severity prediction model for acute pancreatitis (AP) and to examine blood urea nitrogen (BUN) level changes from admission as a severity predictor. STUDY DESIGN: Patients from 2 hospitals were included for the validation model (Children’s Hospital of the King’s Daughters and Children’s National Hospital). Children’s Hospital of the King’s Daughters and Cincinnati Children’s Hospital Medical Center data were used for analysis of BUN at 24 to 48 hours. RESULTS: The validation cohort included 73 patients; 22 (30%) with either severe or moderately severe AP, combined into the all severe AP (SAP) group. Patients with SAP had higher BUN (P = 0.002) and lower albumin (P = 0.005). Admission BUN was confirmed as a significant predictor (P = 0.005) of SAP (area under the receiver operating characteristic [AUROC] 0.73, 95% confidence interval [CI] 0.60–0.86). Combining BUN (P = 0.005) and albumin (P = 0.004) resulted in better prediction for SAP (AUROC 0.83, 95% CI 0.72–0.94). A total of 176 AP patients were analyzed at 24–48 hours; 39 (22%) met criteria for SAP. Patients who developed SAP had a significantly higher BUN (P < 0.001) after 24 hours. Elevated BUN levels within 24 to 48 hours were independently predictive of developing SAP (AUROC: 0.76, 95% CI: 0.66–0.85). Patients who developed SAP had a significantly smaller percentage decrease in BUN from admission to 24 to 48 hours (P = 0.002). CONCLUSION: We externally validated the prior model with admission BUN levels and further optimized it by incorporating albumin. We also found that persistent elevation of BUN is associated with development of SAP. Our model can be used to risk stratify patients with AP on admission and again at 24 to 48 hours.
format Online
Article
Text
id pubmed-8020899
institution National Center for Biotechnology Information
language English
publishDate 2020
record_format MEDLINE/PubMed
spelling pubmed-80208992021-04-05 Who’s at Risk? A Prognostic Model for Severity Prediction in Pediatric Acute Pancreatitis Farrell, Peter R. Hornung, Lindsey Farmer, Peter DesPain, Angelica W. Kim, Esther Pearman, Ryan Neway, Beemnet Serrette, Ashley Sehgal, Sona Heubi, James E. Lin, Tom K. Nathan, Jaimie D. Vitale, David S. Abu-El-Haija, Maisam J Pediatr Gastroenterol Nutr Article OBJECTIVES: The aim of the study was to validate and optimize a severity prediction model for acute pancreatitis (AP) and to examine blood urea nitrogen (BUN) level changes from admission as a severity predictor. STUDY DESIGN: Patients from 2 hospitals were included for the validation model (Children’s Hospital of the King’s Daughters and Children’s National Hospital). Children’s Hospital of the King’s Daughters and Cincinnati Children’s Hospital Medical Center data were used for analysis of BUN at 24 to 48 hours. RESULTS: The validation cohort included 73 patients; 22 (30%) with either severe or moderately severe AP, combined into the all severe AP (SAP) group. Patients with SAP had higher BUN (P = 0.002) and lower albumin (P = 0.005). Admission BUN was confirmed as a significant predictor (P = 0.005) of SAP (area under the receiver operating characteristic [AUROC] 0.73, 95% confidence interval [CI] 0.60–0.86). Combining BUN (P = 0.005) and albumin (P = 0.004) resulted in better prediction for SAP (AUROC 0.83, 95% CI 0.72–0.94). A total of 176 AP patients were analyzed at 24–48 hours; 39 (22%) met criteria for SAP. Patients who developed SAP had a significantly higher BUN (P < 0.001) after 24 hours. Elevated BUN levels within 24 to 48 hours were independently predictive of developing SAP (AUROC: 0.76, 95% CI: 0.66–0.85). Patients who developed SAP had a significantly smaller percentage decrease in BUN from admission to 24 to 48 hours (P = 0.002). CONCLUSION: We externally validated the prior model with admission BUN levels and further optimized it by incorporating albumin. We also found that persistent elevation of BUN is associated with development of SAP. Our model can be used to risk stratify patients with AP on admission and again at 24 to 48 hours. 2020-10 /pmc/articles/PMC8020899/ /pubmed/32541203 http://dx.doi.org/10.1097/MPG.0000000000002807 Text en http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License 4.0 (CCBY), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Article
Farrell, Peter R.
Hornung, Lindsey
Farmer, Peter
DesPain, Angelica W.
Kim, Esther
Pearman, Ryan
Neway, Beemnet
Serrette, Ashley
Sehgal, Sona
Heubi, James E.
Lin, Tom K.
Nathan, Jaimie D.
Vitale, David S.
Abu-El-Haija, Maisam
Who’s at Risk? A Prognostic Model for Severity Prediction in Pediatric Acute Pancreatitis
title Who’s at Risk? A Prognostic Model for Severity Prediction in Pediatric Acute Pancreatitis
title_full Who’s at Risk? A Prognostic Model for Severity Prediction in Pediatric Acute Pancreatitis
title_fullStr Who’s at Risk? A Prognostic Model for Severity Prediction in Pediatric Acute Pancreatitis
title_full_unstemmed Who’s at Risk? A Prognostic Model for Severity Prediction in Pediatric Acute Pancreatitis
title_short Who’s at Risk? A Prognostic Model for Severity Prediction in Pediatric Acute Pancreatitis
title_sort who’s at risk? a prognostic model for severity prediction in pediatric acute pancreatitis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8020899/
https://www.ncbi.nlm.nih.gov/pubmed/32541203
http://dx.doi.org/10.1097/MPG.0000000000002807
work_keys_str_mv AT farrellpeterr whosatriskaprognosticmodelforseveritypredictioninpediatricacutepancreatitis
AT hornunglindsey whosatriskaprognosticmodelforseveritypredictioninpediatricacutepancreatitis
AT farmerpeter whosatriskaprognosticmodelforseveritypredictioninpediatricacutepancreatitis
AT despainangelicaw whosatriskaprognosticmodelforseveritypredictioninpediatricacutepancreatitis
AT kimesther whosatriskaprognosticmodelforseveritypredictioninpediatricacutepancreatitis
AT pearmanryan whosatriskaprognosticmodelforseveritypredictioninpediatricacutepancreatitis
AT newaybeemnet whosatriskaprognosticmodelforseveritypredictioninpediatricacutepancreatitis
AT serretteashley whosatriskaprognosticmodelforseveritypredictioninpediatricacutepancreatitis
AT sehgalsona whosatriskaprognosticmodelforseveritypredictioninpediatricacutepancreatitis
AT heubijamese whosatriskaprognosticmodelforseveritypredictioninpediatricacutepancreatitis
AT lintomk whosatriskaprognosticmodelforseveritypredictioninpediatricacutepancreatitis
AT nathanjaimied whosatriskaprognosticmodelforseveritypredictioninpediatricacutepancreatitis
AT vitaledavids whosatriskaprognosticmodelforseveritypredictioninpediatricacutepancreatitis
AT abuelhaijamaisam whosatriskaprognosticmodelforseveritypredictioninpediatricacutepancreatitis