The Modified Pancreatitis Activity Scoring System Shows Distinct Trajectories in Acute Pancreatitis: An International Study.


Journal

Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association
ISSN: 1542-7714
Titre abrégé: Clin Gastroenterol Hepatol
Pays: United States
ID NLM: 101160775

Informations de publication

Date de publication:
06 2022
Historique:
received: 17 07 2021
revised: 09 09 2021
accepted: 14 09 2021
pubmed: 21 9 2021
medline: 10 5 2022
entrez: 20 9 2021
Statut: ppublish

Résumé

The aims of this study were to: (1) assess the performance of the Pancreatitis Activity Scoring System (PASS) in a large intercontinental cohort of patients with acute pancreatitis (AP); and (2) investigate whether a modified PASS (mPASS) yields a similar predictive accuracy and produces distinct early trajectories between severity subgroups. Data was prospectively collected through the Acute Pancreatitis Patient Registry to Examine Novel Therapies In Clinical Experience (APPRENTICE) consortium (2015-2018) involving 22 centers from 4 continents. AP severity was categorized per the revised Atlanta classification. PASS trajectories were compared between the three severity groups using the generalized estimating equations model. Four mPASS models were generated by modifying the morphine equivalent dose (MED), and their trajectories were compared. A total of 1393 subjects were enrolled (median age, 49 years; 51% males). The study cohort included 950 mild (68.2%), 315 (22.6%) moderately severe, and 128 (9.2%) severe AP. Mild cases had the lowest PASS at each study time point (all P < .001). A subset of patients with outlier admission PASS values was identified. In the outlier group, 70% of the PASS variation was attributed to the MED, and 66% of these patients were from the United States centers. Among the 4 modified models, the mPASS-1 (excluding MED from PASS) demonstrated high performance in predicting severe AP with an area under the receiver operating characteristic curve of 0.88 (vs area under the receiver operating characteristic of 0.83 in conventional PASS) and produced distinct trajectories with distinct slopes between severity subgroups (all P < .001). We propose a modified model by removing the MED component, which is easier to calculate, predicts accurately severe AP, and maintains significantly distinct early trajectories.

Sections du résumé

BACKGROUND & AIMS
The aims of this study were to: (1) assess the performance of the Pancreatitis Activity Scoring System (PASS) in a large intercontinental cohort of patients with acute pancreatitis (AP); and (2) investigate whether a modified PASS (mPASS) yields a similar predictive accuracy and produces distinct early trajectories between severity subgroups.
METHODS
Data was prospectively collected through the Acute Pancreatitis Patient Registry to Examine Novel Therapies In Clinical Experience (APPRENTICE) consortium (2015-2018) involving 22 centers from 4 continents. AP severity was categorized per the revised Atlanta classification. PASS trajectories were compared between the three severity groups using the generalized estimating equations model. Four mPASS models were generated by modifying the morphine equivalent dose (MED), and their trajectories were compared.
RESULTS
A total of 1393 subjects were enrolled (median age, 49 years; 51% males). The study cohort included 950 mild (68.2%), 315 (22.6%) moderately severe, and 128 (9.2%) severe AP. Mild cases had the lowest PASS at each study time point (all P < .001). A subset of patients with outlier admission PASS values was identified. In the outlier group, 70% of the PASS variation was attributed to the MED, and 66% of these patients were from the United States centers. Among the 4 modified models, the mPASS-1 (excluding MED from PASS) demonstrated high performance in predicting severe AP with an area under the receiver operating characteristic curve of 0.88 (vs area under the receiver operating characteristic of 0.83 in conventional PASS) and produced distinct trajectories with distinct slopes between severity subgroups (all P < .001).
CONCLUSION
We propose a modified model by removing the MED component, which is easier to calculate, predicts accurately severe AP, and maintains significantly distinct early trajectories.

Identifiants

pubmed: 34543736
pii: S1542-3565(21)00978-2
doi: 10.1016/j.cgh.2021.09.014
pmc: PMC9060638
mid: NIHMS1801101
pii:
doi:

Types de publication

Journal Article Research Support, N.I.H., Extramural

Langues

eng

Sous-ensembles de citation

IM

Pagination

1334-1342.e4

Subventions

Organisme : NCI NIH HHS
ID : T32 CA186873
Pays : United States
Organisme : NIDDK NIH HHS
ID : U01 DK108323
Pays : United States

Informations de copyright

Copyright © 2022 AGA Institute. Published by Elsevier Inc. All rights reserved.

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Auteurs

Pedram Paragomi (P)

University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania; University of Pittsburgh Medical Center Hillman Cancer Center, Pittsburgh, Pennsylvania.

Alice Hinton (A)

Division of Biostatistics, College of Public Health, The Ohio State University, Columbus, Ohio.

Ioannis Pothoulakis (I)

University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania; MedStar Washington Hospital Center, Washington, District of Columbia.

Rupjyoti Talukdar (R)

Asian Gastroenterology Institute, Hyderabad, India.

Rakesh Kochhar (R)

Postgraduate Institute of Medical Education and Research, Chandigarh, India.

Mahesh K Goenka (MK)

Apollo Gleneagles Hospitals Kolkata, Kolkata, India.

Aiste Gulla (A)

Institute of Clinical Medicine, Faculty of Medicine, Vilnius University, Vilnius, Lithuania; Georgetown University Hospital, Washington DC.

Jose A Gonzalez (JA)

Universidad Autónoma de Nueva León, Monterrey, Mexico.

Vikesh K Singh (VK)

Division of Gastroenterology, John Hopkins Medical Institution, Baltimore, MA.

Miguel Ferreira Bogado (MF)

Hospital Nacional de Itauguá, Itaugua, Paraguay.

Tyler Stevens (T)

Cleveland Clinic, Cleveland, Ohio.

Sorin T Barbu (ST)

University of Medicine and Pharmacy "Iuliu Hatieganu," Cluj-Napoca, Romania.

Haq Nawaz (H)

Eastern Maine Medical Center, Bangor, Maine.

Silvia C Gutierrez (SC)

Hospital Nacional "Profesor Alejandro Posadas," Buenos Aires, Argentina.

Narcis Zarnescu (N)

University of Medicine and Pharmacy, Bucharest, Romania.

Livia Archibugi (L)

Pancreato-Biliary Endoscopy and Endosonography Division, Pancreas Translational and Clinical Research Center, San Raffaele Scientific Institute IRCCS, Milan, Italy; Digestive and Liver Disease Unit, Sant'Andrea Hospital, Rome, Italy.

Jeffrey J Easler (JJ)

Indiana University School of Medicine, Indianapolis, Indiana.

Konstantinos Triantafyllou (K)

Attikon University General Hospital, Athens, Greece.

Mario Peláez-Luna (M)

Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán-Universidad Autónoma de Mexico, Mexico City, Mexico.

Shyam Thakkar (S)

Division of Gastroenterology, West Virginia University, Morgantown, West Virginia.

Carlos Ocampo (C)

Hospital General de Argudos "Dr. Cosme Argerich," Buenos Aires, Argentina.
Gastroenterology Department, Alicante University General Hospital, ISABIAL, Alicante, Spain.

Gregory A Cote (GA)

Medical University of South Carolina, Charleston, South Carolina.

Peter J Lee (PJ)

Division of Gastroenterology, Department of Medicine, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania.

Somashekar Krishna (S)

Division of Gastroenterology, Hepatology, and Nutrition, The Ohio State University, Wexner Medical Center, Columbus, Ohio.

Luis F Lara (LF)

Division of Gastroenterology, Hepatology, and Nutrition, The Ohio State University, Wexner Medical Center, Columbus, Ohio.

Samuel Han (S)

Division of Gastroenterology, Hepatology, and Nutrition, The Ohio State University, Wexner Medical Center, Columbus, Ohio.

Bechien U Wu (BU)

Kaiser Permanente, Los Angeles, California.

Georgios I Papachristou (GI)

Division of Gastroenterology, Hepatology, and Nutrition, The Ohio State University, Wexner Medical Center, Columbus, Ohio. Electronic address: georgios.papachristou@osumc.edu.

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