Machine learning-driven pathogen cluster analysis identifies high-risk subtypes of infected pancreatic necrosis in a multi-center cohort

doi:10.3748/wjg.118717

Advanced Search

BPG is committed to discovery and dissemination of knowledge

Home / Archive / Volume 32, Issue 27

This Article

(24)

(20)

(0)

(11)

(318)

Peer-Review Report of This Article

CrossCheck and Google Search of This Article

Academic Rules and Norms of This Article

Supplementary Materials of This Article

Citation of this article

Corresponding Author of This Article

Research Domain of This Article

Article-Type of This Article

Open-Access Policy of This Article

Times Cited Counts in Google of This Article

Journal Information of This Article

Publication Name

World Journal of Gastroenterology

ISSN

1007-9327

Publisher of This Article

Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA

Retrospective Study

Copyright: ©Author(s) 2026. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial (CC BY-NC 4.0) license. No commercial re-use. See permissions. Published by Baishideng Publishing Group Inc.

World J Gastroenterol. Jul 21, 2026; 32(27): 118717
Published online Jul 21, 2026. doi: 10.3748/wjg.118717

Table 2 Statistical test results of in-hospital mortality among the clusters in the derivation cohort

Outcome	Statistical test P value
	General	Pairwise¹
	General	α vs β	α vs γ	α vs δ	β vs γ	β vs δ	γ vs δ
90-day mortality	0.008	0.300	1.000	0.480	0.024	0.006	1.000

¹P values for pairwise comparisons were adjusted using Bonferroni correction.

α: Enterococcus faecium/Enterobacter cloacae–predominant; β: Escherichia coli–dominant; γ: Multidrug-resistant organism-enriched; δ: Acinetobacter baumannii–Candida glabrata.

Full Size Table

Citation: Liu BQ, Sun ZF, Ning CH, Xiao J, Wu D, Lin CY, Hong XY, Guo R, Chen L, Cao XT, Shen DC, Huang GW. Machine learning-driven pathogen cluster analysis identifies high-risk subtypes of infected pancreatic necrosis in a multi-center cohort. World J Gastroenterol 2026; 32(27): 118717
URL: https://www.wjgnet.com/1007-9327/full/v32/i27/118717.htm
DOI: https://dx.doi.org/10.3748/wjg.118717

Liu BQ, Sun ZF, Ning CH, Xiao J, Wu D, Lin CY, Hong XY, Guo R, Chen L, Cao XT, Shen DC, Huang GW. Machine learning-driven pathogen cluster analysis identifies high-risk subtypes of infected pancreatic necrosis in a multi-center cohort. World J Gastroenterol 2026; 32(27): 118717 [DOI: 10.3748/wjg.118717]

All content on this site: Copyright © 1993-2026 Baishideng Publishing Group Inc, its licensors, and contributors. All rights are reserved, including those for text and data mining, AI training, and similar technologies. For all open access content, the relevant licensing terms apply.