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Articles in Press
4/23/2026 6:34:03 AM | Browse: 3 | Download: 0
| Category |
Gastroenterology & Hepatology |
| Manuscript Type |
Retrospective Study |
| Article Title |
Association of prealbumin with risk of abdominal surgery and endoscopic recurrence in Crohn’s disease: A machine learning study
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| Manuscript Source |
Unsolicited Manuscript |
| All Author List |
Kai-Ling Xie, Gang Long, Lian-Wen Yuan and Dan Zhang |
| Funding Agency and Grant Number |
| Funding Agency |
Grant Number |
| Fundamental Research Funds for the Central Universities of Central South University |
2024ZZTS0959 |
| National Natural Science Foundation of China |
82270590 |
| Hunan Provincial Natural Science Foundation |
2025JJ50584 |
| Research Project on Degree and Graduate Education Reform at Central South University |
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| Corresponding Author |
Dan Zhang, Professor, Clinical Nursing Teaching and Research Section, The Second Xiangya Hospital, Central South University, No. 139 Renmin Middle Road, Changsha 410011, Hunan Province, China. dunbaby@126.com |
| Key Words |
Crohn’s disease; Prealbumin; Abdominal surgery; Postoperative endoscopic recurrence; Machine learning; Predictive and personal medicine |
| Core Tip |
Serum prealbumin (PA), reflecting inflammatory and nutritional status, may serve as a pragmatic biomarker for risk stratification in Crohn’s disease. Higher PA levels were associated with lower risks of abdominal surgery and postoperative endoscopic recurrence (highest vs lowest quartile: Hazard ratio = 0.45 and 0.20, respectively). Incorporating PA into machine learning models further improved prognostic performance (C-index = 0.784 for surgery and 0.764 for recurrence). Moreover, serum PA showed approximately 70% concordance with machine learning-derived risk tiers and helped identify patients more likely to benefit from biologic therapy, thereby supporting earlier risk prediction and more individualized treatment decisions. |
| Citation |
Xie KL, Long G, Yuan LW, Zhang D. Association of prealbumin with risk of abdominal surgery and endoscopic recurrence in Crohn’s disease: A machine learning study. World J Gastroenterol 2026; In press |
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Received |
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2026-02-02 02:12 |
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Peer-Review Started |
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2026-02-02 02:15 |
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First Decision by Editorial Office Director |
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2026-03-12 08:56 |
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Return for Revision |
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2026-03-12 08:56 |
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Revised |
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2026-03-31 16:53 |
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Publication Fee Transferred |
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Second Decision by Editor |
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2026-04-23 02:37 |
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Second Decision by Editor-in-Chief |
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Final Decision by Editorial Office Director |
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2026-04-23 06:34 |
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Articles in Press |
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2026-04-23 06:34 |
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Edit the Manuscript by Language Editor |
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Typeset the Manuscript |
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| ISSN |
1007-9327 (print) and 2219-2840 (online) |
| Open Access |
This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/Licenses/by-nc/4.0/ |
| Copyright |
©Author(s) (or their employer(s)) 2026. No commercial re-use. See Permissions. Published by Baishideng Publishing Group Inc. |
| Permissions |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/207
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| Publisher |
Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA |
| Website |
http://www.wjgnet.com |
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