Evidence map›Paper›PMID 42375329›Full record

ArticleFrontiers in endocrinology2026

The clinical value of analyzing predictive models for gastric function and gastric organic lesions.

Youlin Song, Yi Hu, Kang Wang, Yanhua Zhu, Yang Wang, Tao Liu, Lihao Wu, Xingxiang He, Lei Wu

Abstract read
In one paragraph

Article in Frontiers in endocrinology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Youlin Song *Department of Gastroenterology/Microbiota Medicine, The First Affiliated Hospital of Guangdong Pharmaceutical University, Guangzhou, China.
Yi Hu *Department of Gastroenterology/Microbiota Medicine, The First Affiliated Hospital of Guangdong Pharmaceutical University, Guangzhou, China.
Kang Wang *Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Army Medical University, Chongqing, China.
Yanhua ZhuDepartment of Information; Information Section; Information Center, The First Affiliated Hospital of Guangdong Pharmaceutical University, Guangzhou, China.
Yang WangSchool of Life and Health Technology, Dongguan University of Technology, Dongguan, China.
Tao LiuDepartment of Medical Record Statistics, The First Affiliated Hospital of Guangdong Pharmaceutical University, Guangzhou, China.
Lihao WuDepartment of Gastroenterology/Microbiota Medicine, The First Affiliated Hospital of Guangdong Pharmaceutical University, Guangzhou, China.
Xingxiang HeDepartment of Gastroenterology/Microbiota Medicine, The First Affiliated Hospital of Guangdong Pharmaceutical University, Guangzhou, China.
Lei WuDepartment of Gastroenterology/Microbiota Medicine, The First Affiliated Hospital of Guangdong Pharmaceutical University, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To explore the clinical value of the predictive models for gastric function and gastric organic lesions. Methods: Clinical data from 1,677 patients with digestive tract-related symptoms at the First Affiliated Hospital of Guangdong Pharmaceutical University between June 2015 and March 2023 were selected, including questionnaire responses, serum gastric function tests, gastroscopy, and gastroscopic pathology data. The above data were input into a gastric function prediction model based on question-and-answer [GFPSBQA] V1.0 and a gastric organic lesion prediction model [GDPSIQSM] V1.0, both of which integrated questionnaires and serum markers. The model's output results were compared with the results of laboratory tests and gastroscopy (including pathology), and the model's accuracy was analyzed. Results: The sensitivity of the gastric function prediction model was 91.16%, the specificity was 39.18%, the positive predictive value was 83.27%, the negative predictive value was 57.14%, the area under the receiver operating characteristic curve (AUC) was 0.702, and the Youden index was 0.303. The sensitivity of the gastric organic lesion prediction model was 89.55%, the specificity was 33.22%, the positive predictive value was 70.86%, the negative predictive value was 63.67%, the AUC was 0.672, and the Youden index was 0.228. Conclusion: Both the gastric function prediction model and the gastric organic lesion prediction model demonstrate high sensitivity and good predictive performance, and may have potential clinical applicability.

Indexed as

StomachStomach DiseasesAdultAgedFemaleGastroscopyHumansMaleMiddle AgedPrediction AlgorithmsPredictive Value of TestsSurveys and Questionnairesclinical valuegastric functiongastric organic lesionsprediction modelserum markers

Identifiers

PMID42375329
PMCPMC13310679

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.