Evidence map›Paper›PMID 41919170›Full record

ArticleFrontiers in medicine2026

Exploring core and sentinel symptoms in elderly patients with type 2 diabetes through network analysis and the Apriori algorithm.

Tingting Tan, Chongyao Yang, Qingqing Wang, Cong Xu, Sijing Wang, Bingbing Xiao, Jing Zhao, Huan He, Miaoqin Wang

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Article in Frontiers in medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Tingting Tan *Department of nursing, Affiliated Hospital of North Sichuan Medical College, Nanchong, China.
Chongyao Yang *Department of nursing, Affiliated Hospital of North Sichuan Medical College, Nanchong, China.
Qingqing WangDepartment of nursing, Affiliated Hospital of North Sichuan Medical College, Nanchong, China.
Cong XuDepartment of nursing, Affiliated Hospital of North Sichuan Medical College, Nanchong, China.
Sijing WangWest China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China.
Bingbing XiaoDepartment of nursing, Affiliated Hospital of North Sichuan Medical College, Nanchong, China.
Jing ZhaoDepartment of nursing, Affiliated Hospital of North Sichuan Medical College, Nanchong, China.
Huan HeDepartment of Stomatology, Affiliated Hospital of North Sichuan Medical College, Nanchong, China.
Miaoqin WangOutpatient Department, Affiliated Hospital of North Sichuan Medical College, Nanchong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To construct the symptom network of elderly patients with type 2 diabetes mellitus (T2DM) and perform association rule analysis for each symptom cluster, identify core symptoms, and explore the sentinel symptoms, to provide references for accurate and efficient symptom management. Methods: Convenience sampling was employed. Eligible elderly patients with T2DM were enrolled from the department of endocrinology, affiliated hospital of North Sichuan Medical College, Nanchong City, from March 2024 to July 2024, with data collected using the Chinese Version of Diabetes Symptom Checklist-Revised (DSC-R). The correlation was analyzed using the Apriori algorithm model to identify the sentinel symptoms of each symptom cluster, and the core symptom was identified based on the network analysis method. Results: The most prevalent symptoms were thirst and dry mouth (71.69%), general fatigue (70.78%), and frothy urine (69.58%). Regarding symptom burden severity, general fatigue (2.48 ± 1.89), asthenia (2.42 ± 1.94), and insomnia (2.39 ± 1.98) had the highest scores. Sentinel symptoms, including excessive sleepiness, limb numbness, limb swelling, and polydipsia, are characteristic manifestations of distinct symptom clusters: psychological cognition symptom cluster, peripheral nerve symptom cluster, nephropathy symptom cluster, and hyperglycemia symptom cluster. At the global level, general fatigue (r Conclusion: This study identifies general fatigue as the core symptom, with excessive sleepiness, limb numbness, limb swelling, and polydipsia emerging as sentinel symptoms, within their respective symptom clusters. From the perspective of symptom network analysis and sentinel symptoms, clinical staff can develop accurate and efficient intervention measures to improve the efficiency of symptom management and reduce the burden of symptoms in elderly patients with T2DM.

Indexed as

core symptomselderly patients with type 2 diabetes mellitusnetwork analysissentinel symptomssymptom management

Identifiers

PMID41919170
PMCPMC13034604

What Socratic holds

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LicenceCC BY
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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 Socratic graph.