Evidence map›Paper›PMID 42109747›Full record

ArticleFrontiers in endocrinology2026

Evaluating the efficacy of a telehealth management model for chronic diabetes in resource-constrained regions.

Min Chen, Jing Fu, Puxian Tang, Dizhi Liu, Ying Wang, Xia Huang, Yan Wen, Chenghua Liu, Kai Zhou, Ge Yu and 1 more

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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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Min Chen *Department of Nephrology and Rheumatology/Immunology, People's Hospital of Dafang, Bijie, Guizhou, China.
Jing Fu *General Practice Department, Beijing Hospital, National Center of Gerontology; National Clinical Research Center for Gerontology; The Key Laboratory of Geriatrics of NHC; Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.
Puxian Tang *Medical Department, Beijing Hospital, National Center of Gerontology; National Clinical Research Center for Gerontology; The Key Laboratory of Geriatrics of NHC; Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.
Dizhi LiuThe Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing Hospital/National Center of Gerontology of National Health Commission, Beijing, China.
Ying WangDepartment of Endocrinology, People's Hospital of Dafang, Bijie, Guizhou, China.
Xia HuangDepartment of Endocrinology, People's Hospital of Dafang, Bijie, Guizhou, China.
Yan WenDepartment of Geriatrics and Clinical Nutrition, People's Hospital of Dafang, Bijie, Guizhou, China.
Chenghua LiuThe Health Center of Huannitang Town, Bijie, Guizhou, China.
Kai ZhouThe Health Center of Daxi Town, Bijie, Guizhou, China.
Ge YuThe Health Center of Xiaotun Town, Bijie, Guizhou, China.
Yan ZhouGeneral Practice Department, Beijing Hospital, National Center of Gerontology; National Clinical Research Center for Gerontology; The Key Laboratory of Geriatrics of NHC; Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To assess the effects of a telehealth-enhanced integrated county-township-village management model (hereafter referred to as the telehealth management model) on metabolic indicators and chronic complications of rural-dwelling individuals with diabetes mellitus (DM), seeking an effective chronic disease management approach for regions with limited medical resources. Methods: An exploratory quasi-experimental study was conducted in Dafang County, Guizhou Province. Three townships were assigned to the management group, while the remaining townships constituted the control group. The management group participated in a 12-month diabetes intervention using a telemedicine platform for comprehensive care, while the control group received standard outpatient follow-up. Key indicators measured before and after the intervention included fasting blood glucose (FBG), 2-hour postprandial blood glucose (2hPG), haemoglobin A1c (HbA1c), blood lipids, blood pressure, body mass index (BMI), the incidence of new chronic complications, and the pass rate on a diabetes knowledge assessment. Statistical analyses, including descriptive analyses for patient characteristics, multivariable regression for associations and adjusted effects, subgroup and restricted cubic spline analyses for heterogeneous and nonlinear relationships, and a propensity score matching combined with difference-in-differences (PSM-DID) approach to estimate the causal effect of the intervention, were performed. Results: In this study including 215 patients (88 in the management group and 127 in the control group), compared with the control group, the management group showed significant improvements after 12 months, including lower FBG (8.97 vs. 10.77), 2hPG (13.30 vs. 16.96), HbA1c (7.84 vs. 9.45), triglyceride (TG, 1.84 vs. 2.43), and BMI (23.94 vs. 26.09) levels and higher high-density lipoprotein cholesterol (HDL-C, 1.26 vs. 1.10) levels (all Conclusion: Compared to standard of care, the telehealth management model improved patients' metabolic indicators, decreased complication risks, and strengthened primary health care services. This model provides a replicable example for the scalable implementation of integrated diabetes management in similar underdeveloped regions.

Indexed as

Diabetes MellitusDiabetes Mellitus, Type 2Health ResourcesTelemedicineAgedBlood GlucoseChinaChronic Care ModelChronic DiseaseDigital HealthDisease ManagementFemaleGlycated HemoglobinHumansMaleMiddle AgedBlood GlucoseGlycated Hemoglobinchronic disease managementdiabetes mellitusglycemic controlintegrated caretelehealth

Identifiers

PMID42109747
PMCPMC13149080

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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.