Evidence map›Paper›PMID 39831189›Full record

ArticleFrontiers in big data2024

Exploring the pivotal variables of tongue diagnosis between patients with chronic kidney disease and health participants.

Po-Chi Hsu, Jia-Ming Chen, Chia-Chu Chang, Yu-Jun Chang, Ping-Fang Chiu, John Y Chiang, Lun-Chien Lo

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Article in Frontiers in big data, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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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

7 authors.

Po-Chi HsuSchool of Chinese Medicine, China Medical University, Taichung, Taiwan.
Jia-Ming ChenDepartment of Traditional Chinese Medicine, Changhua Christian Hospital, Changhua, Taiwan.
Chia-Chu ChangDivision of Nephrology, Department of Internal Medicine, Kuang Tien General Hospital, Taichung, Taiwan.
Yu-Jun ChangBig Data Center, Epidemiology and Biostatistics Center, Changhua Christian Hospital, Changhua, Taiwan.
Ping-Fang ChiuNephrology Division, Department of Internal Medicine, Changhua Christian Hospital, Changhua, Taiwan.
John Y ChiangDepartment of Computer Science and Engineering, National Sun Yat-Sen University, Kaohsiung, Taiwan.
Lun-Chien LoSchool of Chinese Medicine, China Medical University, Taichung, Taiwan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Chronic kidney disease (CKD) is a significant global health problem associated with high morbidity and mortality rates. Traditional Chinese Medicine (TCM) utilizes tongue diagnosis to differentiate symptoms and predict prognosis. This study examines the relationship between tongue characteristics and CKD severity using an automatic tongue diagnosis system (ATDS), which captures tongue images non-invasively to provide objective diagnostic information. Methods: This cross-sectional, case-control study was conducted from July 1, 2019, to December 31, 2021. Participants were divided into three groups based on estimated glomerular filtration rate (eGFR): control (eGFR > 60 ml/min/1.732), CKD stage 3 (30 ≤ eGFR < 60 ml/min/1.732), and CKD stage 4-5 (eGFR < 30 ml/min/1.732). Tongue images were analyzed using ATDS to extract nine primary features: tongue shape, color, fur, saliva, fissures, ecchymosis, tooth marks, and red dots. Statistical analyses included non-parametric methods and ordinal logistic regression. Results: This study revealed that significant differences in the fur thickness, tongue color, amount of ecchymosis, and saliva among three groups. Ordinal logistic regression indicated that pale tongue color (OR: 2.107, Conclusion: Tongue features such as paleness, wet saliva, yellow fur, and ecchymosis are prevalent in CKD patients and can serve as early clinical indicators of the disease. This study demonstrates that TCM tongue diagnosis, facilitated by ATDS, is a valuable, non-invasive method for identifying CKD and distinguishing its stages.

Indexed as

automatic tongue diagnosis system (ATDS)chronic kidney disease (CKD)renal functiontongue diagnosisTraditional Chinese Medicine (TCM)

Identifiers

PMID39831189
PMCPMC11739136

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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.