Evidence map›Paper›PMID 38481553›Full record

ArticleJournal of traditional and complementary medicine2024

Peripheral pulse harmonic analysis and its clinical application: A systematic review.

Kun-Yuan Hsiao, Jiunn-Horng Kang, Yeong-Shing Wu, Hen-Hong Chang, Cheng-Ta Yang

Open access · diamondAbstract read
In one paragraph

Article in Journal of traditional and complementary medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
2.8field-weighted citation impact, top 10% of its field
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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

5 citing papers in PubMed, 7 citations in OpenAlex.

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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

5 authors at 4 institutions in 1 country.

Kun-Yuan HsiaoInstitute of Allied Health Sciences, National Cheng Kung University, Tainan, Taiwan.
Jiunn-Horng KangProfessional Master Program in Artificial Intelligence in Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan.
Yeong-Shing WuGraduate Institute of Integrated Medicine, College of Chinese Medicine, and Chinese Medicine Research Center, China Medical University, Taichung, Taiwan.
Hen-Hong ChangGraduate Institute of Integrated Medicine, College of Chinese Medicine, and Chinese Medicine Research Center, China Medical University, Taichung, Taiwan.
Cheng-Ta YangInstitute of Allied Health Sciences, National Cheng Kung University, Tainan, Taiwan.
China Medical University · TWMinistry of Health and Welfare · TWTaipei Medical University · TWTaipei Medical University Hospital · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Pulse harmonic analysis is a quantitative and objective methodology within traditional Chinese medicine (TCM) used to evaluate pulse characteristics. However, interpreting pulse wave data is challenging due to its inherent complexity. This study aims to provide a comprehensive review and comparison of existing human pulse wave harmonic analysis methods to elucidate their patterns and characteristics. Methods: A systematic review of clinical research reports published from 1990 to 2021 was conducted, focusing on variations in harmonic characteristics across different medical conditions and physiological states. Keyword searches included terms related to analysis methods (e.g., "Pulse Spectrum," "harmonic analysis," "harmonic index") and measured indicators (e.g., "vascular response," "PPG," "Photoplethysmography," "aortic," "arterial," "blood pressure"). Supplementary research using PubMed's Mesh terms specifically targeted "Pulse wave analysis" within the methods and statistical analysis domain. Articles were filtered based on predefined criteria, including human participants and research related to pulse pressure or vascular volume changes. Conference papers, animal studies, and irrelevant research were excluded, with literature evaluation scales selected based on the retrieved research reports. Results: Initially, 6487 research reports were identified, and after screening, 50 reports were included in the review. The analysis revealed that low-frequency harmonics increase following vigorous activity or sympathetic excitation but decrease during rest or parasympathetic excitation. Cardiovascular patients exhibited elevated first harmonics associated with the liver meridian, while diabetes patients displayed weakened third harmonics related to the spleen meridian. Liver dysfunction was linked to changes in the first harmonic, and cancer patients showed signs of liver and kidney yin deficiency in the first and second harmonics. These findings underscore the potential of harmonic analysis for TCM disease diagnosis and organ assessment. Moreover, individuals with conditions such as liver dysfunction, cancer, and gynecological disorders displayed distinct intensity patterns across harmonics one through ten compared to healthy controls, albeit with some variations. Heterogeneity in these studies mainly stemmed from differences in measurement methods and study populations. Additionally, research suggested that factors like blood circulation and cognitive activity influenced harmonic intensity. Conclusions: In summary, this report consolidates prior research on pulse wave harmonics analysis, revealing unique patterns associated with various physiological conditions. Despite limitations, such as limited sample sizes in previous studies, the observed associations between physiological states and harmonics hold promise for potential clinical applications. This study lays a solid foundation for future applications of arterial wave harmonics analysis, promoting wider adoption of this analytical approach.

Indexed as

Diagnostic toolsHarmonic characteristicsPulse diagnosisPulse harmonic analysisTraditional Chinese medicine

Identifiers

PMID38481553
PMCPMC10927382
OpenAlexW4388835537

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.