Evidence map›Paper›PMID 39066543›Full record

ArticleJournal of traditional Chinese medicine = Chung i tsa chih ying wen pan2024

A real-world study of the differences in Traditional Chinese Medicine diagnosis and treatment rules for coronavirus disease 2019 between Northern and Southern China.

S U Rui, S U Youzhu, Wang Shuo, Fan Jie, Liu Qingquan, Liu Mifeng

Abstract read
In one paragraph

Article in Journal of traditional Chinese medicine = Chung i tsa chih ying wen pan, 2024. 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

6 authors.

S U RuiDepartment of infectious diseases, Capital Medical University Beijing Hospital of Traditional Chinese Medicine, Beijing 100010, China.
S U YouzhuDepartment of infectious diseases, Capital Medical University Beijing Hospital of Traditional Chinese Medicine, Beijing 100010, China.
Wang ShuoDepartment of infectious diseases, Capital Medical University Beijing Hospital of Traditional Chinese Medicine, Beijing 100010, China.
Fan JieDepartment of infectious diseases, Capital Medical University Beijing Hospital of Traditional Chinese Medicine, Beijing 100010, China.
Liu QingquanDepartment of infectious diseases, Capital Medical University Beijing Hospital of Traditional Chinese Medicine, Beijing 100010, China.
Liu MifengDepartment of infectious diseases, Capital Medical University Beijing Hospital of Traditional Chinese Medicine, Beijing 100010, China.

Funding

National Key Research and Development Plan: Study on TCM Syndrome Regularity and Optimization of Coronavirus Disease 2019 Diagnosis and Treatment Plan 2021YFC1712901
6 · The paper itself

Abstract

objectiveTo explore the differences in Traditional Chinese Medicine (TCM) diagnosis and treatment rules for coronavirus disease 2019 (COVID-19) between Northern and Southern China based on the real-world data from 982 COVID-19 patients.

methodsAll consecutive cases of COVID-19 admitted to the TCM department of designated COVID-19 hospitals in eight provinces and cities were retrospectively analyzed. Patients were divided into a Northern and a Southern group according to the location of the admitting hospital. The symptoms, syndrome elements, syndrome distribution and herbal treatments were analyzed. The core prescriptions were extracted using the multiscale backbone-based network comparison algorithm (msbNC).

resultsThe distribution of syndrome elements showed that dampness was common in Northern and Southern China, wind and heat were more often present in the South, while fire toxin and spleen deficiency were more often encountered in the North. The distribution of syndromes showed that the South was dominated by heat dampness accumulating in the lung (55.69%), while the North was dominated by dampness-toxin stagnating in the lung (44.90%).The results of core prescription mining showed that dispelling dampness, dispersing wind, clearing heat and strengthening spleen were the common treatment methods in Northern and Southern China. For mild cases, Jinyinhua (

conclusionThere were certain North-South differences in terms of symptoms, syndrome elements and syndrome distribution of COVID-19, as well as differences in core prescriptions during different periods of the disease. The regional differences in the rules of TCM diagnosis and treatment for COVID-19 should be further considered in the process of optimization and revision of relevant treatment guidance.

Indexed as

COVID-19COVID-19 Drug TreatmentDrugs, Chinese HerbalMedicine, Chinese TraditionalSARS-CoV-2AdultAgedChinaFemaleHumansMaleMiddle AgedRetrospective StudiesDrugs, Chinese Herbalcore prescriptionCOVID-19medicine, Chinese traditionalNorth-South differenceretrospective studiessyndrome

Identifiers

PMID39066543
PMCPMC11337256

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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.