Traditional Chinese medicine application and evidence analysis of 1426 cases of long COVID: A retrospective study

At present, the focus of COVID-19's treatment has shifted from the prevention and treatment of acute viral infection to the treatment and rehabilitation of symptoms in the recovery period of long COVID and the associated diseases. To preliminarily evaluate the clinical efficacy of integrated Chinese and Western medical treatment plans and to describe the characteristics of “long COVID” syndromes. Eligible “long COVID” patients diagnosed between December 2022 and June 2023 at the Third Affiliated Hospital of Zhejiang Chinese Medical University were identified through electronic medical records. Baseline demographic information was collected, and patients were divided into a TCM group and a Western medicine group based on their treatment methods. The primary outcome for efficacy evaluation was TCM syndrome scores and symptom improvement time, with secondary outcomes including symptom improvement rates. Survival curve analysis was used to assess symptom improvement time, and a Cox regression model was employed to identify potential risk factors affecting symptom prognosis. Chi-square tests were used to compare binary data between or among groups. The Jaccard method was applied for systematic clustering of TCM syndromes, and clinical characteristics at the start and end of treatment were reported. Analysis showed that younger patients, those with underweight, and those receiving TCM treatment had shorter recovery times ( P < 0.0001). Systematic clustering of the main symptom elements (33 elements with a frequency ≥ 5%) identified six core combinations. The main symptoms of long COVID included cough, excessive sputum, nasal congestion, chest tightness, sore throat, and fatigue. Notably, symptoms such as fatigue, shortness of breath, and loss of appetite, classified as deficiency syndromes in TCM, had longer recovery times. Elderly, obesity, underlying diseases, and exclusive Western medicine treatment were associated with poorer prognosis. The early recovery period is characterized by a mix of deficiency and excess syndromes, whereas the later period is dominated by deficiency syndromes. TCM treatment can effectively improve clinical symptoms and shorten symptom duration, but further research is needed.

Authors

Institutions

Publication Details

Journal
Clinical Traditional Medicine and Pharmacology
Published
2024-11-20
DOI
https://doi.org/10.1016/j.ctmp.2024.200175
Citations
2
Primary Topic
Long-Term Effects of COVID-19
Type
article
Field-Weighted Citation Impact
0.74
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Traditional Chinese medicine application and evidence analysis of 1426 cases of long COVID: A retrospective study

Xuewen Wu, Lilei Xu, Kangshun Zhu, Jiangsong Zhang et al.
2 citations
Clinical Traditional Medicine and Pharmacology
Long-Term Effects of COVID-19
0.74
article

Traditional Chinese medicine application and evidence analysis of 1426 cases of long COVID: A retrospective study

Xuewen Wu, Lilei Xu, Kangshun Zhu, Jiangsong Zhang, Conghua Ji, Ting Chen, Yang Chen, Xianming Lin, Jisheng Zhang
article en
2 citations

Abstract

At present, the focus of COVID-19's treatment has shifted from the prevention and treatment of acute viral infection to the treatment and rehabilitation of symptoms in the recovery period of long COVID and the associated diseases. To preliminarily evaluate the clinical efficacy of integrated Chinese and Western medical treatment plans and to describe the characteristics of “long COVID” syndromes. Eligible “long COVID” patients diagnosed between December 2022 and June 2023 at the Third Affiliated Hospital of Zhejiang Chinese Medical University were identified through electronic medical records. Baseline demographic information was collected, and patients were divided into a TCM group and a Western medicine group based on their treatment methods. The primary outcome for efficacy evaluation was TCM syndrome scores and symptom improvement time, with secondary outcomes including symptom improvement rates. Survival curve analysis was used to assess symptom improvement time, and a Cox regression model was employed to identify potential risk factors affecting symptom prognosis. Chi-square tests were used to compare binary data between or among groups. The Jaccard method was applied for systematic clustering of TCM syndromes, and clinical characteristics at the start and end of treatment were reported. Analysis showed that younger patients, those with underweight, and those receiving TCM treatment had shorter recovery times ( P < 0.0001). Systematic clustering of the main symptom elements (33 elements with a frequency ≥ 5%) identified six core combinations. The main symptoms of long COVID included cough, excessive sputum, nasal congestion, chest tightness, sore throat, and fatigue. Notably, symptoms such as fatigue, shortness of breath, and loss of appetite, classified as deficiency syndromes in TCM, had longer recovery times. Elderly, obesity, underlying diseases, and exclusive Western medicine treatment were associated with poorer prognosis. The early recovery period is characterized by a mix of deficiency and excess syndromes, whereas the later period is dominated by deficiency syndromes. TCM treatment can effectively improve clinical symptoms and shorten symptom duration, but further research is needed.

Clinical Traditional Medicine and PharmacologyVol. 5(4)
Zhejiang Chinese Medical University (CN), The Third Affiliated Hospital of Zhejiang Chinese Medical University (CN)
Openalex Percentile: Top 25%
Long-Term Effects of COVID-19
0.74
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.