ArticlePharmacological research2022
Timely treatment and higher compliance to traditional Chinese medicine: New influencing factors for reducing severe COVID-19 based on retrospective cohorts in 2020 and 2021.
Article in Pharmacological research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed.
- Effect of Chinese Medicine in Patients with COVID-19: A Multi-center Retrospective Cohort Study.Chinese journal of integrative medicine · 2024Article
- Review
- Practice and principle of traditional Chinese medicine for the prevention and treatment of COVID-19.Frontiers of medicine · 2023Review
- Urine metabolites and viral pneumonia among children: a case-control study in China.Translational pediatrics · 2023Article
- Quantitative evaluation of traditional Chinese medicine development policy: A PMC index model approach.Frontiers in public health · 2022Article
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8 authors.
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Abstract
objectiveFrom the beginning of 2020, our study team formulated a traditional Chinese medicine (TCM) prescription named Sanhanhuashi formula (SHHS) to treat COVID-19 patients. Then we conducted several studies to explore the effectiveness of SHHS formula and other influencing factors on prognosis of disease. The purpose of this study was to describe the trends of patients' characters from 2020 to 2021 based on two separate cohorts, and to explore the influencing factors on incidence of severe COVID-19 conditions, especially the contributions of timely treatment and higher compliance to SHHS formula.
methodsA retrospective cohort study was conducted in Wuhan, Hubei province and Tonghua, Jilin province. Participants were hospitalized mild to moderate COVID-19 consecutive enrolled patients in Wuhan hospital of traditional Chinese and western medicine (from Feb 13, 2020 to March 8, 2020) and Tonghua central hospital (from Jan 17, 2021 to Feb 5, 2021). Age, sex, time waiting to be hospitalized, medical history, initial symptoms, concomitant medication, and severity of disease were collected. Univariate and multivariate logistic regression were used to explore the associations between various exposures and the outcome, ie. the proportion of patients who were converted to severe status. E-values and its lower control limit (LCL) were calculated for sensitivity analysis.
resultsTotally, 176 COVID-19 patients in two hospitals were enrolled. 81 patients were from Wuhan hospital of traditional Chinese and western medicine and 95 from Tonghua central hospital. 42 patients used SHHS formula arrival or exceed 7 days, and 2 (4.8%) progressed to severe condition. Among 134 patients who were exposed SHHS less than 7 days, 18 (13.4%) were converted to severe situation. Compared with those diagnosed in 2020, cases in 2021 were characterized as lower rates of initial symptoms (88.9% vs 35.8%, P < 0.001) and concomitant medications ever widely used, eg. antiviral medicine (71.6% vs 43.2%, P < 0.001), antibiotics (61.7% vs 13.7%, P < 0.001) and Chinese patent medicine (76.5% vs 44.2%, P < 0.001). They also waited less time for hospitalization (median: 12 vs 2 days, P < 0.001). The final multivariate logistic regression model showed that age (> 60 yrs) (OR: 3.943; 95% CI: 1.402-11.086; P = 0.009; E-value = 7.35, LCL:2.15), diagnosis year (OR: 0.165; 95% CI: 0.050-0.551; P = 0.003; E-value=11.6, LCL: 3.03) and SHHS exposure (OR: 0.118; 95% CI: 0.014-0.992; P = 0.049; E-value = 16.43, LCL:1.1) were independent risk factors for predicting severe status.
conclusionsThe profile of COVID-19 patients has changed after one year. In addition to age, diagnosis year and SHHS exposure are two new factors to predict the prognosis of disease. The patients diagnosed in 2021 were mainly benefited from timely treatment. Subsequently, adhere to use SHHS formula a quite longer time reduced the number of severe cases. Therefore, both the current epidemic prevention and control measures and increasing compliance to traditional Chinese medicine are effective ways to reducing severe cases and improving public health.
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