BACKGROUND: Over 65 million people have long COVID. Evidence for using Chinese herbal medicine (CHM) to treat long COVID is growing. A systematic review of evidence for guiding clinical decision is warranted. OBJECTIVE: To examine the effects and safety of CHM in alleviating the severity of dyspnea, fatigue, exercise intolerance, depression, anxiety and insomnia in long COVID adults based on registered randomized clinical trials (RCT). SEARCH STRATEGY: World Health Organization International Clinical Trials Registry Platform and Chinese Clinical Trial Registry were searched for registered trial protocols from database inception to February 10, 2023. English (PubMed, Embase, AMED and CINAHL) and Chinese databases (CNKI, Wanfang Data and CQVIP) were then searched to identify relevant publications from December 2019 through April 6, 2023. INCLUSION CRITERIA: Registered RCTs that compared the effects of Chinese herbal medicines or Chinese herbal formulas against a control treatment (i.e., the placebo or usual care) in adults with persistent symptoms of long COVID. The primary outcome of dyspnea, and secondary outcomes of fatigue, exercise intolerance, depression, anxiety and insomnia were measured using validated tools at the end of the treatment. DATA EXTRACTION AND ANALYSIS: Data were extracted, and eligible RCTs were evaluated using version 2 of the Cochrane risk-of-bias tool for randomized trials and Grading of Recommendations, Assessment, Development and Evaluations independently by two researchers. Effect sizes were estimated by random-effects modelling and mean difference (MD). Heterogeneity between trials was quantified by I². RESULTS: Among the 38 registered clinical trials we identified, seven RCTs (1,519 patients) were included in the systematic review. One RCT had a low overall risk of bias. Compared to the control, CHM reduces dyspnea on the Borg Dyspnea Scale score (MD = -0.2, 95% confidence interval [CI] = -0.65 to 0.25) with moderate certainty, and reduces fatigue on the Borg Scale (MD = -0.48, 95% CI = -0.74 to -0.22) with low certainty. CHM clinically reduces depression on Hamilton Depression Rating Scale score (MD = -6.00, 95% CI = -7.56 to -4.44) and anxiety on Hamilton Anxiety Rating Scale score (MD = -6.10, 95% CI = -7.67 to -4.53), and reduces insomnia on the Insomnia Severity Index (MD = -4.86, 95% CI = -12.50 to 2.79) with moderate certainty. Meta-analysis of two RCTs (517 patients) showed that CHM clinically improves exercise intolerance by increasing 6-minute walking distance (MD = -15.92, 95% CI = -10.20 to 42.05) with substantial heterogeneity (I² = 68%) and low certainty. CONCLUSION CHM is associated with a post-treatment clinical reduction in depression and anxiety in long COVID adults, compared to the control, but it does not have a strong treatment effect on dyspnea and insomnia. Effects of CHM on exercise intolerance and fatigue are uncertain, and the safety of using CHM remains questionable. Please cite this article as: Tsang MS, Zhou IW, Zhang AL, Xue CC. Chinese herbal medicine for dyspnea and persistent symptoms of long COVID: A systematic review and meta-analysis of randomized controlled trials. J Integr Med. 2025; 23(2): 126-137.
Humans ; Dyspnea/etiology* ; Drugs, Chinese Herbal/therapeutic use* ; Randomized Controlled Trials as Topic ; COVID-19/complications* ; Fatigue/drug therapy* ; SARS-CoV-2 ; Anxiety/drug therapy* ; Depression/drug therapy* ; Sleep Initiation and Maintenance Disorders/drug therapy* ; Betacoronavirus

Asymptomatic Infections ; Betacoronavirus ; Carrier State ; Coronavirus Infections ; transmission ; Female ; Humans ; Middle Aged ; Pandemics ; Pneumonia, Viral ; transmission

Acute Kidney Injury ; etiology ; Betacoronavirus ; Coronavirus Infections ; complications ; Humans ; Kidney ; enzymology ; Pandemics ; Peptidyl-Dipeptidase A ; physiology ; Pneumonia, Viral ; complications ; Sequence Analysis, RNA ; methods ; Serine Endopeptidases ; physiology ; Single-Cell Analysis ; methods

BACKGROUND: The ongoing new coronavirus pneumonia (Corona Virus Disease 2019, COVID-19) outbreak is spreading in China, but it has not yet reached its peak. Five million people emigrated from Wuhan before lockdown, potentially representing a source of virus infection. Determining case distribution and its correlation with population emigration from Wuhan in the early stage of the epidemic is of great importance for early warning and for the prevention of future outbreaks. METHODS: The official case report on the COVID-19 epidemic was collected as of January 30, 2020. Time and location information on COVID-19 cases was extracted and analyzed using ArcGIS and WinBUGS software. Data on population migration from Wuhan city and Hubei province were extracted from Baidu Qianxi, and their correlation with the number of cases was analyzed. RESULTS: The COVID-19 confirmed and death cases in Hubei province accounted for 59.91% (5806/9692) and 95.77% (204/213) of the total cases in China, respectively. Hot spot provinces included Sichuan and Yunnan, which are adjacent to Hubei. The time risk of Hubei province on the following day was 1.960 times that on the previous day. The number of cases in some cities was relatively low, but the time risk appeared to be continuously rising. The correlation coefficient between the provincial number of cases and emigration from Wuhan was up to 0.943. The lockdown of 17 cities in Hubei province and the implementation of nationwide control measures efficiently prevented an exponential growth in the number of cases. CONCLUSIONS The population that emigrated from Wuhan was the main infection source in other cities and provinces. Some cities with a low number of cases showed a rapid increase in case load. Owing to the upcoming Spring Festival return wave, understanding the risk trends in different regions is crucial to ensure preparedness at both the individual and organization levels and to prevent new outbreaks.
Betacoronavirus ; China ; epidemiology ; Coronavirus Infections ; epidemiology ; Emigration and Immigration ; Epidemics ; Humans ; Pandemics ; Pneumonia, Viral ; epidemiology

Betacoronavirus ; Clinical Protocols ; Coronavirus Infections ; therapy ; Extracorporeal Membrane Oxygenation ; Humans ; Pandemics ; Pneumonia, Viral ; therapy

Betacoronavirus ; Coronavirus Infections ; diagnosis ; epidemiology ; prevention & control ; therapy ; Humans ; Pandemics ; prevention & control ; Pneumonia, Viral ; diagnosis ; epidemiology ; prevention & control ; therapy ; Viral Vaccines ; therapeutic use

Betacoronavirus ; Coronavirus Infections ; epidemiology ; transmission ; Disease Outbreaks ; Humans ; Pandemics ; Pneumonia, Viral ; epidemiology ; transmission ; Severe Acute Respiratory Syndrome ; epidemiology

BACKGROUND: Since early December 2019, the 2019 novel coronavirus disease (COVID-19) has caused pneumonia epidemic in Wuhan, Hubei province of China. This study aimed to investigate the factors affecting the progression of pneumonia in COVID-19 patients. Associated results will be used to evaluate the prognosis and to find the optimal treatment regimens for COVID-19 pneumonia. METHODS: Patients tested positive for the COVID-19 based on nucleic acid detection were included in this study. Patients were admitted to 3 tertiary hospitals in Wuhan between December 30, 2019, and January 15, 2020. Individual data, laboratory indices, imaging characteristics, and clinical data were collected, and statistical analysis was performed. Based on clinical typing results, the patients were divided into a progression group or an improvement/stabilization group. Continuous variables were analyzed using independent samples t-test or Mann-Whitney U test. Categorical variables were analyzed using Chi-squared test or Fisher's exact test. Logistic regression analysis was performed to explore the risk factors for disease progression. RESULTS: Seventy-eight patients with COVID-19-induced pneumonia met the inclusion criteria and were included in this study. Efficacy evaluation at 2 weeks after hospitalization indicated that 11 patients (14.1%) had deteriorated, and 67 patients (85.9%) had improved/stabilized. The patients in the progression group were significantly older than those in the disease improvement/stabilization group (66 [51, 70] vs. 37 [32, 41] years, U = 4.932, P = 0.001). The progression group had a significantly higher proportion of patients with a history of smoking than the improvement/stabilization group (27.3% vs. 3.0%, χ = 9.291, P = 0.018). For all the 78 patients, fever was the most common initial symptom, and the maximum body temperature at admission was significantly higher in the progression group than in the improvement/stabilization group (38.2 [37.8, 38.6] vs. 37.5 [37.0, 38.4]°C, U = 2.057, P = 0.027). Moreover, the proportion of patients with respiratory failure (54.5% vs. 20.9%, χ = 5.611, P = 0.028) and respiratory rate (34 [18, 48] vs. 24 [16, 60] breaths/min, U = 4.030, P = 0.004) were significantly higher in the progression group than in the improvement/stabilization group. C-reactive protein was significantly elevated in the progression group compared to the improvement/stabilization group (38.9 [14.3, 64.8] vs. 10.6 [1.9, 33.1] mg/L, U = 1.315, P = 0.024). Albumin was significantly lower in the progression group than in the improvement/stabilization group (36.62 ± 6.60 vs. 41.27 ± 4.55 g/L, U = 2.843, P = 0.006). Patients in the progression group were more likely to receive high-level respiratory support than in the improvement/stabilization group (χ = 16.01, P = 0.001). Multivariate logistic analysis indicated that age (odds ratio [OR], 8.546; 95% confidence interval [CI]: 1.628-44.864; P = 0.011), history of smoking (OR, 14.285; 95% CI: 1.577-25.000; P = 0.018), maximum body temperature at admission (OR, 8.999; 95% CI: 1.036-78.147, P = 0.046), respiratory failure (OR, 8.772, 95% CI: 1.942-40.000; P = 0.016), albumin (OR, 7.353, 95% CI: 1.098-50.000; P = 0.003), and C-reactive protein (OR, 10.530; 95% CI: 1.224-34.701, P = 0.028) were risk factors for disease progression. CONCLUSIONS Several factors that led to the progression of COVID-19 pneumonia were identified, including age, history of smoking, maximum body temperature at admission, respiratory failure, albumin, and C-reactive protein. These results can be used to further enhance the ability of management of COVID-19 pneumonia.
Adult ; Aged ; Betacoronavirus ; Coronavirus Infections ; Female ; Hospitals ; Humans ; Logistic Models ; Male ; Middle Aged ; Pandemics ; Pneumonia, Viral ; Risk Factors

BACKGROUND: A patient's infectivity is determined by the presence of the virus in different body fluids, secretions, and excreta. The persistence and clearance of viral RNA from different specimens of patients with 2019 novel coronavirus disease (COVID-19) remain unclear. This study analyzed the clearance time and factors influencing 2019 novel coronavirus (2019-nCoV) RNA in different samples from patients with COVID-19, providing further evidence to improve the management of patients during convalescence. METHODS: The clinical data and laboratory test results of convalescent patients with COVID-19 who were admitted to from January 20, 2020 to February 10, 2020 were collected retrospectively. The reverse transcription polymerase chain reaction (RT-PCR) results for patients' oropharyngeal swab, stool, urine, and serum samples were collected and analyzed. Convalescent patients refer to recovered non-febrile patients without respiratory symptoms who had two successive (minimum 24 h sampling interval) negative RT-PCR results for viral RNA from oropharyngeal swabs. The effects of cluster of differentiation 4 (CD4)+ T lymphocytes, inflammatory indicators, and glucocorticoid treatment on viral nucleic acid clearance were analyzed. RESULTS: In the 292 confirmed cases, 66 patients recovered after treatment and were included in our study. In total, 28 (42.4%) women and 38 men (57.6%) with a median age of 44.0 (34.0-62.0) years were analyzed. After in-hospital treatment, patients' inflammatory indicators decreased with improved clinical condition. The median time from the onset of symptoms to first negative RT-PCR results for oropharyngeal swabs in convalescent patients was 9.5 (6.0-11.0) days. By February 10, 2020, 11 convalescent patients (16.7%) still tested positive for viral RNA from stool specimens and the other 55 patients' stool specimens were negative for 2019-nCoV following a median duration of 11.0 (9.0-16.0) days after symptom onset. Among these 55 patients, 43 had a longer duration until stool specimens were negative for viral RNA than for throat swabs, with a median delay of 2.0 (1.0-4.0) days. Results for only four (6.9%) urine samples were positive for viral nucleic acid out of 58 cases; viral RNA was still present in three patients' urine specimens after throat swabs were negative. Using a multiple linear regression model (F = 2.669, P = 0.044, and adjusted R = 0.122), the analysis showed that the CD4+ T lymphocyte count may help predict the duration of viral RNA detection in patients' stools (t = -2.699, P = 0.010). The duration of viral RNA detection from oropharyngeal swabs and fecal samples in the glucocorticoid treatment group was longer than that in the non-glucocorticoid treatment group (15 days vs. 8.0 days, respectively; t = 2.550, P = 0.013) and the duration of viral RNA detection in fecal samples in the glucocorticoid treatment group was longer than that in the non-glucocorticoid treatment group (20 days vs. 11 days, respectively; t = 4.631, P < 0.001). There was no statistically significant difference in inflammatory indicators between patients with positive fecal viral RNA test results and those with negative results (P > 0.05). CONCLUSIONS In brief, as the clearance of viral RNA in patients' stools was delayed compared to that in oropharyngeal swabs, it is important to identify viral RNA in feces during convalescence. Because of the delayed clearance of viral RNA in the glucocorticoid treatment group, glucocorticoids are not recommended in the treatment of COVID-19, especially for mild disease. The duration of RNA detection may relate to host cell immunity.
Adult ; Aged ; Betacoronavirus ; genetics ; Clinical Laboratory Techniques ; Coronavirus Infections ; diagnosis ; genetics ; rehabilitation ; Female ; Humans ; Male ; Middle Aged ; Pandemics ; Pneumonia, Viral ; genetics ; rehabilitation ; RNA, Viral ; genetics ; Real-Time Polymerase Chain Reaction ; Retrospective Studies

Animals ; Betacoronavirus ; Coronavirus Infections ; epidemiology ; Disease Outbreaks ; Humans ; Pandemics ; Pneumonia, Viral ; epidemiology ; Zoonoses ; epidemiology