1. Introduction
The coronavirus disease 2019 (COVID-19) pandemic poses a threat to human health [
1]. A range of symptoms may persist long after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, and cough is one of the most prevalent symptoms of COVID-19 [
2]. Following SARS-CoV-2 infection, coughing can last for weeks or months and is frequently accompanied by persistent fatigue, dyspnea, or sleep disorders, which are long-term consequences affecting quality of life [
3]. The risk of prolonged coughing persists even beyond one year post-SARS-CoV-2 infection [
4]. A multicenter prospective cohort study that examined COVID-19 aftereffects in elderly patients one year after hospital discharge revealed that 5.8% of 1233 eligible participants experienced cough aftereffects [
5]. As the most prevalent pandemic strain on a global scale, the Omicron variant has significantly less severe pulmonary effects, and most patients report symptoms of upper respiratory tract infection [
6]. Therefore, effective treatment options for long COVID cough patients are urgently needed.
Chinese medicinal therapies can be used to treat cough through evidence-based treatment, and they have a rich history in the treatment of viral infectious respiratory diseases. Lianhua Qingke tablets are a patented traditional Chinese medicine (TCM) specifically designed for relieving cough, and they are clinically effective in treating patients with mild and common forms of COVID-19 and play a significant role in suppressing cough [
7]. However, the therapeutic effects of Lianhua Qingke tablets for treating long COVID cough remain unclear.
The aim of this study was to evaluate the efficacy and safety of Lianhua Qingke tablets for the treatment of long COVID cough, contributing to evidence-based medicine.
2. Materials and methods
2.1. Study design
This was a randomized, double-blind, placebo-controlled, multicenter clinical study including 19 hospitals and 23 community health centers in China.
This study was approved by the Ethics Committee of Beijing Hospital of Traditional Chinese Medicine, Capital Medical University, and registered in the Chinese Clinical Trial Registry (ChiCTR-IPR-2300068877). Each study participant signed an informed consent form. Participants were enrolled from March 2023 to July 2023. During the trial, each participant was followed for 14 days, and attended three visits: the first visit occurred between three days (day −3) before the trial and the day the trial started, the second visit occurred on day 7 (± 1 day), and the third visit occurred on day 14 (± 2 days). Participants whose cough did not disappear during the trial received an additional follow-up at (30 ± 2) days after the conclusion of the trial.
2.2. Participants
The inclusion criteria were as follows: ① met the diagnostic criteria according to the Expert Consensus on the Diagnosis and Treatment of Cough after COVID-19 infection; ② were 18-65 years old; ③ had cough onset at 3-8 weeks postinfection; and ④ had a cough visual analog scale (VAS) score ≥ 40 mm.
The exclusion criteria were as follows: ① acute cough, drug-induced cough, allergic cough, cough-variant asthma, upper airway cough syndrome, eosinophilic bronchitis, or gastroesophageal reflux cough; ② cough due to chronic bronchitis, chronic obstructive pulmonary disease, bronchiectasis, lung abscess, interstitial lung disease (including severe pulmonary fibrosis after COVID-19 infection), lung cancer, bronchiolitis, bronchopneumonia, or others; ③ nasopharyngeal diseases, such as chronic rhinitis, sinusitis, pharyngitis, or allergic rhinitis; ④ severe cardiovascular, cerebrovascular, digestive, endocrine, nervous, or mental disorders; ⑤ temperature > 37.3 °C; ⑥ white blood cell count > 12 × 109 per litre, suspected of bacterial infection; ⑦ liver function impairment (alanine aminotransferase (ALT) or aspartate aminotransferase (AST) ≥ 1.5 times the upper limit of normal value) or renal insufficiency (Cr level greater than the upper limit of the normal range); ⑧ the administration of TCM for cough and phlegm with functions and indications similar to those of the trial drugs three days before the study; ⑨ an allergic constitution (allergic to more than two types of substances) or allergic to the trial drugs or their constituents; ⑩ alcoholism and/or drug abuse within one year before the trial; ⑪ pregnant or lactating, pregnant and planning future pregnancies, or inability to employ reliable contraceptive measures; ⑫ participation in interventional clinical studies that may affect the results of this study; and ⑬ deemed inappropriate for enrollment in this trial by investigators.
The criteria for withdrawal from the study as decided by the investigator were as follows: ① no response to treatment or worsening of symptoms; ② allergic reactions or serious adverse events (AEs); ③ comorbidities, complications, or peculiar physiological changes that can negatively affect the efficacy and safety; ④ poor compliance (trial medicine compliance < 80% or > 120%); ⑤ spontaneous replacement of treatment midway or use of prohibited medicines; and ⑥ ineffectiveness of blinding methods for various reasons.
The criteria for withdrawal from the study as decided by the participant were as follows: ① the participant was unwilling or unable to continue with the study; or ② the participant had not received any treatment or visits. In cases of withdrawal from the trial midway or loss to follow-up, the investigator actively attempted to encourage the participant to complete the last follow-up visit as much as possible to help with the efficacy and safety analysis. All participants who withdrew from the study completed the study summary form and included the reasons for dropping out on the case report form.
The termination criteria were as follows: ① serious safety concerns arose, with the well-being of participants being compromised; ② significant flaws were identified in the trial design, posing challenges in assessing the efficacy of the treatment; and ③ despite a rigorous research design, crucial deviations occurred during implementation, hindering the accurate evaluation of the effectiveness of the treatment.
The complete termination criteria were as follows: ① poor efficacy or ② a study suspension request by sponsor (due to funding, management reasons, etc.).
2.3. Randomization and masking
Block randomization and randomization mechanisms were employed for random grouping. During the clinical trial, both participants and investigators were blinded. Linking a participant's randomization number to a treatment code ensures that the random assignment is hidden through a centralized and secure system. The participants did not interact with the investigators and were unaware of the size and stratification of the blocks. All trial medications were administered by the sponsor in line with the blinding specifications and in accordance with the quality specifications, and the excess trial medications were retrieved and disposed of by the sponsor after the trial. During the study, only the medication administrators and nurses who prepared the study medications were aware of participant-dispensing information; however, these medication administrators and nurses were not involved in the collection of data or the assessment of outcomes. In the case of a major AE, the investigator could request unblinding to determine the identity of the study drug. Study unblinding was not performed until after the statistical analysis plan was created, the data review report was finalized, the database was locked, and the treatment group corresponding to the randomization number was revealed upon request by the project statistician and approved by the sponsor for postrandomization statistical analyses of all the data.
2.4. Data collection and monitoring
Completed case report forms (CRFs) were reviewed by clinical investigators who entered the information entered into the database and sent that information to the Data Statistics Unit. Before the first CRF was delivered, a data manager created a database. The data manager wrote a data verification plan and procedures according to the range and interrelationships of the values of the indicators in the CRF. All errors and modification results were recorded in detail and maintained. After the above work was completed, the principal investigator, trial statistician, and data administrator determined the analysis set to which each reporting patient belonged and discussed the treatment of missing values and the judgment of outliers. After the correctness of the database was reviewed and discussed, it was locked.
2.5. Procedures
Participants were divided into the following two groups: the Lianhua Qingke tablet group (the trial group) and the placebo control group (the control group). Assuming that the median time to improvement were seven and five days in the control and Lianhua Qingke tablet groups, respectively, using α = 0.05, β = 0.85 (α and β refer to the statistical significance and power during the two-sided testing, respectively), and a ratio of 1:1, the power calculation revealed that 199 patients were needed for each group. The final sample size was estimated to be 480 patients considering a 20% dropout rate. The majority of the reported outcomes were assessed at three visits (between day −3 and 0, day (7 ± 1), and day (14 ± 2)), and safety assessments were conducted (see Table S1 in Section S1 in Appendix A). Three clinical score sheets are provided in Tables S2-S4 in Section S1. The flowchart is provided in Fig. S1 in Section S2 in Appendix A.
2.6. Medication
Both Lianhua Qingke tablets and placebo tablets were prepared by Shijiazhuang Yiling Pharmaceutical Co. (China). Participants were treated with Lianhua Qingke or placebo tablets (four tablets, 1.84 g) three times a day for 14 days (see production process, quality control standard tests, and fingerprint chromatograms in Sections S3.1-S3.3 in Appendix A).
The following other medication usage scenarios were not permitted. ① During the trial period, similar medication and other medication that interfered with the treatment of this trial were prohibited, including cough suppressants in any dosage form, anti-allergic medication, and other Chinese medicines. ② The use of Chinese herbal tonics or proprietary Chinese medicines that contained the same ingredients or had effects similar to those of the Lianhua Qingke tablets was not permitted during the trial.
However, the following other medication usage scenarios were permitted. ① If the participant had other comorbidities, such as hypertension or hyperlipidemia, and was undergoing other necessary medication routines and treatments, then that participant could continue the trial but was asked to maintain the same dosage of medication during the trial period, and the combined use of medication was recorded in the table on the case report form. ② Combinations of drugs for other diseases were maintained according to the original regimen or used in accordance with the relevant specifications; the name, dosage, route of administration, time of use, and reason for use of the combined medication were recorded in detail for all combined medications.
2.7. Assessment
The primary efficacy indicator was the time to disappearance of cough within 14 days of observation. Secondary efficacy indicators were ① the disappearance rate of cough within 14 days of observation; ② the remission time and rate of cough within 14 days of observation; ③ the value and rate of change in the total symptom score of long COVID cough on days 7 and 14 during the observation; ④ the value and rate of change in the VAS score of cough on days 7 and 14 during the observation; and ⑤ the value and rate of change in the cough evaluation test (CET) score on days 7 and 14 during the observation.
Cough disappearance was defined as a daytime and nighttime cough score of 0 for the previous 24 h reported on the participant's diary card. Cough remission was defined as a daytime or nighttime cough score of ≤ 1 for the previous 24 h reported on the participant's diary card.
2.8. AEs
The degree of association of AEs with medication treatment was determined by an authorized clinician who described the basis for each decision as much as possible. When the severity of the AE was aggravated or considered serious, the principal investigator or assistant was required to assume primary responsibility to determine the causality, maintain a medical record, and organize a consultation or diagnosis by relevant healthcare professionals as appropriate. To determine whether an AE is causally related to medication treatment, the following points were considered: ① whether there is a reasonable temporal relationship between the administration of the medication and the emergence of the AE; ② whether it is consistent with the type of adverse reaction known to occur with the drug; ③ whether the AE diminishes or disappears after discontinuation or dosage reduction; ④ whether the AE recurred after resuming the suspected drug; and ⑤ whether the AE can be explained by the effects of adjuvant drugs, progression of the condition or effects of other treatments. The criteria for determining the relationship between AEs and medication treatment are described in Table S5 in Section S2.
At the occurrence of an AE, the investigator was expected to respond immediately, inform the department head, consider the appropriate diagnostic and therapeutic actions based on the situation, and interrupt the clinical research observation. Until they are fully resolved or the situation stabilizes, all AEs should be monitored and investigated, and the treatment and outcomes should be meticulously documented. Depending on the severity of the AEs, different follow-up methods may be used, including hospitalization, outpatient care, home visits, telephone follow-ups, and emails.
2.9. Statistical analysis
Statistical analysis was performed using SAS 9.4 (order number: 9C1XJD; SAS Institute, USA).
We tested the superiority of the treatment for its effects on the primary endpoint. Other indicators were tested, and a two-sided P < 0.05 was considered to indicate statistical significance. The data are presented as the mean ± standard deviation, median (quartiles), and extreme deviation (minimum-maximum), and counts are presented as frequencies (percentages). For normally or nonnormally distributed measures, two independent samples t tests or Mann-Whitney U rank sum tests were used. For pre- and posttreatment changes, analysis of covariance was used to correct for baseline levels. For count data, the χ2 test or Fisher exact probability method was used. Survival analysis for the 14-day cough disappearance and remission times by using Kaplan-Meier survival curves and log-rank tests. If the median survival time could not be calculated, the restricted mean survival time (RMST) method was used to calculate the 14-day cough disappearance time.
The analysis population was divided into the following three categories: ① the full analysis set (FAS), which included all patients who were randomized into groups and used the trial medication at least once (analyzed by the principle of intention-to-treat); ② the per-protocol set (PPS), which included participants who fully complied with the trial protocol; and ③ the safety set (SS), which included participants who received at least one treatment after randomization and for whom a safety evaluation was available.
Descriptive findings of the statistical demographics and other baseline eigenvalues were generated based on the FAS.
Medication adherence and comorbid medication analyses were conducted among participants whose medication adherence ranged from 80% to 120% and were analyzed based on the FAS. When analyzing medication compliance, the χ2 test or Fisher's exact probability test was used to compare differences between groups. When analyzing the actual medicine dosage and medicine exposure time, a t test was used to compare differences between groups. Concomitant medications were coded using the World Health Organization (WHO) Anatomical Therapeutic Chemical (ATC) Classification System, and the numbers and proportions of cases were calculated after summarizing the data according to the ATC classification.
The primary efficacy indicator analysis was based on the FAS and PPS. When analyzing the time to disappearance of cough within 14 days of observation, the censoring rate, quartile, and 95% confidence interval (CI) were calculated, and Kaplan-Meier curves were drawn. Comparisons between groups were performed using the log-rank test.
The secondary efficacy indicator analysis was based on the FAS. When analyzing the cough disappearance rate and remission rate within the 14-day observation period, the chi-square test was used to compare differences between groups. When analyzing the cough remission time within 14 days, the log-rank test was used to analyze differences between groups. When analyzing the change in the total symptom score, VAS, and CET scores on days 7 and 14 of the observation period, paired-samples t tests were used to compare the changes before and after treatment within the groups, and independent-samples t tests were used for comparisons between groups.
AEs were coded according to the International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH) Medical Dictionary for Regulatory Activities (MedDRA). Based on the SS, safety analysis was performed with descriptive statistics on changes from the baseline of the measured values of vital signs and indicators. Based on system organ class (SOC), preferred term (PT), and severity, AEs that occurred during treatment or led to withdrawal from the trial were recorded in a detailed table with the number, frequency, and incidence of the AEs. Cross-tabulation of laboratory indices, electrocardiogram (ECG), and physical examination data before and after dosing were established. Lists of abnormal laboratory indices, ECG, physical examinations, and clinical explanations were saved. Descriptive statistics of changes from baseline values of vital signs to measured values were generated.
3. Results
3.1. Study recruitment and follow-up
A total of 482 participants who met the study requirements and were recruited from 19 hospitals and 23 community health centers between January 2023 to July 2023 were included in the study (
Fig. 1). Participants were randomly enrolled, with 241 participants each in the trial and control groups. The FAS and SS both included 480 participants, with 239 and 241 participants in the trial and control groups, respectively (2 were excluded for not taking the trial medication). The PPS comprised 470 participants, with 235 each in the trial and control groups (12 were excluded: 2 did not take the trial medication; 4 withdrew consent; 3 had a medication compliance rate < 80%; 2 took prohibited medication; and 1 had medication-related complication at enrollment). A total of 471 participants completed the trial, with 235 and 236 participants in the trial and control groups, respectively. There were 11 participants who did not complete the trial, including 6 in the trial group and 5 in the control group. Of the participants who did not complete the trial, 5 withdrew for lack of efficacy, 1 withdrew for concerns about liver function damage, and 5 withdrew for unknown reasons. When performing the statistical analysis, 2 participants were excluded from the FAS and SS, and 4 were excluded from the PPS.
3.2. Subject characteristics
According to the FAS analysis (
Table 1), there was no statistically significant difference in baseline participant characteristics (demographic characteristics, history of disease or surgery, history of COVID-19 infection, vital signs, medication use, laboratory tests, or other necessary characteristics) between the trial and control groups (
P > 0.05). Accordingly, baseline alignment was implemented in PPS. The principal baseline demographic characteristics, history of disease or surgery, history of COVID-19 infection, and medication use are presented in
Table 1.
3.3. Clinical outcomes
The analysis of efficacy indicators in the FAS and PPS yielded different outcomes but consistent conclusions. The following is based on the FAS as an example.
In terms of the primary efficacy indicator, participants in the trial group showed significant improvement in the time to cough disappearance within 14 days compared to those in the control group (11.98 vs 13.88 d,
P < 0.001;
Fig. 2(a)). The 14-day rate of cough disappearance was 32.37% (78 of 241 participants) in the control group and 54.81% (131 of 239 participants) in the trial group (
P < 0.001), with a hazard ratio of 0.45 (95% CI, 0.34-0.60). The Kaplan-Meier survival curve for the FAS is shown in
Fig. 2(b).
The study population was divided into different subgroups according to age (≤ 45 years, > 45 years), sex (male, female), time from diagnosis to randomization (≤ 35 d, > 35 d), and duration of cough (≤ 30 d, > 30 d;
Table 2). At the follow-up visit, the mean time to disappearance was significantly shorter in the trial group than in the control group, as indicated in
Table 2.
Table 2 shows a comparison of cough disappearance times among the different subgroups.
In terms of secondary efficacy indicators, the time to cough remission was significantly shorter in the trial group than in the control group (11 vs 13 d,
P < 0.001;
Fig. 2(c)). The 14-day remission rate of cough was 58.51% (141 of 241 participants) in the control group and 74.48% (178 of 239 participants) in the trial group (
P < 0.001), with a hazard ratio of 0.57 (95% CI, 0.46-0.71; the survival curve is shown in
Fig. 2(d)).
The clinical scores were used to further estimate the effect of Lianhua Qingke tablets on improving symptoms of long COVID cough. The changes in the total symptom score were significantly greater in the trial group than in the control group on days 7 and 14 (7 d: −5.33 vs −3.64,
P < 0.001; 14 d: −7.97 vs −6.81,
P < 0.001;
Fig. 3(a)), consistent with the results indicated by the VAS score (7 d: −29.00 vs −19.26,
P < 0.001; 14 d: −50.94 vs −39.70,
P < 0.001;
Fig. 3(b)) and CET score (7 d: −5.11 vs −3.76,
P < 0.001; 14 d: −8.37 vs −6.96,
P < 0.001;
Fig. 3(c)).
In the subsequent follow-up after the trial, participants who continued to report coughing at the end of the trial in both the FAS and PPS recorded the cough disappearance time after the trial (
Table 3). The median time to cough disappearance in the trial group was 11 days, with a mean time to disappearance of (16.15 ± 11.97) days; the median time to cough disappearance in the control group was 17 days, with a mean time to disappearance of (21.48 ± 14.19) days. The time to cough disappearance was significantly lower in the trial group than in the control group (
P < 0.001). Similarly, in the PPS, the time to cough disappearance was significantly lower in the trial group than in the control group (
P < 0.001). During the follow-up after the trial, the cough disappearance time of participants in both the FAS and PPS was accurately recorded. The number of people involved in this condition, the median time to cough disappearance, and the average time to cough disappearance are shown in
Table 3.
3.4. Safety
AEs occurred in 19 (7.88%) participants in the control group and 7 (2.93%) participants in the trial group during the treatment period. Of the 7 AEs in the trial group, 2 were associated with increased homocysteine, and the others were related to hyperuricemia, excessive urea, elevated uric acid, positive urine protein, anemia, hyperglycemia, impaired fasting blood glucose, liver function injury, hyperlipidemia, and the common cold. The incidence of AEs in the trial group was significantly lower than that in the control group (
P = 0.016). Among those who experienced AEs, there was no statistically significant difference between the two groups in the correlation between AEs and trial medication (
P = 0.679). No serious AEs (SAEs) were recorded during the study duration. None of the participants withdrew from the trial because of AEs. During the treatment period, there was no statistically significant difference in the incidence of AEs or SAEs associated with medication treatment between the two groups (
P > 0.05;
Table 4). The results of the AEs were analyzed based on whether an AE occurred, the severity of the AE, the correlation between the AEs and the trial medication, and the measures taken for the trial medication and the prognosis. The criteria for determining the relationship between AEs and medication treatment are described in Table S5 in Section S2.
Table 4 shows the comparison of the AEs rates.
4. Discussion
Despite resolving faster with less severe symptoms, the SARS-CoV-2 Omicron variant is associated with long-term symptoms, including increased rates of cough [
8]. Long COVID cough affects many people's lives on a large scale. Several medications may help patients with long COVID cough. Medications aimed at suppressing the cough reflex include antihistamines (levocetirizine dextromethorphan) [
9], centrally acting antitussive drugs/neuro-modulating drugs (gabapentin) [
10], leukotriene receptor antagonists (LTRAs; montelukast) [
11], purinergic receptor P2X3 antagonist (P2X3 antagonist; gefapixant) [
12], [
13], natural killer cell#-1 (NK#-1) receptor antagonist (aprepitant orvepitant) [
14], and inhaled steroids (glycopyrronium, formoterol, and budesonide) [
15]. Moreover, physiotherapy methods and modified pulmonary rehabilitation programs are examples of nonpharmacological therapeutic approaches that may help with symptom relief [
16]. To date, none of this evidence has clearly demonstrated a validated definitive association with long COVID cough, except for montelukast.
Moreover, anti-COVID-19 medications and TCM may interact with herbal drugs to enhance therapeutic results and minimize harmful effects [
17]. Our recent study confirmed that Lianhua Qingke tablets may be effective for treating symptomatic mild and common-type COVID-19, particularly for relieving cough [
7]. In this study, we further confirmed that Lianhua Qingke tablets improved the main clinical symptoms of long COVID-19 patients by shortening the cough disappearance and remission times and reducing the relative rate after a 14-day course of treatment. Moreover, clinical scoring systems associated with cough were used to evaluate the cough suppression effect of Lianhua Qingke tablets. The total symptom score, VAS score and CET score were also improved by Lianhua Qingke treatment on days 7 and 14. The main results of the subgroup analysis were consistent with those of the preliminary analysis. These clinical benefits persisted at follow-up visits at each stage, with no significant difference in AEs.
Mechanistic studies can help us better understand the clinical effect of Lianhua Qingke tablets. It has been reported that Lianhua Qingke tablets inhibit lipopolysaccharide (LPS)-induced neutrophil extracellular trap (NET) formation and pyroptosis, which significantly decreases lung injury and inflammation [
18]. Another study showed that Lianhua Qingke tablets had a protective effect against acute bronchitis in rats [
19]. In addition, some data suggest that the herbal ingredients of Lianhua Qingke tablets have anti-inflammatory and antiviral properties. The ingredients of Lianhua Qingke tablets include
Ephedra sinica Stapf,
Forsythia suspensa (Thunb.) Vahl,
Scutellaria baicalensis Georgi,
Morus Alba L.,
Prunus sibirica L.,
Peucedanum praeruptorum Dunn,
Pinellia ternate (Thunb.) Breit.,
Citrus reticulata Blanco,
Fritillaria thunbergii Miq.,
Arctium lappa L.,
Lonicera hypoglauca Miq.,
Rheum palmatum L.,
Platycodon grandiflorus (Jacq.) A. DC.,
Glycyrrhiza uralensis Fisch., and
Gypsum fibrosum. Among them,
Ephedra sinica Stapf,
Gypsum fibrosum,
Prunus sibirica L.,
Pinellia ternate (Thunb.) Breit.,
Citrus reticulata Blanco, and
Glycyrrhiza uralensis Fisch. are all considered high-frequency medications based on the law of medication prescription in Chinese medicine for COVID-19. For instance,
Ephedra sinica Stapf was confirmed to have anti-inflammatory effects on asthma [
20] and to have an enhanced inhibitory effect on proinflammatory factors, and it promotes hypothalamic homeostasis when combined with
Gypsum fibrosum [
21]. Licorice-saponin A3, a SARS-CoV-2 spike protein (S protein) receptor-binding domain (RBD) inhibitor, widely inhibits the RBD of SARS-CoV-2 variants [
22].
Ephedra sinica extracts effectively inhibit the interaction between angiotensin-converting enzyme 2 (ACE2) and the SARS-CoV-2 RBD [
23]. Ethanol extracts of
Lonicera hypoglauca Miq. can inhibit SARS-CoV-2 main protease (Mpro) activity and prevent virus entry [
24].
Fritillaria thunbergii Miq. is considered an immunomodulatory medication for treating influenza-related inflammation [
25]. In summary, Lianhua Qingke tablets may exhibit therapeutic effects on relieving cough in patients with long COVID-19, mainly through regulating the inflammatory response and viral infection. However, further mechanistic studies are needed to better understand the pharmacological properties of Lianhua Qingke tablets.
There are several limitations to this study. First, there are no objective or quantitative evaluation criteria for the safety and efficacy of Lianhua Qingke tablets. Only a few clinical trials have evaluated its clinical benefits. Its active ingredients and preliminary mode of action remain to be determined. Second, the participants were self-selected. Some participants may be more likely to report symptoms than others, demonstrating the limitations of self-reported symptom surveys. Third, whether the included patient population is representative of the typical long COVID cough patient population and the clinical heterogeneity of their disease needs to be further explored. Fourth, since all patients in this trial were Chinese, further assessment of this treatment in other populations is needed.
5. Conclusions
Lianhua Qingke treatment improved the clinical symptoms of patients with long COVID cough and was associated with good safety and tolerance. Developed based on the collateral disease theory, Lianhua Qingke tablets have important clinical value in the treatment of long COVID cough.
Acknowledgments
This work was supported by National Multidisciplinary Innovation Team Project of Traditional Chinese Medicine (ZYYCXTD-D-202201) and Beijing Key Specialized Department for Major Epidemic Prevention and Control (Construction Project; Jingweiyi [2019] 161). The funding sources had no involvement in study design, collection and analysis of data, writing of the report, or decision to submit the article for publication.
Compliance with ethics guidelines
Xiaolong Xu, Jie Ying, Taiping Tian, Tengwen Liu, Chunhua Chi, Zhizhong Gong, Jingpeng Gao, Meiping Qian, Wei Tan, Ran Cao, Shuixian Lv, Zhougui Ling, Shuo Wang, Bo Li, and Qingquan Liu declare that they have no conflict of interest or financial conflicts to disclose.
Data availability
The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.
Ethical approval
This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Committee of Beijing Hospital of Traditional Chinese Medicine Affiliated to Capital Medical University (2023BL02-018).
Informed consent
Written informed consent was obtained for each participant according to institutional guidelines.
Appendix A. Supplementary data
Supplementary data to this article can be found online at
https://doi.org/10.1016/j.eng.2024.03.013.
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