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. 2023 Mar 16;18(3):e0282688. doi: 10.1371/journal.pone.0282688

Co-administration of AYUSH 64 as an adjunct to standard of care in mild and moderate COVID-19: A randomized, controlled, multicentric clinical trial

Arvind Chopra 1,*, Girish Tillu 2, Kuldeep Chuadhary 3, Govind Reddy 4, Alok Srivastava 5, Muffazal Lakdawala 6, Dilip Gode 7, Himanshu Reddy 8, Sanjay Tamboli 9, Manjit Saluja 1, Sanjeev Sarmukaddam 1, Manohar Gundeti 3, Ashwini Kumar Raut 10, B C S Rao 11, Babita Yadav 11, Narayanam Srikanth 11, Bhushan Patwardhan 2
Editor: Shu-Hsing Cheng12
PMCID: PMC10019690  PMID: 36928877

Abstract

Objective

Evaluate the efficacy of AYUSH 64, a standard polyherbal Ayurvedic drug in COVID-19.

Methods

During the first pandemic wave, 140 consenting and eligible hospitalized adult participants with mild-moderate symptomatic disease (specific standard RT-PCR assay positive) were selected as per a convenience sample, and randomized (1:1 ratio) to an open-label (assessor blind) two-arm multicentric drug trial; standard of care (SOC as per Indian guidelines) versus AYUSH 64 combined with SOC (AYUSH plus). Participants were assessed daily and discharged once clinical recovery (CR, primary efficacy) was achieved which was based on a predetermined set of criteria (resolution of symptoms, normal peripheral oximetry, and negative specific RT-PCR assay). Each participant was followed using an indigenous software program(mobile phone) and completed a 12-week study period. The dose of AYUSH 64 was 2 tablets oral, 500 mg each, bid for 12 weeks (AYUSH plus only). Significant P was <0.05 (two-sided). On randomization, the groups were found well matched.

Results

The mean interval time from randomization to CR was significantly superior in the AYUSH plus group [mean 6.45 days versus 8.26 days, 95% Confidence Interval of the difference -3.02 to -0.59 (P = 0.003, Student’s ‘t test] as per-protocol analysis (134 participants); significant (P = 0.002) on an intention to treat analysis. 70% of the participants in AYUSH plus recovered during the first week (P = 0.046, Chi-square) and showed a significantly better change in physical health, fatigue, and quality of life measures. 48 adverse events, mostly mild and gut related, were reported by each group. There were 20 patient withdrawals (8 in AYUSH plus) but none due to an AE. There were no deaths. Daily assessment (hospitalization) and supervised drug intake ensured robust efficacy data. The open-label design was a concern (study outcome).

Conclusions

AYUSH 64 in combination with SOC hastened recovery, reduced hospitalization, and improved health in COVID-19. It was considered safe and well-tolerated. Further clinical validation (Phase III) is required.

Trial registration

CTRI/2020/06/025557.

Introduction

The world continues to reel under the tragic burden of the COVID-19 pandemic. The medical system was precariously overstretched and scarred. Several drug trials were completed and many more are underway to unravel evidence-based medicine (EBM) for more effective and safe management [1]. However, despite several advances, the treatment of mild and moderate COVID-19 predominantly remains symptomatic and empirical, and data from drug trials is sparse [13].

It is prudent to state upfront that most of the patients of COVID-19 suffered from asymptomatic or mild and moderate disease and recovered without any complication or sequel [4, 5]. Sometimes the disease was rapidly progressive, and less than 10% of subjects reported severe disease [46]. An exuberant and dysregulated immune response was central to the progression and severity, life-threatening complications, and fatality [6, 7]. Several drugs were repurposed and extensively used for the chemoprophylaxis and treatment of COVID-19 [8]. The widespread use of hydroxychloroquine (HCQS) during the early pandemic in India was grossly restricted when drug trials failed to show unequivocal efficacy [9]. HCQS is no longer recommended [2, 3]. Despite limited evidence but based on good clinical experience, some drugs such as tocilizumab and remdesivir are still being used [2, 10, 11]. The use of steroids in severe disease became pivotal following the result of a single large, controlled drug trial [12].

The search to repurpose drugs (COVID-19) also rekindled vigorous research in the traditional, complementary, and alternative systems of medicine (CAM) [13, 14]. The potential for prophylaxis and treatment of COVID-19 in the Ayurveda medicinal system was encouraged by the popular use of several standard herbal drugs to treat febrile respiratory disorders, improve health and immunity since ancient times and the growing modern experimental evidence of their potent anti-inflammatory and immune modulation effects [15, 16]. Several medicinal plants were considered as potential therapeutic candidates [14, 17, 18]. Despite the limited scientific evidence, a large number of Indian population used Ayurvedic and other CAM drugs to prevent and treat COVID-19 from beginning of the pandemic [19, 20]. The deep-rooted belief in the safety and tolerability of Ayurvedic drugs was certainly an advantage [21].

India has a legal system to regulate and promote plural systems of medicine including Ayurveda, Yoga, Naturopathy, Unani, Siddha, Sowa Rigpa, and Homoeopathy, which together are known as AYUSH systems. The Ministry of AYUSH established an Interdisciplinary AYUSH Research and Development Task Force on COVID-19 to promote scientific research and worked closely with the Ministry of Health and Family Welfare to manage and curb the pandemic [22, 23]. The Ministry of AYUSH and its research wing namely CCRAS (Central Council for Research in Ayurvedic Sciences) in collaboration with the Council of Scientific and Industrial Research (CSIR) also sponsored controlled drug trial studies in April 2020 to individually evaluate the therapeutic efficacy of 3 shortlisted Ayurvedic drugs as an adjunct to the standard of care (SOC) in the treatment of mild and moderate symptomatic COVID-19. Based on a common protocol, three drug trials were carried out at different sites with different investigators [24]. A controlled drug trial of AYUSH 64, a standard proprietary poly-herbal formulation of CCRAS, was amongst the latter studies.

The selection of AYUSH-64 was based on Ayurvedic logic and clinical experience. It was initially developed to treat malaria [25]. Later on, it was also found useful to treat cough and other mild respiratory tract infections and other disorders [18, 26]. Though readily available in AYUSH medical centers, its overall use remained limited. A comprehensive description of AYUSH 64 and other Indian medicinal plants with a therapeutic potential in COVID-19 was recently published [18].

The current report presents the results of the AYUSH-64 drug trial.

Methods

The protocol was approved by the following Institutional Ethics Committee at each study site:-

  1. Institutional Ethics Committee, Datta Meghe Institute of Medical Sciences, Nagpur (No. DMIMS(DU)/IEC/2020/8785)

  2. Institutional Ethics Committee, Central Ayurveda Research Institute, Mumbai (No. 01/20-21)

  3. Institutional Ethics Committee, King George’s Medical University, Lucknow (No. 469/Ethics/2020).

The study was a prospective, randomized, open label (assessor blind), parallel efficacy, two arm multicentric drug trial. The protocol was registered with the Clinical Trials Registry of India (CTRI) (registration number CTRI/2020/06/025557) [24]. The protocol is enclosed as a S2 File. The study duration for each participant was 12 weeks. The study was carried out in the Government approved facilities for COVID- 19 in the medical and teaching hospitals at King George Medical University, Lucknow, Central Ayurveda Research Institute for Cancer, Mumbai, and Datta Meghe Institute of Medical Sciences, Nagpur. The study was carried out in accordance with the principles of Good Clinical Practice (GCP), Declaration of Helsinki (Brazil update 2013), ICMR (Indian Council of Medical Research), and CCRAS Guidelines (2018) [27, 28] The protocol and the study report also complied with CONSORT guidelines (a checklist is enclosed as S1 File) [29]. An independent data safety management board (DSMB) and a monitoring committee were appointed by the sponsor. An independent accredited CRO (Clinical Research Organization) was engaged by the sponsor for study oversight and regular monitoring checks, on-site training of personnel, implementation of study protocol, creation of a central study database and preparation of a study report.

The overall scheme of the study, study procedures, and predetermined time points of evaluation are shown in Fig 1.

Fig 1. Study flow diagram showing study events and timelines.

Fig 1

Patient and public involvement

The patients were not involved in the preparation of the protocol or in carrying out study assessments and analyses. Numerous information bulletins on Ayurvedic remedies and research were posted by the Ministry of AYUSH from time to time [30].

Selection, screening and eligibility, enrollment and management

During the first pandemic wave, all cases of COVID-19 including mild and suspected cases were to be admitted in Government accredited hospitals (COVID-19) [3]. Patients could directly access the hospital. They were first triaged by the general duty medical officer in the emergency casualty department/outpatient. The diagnosis was confirmed by a standard real-time specific (SARS-CoV-2) reverse transcriptase polymerase chain reaction (RT-PCR) assay on a nasal and/or throat swab.

In the current study, the study investigators enrolled mild and moderate cases of COVID-19 which was classified as per Indian guidelines and clinical judgment [3]. Following hospital admission (study sites), the investigator explained the current study to those patients who expressed interest. Volunteer patients signed an informed consent form. The screening was completed within 48 hours of hospital admission as required by the protocol. Patients found eligible were quickly randomized.

Adult patients with a typical COVID-19 illness and a confirmed diagnosis were selected and after fulfilling the inclusion and exclusion criteria described in the protocol (enclosed, S2 File) were enrolled [24]. Patients with severe symptomatic COVID-19 were excluded if they satisfied any two of the following criteria (protocol) (i) respiratory distress at room ambiance (ii) Oxygen saturation (SpO2) at rest ≤ 93% (iii) known COVID-19 complication which may require oxygenation and/or critical care.

An Ayurvedic and a modern medicine physician in the study team supervised medical management on daily basis and along with nursing and paramedic personnel ensured drug compliance and reporting of all adverse events (AE). However, final decisions pertaining to the medical management of COVID-19 and recovery were taken by an independent hospital COVID-19 physician (blinded to treatment allocation). Patients and study personnel were aware of the specific study intervention allocation (open label).

Randomization

Patients were randomized at each site to either of the two arms of a standard of care (SOC) or AYUSH 64 administered along with SOC (AYUSH plus) in a 1:1 ratio on a first come first serve basis. A central randomization schedule was prepared by the study biostatistician (SS) using standard statistical software (WINPEPI version 4.61 for MS Windows). Permuted block randomization was used in a group of 20 participants (strata of size 20) to ensure a number balance. The randomization schedule was provided online with restricted access to the site principal investigator.

Standard of care (SOC)

SOC regimen was begun in-patient by an independent COVID-19 physician according to national and institutional recommendations [3]. However, the physician was permitted to use clinical judgement.

Investigational drug

Each 500 mg tablet of AYUSH 64 contained aqueous extracts (100 mg each) of Alstonia scholaris (bark), Picrorhiza kurroa (rhizome), Swertia chirata (whole plant), and Caesalpinia crista (200 mg seed powder). The dose was two tablets of 500 mg each and taken twice daily with a glass of water soon after a meal, and this dosage remained fixed throughout the study. Patients assigned to the AYUSH 64 plus arm continued the drug following clinical recovery till the completion of the study period (12 weeks). AYUSH 64 was procured from Indian Medicines Pharmaceutical Corporation Limited (IMPCL), Uttarakhand, India under arrangements with CCRAS, New Delhi. The manufacturing facility was a certified ISO 9001 facility (2008) and followed good manufacturing practices’ guidelines in the Ayurvedic Pharmacopoeia of India. Details of composition, quality standards, and features of chemistry, manufacturing, and controls are described in (Tables S3.1-S3.3, S3.1 Fig in S3 File).

Outcome measures

The primary efficacy measure was (i) the mean duration (days) from baseline randomization to day one of clinical recovery (CR) and (ii) the proportion of patients showing clinical recovery, within a time framework of 28 days. Clinical recovery was accepted when all of the following criteria were met for at least 48 hours under the observation of the hospital COVID-19 physician (a) normal body temperature (≤36.6°C axillae or ≤37.2°C oral) (b) absence of cough requiring regular medication (c)absence of breathlessness on routine daily self-care activities and respiratory rate less than 30 breaths per minute without supplemental oxygen (d) absence of any other symptom/sign attributed to COVID-19 illness and requiring continuous treatment (e) normal SpO2 by standard peripheral oximetry device (above 95 percent)(f) negative RT-PCR assay for SARS-CoV-2 from nasal and throat swab. The checklist of symptoms that were monitored daily for recovery was also guided by the WHO guideline [31].

There were several secondary efficacy measures pertaining to (i) timelines such as the mean duration from onset of symptoms to CR, mean duration from hospitalization to CR (ii) COVID-19-related blood assay biomarkers such as C-reactive protein (CRP), D-Dimer, Ferritin, interleukin-6. They are described in the enclosed protocol (S2 File).

Procedures and measures

The assessment of general physical and mental health, psychosocial health, and quality of life (QOL) were carried out by using the standard World Health Organization QOL BREF questionnaire and a recently developed Health-Related-Behavior Habit and Fitness Questionnaire (HR-BHF CRD, Pune 2020 version) [32, S4 File]. Both questionnaires were self-reported and administered in the local language. While the WHO QOL recorded the response on a 5-point Likert categorical scale, the HR-BHF used a horizontal visual analog scale (VAS, 0–100 mm). Both the scales were anchored at either end to show the worst response or the best response, e.g., in the WHO-QOL questionnaire, category 1 was ‘very poor’ and category 5 was ‘very good for certain questions. In the case of HR-BHF, a VAS score of 0 indicated the worst response and a score of 100 indicated the best response for certain questions; the ascending order of better response was reversed for few questions to facilitate understanding by the patient (such as in case of ‘anxiety’ a VAS score of 0 meant absence of anxiety and score 100 meant maximum anxiety), and this was adjusted in the final score. A comprehensive description and scoring method including pre-study validation is provided in the Text Box S4.2, Text Box S4.3 in S4 File.

The WHO QOL-BREF had 27 questions classified into 4 domains- physical health (7–35), psychological health (6–30), social relationships (3–15), and environmental well-being (8–40); the range of score is shown in parenthesis.

HR-BHF contained nine questions pertaining to general health, anxiety, fatigue, energy level, bowel habits, stress, happiness, sleep, and appetite (food). Individual question score (0–100) and the total score (0–900) was used for analysis in the current study.

Standard procedures were used to classify, monitor, record, and assign causality, in the case of an adverse event (AE, System organ classification, clinical grade of severity, preferred terms for recording signs, symptoms, and diagnosis). Guidelines published by ICH-GCP, ICMR (India), MedDRA, and WHO were also followed [28, 33, 34]. All randomized participants were assessed for safety and tolerability (AE).

Clinical evaluation included a routine physical and systemic examination. Both the clinical and laboratory evaluation was carried out several pre-determined study time points which included randomization baseline and study completion (Fig 2). Routine laboratory measures included hematocrit, metabolic hepatic and renal profile, and urinalysis and were carried out in laboratories at each study site that was a-priori endorsed by the ‘National Accreditation Board for Hospital and Health Care Providers’ (NABH). Further, these laboratories were necessarily approved by the Indian Council of Medical Research (ICMR) to carry out real-time RT-PCR assays for diagnosis of SARS-CoV-2 infection as per the existent Indian Government policy. Laboratories followed standard ICMR recommendations for reagents, equipment and procedure, and quality checks [35].

Fig 2. Patient disposition and withdrawals: A randomized controlled study to evaluate the co-administration of AYUSH-64 with Standard of Care (SOC) in–mild-moderate symptomatic COVID-19 (CONSORT flow diagram).

Fig 2

Electrocardiography was recorded during screening, hospital discharge, and on study completion.

Standard skiagram of chest was carried out during screening, on clinical recovery/ hospital discharge, and during any follow-up visits if clinically indicated. The radiological evaluation described in the S5 File pertained to 86 participants at two study sites that provided digital skiagrams of satisfactory quality according to an independent radiologist. Due to hospital priorities, participants at one site were only screened if they had persistent respiratory complaints using a mobile X-Ray unit, and skiagrams were not printed; 6 participants were reported with mild abnormalities and none had severe disease. The latter data were not included in this report. For the current radiographic analysis, all the available digital skiagrams were centrally reassessed by an independent radiologist who was blinded to the allocation of study treatment.

Data were collected on a daily basis during the hospitalization phase. Subsequently, after hospital discharge, it was collected during the predetermined follow-up schedule (4, 8, and 12 weeks) as shown in Fig 2. Participants were counseled to contact the study physicians at any time during the follow-up if they showed any fresh symptoms or worsened or suspected a drug-related side-effect. Patients were also provided with a specially designed software program for mobile application called ‘COVID KAVACH’ for daily monitoring during the follow up. The latter was used by the patient to record any AE or study-related problem which was electronically communicated to the site investigator and the study coordinator (AC) [36].

Data were recorded in the study case report forms at the point of care and later entered into a central electronic database using unique participant ID and study treatment code. The database was handled by pre-designated study team paramedics and locked after validation for any errors by the designated in-charge from CRO. Prior to the data analysis, a backup copy was provided to the sponsor by the CRO. Th database was unlocked and decoded by the study biostatisticians (SS, ST) prior to statistical analysis.

Study withdrawal

Patients worsening clinically and likely to require prolonged oxygen and/or intensive care were withdrawn from the study and transferred to intensive care for further management. All patients were comprehensively evaluated at the time of withdrawal. The site personnel continued to contact withdrawn patients for further disease progress and recovery and for the occurrence of any AE till such time the study was completed. The latter data were not included in the current report.

Statistical analysis

There was no prior data to use for the formal calculation of a sample size. However, we considered relevant clues for a probable medium effect size which recommended 64 participants per group (type-I error = 0.05, power = 80%, Table 2) and was published in a classic reference [37]. Finally, after discussion with the study group experts, the principal investigator and coordinator (AC) and the chief biostatistician (SS) finalized a convenience (non-probabilistic) sample of 140 participants. This was considered adequate to address the clinical research questions. Other factors like study logistics [mainly available time & resources including manpower] and restrictions imposed by the pandemic were also considered.

Table 2. Primary efficacy measure (Randomization to clinical recovery) and selected timeline in the two study groups (n = 134) in per protocol analysis; mean (days)± standard deviation.

Time line (days) Mumbai (n = 57) Nagpur (n = 29) Lucknow (n = 48) Total Study (n = 134)
AYUSH Plus (n = 28) SOC (n = 29) AYUSH Plus (n = 15) SOC (n = 14) AYUSH Plus (n = 23) SOC (n = 25) AYUSH Plus (n = 66) SOC (n = 68)
Randomization to Clinical Recovery (R-CR)
Mean ± SD (R-CR) 6.75± 2.14 8.45± 3.75 8.80± 1.01 11.21± 5.03 4.57± 1.56 6.40± 4.03 6.45± 2.35 8.26± 4.44
95% CI of Difference between Means (R-CR) -3.32 to -0.07 - 5.37 to 0.54 -3.61 to—0.06 - 3.02 to—0.59
On comparison of R-CR between two intervention groups at each study site and study cohort * P = 0.0410 (‘t’ test),0.077 (M-W) P = 0.079 (‘t’ test), 0.013 (M-W) P = 0.046 (‘t’ test),0.121 (M-W) P = 0.003 (‘t’ test), 0.015 (M-W)
Onset symptom to Clinical Recovery (S-CR)
Mean ± SD (S-CR) 15.29 ± 6.15 16.45±5.92 11.07± 1.58 14.50 ± 5.60 11.52 ± 3.26 13.48 ± 6.00 13.02 ± 4.87 14.96 ± 5.95
95% CI of Difference between Means (S-CR) -4.37 to 2.05 -6.76 to -0.11 -4.75 to 0.84 -3.79 to -0.08
On comparison of S-CR between two intervention groups at each study site and study cohort * P = 0.470 (‘t’ test), 0.592 (M-W) P = 0.031(‘t’ test), 0.016 (M-W) P = 0.172 (‘t’ test), 0.525 (M-W) P = 0.041(‘t’ test), 0.066 (M-W)

*Statistically significant (P<0.05)

NS Not statistically significant (P> = 0.05)

a. two independent samples ‘t’ test and M-W (Mann-Whitney statistic

b. Note, AYUSH plus: AYUSH 64 + Standard of Care (SOC); 134 patients qualified for primary efficacy analysis; Clinical recovery was essentially absence of COVID 19 symptoms for two successive days (with negative RT-PCR assay); See Text for detail

The study data was entered by the designated personnel at each study site into a central database and supervised by the CRO. Data were summarized using central tendencies (mean, median), range, standard deviation, and 95% confidence interval (95% CI).

Statistical tests were carried out to compare the two treatment groups as per the distribution (normality) and the type & level of measurement of the variable under consideration (like Student’s ‘t-test, Mann-Whitney non-parametric test, and Chi-square test) The result of statistical analysis was considered significant at P < 0.05 (two-sided). Both intent-to-treat (ITT) and per-protocol/completer (PP) analyses were performed for the primary efficacy analysis and some secondary measures. The ITT included all subjects who completed the randomized treatment observation till clinical recovery. The PP analysis included all subjects from the latter who were randomized within 48 hours of hospital admission and strictly adhered to other protocol requirements.

Participants completing the study intervention as per protocol were considered as qualified for the primary efficacy analysis using parametric (Student’s ‘t-test) and non-parametric tests (Mann-Whitney statistic). Categorical outcomes such as AE were compared using Chi-square statistic. The primary efficacy measure was also analysed for the total number of participants at each study site and in the study. Similarly, the two study groups were also compared for several secondary efficacy measures (timelines, laboratory assays, Quality of life measures) at several time points as per protocol.

A general mixed-effect linear regression model was also carried out with ‘study site’ as a random effect and ‘group intervention ‘ as a fixed effect for the primary efficacy measure. In the latter case, ‘Time from Randomization to Clinical Recovery’ (primary efficacy) was the dependent variable.

Standard statistical software programs were used (GraphPad InStat Version 3.6, BMDP, IBM SPSS Version 20, and Confidence Interval Analysis, BMJ Group, London, 2003). The study arm of ‘AYUSH 64 plus SOC’ is referred to as ‘AYUSH plus ‘ and ‘SOC alone’ is referred to as ‘SOC’ in the current paper.

Results

A total of 140 participants were randomized with 70 participants in each of the two study arms- AYUSH plus and SOC (Fig 2).

Withdrawals

Three participants were withdrawn during the randomization phase -one participant withdrew consent following randomization, one (AYUSH Plus) developed neuropathy (Guillain Barre syndrome) and one (SOC) developed severe pneumonia with respiratory distress. 137 patients completed the randomized treatment phase. A total of 20 (14.3%) participants withdrew (12 in the SOC group and 8 in the AYUSH Plus group) from the study. Seventeen patients did not wish to continue following complete recovery and hospital discharge. The latter did not report any AE during an informal follow up. None of the withdrawals were due to a drug related AE. There were no deaths in the study.

Randomization baseline

Both the study groups were well matched for several demographic, clinical, COVID related timelines, SOC drugs and laboratory variables as shown in Table 1. 80% participants were clinically classified as mild COVID-19 at the time of enrolment and were mostly men in the age range 30–55 years. Several had comorbid disorders- hypertension, known diabetes, or first-time hyperglycemia (fasting blood sugar > 120 mg/dl).

Table 1. Randomization baseline data on demographic, clinical, COVID related timelines, laboratory variables, and Standard of Care (SOC) drugs in the study groups.

VARIABLES AYUSH Plus (n = 69) SOC (n = 70) P-value*
Clinical
Age (years) Mean ± SD 42.87 ± 12.6 42.7 ± 12.0 0.93
Male–number (%) 54 (77.14%) 58 (82.85%) 0.52
Body Weight (kg) Mean ± SD 69.34 ±10.3 68.38 ±12.1 0.61
BMI (kg/m2) Mean ± SD 24.86 ±3.4 24.53 ±3.7 0.65
Symptom onset to randomization (days), mean ± SD 7.61 ±4.8 7.83 ± 4.5 0.51
Symptom onset to Hospitalization, mean ± SD 6.4 ± 4.64 6.5 ± 4.47 0.75
Hospitalization to Randomization, mean ± SD 1.4 ± 0.8 1.5 ± 0.9 0.55
Mild clinical disease number (%) 56 (80) 58 (82.9) 0.82
Moderate clinical disease number (%) 14 (20) 12 (17.1) 0.82
Hypertension number (%) 17 (24.29) 10 (14.29) 0.19
Diabetes mellitus-number (%) 14 (20) 06 (8.57) 0.09
Undiagnosed hyperglycemia-number (%) 9 (12.85) 14 (20) 0.36
Blood sugar level mg/dl, mean ± SD 112.50 ± 37.5 114.17 ± 35.2 0.74
ESR mm fall 1st hour, mean ± SD 50.2 ± 38.0 46.9 ± 37.4 0.79
Blood hemoglobin gm/dl, mean ± SD 13.6 ± 1.42 13.8 ±1.62 0.51
Total leucocyte count/cu mm, mean ± SD 5920.7 ± 2008 6828.3 ± 2085 0.02
Total Lymphocyte count/cu mm, mean ± SD 32.31 ± 9.1 31.07 ± 09.6 0.34
Symptoms at baseline-number of subjects (percent)
Fever 53 (75.71%) 45 (64.28%) 0.10
Sore throat 46 (65.71%) 53 (75.71%) 0.24
Cough 54 (77.14%) 54 (77.14%) 0.87
Dyspnea 24 (34.28%) 25 (35.71%) 0.90
Myalgia 48 (68.57%) 54 (77.14%) 0.31
Headache 37 (52.85%) 32 (45.71%) 0.35
Diarrhea 11 (15.71%) 12 (17.14%) 0.85
Ageusia 19 (27.14%) 19 (27.14%) 0.96
Anosmia 13 (18.57%) 14 (20%) 0.86
Drugs administered-number of subjects (percent)
Tab Azithromycin 48 (70%) 49 (70%) 0.95
Tab Doxycycline 1(2%) 0 0.31
Tab HCQS 29 (42%) 24(34%) 0.35
Tab Zinc 48(70%) 42(60%) 0.24
Tab Vitamin C 69 (100%) 69(99%) 0.32
Tab Vitamin D 3 15(22%) 18(26%) 0.58
Tab Pantoprazole 66(96%) 65(93%) 0.73
Tab Paracetamol 59 (86%) 55(79%) 0.28
Tab Cetirizine 13(19%) 15(21%) 0.70
Tab Ivermectin 3 (4%) 2 (2.9%) 0.99
Anti-coagulant 13(18.8%) 13(19%) 0.97
Oxygen intermittent (< 2 liters/min) 9(13%) 6 (9%) 0.39

*Statistically significant (P<0.05)

NS Not statistically significant (P> = 0.05)

a. Student’s ‘t test (normative data) or Chi-Square statistic (categorical data)

b. Note- n: number of study participants; SD: standard deviation; AYUSH plus: AYUSH 64 + SOC; BMI: body mass index; ESR: erythrocyte sedimentation rate (Wintrobe method); Other comorbid disorders: hyperlipidemia (2), cardiac disorder (1), chronic lung disease (2), thyroid disorder (5), Allergic rhinitis (3), number of participants in parenthesis; See text for details

There were no significant differences between the two study groups for COVID related timelines such as’ onset of symptom to hospital admission’ (-1.34 to 1.72),’ hospital admission to randomization’ (-0.17 to 0.39), and ‘symptom onset to randomization’ (-1.08 to 1.98); 95% CI of the difference (days) between means is shown in parenthesis (Table 1). Site-specific data for selected timelines and SOC drugs, including those related to RT-PCR assay, are shown in (Table S5.2 in S5 File).

A list of SOC drugs is shown in S5 File [R]. Most of the patients were treated with symptomatic drugs, vitamins and minerals. Several patients also received Hydroxychloroquine, or Ivermectin with Azithromycin (Table 1). At one site, anti-coagulants were empirically administered to patients with moderate COVID-19 and or with important risk factors (COVID-19). Except for one patient, none of the trial participants were treated with steroids. Parenteral Dexamethasone was administered to only one patient with progressive respiratory distress who was withdrawn from the study. Importantly, both the intervention study groups were well matched for the use of various drugs (Table 1).

62.8% of the participants showed radiographic abnormalities in the chest which were consistent with COVID-19 and classified as mild or moderate by the radiologist (See, Table S5.6 in S5 File).

Efficacy

134 participants qualified for the primary efficacy analysis and the results on per protocol analysis are shown in Table 2; three study participants were disqualified because of delay in randomization. The mean duration (days) for clinical recovery (primary efficacy) from the randomization baseline was significantly superior in the AYUSH plus (6.45, 95% CI 5.88 to 7.01 days) as compared to SOC (8.26, 95% CI 7.20 to 9.31 days); difference between means -1.81 (95% CI—3.02 to—0.59 days) (Table 2). Significant improvement was also observed at each of the study sites.

At this stage, we did not intend performing statistical analysis for predictor of response to treatment. However, the results of a general linear mixed effect model using the primary efficacy data as a dependent variable are shown in Table S5.4 in S5 File and indicate that the outcome remained significantly different between the two study groups even after controlling/removing the effect of ‘study site’.

In an intention to treat analysis (137 participants), the mean duration (days) for clinical recovery (primary efficacy) from the randomization baseline was significantly superior in the AYUSH plus (6.42, 95% CI 5.99 to 7.59) as compared to SOC (8.33, 95% CI 7.02 to 9.87 days); difference between means was -1.90 (95% CI—3.11 to—0.70 days) (Table S5.5 in S5 File). This improvement was also observed at each of the study site.

A higher proportion of patients in the AYUSH plus (69.75%) showed complete recovery as compared to SOC (52.9% patients) during the first week following randomization (P = 0.046, Chi-square statistic).

The earlier recovery in the AYUSH plus group was also observed for ‘time to clinical recovery from the onset of symptom’ and this was marginally significant as compared to SOC (Table 2).

There was a significant reduction in serum biomarkers of COVID-19 in each of the study groups but the difference between the groups was not significant (Table 3).

Table 3. Selected biomarkers related to COVID-19 in the two study groups (n = 139); mean (days) ± standard deviation.

Variable Study groups Baseline On discharge* Week 12*
Lactose dehydrogenase (LDH) AYUSH plus 403.6 ± 131.6 338.9 ± 109.7 318.7 ± 109.6
SOC 446.7 ± 206.5 363.8 ± 115.2 381.9 ± 164.8
LDH Reference Range: 225–480 U/L
Ferritin AYUSH plus 337.8 ± 280.3 257.7 ± 226.1 84.4 ± 70.2
SOC 337.4 ± 278 201.8 ± 206 92.5 ± 89.3
Ferritin Reference Range: Male 30–350 ng/ml; Female 20–250 ng/ml
Procalcitonin AYUSH plus 0.1 ± 0.1 0.1 ± 0.1 0.1 ± 0.2
SOC 0.1 ± 0.04 0.1 ± 0.2 0.1 ± 0.2
Prolactin Reference Range: <0.2 ng/ml
C-reactive protein AYUSH plus 20.83 ± 27.55 10.3 ± 19.1 6.3 ± 6.5
SOC 25.5 ± 35.3 10.7 ± 12.5 6.39 ± 8.98
C-Reactive Protein Reference Range <3 mg/L
D-Dimer AYUSH plus 462.5 ± 439.9 334 ± 224.9 297.3 ± 277.6
SOC 523.2 ± 672.8 345.3 ± 324.2 317.9 ± 418.4
D-Dimer Reference Range:0–400 ng/ml
Interleukin-6 AYUSH plus 30.6 ± 46.0 7.7 ± 12.2 8.5 ± 22.1
SOC 32.6 ± 42.2 8.5 ± 15.8 7.4 ± 10.3
Interleukin-6 Reference Range: Up to 7 pg/ml

*Statistically significant (P<0.05, Mann Whitney statistic) change from baseline within the study group for all variables except Pro-calcitonin

**NS Not statistically significant (P> = 0.05)

Note, Abbreviation: AYUSH plus: AYUSH 64 + Standard of Care (SOC); n = number of participants; See text for detail

Eight participants (18.6%) in the AYUSH plus and 13 participants (30.2%) in the SOC group showed radiological features of definite COVID-19 pneumonia at the time of randomization baseline (See Table S5.6 in S5 File). A higher number of participants (84.6%) in the SOC showed incomplete resolution as compared to AYUSH plus SOC (62.5%) at the time of clinical recovery (Table S5.6 in S5 File). None of the patients with COVID-19 radiographic abnormalities during the initial hospitalization complained of fever, persistent cough, or continuous breathlessness on follow up till completion of the study. There were no clinically suspected post-COVID lung complications and the skiagrams of several patients were reported normal.

In comparison to SOC, AYUSH Plus showed significant improvement in several domains (physical health, psychological health, social relationship, and environmental well-being) in the WHO QOL BREF and the total HR-BHF score at the time of clinical recovery and during follow-up (Table 4). It was notable that the AYUSH Plus also showed significant improvement in several individual item scores (fatigue, stress, anxiety, appetite, and happiness) in the HR-BHF questionnaire as compared to SOC (See Table S4.1 in S4 File).

Table 4. Quality of life questionnaires and health scores (HR-BHF and WHO QOL Bref) in the two study groups (n = 139).

Variable Baseline (n = 139) Discharge (n = 137) Week 4 (n = 129) Week 8 (n = 127) Week 12 (n = 120)
Health-Related- Behavior, Habit and Fitness (HR-BHF) questionnaire: combined score
AYUSH plus 500.1 ± 89.9 667.4 ± 85.7* 690.7 ± 111* 721.6 ± 105.5* 748.1 ± 114.5**
SOC 493.4 ± 81 637.5 ± 81.1 650.6 ± 100.6 677.7 ± 89.9 682.4 ± 90.9
WHO BREF Quality of life (QOL) Domain I (Physical health)
AYUSH plus 24.6 ± 4.1 28.8 ± 2.2* 28.9 ± 2.34 30.0 ± 2.15 30.2 ± 2.07
SOC 23.05 ± 4.42 27.8 ± 2.82 28.6 ± 2.7 29.3 ± 1.8 29.4 ± 2.1
WHO BREF Quality of life (QOL) Domain II (Psychological health)
AYUSH plus 20.81 ± 3.67 23.48 ± 2.28 24.2 ± 1.51 24.6 ± 1.70* 24.7 ± 1.88
SOC 20.1 ± 4.04 23.2 ± 2.29 23.4 ± 2.21 23.9 ± 1.57 24.1 ± 1.88
WHO BREF Quality of life (QOL) Domain III (Social health)
AYUSH plus 10.21 ± 2.03 11.34 ± 1.33 11.98 ± 1.02 12.05 ± 1.19* 12.30 ± 1.22**
SOC 10.26 ± 2.21 11.52 ± 1.29 11.74 ± 1.35 11.55 ± 1.48 11.62 ± 1.25
WHO BREF Quality of life (QOL) Domain IV (Environmental health)
AYUSH plus 27.27 ± 4.68 30.81 ± 2.30 31.74 ± 2.40 32.32 ± 2.73 32.22 ± 2.52*
SOC 26.66 ± 5.21 30.38 ± 2.45 30.90 ± 2.54 31.55 ± 2.06 31.43 ± 2.32

*Statistically significant (P<0.05, Mann Whitney statistic)

**Statistically highly significant (P<0.01, Man Whitney statistic)

NS Not statistically significant (P> = 0.05)

a HR-BHF total score and WHO BREF QOL domain score (physical, psychological social, and environmental health) were significantly better in AYUSH plus study group at several study time points

b. Note, See S4 File for methods and scoring of WHO QOL Bref and HR-BHF (Health Related-Behavior Health and Fitness) questionnaire; HR-BHF score range 0–900; WHO QOL Bref domain scores vary as shown in S 4 File but higher score generally meant better outcome; n: number of participants; AYUSH 64 plus: AYUSH 64 plus Standard of Care (SOC); See text for details

Safety and related issues

28 patients in the AYUSH Plus and 29 patients in the SOC group reported adverse events: there were no statistically significant differences (Table 5). Each of the study group reported 48 AE. Additional data on AE is shown in Table S6.1 in S6 File.

Table 5. Adverse events (AE) in the two study groups* (n = 139).

Adverse Events AYUSH plus (n = 69) OC (n = 70)
Participant Events Participant Events
Summary
Total 28 48 29 48
Mild 14 27 14 33
Moderate 12 19 13 14
Severe 2 2 2 2
Serious AE 1 1 2 2
Causality
Unrelated - 45 - 47
Unlikely - 03 - 2
AE is classified according to System Organ Classification and Preferred Term/Diagnosis (according to the investigator)
Cardiac 1 1 0 0
Transient hypertension 1 1 0 0
Ear and labyrinth 0 0 1 1
Ear ache 0 0 1 1
GIT 10 10 5 5
Gastritis 0 0 1 1
Dyspepsia 1 1 1 1
Diarrhea 4 4 1 1
Constipation 2 2 1 1
Epigastric pain 1 1 0 0
Vague pain 0 0 1 1
Hyperacidity 2 2 0 0
Hepatic 1 1 0 0
Transaminitis 1 1
Infections & infestations 5 6 6 9
Episodic Fever 5 5 2 2
Malaria 0 0 2 2
Cellulitis 0 0 1 1
Sore throat 1 1 3 4
Skin 2 2 1 1
Itch 1 1 0 0
Eczema 1 1 0 0
Non-specific 1 1
Respiratory 6 7 7 8
Cough 1 1 2 2
Episodic Breathlessness 5 6 4 5
Non-specific 0 0 1 1
Nervous system 3 3 0 0
Neuropathy 1 1 0 0
Vertigo 2 2 0 0
Renal 0 0 1 1
Dysuria 0 0 1 1
Endocrine 6 6 6 6
Hyperglycemia 6 6 6 6
Investigation (Laboratory) 0 0 1 1
Hyperlipidemia 0 0 1 1
Others 12 13 12 15
Weakness 2 2 5 6
Chills 0 0 1 1
Myalgia 5 6 6 8
Arthralgia 2 2 0 0
Headache 3 3 0 0

(1) Abbreviations: AYUSH Plus: AYUSH 64 plus Standard of Care (SOC); n: number of participants; GIT: gastrointestinal

(2) Clinical grading as per WHO classification

(3) Causality in the AYUSH plus pertained to AYUSH 64 drug while causality in the SOC arm was not specified to any particular drug

(4) Transaminitis: raised serum glutamic oxalacetate and or pyruvate

(5) No AE recorded for Disorders of blood and lymphatic, immune system, metabolism and nutrition, psychiatric, reproductive system and breast, eye, vascular system, congenital familial and genetic, injury poisoning and procedural complications, and surgical and medical procedures

(6)See Text and S6 File for further detail

AE were generally mild in nature and pertained to episodic fever, myalgias, fatigue, occasional breathlessness, loss of taste and/or smell and were mostly reported during the post-hospitalization follow-up. Several AE were possibly symptoms of COVID-19 rather than due to any study drug. A probable or definite causality of AE with AYUSH 64 could not be confirmed in any of the study participants. However, based on a-priori knowledge and experience of the Ayurvedic physicians in the study, some of the gut-related AE, albeit mild, which were present in the AYUSH plus may have been due to AYUSH 64 medication. Most of the time, AE did not require any specific treatment. Three participants reported serious AE and all recovered without any complications. Moderate AE was treated symptomatically. Those suspected of severe AE were referred to a specialist for an opinion. Participants with naïve hyperglycemia and/ or dyslipidemia were managed by a specialist physician.

Clinically, none of the AE was related to a drug interaction.

Repeated routine laboratory assays remained within normal limits in the two arms and there were no significant differences between the treatment arms Table S7.1 in S7 File. Electrocardiography of all participants was reported normal at baseline, hospital discharge, and on study completion.

Discussion

This randomized controlled multicentric study showed that a combination regimen of AYUSH 64, a standard Ayurveda drug, and SOC was significantly superior to SOC in the treatment of mild and moderate COVID-19. 140 eligible participants were randomized for study intervention and monitored under direct physician observation in an in-patient COVID hospital setting. The 95% confidence interval of the difference in the mean duration (days) of clinical recovery (a-priori definition) from randomization baseline was—3.02 to—0.59 days (Table 2) as per the protocol analysis and -3.11 to -0.71 as per the intention-to-treat analysis Table S5.5 in S5 File in favor of the AYUSH plus intervention. The latter was also shown at each study site. A significantly higher proportion of AYUSH plus participants (69.7% versus 51.7%) achieved clinical recovery within the first week after randomization. AYUSH Plus also showed substantial, and often significant, improvement in several secondary efficacy and quality of life measures (Tables 2, 4).

AYUSH 64 was well tolerated and found safe over 12 weeks of use in the dosage prescribed in the current study. There were no differences in the AE between the two study groups. AE were generally mild, and none caused the withdrawal of participants. Only 3 serious AE were reported (2 in SOC). 20 participants withdrew from the study and mostly after clinical recovery as per the personal preference not to continue in the study. There were no deaths in the study.

Though enrolled with mild and moderate COVID-19, several participants in the current trial also suffered from chronic co-morbid disorders (Table 1) that have been reported to be risk factors for severe, progressive, and fatal disease [24, 6, 7]. Several naïve participants showed hyperglycemia on enrolment (Table 1) which has been reported to complicate recovery [38]. One participant in the AYUSH Plus developed Guillain Barre Syndrome which has been uncommonly reported as a COVID-19 neurological complication [39]. Over 60% of participants showed radiographic abnormalities consistent with COVID-19. Following recovery, none of the participants complained of persistent respiratory symptoms or were diagnosed with pulmonary fibrosis during the prolonged follow up. It is prudent to add that the current study protocol did not recommend CT scan of the chest for the diagnosis of an asymptomatic pulmonary sequel. Respiratory disorders including pulmonary fibrosis, and which are often asymptomatic, have been reported as an important COVID-19 complication [40].

COVID-19 is a dreadful disease with a huge burden of psychosocial disorders [41]. A meta-analysis from India reported several psychological comorbidities ranging from 26% (anxiety and depression) to 40% (poor sleep quality) of study participants [42]. In the current study, WHO QOL Bref and HR-BHF questionnaires were used. The significantly superior improvement in both the physical (including fatigue) and mental health (such as reduction in anxiety, and stress) shown in the AYUSH Plus was clinically important and needs to be emphasized (Table S4.1 in S4 File). Several Ayurvedic medicines including the herbal ingredients of AYUSH 64 are reported to improve mental health [15, 17, 18, 20]. Several other QOL measures also showed a better improvement in the AYUSH Plus group (Table 4). In the passing, we wish to add that our study participants found it easier to answer visual analog scale-based questions in the HR-BHF questionnaire as compared to the somewhat cumbersome but popular WHO QOL BREF questionnaire (S4 File) [32].

More participants in the SOC arm showed definite radiographic pneumonitis (30% versus 19%) and failed resolution of radiographic abnormalities (85% versus 63%) at the time of clinical recovery/hospital discharge. One patient with mild radiographic disease in the SOC arm developed acute onset of progressive respiratory distress and required oxygenation and intensive care for recovery. All of this may suggest a more serious form of disease in the SOC arm, but this does not seem to be the case as shown by several other clinical variables, serum biomarkers, and overall clinical progress and response to standard of care treatment (Tables 1, 3 and S5 File). No uniform protocol was followed for radiological evaluation in the current study. Radiographic abnormalities often persist beyond clinical recovery and take a longer time for resolution, and often do not conform to the clinical severity of symptoms or disease [40]. Also, there is insufficient data on a prospective evaluation of radiographic abnormalities shown by conventional skiagrams in COVID-19 [40].

This study was exploratory in design and carried out during the first year of the pandemic. There were several concerns while the preparing the protocol. The pandemic and the stringent lock down imposed unique challenges for enrollment, physical and other examination, and monitoring of study participants. Our overall experience was consistent with that described recently in a report on drug trials in COVID-19 [43]. People were intensely scared and reluctant to participate. All treatment was mostly empirical and based on repurposed drugs [13]. There was no uniform protocol for standard care [3]. There were ethical issues with the use of placebo and blind study design.

Strengths and limitations

The study data was captured using a pragmatic protocol. Presuming a modest effect size, a sample size of 128 subjects was suggested [37]. However, as there was no prior data to guide the latter assumption (see section above on statistical analyses), a convenience sample of 140 participants was agreed by the study experts. The concern of a selection bias due to a convenience sample size and an open label design seemed to have been nicely addressed by the randomization process and the study drug administration under direct medical observation during the hospitalization phase. Encouragingly, the two intervention groups were found to be well matched for several variables at randomization baseline (Table 1). The daily diligent clinical observation in the hospital ensured good compliance to the study intervention and robust efficacy data. The latter was also crucial for capturing AE and any obvious drug interaction. The tolerability and safety profile of AYUSH 64 was good and reassuring.

The confirmation of ‘Clinical Recovery’ (CR) in the current study may seem to be unduly subjective but was based on a pre-determined set of stringent criteria which included clinical and investigation measures (normal peripheral oximetry and a negative standard RT-PCR assay). Importantly, 48 hours of observation was mandatory to declare the resolution of symptoms and the total assessment was performed in a blinded manner. To the best of our knowledge, we did not find use of a similar set of criteria in any other interventional drug trial in COVID-19 during a search for relevant literature in the current study [4446]. We did not measure ‘viral load’ as was performed in most of the drug trials [44]. The viral load may not correlate with symptoms in mild and moderate disease, and during recovery [45]. It is notable that none of the study participants reported any clinical post COVID complication and actually improved their general physical and mental health during the follow-up period (Table 4).

There were other limitations that may have influenced the study outcome. Enrolment of subjects with early illness was a complex issue as was observed in several other COVID drug trials [4345]. The delay was about a week from the onset of symptoms (Table 1 and S5 File). Investigations were not carried out in a central lab due to difficult logistics, but all study site laboratories were accredited (national standards) and compelled to strictly adhere to the guidelines on molecular testing for SARS-CoV-2 and quality control [35].

We were concerned about the surreptitious use of Ayurvedic drugs in the current drug trial. Ayurveda drugs and other popular traditional home remedies were extensively used in India during the pandemic and AYUSH 64 was available in the market [19, 20, 23]. None of the study participants admittedly used Ayurvedic drugs prior to hospital admission. It is unlikely that any medicine other than that permitted in the current study was taken by the participants during the in-patient treatment phase. Patients were counseled regarding medication by the study physician at the time of hospital discharge. Only the AYUSH plus participants were to continue AYUSH 64 drug till study completion. A special mobile software application (see methods) was used to maintain regular contact with the study participants. It is noteworthy, that several participants who continued AYUSH 64 showed better improvement in physical and mental health during the prolonged follow-up (Table 4).

The current study dealt with mild and moderate COVID-19 and no extrapolation of the outcome can be made to progressive and or severe disease. By the last quarter of 2020, the management of mild and moderate COVID-19 was rapidly shifted to a domiciliary or a quarantine facility in India [47]. Though the current trial participants were treated in a hospital setting (current study), it seemed fair to recommend the use of AYUSH 64 in a domiciliary or a quarantine setting under appropriate medical supervision [48].

Mechanism of action

The human host, and not the microbe, is the therapeutic focus in Ayurveda while treating infections. The primary objective is to strengthen immunity. Ayurvedic physicians use a holistic approach to treat and heal which includes assessment of the individual constitution (called Prakruti and Doshas in Ayurveda) and several lifestyle changes [15, 21]. The pharmacological and therapeutic properties and experimental evidence (non-clinical) of AYUSH 64 and its ingredient medicinal plant extracts were recently published [18]. Some of the purported therapeutic properties were antipyretic, anti-infective, anti-inflammatory, anti-allergic, and immunomodulatory (called Rasayana in Ayurveda) [18, 26, 49].

Several experimental studies (animal, cell culture, and in-vitro model) of individual plant extract ingredients of AYUSH 64 have provided a wide array of evidence to explain the reduction in inflammation and modulation of immune response (anti-oxidant effect, increased phagocytosis and altered inflammatory pathways- Nuclear Factor Kappa B, p 65), direct inhibition of pro-inflammatory biochemical mediators and cytokines (prostaglandins, tumour necrosis factor alfa, Interleukin (IL)-1 beta, IL-6, and IL- 8), and suppression of inflammatory and allergic response in airways (cellular and cytokines) [18, 26, 4953]. Interestingly, several inhibitory effects were also shown against viral protein R (HELA cells and plasmids) and some specific viruses (such as Herpes Simplex Type I, Coxsackie B2, Adenovirus, Poliovirus, and Chikungunya) [25, 5053]. In a more recent in-silico molecular docking study, several ingredients of AYUSH 64 (and especially Akuammicine N-Oxide from Alstonia scholaris) showed good binding with the main protease enzyme of the SARS-CoV-2 [54]. AYUSH 64 showed uncomplicated recovery with lesser requirement of symptomatic drugs and good safety when administered along with standard symptomatic treatment to 38 patients suffering from influenza-like illness in a prospective uncontrolled study of about one week duration [26].

Other selected studies

Several Ayurvedic drug trials in COVID-19 were registered during the pandemic and the results of few published studies were encouraging [55, 56]. A uniform wholesome Ayurvedic regimen showed a reduction in the viral load in asymptomatic and early COVID-19 patients in a randomized placebo-controlled drug trial study but did not provide sufficient clinical data [57].

A meta-analysis of 18 randomized controlled drug trials showed the clinical benefit of co-administration of Chinese Herbal Medicine (CHM) with conventional Western Medicine (WM) in treating COVID-19; two trials showed that CHM plus WM significantly reduced hospital stay (95% CI of the mean difference -3.28 to -0.70 days) [14]. There were several methodological differences between the latter and the current study but intriguingly, the outcome of a mean reduction in hospital stay was almost similar. Superior cure rates and amelioration of individual symptoms were reported in a more recent systematic review and meta-analysis of controlled drug trials which used a combination of CHM and WM in mild to moderate COVID-19 [58].

Of late, monoclonal antibodies (MAB) are at the forefront of treating COVID-19 although they are presently contraindicated in severe and progressive disease [59]. However, MAB are specific for a particular SARS-CoV-2 variant and are recommended for use in subjects with early disease and risk factors (COVID-19). However, several issues connected with cost and logistics are hurdles in their clinical use in the Indian context [45]. Oral drugs like AYUSH 64 hold a greater appeal.

Despite extensive clinical use during the pandemic, CAM therapies such as Ayurveda and Traditional Chinese medicine seemed under-reported. [14, 20, 58]. A recent report based on a large cross-sectional survey of in-patients treated for COVID-19 described the use of repurposed and adjuvant modern medicines but failed to make mention of herbal drugs or other CAM therapies [60].

Study implications and dissemination of results

In view of the lack of evidence for effective and safe drug therapy in COVID-19, several potential Ayurveda drugs and CAM were selected for repurpose and accelerated research and development [1, 2, 8, 9, 42]. Overall, the data from mild and moderate COVID-19 drug trials was sparse [4345]. The current drug- trial of AYUSH 64 ought to be viewed from this perspective. In our experience, the success of the current study provided a substantial boost to the ongoing research efforts in Ayurveda and CAM. We believe that it will also encourage an integrative medicinal approach to treating difficult diseases like COVID-19.

It is prudent to add that several medicinal plant ingredients of AYUSH 64 have been used to promote health and treat diverse medical disorders for several centuries by physicians and traditional healers in India, China, Southeast Asia, Europe, and North America [18, 26, 4951].

Study participants were informed about the current study results telephonically and/or through small virtual meetings by investigators and coordinators. A widely circulated Government press release in May 2021 announced the core study results and promoted the use of AYUSH 64 in COVID-19 [58]. A national education program was launched by the Ministry of AYUSH to disseminate information about AYUSH 64 and other drugs [61]. Along with the latter, a nationwide distribution campaign (AYUSH 64) was also launched [61]. Simultaneously, the Ministry of AYUSH launched an evidence-based management protocol for Ayurveda and Yoga for the management of COVID-19 which contained a reference to the current study [48].

Future research

AYUSH 64 ought to be further evaluated for the treatment of mild and moderate COVID-19, both as mono and a combination therapy (modern medicine), in a phase III drug trial. Studies should also evaluate the potential of AYUSH 64 to block progression of COVID-19 to severe disease and reduce post-COVID-19 complications. Experimental evidence is required to validate its anti-viral and other health benefits.

Conclusion

AYUSH 64 (a standardized polyherbal Ayurveda drug) was shown to be a significantly effective and safe adjunct in the treatment of mild and moderate COVID-19 in a prospective, randomized controlled drug trial. Open-label study design and other limitations necessitate judicious interpretation and extrapolation of the current study data and outcome. AYUSH 64 hastened clinical recovery, reduced hospitalization period, and showed early persistent health benefits with minimal/ absent drug-related side effects.

Supporting information

S1 File. CONSORT check list.

(DOC)

S2 File. Study protocol.

(DOCX)

S3 File. Composition, chemistry, manufacturing, and controls of AYUSH 64.

(DOCX)

S4 File. Health and quality of life questionnaires (WHO-QOL & HR-BHF).

(DOCX)

S5 File. Additional data–standard of care drugs, site specific drugs & timelines, general linear model output, intention to treat analysis, and radiological data.

(DOCX)

S6 File. Additional data- adverse events.

(DOCX)

S7 File. Additional data- laboratory results.

(DOCX)

S8 File. Selected raw data—efficacy, withdrawals, adverse events.

(DOCX)

Acknowledgments

A special thanks to Vaidya Dr. Rajesh Kotecha, Secretary, Ministry of AYUSH, Government of India, for his invaluable guidance and encouragement towards the current study project and preparation of study publication. We are grateful to senior Vaidya KS Dhiman, former DG CCRAS, GOI for the speedy completion of the drug trial. We thank several research colleagues in the CCRAS—Dr Ravindra Singh, Dr Shruti Khunduri, and Dr B S Sharma. We acknowledge with gratitude several colleagues from each trial site- Dr Manish Deshmukh, Dr Swati Munde, Dr Pratap Makhija, Dr Alia Rizvi, Prof Wahid Ali, Dr. Neeta Warty, Dr. Parth Dave and Mr Akash Saggam. We make a special mention of Dr Manesha Talekar, an Ayurvedic physician, who volunteered to be a co-investigator despite pregnancy and contracted COVID-19 during her medical duty. Dr Vinay Pawar played an important role in statistical analysis. Finally, we thank all the patients with folded hands for their participation and wholehearted support.

Data Availability

Several relevant data are within the manuscript and its Supporting Information files (S8F).All relevant data on primary efficacy, adverse events and withdrawals is available enclosed with the manuscript as a Supporting Information file (S8 File). The full data set is archived by the CCRAS, Government of India (http://www.ccras.nic.in), as an electronic data base and access will be provided after approval by Director General, CCRAS as explained below. Access to full data set will be available for any kind of non-commercial purpose and without any other restriction after approval by the sponsor (Director General, Central Council for Research in Ayurvedic Sciences/ CCRAS, Government of India) six months after publication. The latter will require a formal request from the applicant stating the reason for access and accompanied with a CV (applicant) and may be sent Email (crdp5624@gmail.com) to Arvind Chopra (first author) for further processing by CCRAS.

Funding Statement

The current study was sponsored by Central Council of Research in Ayurvedic Sciences (CCRAS), Ministry of AYUSH, Government of India. CCRAS authorized the study grant vide their Order Reference F.No.3-61/2020-CCRAS/Admn/IMR/458 dated 02 June 2020 (CCRAS website: http://www.ccras.nic.in). The grant was distributed and supervised by the authorized CCRAS officer to the 3 CCRAS run study sites. No individual was paid any part of the research grant. CCRAS selected the principal investigators from the study sites. The PIs selected the study site staff who were paid salary/compensation from the site grant as a-priori approved by the CCRAS. CCRAS also appointed a 'Contract research organization (CRO)' on contract payment to supervise and co-ordinate the trial as per the Government policy. CCRAS did not play any role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. AYUSH 64, the investigational product in this study, was a proprietary formulation of CCRAS and directly (central procurement) supplied to the study sites. None of the authors received any funding for participation in the current study project. Amongst the authors, KC, GR, AS, ML,DG,HR, MG, BCSR, BY, NS were Ayurvedic physician investigators and salaried employees of CCRAS run Government medical institutions. ST was paid by the CRO. AR and GT were Ayurvedic physician consultants and AR was paid a honorarium by the CCRAS. AC was a rheumatologist in practise and appointed as the Chief Clinical Coordinator of AYUSH CSIR Project (research drug trials in COVID-19). BP was the Chairman, Interdisciplinary AYUSH R & D Task Force on COVID-19 set up Ministry of AYUSH, Government of India. MS was a research coordinator and assisted AC. AC, MS and BP worked in a voluntary capacity and did not receive any remuneration from CCRAS.

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Decision Letter 0

Katrien Janin

Transfer Alert

This paper was transferred from another journal. As a result, its full editorial history (including decision letters, peer reviews and author responses) may not be present.

1 Jun 2022

PONE-D-21-24749

Coadministration of AYUSH 64 as an adjunct to Standard of Care in mild and moderate COVID-19: A randomised, controlled, multicentric clinical trial

PLOS ONE

Dear Dr. Chopra,

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Reviewer #1: Partly

Reviewer #2: Yes

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2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: I Don't Know

Reviewer #2: Yes

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Reviewer #1: No

Reviewer #2: Yes

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Reviewer #1: Yes

Reviewer #2: No

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5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The authors do not provide line numbers, so it is quite tedious to give specific edits. However, there are a good number of minor errors in English language usage throughout the manuscript. Given the standard to which the authors aspire, these should be corrected. There are verb tense issues in several places as well.

The authors do not provide raw data for evaluation. This seems indicated in what could be thought of as a somewhat contentious area.

The authors write "drugs such as hydroxychloroquine fell into disrepute". This is needless editorializing on a matter where there appears to be at least some good faith disagreement. There are certainly many western authors who would say the same about non-western systems of medicine, so it seems pointless to engage in such statements. It seems ironic that hydrochloroquine is then listed as part of standard of care later.

The authors write "It is now known that the exuberant and dysregulated immune response in COVID-19 leads to life threatening complications." Please provide citations and appropriately scope this statement with an estimate of the incidence of these in general populations.

The authors write "We used manually calculated raw scores (summation) for each domain". Why is "manually" stipulated here? Were computations performed by individuals and then entered into case report forms (CRFs)?

The authors write "A convenience study sample of 140 participants was finalized by AC and SS and considered

adequate to address the study research questions." This sounds quite ad hoc. What process was used to establish the convenience sample? What sampling biases were introduced by this process?

The statistical methods are described poorly, with a mix of jargon and software thrown together. Please describe the study endpoints and their analyses a little more clearly, perhaps grouping as seems fit to save tedious listing.

The actual structure of the analysis of variance (ANOVA) performed is unclear. Also, see below. The authors should provide a description that includes fixed effects, interaction terms, random effects (if any), and R-side correlation (if any). Linear model analysis must be accompanied by an assessment of model fit diagnostics, and corrective measures should be described in advance and described in the methods as necessary. All contrasts or estimates to be obtained should be described.

Generally, the analysis should be performed on both an intent-to-treat (ITT) and a per-protocol basis. The ITT analysis could be placed in a supplementary document.

Usual format for tables such as Table 1 are to footnote the p-values with the specific tests used.

Looking at Table 2 makes it clear that the data follow one of two structures:

* Fixed effect for treatment.

* Random effect for site.

* Potential random interaction of treatment and site.

* Repeated measures in cases where serial measurements are taken on a patient over time.

This structure can be handled easily within the linear mixed effects model framework. A consistent model should be used in all cases. If repeated measures are used, probably an unstructured correlation matrix will be most sensible and most flexible.

In Table 3 the authors use the footnote "*" to indicate "no difference"---the same footnote used before to indicate statistical significance. This is pointlessly confusing. Please use the standard approach that everyone else uses when reporting such results.

In Table 4 the authors note "(anchored with best and worst response)". What does this mean? This procedure is not described in the methods section.

Please modify Table 5 to industry norms.

The authors write "Despite serious concerns, the study arms were well matched on several measures including SOC." What are these concerns? Please demonstrate that these concerns are not an issue or please appropriately caveat the results of this trial.

The authors write "We believe that the current study has boldly addressed the need for evidence-based medicine to treat mild and moderate COVID-19." Doesn't this seem rather overblown?

The authors write "Several limitations were imposed by the chaotic and tragic pandemic situation. We encountered uncertainties and often contradictory advice regarding SOC and other COVID-19 related health

matters in the social and news media. During the first pandemic year, the patients were reluctant to seek medical care for fear of being stigmatized and this probably delayed the treatment for several patients as shown by the timelines in Table 1. Though, the primary efficacy was assessed by the attending physician in a blinded manner, a placebo response to some extent cannot be ruled out. Ayurveda is endearing to the Indian community. In view of absence of a-priori data, we settled for a convenience sample size for this study."

This further points up the need for a *very* clear description of how exactly this sample was selected. This is critical to the manuscript. Aside from that, this paragraph is overly dramatic and chatty. Everyone working in clinical trials had many, many issues during this time.

Please discuss the following potential limitations in much more detail:

* The study was open label and unblinded.

* The study sample was drawn as a "convenience sample".

Both of these issues have important implications for the interpretability of the results of the trial.

Reviewer #2: The reviewer’s comments on the article, ” Coadministration of AYUSH 64 as an adjunct to Standard of Care in mild and moderate COVID-19: A randomised, controlled, multicentric clinical trial” are as follows:

This is a multicentered clinical trial on AYUSH 64 as an adjunct to standard of care. The authors concluded that the AYUSH 64 group had shorter time to clinical recovery from randomization, higher proportion of recovery in the first week, and better performance in general health, quality of life, fatigue, anxiety, stress, sleep and other psychosocial metrics. In general, native-speaker English editing would be suggested since some sentences/words were difficult to understand. Besides, there were some points needed to explain in detail.

Abstract

In Results, please mention mean±95% CI days of 2 group.

Introduction

Reference 7 should be re-indexed. The authors may mention remdesivir, that is a commonly cited repurposing drug for COVID-19.

The authors may add some descriptions about the mechanisms that how AYUSH 64 works.

Methods

Is the sentence, “the duration of study was 12 weeks”, meant that for each participant, the treatment interval was 12 weeks? Please make the sentence clear.

Since AYUSH 64 is popularly used to treat acute onset febrile respiratory illnesses for over three decades in India, how did the authors prevent the participants to buy AYUSH 64 over the counter or on-line? In addition, how did the authors evaluate the compliance of both groups after discharge from hospitals?

Why and when did the study results be disseminated to the public through electronic social and print media, described in the section of subheading patient and public involvement?

In supplementary material, the protocol mentioned 3 regimen: i)AYUSH-64: 500 mg tablet, 2 tablets bid (twice daily) ii)Yashtimadhu: 300 mg tablet, 2 tablets bid (twice daily) iii)Sanshamani Vati Plus: Each tablet to contain 300 mg Guduchi plus 75 mg Pippali, 2 tablets bid (twice daily). Were the regimen ii, and iii used in this study?

Results

For CXR, moderate abnormalities in 2% patients in the AYUSH plus and 13% in the SOC were noted. Did the authors think patients in SOC had higher proportion of severe illness than those in AYUSH plus group?

On day 28, CXR showed mild abnormalities in 22% patients AYUSH plus and 21% patients SOC. Did the authors think that the residual abnormal CXR findings resolve later, after patients recovered clinically? Did the authors follow up the resolution of CXR findings?

In Table 2, * and ** deserved footnotes

In the subheading of adverse events in Table 5, the authors may change system organ classification to symptoms or diagnosis for clarification.

Discussions

The authors described “In our experience, despite sound medical advice, a large proportion of mild and moderate uncomplicated cases are admitted in the hospital and clog the system. AYUSH 64 plus SOC seemed to have significantly reduced the duration of hospitalization.” Please explain the government policy for admission and isolation of COVID-19 patients.

Since AYUSH 64 is popular in India and the study results was disseminated to the public through electronic social and print media, as per the authors’ description, could AYUSH 64 be so popular and could be bought over the counter? Did the authors consider the influence and deviation by SOC group who had taken AYUSH 64?

Did the authors consider that patients may take AYUSH 64 at home without admission in the future? For AYUSH 64 is popularly used to treat acute onset febrile respiratory illnesses for over three decades in India, why did the authors emphasize they need to be medically supervised?

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Reviewer #1: No

Reviewer #2: Yes: Shu-Hsing Cheng

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

PLoS One. 2023 Mar 16;18(3):e0282688. doi: 10.1371/journal.pone.0282688.r002

Author response to Decision Letter 0


19 Jul 2022

Reviewer #1:

1)The authors do not provide line numbers, so it is quite tedious to give specific edits. However, there are a good number of minor errors in English language usage throughout the manuscript. Given the standard to which the authors aspire, these should be corrected. There are verb tense issues in several places as well.

Response: The line numbers are now provided in the revision. The entire text is reviewed by a native English language person and errors in grammar etc corrected.

2) The authors do not provide raw data for evaluation. This seems indicated in what could be thought of as a somewhat contentious area.

Response: This is now provided as a supporting document and further description for access to data also mentioned in the section on ‘data availability’.

3)The authors write "drugs such as hydroxychloroquine fell into disrepute". This is needless editorializing on a matter where there appears to be at least some good faith disagreement. There are certainly many western authors who would say the same about non-western systems of medicine, so it seems pointless to engage in such statements. It seems ironic that hydrochloroquine is then listed as part of standard of care later.

Response: The point is well taken and the sentence modified to indicate that the widespread use of HCQS in the earlier part of the pandemic in India was grossly restricted when several drug trials did not shown unequivocal evidence. Since submission of this manuscript in mid 2021, the Government of India has removed HCQS from the ‘standard of care’ and the same is now reflected in the revision.

4) The authors write "It is now known that the exuberant and dysregulated immune response in COVID-19 leads to life threatening complications." Please provide citations and appropriately scope this statement with an estimate of the incidence of these in general populations.

Response: A citation is provided. There are no truly suitable prospective population studies to estimate the incidence of severe or life-threatening complications in the general population. However, we provide an estimate from hospital-based studies and a recent study published in PLOS ONE [: Grant MC, Geoghegan L, Arbyn M, Mohammed Z, McGuinness L, Clarke EL, et al. (2020) The prevalence of symptoms in 24,410 adults infected by the novel coronavirus (SARSCoV-2; COVID-19): A systematic review and meta-analysis of 148 studies from 9 countries. PLoS ONE 15(6): e0234765].

5) The authors write "We used manually calculated raw scores (summation) for each domain". Why is "manually" stipulated here? Were computations performed by individuals and then entered into case report forms (CRFs)?

Response: This was with reference to WHO Quality of Life Instrument- BREF. We followed the instructions contained in the WHO publication for calculating the domain and total score. Reference is provided in the main text. There were 27 questions belonging to 4 major domains. Each question was answered using a 5-point Likert response scale. Each of the 5 points of response (such as very poor, poor, neither poor nor good, good, and very good) were scored 1 to 5 - 1 was equivalent to very poor and 5 was equivalent to very good. The score for 3 questions reversed to follow the ascendancy order of the remaining questions so that higher scores meant better quality of life. A hard copy of the questionnaire was provided to each of the study subject for completion as per time points in the study protocol. The subject was asked to choose the likely response to each question and place a tick mark in the adjacent box showing the score of the response. The score of each question was added by the designated paramedic manually to calculate the score for each domain (manually calculated sum of raw scores in each domain); recorded in the questionnaire. The score for each domain and total for each participant was entered into the Excel based data sheet.

6)The authors write "A convenience study sample of 140 participants was finalized by AC and SS and considered adequate to address the study research questions." This sounds quite ad hoc. What process was used to establish the convenience sample? What sampling biases were introduced by this process?

Response: We have rewritten the section.

To find possible answers to address the study research questions and considering the logistics, a convenience study sample of 140 participants was felt to be adequate by AC (first author) and SS (Biostatistician co-author)”. This was also on the basis of available time & resources and relevant experience available then to carry out this trial. No formal estimation of required sample size for this study was attempted.

7) The statistical methods are described poorly, with a mix of jargon and software thrown together. Please describe the study endpoints and their analyses a little more clearly, perhaps grouping as seems fit to save tedious listing.

Response: Please see the answer above in question No 6 above

8)The actual structure of the analysis of variance (ANOVA) performed is unclear. Also, see below. The authors should provide a description that includes fixed effects, interaction terms, random effects (if any), and R-side correlation (if any). Linear model analysis must be accompanied by an assessment of model fit diagnostics, and corrective measures should be described in advance and described in the methods as necessary. All contrasts or estimates to be obtained should be described.

Response: The statistical analysis and results are revised and shown in Table 2 and the primary efficacy measure result was revised as per the original plan. Being a 2 arm study, we adhere to the Student’s ‘t- test for independent samples and Mann Whitney statistic. However, to respond to the ‘random effect’ of sites, we have performed a general linear (mixed effect ) model for the primary efficacy measure and enclosed the results (SPSS output) in the supplement file (S5 File).

9) Generally, the analysis should be performed on both an intent-to-treat (ITT) and a per-protocol basis. The ITT analysis could be placed in a supplementary document.

Response: The results of an ITT analysis on 137 participants who completed the randomization treatment phase are enclosed in the supplement file (S5 File)

10) Usual format for tables such as Table 1 are to footnote the p-values with the specific tests used.

Response: The format for Tables and foot notes is revised.

11)Looking at Table 2 makes it clear that the data follow one of two structures:

* Fixed effect for treatment.

* Random effect for site.

* Potential random interaction of treatment and site.

* Repeated measures in cases where serial measurements are taken on a patient over time.

This structure can be handled easily within the linear mixed effects model framework. A consistent model should be used in all cases. If repeated measures are used, probably an unstructured correlation matrix will be most sensible and most flexible.

Response: Please see the answer to Question No 8. We have enclosed the results of a general linear (mixed effects) model.

12) In Table 3 the authors use the footnote "*" to indicate "no difference"---the same footnote used before to indicate statistical significance. This is pointlessly confusing. Please use the standard approach that everyone else uses when reporting such results.

Response: The Tables and foot notes have been revised to ensure uniform method of reporting data and in particular the ‘footnote’

13) In Table 4 the authors note "(anchored with best and worst response)". What does this mean? This procedure is not described in the methods section.

Response: The error is regretted. This pertains to a visual analogue scale and a a elaborate description is provided on the scoring technique of the two health and quality of life questionnaires used in the ‘methods section’. Table 4 and S4 File is modified accordingly.

14) Please modify Table 5 to industry norms.

Response: The suggestion is now incorporated and Table 5 is revised to show the AE are now classified as per symptom, sign and diagnosis along with the System organ classification .

15) The authors write "Despite serious concerns, the study arms were well matched on several measures including SOC." What are these concerns? Please demonstrate that these concerns are not an issue or please appropriately caveat the results of this trial.

Response: The word ‘serious’ was a wrong choice of word, and we acknowledge the error. It should be ‘important concerns. Accordingly, the text has been now been modified. There were several important a-priori concerns for the current drug trial study such as challenges of a drug trial during the upsurge of pandemic, fear and reluctance of COVID patients to participate, delay in the diagnosis and enrolment, different standards of care (COVID-19) at study sites, open label nature of AYUSH 64 intervention and placebo response, bias in the assessment of clinical recovery, and surreptitious use of AYUSH 64 and other Ayurvedic drugs. Several concerns were adequately addressed by the diligence of the study team, randomization procedure and treatment under direct observation (hospitalization phase). The study arms were well matched (Table 1). It seemed prudent to emphasize that hospitalization in the current study was responsible for good compliance and capture of robust data. The latter also made it possible to carry out a daily physical assessment of study participants by a competent COVID-19 physician to identify and endorse clinical recovery in a timely and systematic manner. Intense monitoring was also crucial to document the safety and tolerability of AYUSH 64. Importantly there were no clinically obvious drug interactions with the modern drugs. 16) The authors write "We believe that the current study has boldly addressed the need for evidence-based medicine to treat mild and moderate COVID-19." Doesn't this seem rather overblown?

Response: Yes. In hind sight the statement could be interpreted as an exaggeration. The statement is modified and reads ‘We believe that the current study has been able to provide some degree of evidence based medicine for the treatment mild and moderate COVID-19 (non emergency) using an integrative approach with an Ayurvedic drug (AYUSH 64) combined with standard modern medicine care’.

17) The authors write "Several limitations were imposed by the chaotic and tragic pandemic situation. We encountered uncertainties and often contradictory advice regarding SOC and other COVID-19 related health matters in the social and news media. During the first pandemic year, the patients were reluctant to seek medical care for fear of being stigmatized and this probably delayed the treatment for several patients as shown by the timelines in Table 1. Though, the primary efficacy was assessed by the attending physician in a blinded manner, a placebo response to some extent cannot be ruled out. Ayurveda is endearing to the Indian community. In view of absence of a-priori data, we settled for a convenience sample size for this study." This further points up the need for a *very* clear description of how exactly this sample was selected. This is critical to the manuscript. Aside from that, this paragraph is overly dramatic and chatty. Everyone working in clinical trials had many, many issues during this time.

Response: We readily agree with the comment and incorporate the suggestion in the discussion . However, the issue at stake is complex and we have tried to express that in brief. Though it may be general knowledge , it may be appropriate to submit to the reader how challenging and complex drug trials were during the pandemic. The latter was more so during the initial six months or so during which time the current study was launched. It is prudent to add that some issues connected with drug trials were more regional than global. We believe that it is appropriate to state ‘ "Several limitations were imposed by the pandemic situation. We encountered uncertainties and often contradictory advice regarding SOC and other COVID-19 related health matters in the social and news media. During the first pandemic year, the patients were reluctant to seek medical care for fear of being stigmatized and this probably delayed the treatment for several patients as shown by the timelines in Table 1.’ We have further provided an informative reference from a recent PLOS ONE publication [: Chen Z, Chen L, Chen H (2021) The impact of COVID-19 on the clinical trial. PLoS ONE 16(5): e0251410]

With reference to the second half of the paragraph regarding physician centric issues and selection of participants, we acknowledge the need to elaborate the subject of selection of trial participants in the methods section. We first briefly introduce the then Government policy on treatment of COVID-19 which was followed. A new elaborate section on ‘Selection, Screening and Eligibility, and Management’ is now added under the methods section.

A description of the ‘convenience sample size’ used in the current study is provided above under Question number 6 above. This is also clarified under the statistical design and analysis section of the manuscript.

18) Please discuss the following potential limitations in much more detail:

* The study was open label and unblinded.

* The study sample was drawn as a "convenience sample".

Both of these issues have important implications for the interpretability of the results of the trial.

Response: Agreed. Both the limitations were mentioned in the discussion section and are now modified for better clarity. The subject of sample size is also mentioned above in Question serial number 6 above.

Reviewer #2: The reviewer’s comments on the article, ” Coadministration of AYUSH 64 as an adjunct to Standard of Care in mild and moderate COVID-19: A randomised, controlled, multicentric clinical trial” are as follows:

1) This is a multi-cantered clinical trial on AYUSH 64 as an adjunct to standard of care. The authors concluded that the AYUSH 64 group had shorter time to clinical recovery from randomization, higher proportion of recovery in the first week, and better performance in general health, quality of life, fatigue, anxiety, stress, sleep and other psychosocial metrics.

Response: This was the essence of the current study. It was a randomized controlled study. There were limitations too which were mostly related to convenience sample size and non-blinding nature intervention and several difficulties imposed by the COVID-19 pandemic on patient logistics and monitoring. All said and done, we believe that the outcome in favour of the Ayurvedic medicine AYUSH 64 to treat mild and moderate cases of COVID-19 along with standard care is encouraging. There is now community based observational data to support its standalone use also in such uncomplicated COVID-19 situations.

2) In general, native-speaker English editing would be suggested since some sentences/words were difficult to understand. Besides, there were some points needed to explain in detail.

Response: The point is well taken. We have corrected the manuscript with expert professional help for several grammatical and other errors and this is visible in the marked revision copy. Further, the sections on introduction, patient selection, trial procedures, and statistical design and analysis have been described in greater detail. Information on Remdesivir and other anti-COVID 19 drugs is also revised. Also, the discussion has been modified accordingly.

3)Abstract

In Results, please mention mean±95% CI days of 2 group.

Response: We had incorporate the suggestion in the abstract.

4) Introduction

Reference 7 should be re-indexed. The authors may mention remdesivir, that is a commonly cited repurposing drug for COVID-19.

Response: yes. A reference has been added

5) The authors may add some descriptions about the mechanisms that how AYUSH 64 works.

Response: A brief description about the likely mechanism of action of AYUSH 64 is added in the discussion .

AYUSH 64 was not a classic Ayurveda formulation but contains medicinal plants described in classic texts and used by Ayurveda practitioners for several centuries in the Indian subcontinent. These medicinal plants were considered therapeutically useful to treat fever, pain and inflammation of varying aetiology and several medical disorders that include cough and breathing disorders and asthma. Several experimental studies, both in vitro and animal, have demonstrated some antiviral (herpes simplex, adenovirus and Chikungunya virus), anti-inflammatory and beneficial immunological effects of the medicinal plants in AYUSH 64. In a more recent in-silico molecular docking study, several ingredients of AYUSH 64 (and Akuammicine N-Oxide from Alstonia scholaris in particular) were found to bind well with the main protease enzyme of the SARS-CoV-2 and may well be an important mechanism of action. An uncontrolled exploratory clinical study of 38 patients suffering from influenza like illness and treated with AYUSH 64 for one week along with standard care showed no safety concerns and uncomplicated recovery and probably a lesser need of paracetamol and anti-allergic drugs.

6) Methods

Is the sentence, “the duration of study was 12 weeks”, meant that for each participant, the treatment interval was 12 weeks? Please make the sentence clear.

Response: Thanks for this important observation. Each individual participant completed 12 weeks of study period and we have clarified the same in the text under methods.

7) Since AYUSH 64 is popularly used to treat acute onset febrile respiratory illnesses for over three decades in India, how did the authors prevent the participants to buy AYUSH 64 over the counter or on-line?

Response: This is an important comment and we have provided an elaborate description under the ‘strengths and limitations’ section of the discussion.

We were aware of a possibility of confounding by unauthorized use of drugs to treat COVID-19 by the study participants. All patients were counselled in detail prior to enrolment. A strict vigil and close monitoring during hospitalization phase was ensured by a study dedicated staff as per protocol. Following discharge, a close contact was kept with study participants using a special mobile phone app (see study methods) and telephonic reminders. However, it was difficult to vouch for total avoidance of other Ayurvedic drugs and or AYUSH 64 by study participants especially prior to enrolment or after discharge.

It is prudent to add that as per the Government policy in vogue then, all study participants were admitted in Government run COVID dedicated hospitals for treatment irrespective of the severity of the illness. The latter ensured a strict direct observation of the study participants and compliance with all methods and procedures. Both the intervention groups were well matched for several variables at randomization baseline though our recorded did not show any prior Ayurvedic drug use. The study intervention was unblinded. It is unlikely that any drug other than that prescribed by the current study was used during in-patient treatment. Following discharge, patients were followed till week 12 completion and examined monthly. During the latter phase, patients from the AYUSH 64 plus standard care arm continued AYUSH 64 but not the patients from previous standard arm care.

Ayurvedic drugs and Ashwagandha (Withania somnifera) and Guduchi (Tinospora cordifolia) in particular were used extensively both for prophylaxis and treatment of COVID-19 by the India population. Ayurvedic drugs were available over the counter and did not require a prescription. To begin with, AYUSH 64 was a lesser-known drug for use in COVID-19 in the earlier phase of the pandemic but in time was included in the Ayurveda drug promotional campaign by Government agencies. The current drug trial was begun on 18 June 20 and completed on 25 Oct 20.

We have also described the measures taken by us to safeguard the study.

Several measures were taken to safeguard against a surreptitious use of Ayurvedic drugs in the current study. Participants with a history of prior use of Ayurvedic drugs or any CAM were excluded. As mentioned above, the treatment during hospitalization was directly observed. A strict vigil was maintained by the nursing and paramedical staff who also recorded the consumption of AYUSH 64 as per protocol. Participants were closely monitored and examined during the follow up phase. A special mobile app was used for daily monitoring (see methods section above). Participants were repeatedly counselled against self-treatment. We believe that the surreptitious use of Ayurvedic medicines, if at all, was negligible in the current study and that the unauthorized use of AYUSH 64 was unlikely. On the other hand, the better health related outcome observed in the AYUSH Plus group during the pre-planned follow was indeed encouraging (Table 4).

8)In addition, how did the authors evaluate the compliance of both groups after discharge from hospitals?

Response: Patients randomized to AYUSH 64 plus standard care arm continued AYUSH 64 to complete 12 weeks of administration as per protocol. AYUSH 64 was provided free of cost to each patient and consumption monitored. Patients from the controlled arm of standard care continued non-specific treatment with drugs such as vitamins as per physician judgement and were not prescribed AYUSH 64. Patients were examined monthly and for long COVID symptoms and quality of life issues. In addition, patients were closely monitored using telephonic reminders and a specially designed mobile phone app (see methods). Some of the measures are described in the answer to Question No.7 above

9)Why and when did the study results be disseminated to the public through electronic social and print media, described in the section of subheading patient and public involvement?

Response: We have incorporated the excellent suggestion.A press release was issued by CCRAS, Ministry of AYUSH, Government of India, in May 2021 after completion of the current study. This was followed by a press meeting with selected leading news media to announce important results of the current study by the first author and other co-authors and experts . The management guidelines of COVID-19 issued by CCRAS from time to time were also updated with the key study results on the efficacy and safety of AYUSH 64. Simultaneously, all the principle investigators informed the outcome of the current study to each participant telephonically and those desirous were called for a meeting with the study physician.

10) In supplementary material, the protocol mentioned 3 regimen: i)AYUSH-64: 500 mg tablet, 2 tablets bid (twice daily) ii)Yashtimadhu: 300 mg tablet, 2 tablets bid (twice daily) iii)Sanshamani Vati Plus: Each tablet to contain 300 mg Guduchi plus 75 mg Pippali, 2 tablets bid (twice daily). Were the regimen ii, and iii used in this study?

Response: We regret this confusion caused by the lack of clarity in the beginning of the ‘methods section’. We have now modified the introduction section to describe the initiative of AYUSH CCRAS Government of India under which three potential Ayurvedic drugs including AYUSH 64 were selected for independent randomized controlled drug trial studies using a different study team and study sites. However, there was a common protocol for methods which was registered in the Clinical Trial Registry of India and is enclosed as supplementary file (S2 File). All this is further clarified in the beginning of the ‘methods section’.

Here we only report the drug trial of AYUSH-64.

To complete the answer, the other two drug trial studies were also completed in 2021 but the results are still under review with the sponsor.

11) Results- For CXR, moderate abnormalities in 2% patients in the AYUSH plus and 13% in the SOC were noted. Did the authors think patients in SOC had higher proportion of severe illness than those in AYUSH plus group? On day 28, CXR showed mild abnormalities in 22% patients AYUSH plus and 21% patients SOC. Did the authors think that the residual abnormal CXR findings resolve later, after patients recovered clinically? Did the authors follow up the resolution of CXR findings?

Response: We first regret the error in the data caused by lack of stringent review of the earlier radiographic data that was extracted from the case record forms and was not properly recorded in all cases. Also we found post submission, that no XRays were printed in one site and only the screening results were recorded. We thank you for the excellent comment and we now incorporate a more elaborate analysis and description.

Soon after submission, we completed a reassessment of the radiographic evaluation in the current study by a newly appointed independent radiologist. We have now revised the relevant sections pertaining to radiographic assessment.

At the outset, we concede that (i) Chest X-Rays were carried out only for diagnosis of atypical COVID-19 pneumonia and to ensure that there was no worsening on hospital discharge (ii) no standard protocol or scoring system was followed (iii) following discharge, X-Rays were only taken if the patient had a relapse of respiratory symptoms (iv) High resolution computed tomography scan was not taken as a routine or used to confirm resolution and absence of any complication such as pulmonary fibrosis (v) uncomplicated radiographic pneumonitis was labelled as moderate COVID-19 by the radiologist (vi) Digital X-Rays were taken at two sites (Mumbai and Nagpur) only and which are now used for detail analysis and inclusion in the current revised manuscript.

All digital X-Rays (90) were blinded for treatment allocation for the analysis report in the revision.

The revision contained the corrected results shown in S5 File (Supplement file).

In specific response to the Reviewer’s query, we agree that the radiographic severity (definite pneumonitis) of COVID-19 seems to be somewhat more in the standard care group though it may not be of clinical significance. Also, there were other caveat that we explain. We also agree with the reviewer’s observation that radiographic resolutions may take much longer than clinical recovery and we have included a citation from a research study. In hindsight, we should have followed participants with abnormal X-Rays during hospitalization with repeated radiological evaluation to document radiographic resolution, but we were discouraged by small numbers of participants with abnormal X-Ray on discharge and logistics and study budget. Both the groups were well balanced and patients were closely monitored during randomization treatment and during follow up. Only in one case, there was rapid clinical and radiologic deterioration of respiratory status warranting ICU care and oxygen administration and withdrawal from the study-the patient made complete recovery and belonged to standard care intervention arm in the study..

As regards a more serious nature of illness in the SOC group we submit the following statement in the discussion section. But also add that in view of the limitations, the reader needs to exercise caution while interpreting the radiographic results

More participants in the SOC arm showed definite radiographic pneumonitis (30% versus 19%) and also a higher proportion of failure of resolution (85% versus 63%) at the time of clinical recovery/hospital discharge; one patient with mild radiographic disease in SOC rapidly developed rapidly progressive respiratory distress and required oxygenation and intensive care for recovery. All this may suggest a more serious disease in the SOC arm but this does not seem to have been the case as shown by several other clinical variables, serum biomarkers and overall standard of care drugs used and the treatment response in the current study (Table 1. Table 3, and S5 File). However, it is important to concede that neither a uniform standard protocol nor CT scan imaging was used to evaluate chest skiagrams and/or resolution and thus any interpretation of the current findings of resolution may be premature and requires utmost caution. Radiographic abnormalities may persist beyond clinical recovery and take a longer time for complete resolution [38]. Also, there is insufficient data on prospective evaluation of conventional radiography in COVID-19 [38].

12) In Table 2, * and ** deserved footnotes

Response: Table 2 has been revised, also in view of comments of Reviewer 1.

13) In the subheading of adverse events in Table 5, the authors may change system organ classification to symptoms or diagnosis for clarification.

Response: Earlier we used the WHO organ classification system. The AE are not mentioned as symptoms or diagnosis

14)Discussions- The authors described “In our experience, despite sound medical advice, a large proportion of mild and moderate uncomplicated cases are admitted in the hospital and clog the system. AYUSH 64 plus SOC seemed to have significantly reduced the duration of hospitalization.” Please explain the government policy for admission and isolation of COVID-19 patients.

Response: We have revised our statement. Firstly, all COVID-19 cases were admitted in the hospital during the early pandemic as per the recommendations of the Government. This policy was quickly revised as the burden was overwhelming and mild and moderate cases were to monitored in a domiciliary setting or quarantine facility.. However, in the current study, all patients were admitted as per Government recommendations for COVID-19 but seemed to have improved the quality of clinical monitoring and capture of robust data. The results of the current study show that addition of AYUSH hastened clinical recovery and reduced the hospital period. Mild and moderate COVID-19 does not require hospitalization unless there are risk factors and/or likelihood of disease progression or complications. In the study we only treated mild and moderate cases of COVID-19 and the observations of the current study cannot be extrapolated to severe and complicated cases.

15) Discussion-Since AYUSH 64 is popular in India and the study results was disseminated to the public through electronic social and print media, as per the authors’ description, could AYUSH 64 be so popular and could be bought over the counter? Did the authors consider the influence and deviation by SOC group who had taken AYUSH 64?

Did the authors consider that patients may take AYUSH 64 at home without admission in the future? For AYUSH 64 is popularly used to treat acute onset febrile respiratory illnesses for over three decades in India, why did the authors emphasize they need to be medically supervised?

Response: The above comment is well taken and accordingly the current revision contains appropriate clarifications and references on the subject. Please refer to the response described in Question serial 6 , 7 and 9 which also addresses a large part of this question. Undoubtedly, Ayurvedic drugs including AYUSH 64 were available across-the-counter without any restrictions. None of the participant patients stated having taken Ayurvedic drug prior to hospital admission but this cannot be vouched for veracity. Patients may have taken drugs from their general practitioner without knowledge of the name or nature (drug) as is often the practise in India. Any effect of AYUSH 64 or Ayurvedic drugs taken prior to admission hopefully will be balanced in the two study treatment arms by randomization. Post discharge, the arm with continued AYUSH 64 did better than the arm without AYUSH 64 in several measures of quality of life and did not differ for long COVID-19 or any other COVID related complication. It is difficult to exclude with certainty the effect of a surreptitious use of Ayurvedic drug or AYUSH 64 by some participants in the post-discharge follow up phase but this would not be of relevance to at least the primary efficacy measure. Compliance during the study is discussed in response to Question number 8.

Attachment

Submitted filename: Response to Editor_Referee.docx

Decision Letter 1

Shu-Hsing Cheng

1 Sep 2022

PONE-D-21-24749R1Coadministration of AYUSH 64 as an adjunct to Standard of Care in mild and moderate COVID-19: A randomized, controlled, multicentric clinical trialPLOS ONE

Dear Dr. Chopra

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

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Guest Editor

PLOS ONE

Journal Requirements:

Additional Editor Comments:

I will suggest major revision according to 2 reviewers’ comments. Especially, strength and limitation should focus on the methods and data interpretation.

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: (No Response)

Reviewer #3: All comments have been addressed

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2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: (No Response)

Reviewer #3: Yes

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3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: (No Response)

Reviewer #3: Yes

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4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: (No Response)

Reviewer #3: Yes

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5. Is the manuscript presented in an intelligible fashion and written in standard English?

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Reviewer #1: (No Response)

Reviewer #3: No

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6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: In general, most issues have been dealt with in the response. The manuscript is improved. The following are less important issues:

There still are many minor issues with English language usage throughout the manuscript. These are not critical, but do detract from the presentation.

Lines 163-164 seem quite odd. Perhaps these are not correctly expressing the authors' desired meaning?

The statistical methods section is somewhat improved with regard to content. However, the English language usage requires a lot of rewriting.

It appears that the authors ran both a fixed effects model (with treatment and site as fixed effects) and a linear mixed effects model (with treatment as a fixed effect and site as a random effect). Is this correct? If so, why? The mixed effects model is arguably better if the authors wish to generalize to "all sites" --- assuming these sites can be thought of as a representative sample if "all sites". The fixed effects model is appropriate if the authors wish to restrict their inference to "only the sites studied".

For tabulation, please footnote "not significant" results with "NS" and not with "*". Use the following scheme:

* Statistically significant (p < 0.05)

NS Not statistically significant (p >= 0.05)

a Other footnote that does not relate to statistical significance

b Other footnote that does not relate to statistical significance

etc.

Table 2 requires some reformatting for readability, in particular the rows with the p-values. I was not able to 100% reproduce the values in the table with the raw data --- perhaps there are some data exclusions that are relevant? However, the results are fairly close.

The last column of Table 2 is incorrect. This should show the result of a model that incorporates site as a random variable. A simple t-test is incorrect for the entire data set.

Please see the following code which reproduces part of Table 2 as well as demonstrating how to perform the linear mixed effects analysis using the R programming language.

# Load packages.

library(tidyverse)

library(broom)

library(lme4)

library(car)

# Read data and set data conventions.

S8 <- read_csv("S8_Raw.csv")

names(S8) <- c("PatientID", "Group", "Age", "Gender", "Site", "RtoCR", "SOtoCR")

S8 <- S8 %>%

mutate(Site = str_c("Site ", Site))

#-------------------------------------------------------------------------------

# Perform brief evaluation of time from randomization to complete recovery.

# Plot the data.

S8 %>%

ggplot(aes(x = Group, y = RtoCR)) +

geom_boxplot() +

facet_grid( ~ Site)

S8 %>%

ggplot(aes(x = Group, y = RtoCR)) +

geom_boxplot() +

facet_grid( ~ Site) +

scale_y_log10()

S8 %>% ggplot(aes(x = Age, y = RtoCR, col = Group)) +

geom_point() +

facet_grid(~ Site)

S8 %>% ggplot(aes(x = Gender, y = RtoCR, col = Group)) +

geom_boxplot() +

facet_grid(~ Site)

S8 %>% ggplot(aes(x = SOtoCR, y = RtoCR, col = Group)) +

geom_point() +

facet_grid(~ Site)

# Perform t-tests within each site.

Stats <- S8 %>%

group_by(Site) %>%

nest() %>%

mutate(

fit = map(data, ~t.test(.x$RtoCR ~ .x$Group)),

tidy = map(fit, tidy)

) %>%

unnest(tidy)

Stats

# Perform linear mixed effect analysis with site as a random effect.

fit <- lmer(RtoCR ~ Group + (1 | Site), data = S8)

#fit <- lmer(log(RtoCR) ~ Group + (1 | Site), data = S8)

plot(fit)

Anova(fit, test = "F")

# NOTE Arguably slightly better fit on logarithmic scale with no change in

# conclusion. It is easiest to interpret on the original scale.

#-------------------------------------------------------------------------------

# Perform brief evaluation of time from symptom onset to complete recovery.

# Plot the data.

S8 %>%

ggplot(aes(x = Group, y = SOtoCR)) +

geom_boxplot() +

facet_grid( ~ Site)

S8 %>%

ggplot(aes(x = Group, y = SOtoCR)) +

geom_boxplot() +

facet_grid( ~ Site) +

scale_y_log10()

S8 %>% ggplot(aes(x = Age, y = SOtoCR, col = Group)) +

geom_point() +

facet_grid(~ Site)

S8 %>% ggplot(aes(x = Gender, y = SOtoCR, col = Group)) +

geom_boxplot() +

facet_grid(~ Site)

# Perform t-tests within each site.

Stats <- S8 %>%

group_by(Site) %>%

nest() %>%

mutate(

fit = map(data, ~t.test(.x$SOtoCR ~ .x$Group)),

tidy = map(fit, tidy)

) %>%

unnest(tidy)

Stats

# Perform linear mixed effect analysis with site as a random effect.

fit <- lmer(SOtoCR ~ Group + (1 | Site), data = S8)

fit <- lmer(log(SOtoCR) ~ Group + (1 | Site), data = S8)

plot(fit)

Anova(fit, test = "F")

# NOTE Better fit on logarithmic scale but again with no change in overall

# conclusion. It is easiest to interpret on the original scale.

Reviewer #3: This manuscript described coadministration of AYUSH 64 as an adjunct to Standard of Care in mild and moderate COVID-19 in India: A randomized, controlled, multicentric clinical trial.

The study explored the efficacy of AYUSH 64, a standard polyherbal Ayurvedic drug in mild and moderate COVID-19. The result presents AYUSH 64 in combination with SOC hastened recovery, reduced hospitalization, and improved health in COVID-19. It was considerably safe and well-tolerated.

In general, this is a fair-written manuscript. Other points in this manuscript needed to be clarified are listed below:

Major revisions:

1. In Method, line 145 and 220: open label study is one of selection bias in your study, and your primary endpoint and secondary points are subjective, not scientific or medical specific term. How did you measure RT-PCR of SARS CoV-2? Roche Cobas? What is the definition of negative? Did every center use the same machine? or central lab was provided? If not, you might have information bias in analyzing outcome.

2. Standard of care, line 202: there are several listed medications in supplement file, and dexamethasone was proved effective treatment in COVID-19, except remdesvir. Could you provide the proportion of dexamethasone used in two arms? I think the data would impact the outcome.

3. In Discussion, strength and limitation, line 566: A convenience study sample of 140 participants was felt to be adequate by AC (first author) and SS (Biostatistician co-author)”, and no formal estimation of required sample size for this study was attempted. I think that the authors might write in paragraph of limitations of conclusion, because sampling bias or selection bias is possible. Moreover, the authors sould list some bias in terms of limitations, not to describe the chaos situation when the study was conducted during the pandemic.

Minor revisions:

1. Discussion, line 470: completer analysis should be corrected as per protocol analysis.

2. Reference 50 and 52, line 925 and 935: volume and page are missed.

**********

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Reviewer #1: No

Reviewer #3: Yes: CHIEN-YU CHENG

**********

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Attachment

Submitted filename: comments of AYUSH 64 in COVID-19.docx

PLoS One. 2023 Mar 16;18(3):e0282688. doi: 10.1371/journal.pone.0282688.r004

Author response to Decision Letter 1


4 Oct 2022

PONE-D-21-24749R1

Coadministration of AYUSH 64 as an adjunct to Standard of Care in mild and moderate COVID-19: A randomized, controlled, multicentric clinical trial

PLOS ONE

Response to Author/Referee Comments on the First Revision dated 02 Sept 2022.

Please Note: The author response is shown below each comment as provided by the journal editor.

Comments to the Author and Response

I) General:

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: (No Response)

Reviewer #3: All comments have been addressed

Author: No comment

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: (No Response)

Reviewer #3: Yes

Author: No comment

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: (No Response)

Reviewer #3: Yes

Author: No comment

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: (No Response)

Reviewer #3: Yes

Author : Further data has been added to address the comment on the efficacy analysis (below)

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: (No Response)

Reviewer #3: No

Author: The revision was suitably edited by professional in English language. However, we note (see below) that there are still ‘minor issues with English language usage throughout the manuscript’ according to Reviewer 1. The current revision has been edited by a new professional in English language.

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Author: we are grateful to the author and the referees for their comments to improve the manuscript

II) Reviewer #1: In general, most issues have been dealt with in the response. The manuscript is improved.

The following are less important issues:

1)There still are many minor issues with English language usage throughout the manuscript. These are not critical but do detract from the presentation.

Author: This revision has been checked by a new professional in English language use.

2)Lines 163-164 seem quite odd. Perhaps these are not correctly expressing the authors' desired meaning?

Author: Deleted

3)The statistical methods section is somewhat improved with regard to content. However, the English language usage requires a lot of rewriting.

Author: This has been again checked and revised by the study Biostatistician. We followed the a-priori statistical plan as per protocol. However, some additional analysis was performed in response to the excellent suggestion of the referee.

4) It appears that the authors ran both a fixed effects model (with treatment and site as fixed effects) and a linear mixed effects model (with treatment as a fixed effect and site as a random effect). Is this correct? If so, why? The mixed effects model is arguably better if the authors wish to generalize to "all sites" --- assuming these sites can be thought of as a representative sample if "all sites". The fixed effects model is appropriate if the authors wish to restrict their inference to "only the sites studied".

Author: (a) The data on the primary efficacy measure ‘time from randomization to clinical recovery’ in the study between the two study groups was analysed using Students’ t test and MW statistic and the results are shown in Table 2.

(b) We further performed a linear mixed effect model (treatment as fixed effect and site as random) as recommended by the referee the results were consistent with our earlier primary efficacy analysis. This is mentioned in the text and the detail model output is shown in Supplementary 5 File (Table S5.4).

5)For tabulation, please footnote "not significant" results with "NS" and not with "*". Use the following scheme:

* Statistically significant (p < 0.05)

NS Not statistically significant (p >= 0.05)

a Other footnote that does not relate to statistical significance

b Other footnote that does not relate to statistical significance

etc.

Author: We have used this scheme for the Tables and we thank the referee

6) Table 2 requires some reformatting for readability, in particular the rows with the p-values.

Author: This has been done.

7)I was not able to 100% reproduce the values in the table with the raw data --- perhaps there are some data exclusions that are relevant? However, the results are fairly close.

Author: Please note that the raw data of 136 subjects in the earlier supplement pertained to per protocol analysis. Now we have provided the data of 140 subjects out of which 137 qualify for ITT analysis (3 withdrawn prematurely and did not provide data on clinical recovery).

We have reanalysed both per protocol and ITT analysis using the raw data provided in the supplement. Overall there are no variations from the earlier results..

8) The last column of Table 2 is incorrect. This should show the result of a model that incorporates site as a random variable. A simple t-test is incorrect for the entire data set.

Author: As per protocol, we first carried out a standard head-to-head comparison of the two study intervention groups using Students T test and MW statistic and wish to retain this as the primary efficacy measure analysis . However, we carried out a liner mixed effect model to exclude the effect of study site on primary outcome as suggested by the referee and include the result in the text.

9)Please see the following code which reproduces part of Table 2 as well as demonstrating how to perform the linear mixed effects analysis using the R programming language.

# Load packages.

library(tidyverse)

library(broom)

library(lme4)

library(car)

# Read data and set data conventions.

S8 <- read_csv("S8_Raw.csv")

names(S8) <- c("PatientID", "Group", "Age", "Gender", "Site", "RtoCR", "SOtoCR")

S8 <- S8 %>%

mutate(Site = str_c("Site ", Site))

#-------------------------------------------------------------------------------

# Perform brief evaluation of time from randomization to complete recovery.

# Plot the data.

S8 %>%

ggplot(aes(x = Group, y = RtoCR)) +

geom_boxplot() +

facet_grid( ~ Site)

S8 %>%

ggplot(aes(x = Group, y = RtoCR)) +

geom_boxplot() +

facet_grid( ~ Site) +

scale_y_log10()

S8 %>% ggplot(aes(x = Age, y = RtoCR, col = Group)) +

geom_point() +

facet_grid(~ Site)

S8 %>% ggplot(aes(x = Gender, y = RtoCR, col = Group)) +

geom_boxplot() +

facet_grid(~ Site)

S8 %>% ggplot(aes(x = SOtoCR, y = RtoCR, col = Group)) +

geom_point() +

facet_grid(~ Site)

# Perform t-tests within each site.

Stats <- S8 %>%

group_by(Site) %>%

nest() %>%

mutate(

fit = map(data, ~t.test(.x$RtoCR ~ .x$Group)),

tidy = map(fit, tidy)

) %>%

unnest(tidy)

Stats

# Perform linear mixed effect analysis with site as a random effect.

fit <- lmer(RtoCR ~ Group + (1 | Site), data = S8)

#fit <- lmer(log(RtoCR) ~ Group + (1 | Site), data = S8)

plot(fit)

Anova(fit, test = "F")

# NOTE Arguably slightly better fit on logarithmic scale with no change in

# conclusion. It is easiest to interpret on the original scale.

#-------------------------------------------------------------------------------

# Perform brief evaluation of time from symptom onset to complete recovery.

# Plot the data.

S8 %>%

ggplot(aes(x = Group, y = SOtoCR)) +

geom_boxplot() +

facet_grid( ~ Site)

S8 %>%

ggplot(aes(x = Group, y = SOtoCR)) +

geom_boxplot() +

facet_grid( ~ Site) +

scale_y_log10()

S8 %>% ggplot(aes(x = Age, y = SOtoCR, col = Group)) +

geom_point() +

facet_grid(~ Site)

S8 %>% ggplot(aes(x = Gender, y = SOtoCR, col = Group)) +

geom_boxplot() +

facet_grid(~ Site)

# Perform t-tests within each site.

Stats <- S8 %>%

group_by(Site) %>%

nest() %>%

mutate(

fit = map(data, ~t.test(.x$SOtoCR ~ .x$Group)),

tidy = map(fit, tidy)

) %>%

unnest(tidy)

Stats

# Perform linear mixed effect analysis with site as a random effect.

fit <- lmer(SOtoCR ~ Group + (1 | Site), data = S8)

fit <- lmer(log(SOtoCR) ~ Group + (1 | Site), data = S8)

plot(fit)

Anova(fit, test = "F")

# NOTE Better fit on logarithmic scale but again with no change in overall

# conclusion. It is easiest to interpret on the original scale.

Author: We thank the Referee for his very considerate suggestion and providing the code for R programming. We have no experience with R. We have used standard statistical programs mentioned in the text and hope that the same will be accepted.

III) Reviewer #3: This manuscript described coadministration of AYUSH 64 as an adjunct to Standard of Care in mild and moderate COVID-19 in India: A randomized, controlled, multicentric clinical trial.

The study explored the efficacy of AYUSH 64, a standard polyherbal Ayurvedic drug in mild and moderate COVID-19. The result presents AYUSH 64 in combination with SOC hastened recovery, reduced hospitalization, and improved health in COVID-19. It was considerably safe and well-tolerated. In general, this is a fair-written manuscript. Other points in this manuscript needed to be clarified are listed below:

Author: We thank the referee.

Major revisions:

1). (a) In Method, line 145 and 220: open label study is one of selection bias in your study, and (b) your primary endpoint and secondary points are subjective, not scientific or medical specific term.(c) How did you measure RT-PCR of SARS CoV-2? Roche Cobas? What is the definition of negative? Did every center use the same machine? or central lab was provided? If not, you might have information bias in analyzing outcome.

Author:

(a) Agreed and we have included the possibility of a selection bias due to the open label nature of the study and convenience sample in the study limitation. We have further explained the good match for several variables at randomization baseline. Also, the inpatients were directly observed for drug administration, monitoring of symptoms and oximetry, clinical recovery and adverse events by a dedicated study team. The primary efficacy outcome was assessed blindly by a dedicated independent COVID physician.

(b) We agree that the primary and secondary end points are dependent upon the clinical response elicited from the patient and prone to inaccuracy and bias. But in our case, there was no single criteria but a set of criteria to determine ‘clinical recovery’ (CR) within a time frame of 28 days. CR was a combination of resolution of symptoms and normal peripheral oximetry for 48 hours and a negative RT-PCR assay. We wish to add that the concept of CR in clinical drug trials for COVID-19 was still evolving when we designed this study in May-June 2020. Interestingly, there continues to be paucity of data on the clinical and microbial efficacy endpoints and what constitutes CR in controlled drug trial studies of mild to moderate COVID-19 in published literature. Most of the studies have used ‘viral load’ as the primary efficacy as a surrogate marker of clinical improvement. The WHO index of severity of 7 symptoms to indicate improvement at some fixed time points between 7-14 days after intervention were often used as secondary efficacy measure. There is no universally accepted definition of clinical recovery in mild to moderate COVID-19. Some studies have used clinical end points of hospitalization, morbidity or mortality. In this regard, our primary efficacy measure was unique. It was more wholesome, pragmatic and reasonable and based on our early clinical experience with mild moderate cases of COVID 19. It should be noted that we applied the criteria in hospitalized patients where the clinical monitoring was daily, direct and in real time. There may be more subjectivity in a domiciliary setting or when clinical data was obtained telephonically or through digital platform. It is prudent to add, that only one patient in the study progressed to severe stage. Also, during the follow up of 12 weeks after clinical recovery, there were no clinical concerns of any important COVID sequel. However, encouraged by the referee comment, we have included a brief note on this pivotal issue in discussion section.

(c) None of the labs at study sites used Roche Cobas and we did not use a central lab.

This was a Government of India sponsored study carried out at Government approved medical facilities. It was mandatory for the labs to follow the instructions issues by Indian Council of Medical Research (ICMR) for the specific SARS-CoV-2 RT-PCR assay

[Ref: (i) https://www.icmr.gov.in/ctestlab.html

(ii) Advisory_for_Reagents_TestingLabs_v1.pdf (icmr.gov.in)

(iii) Microsoft Word - SARS_CoV2_using_TaqPath_COVID19_ComboKit (icmr.gov.in) ].

All kits, reagents and equipment was to conform to the recommendations of ICMR. Since then, we have confirmed that the labs at each of the three study sites followed ICMR guidelines of quality control and standard testing but procured reagents and equipment from different manufacturers. Each of the site lab followed the manufacturer guidelines for reporting the results of the RT-PCR assay. A negative RT-PCR was reported usually after a run of 28-30 cycles.

However, we admit that some information bias is likely in reporting outcome based on RT-PCR assay in the current study and this is now included in the manuscript.

2). Standard of care, line 202: there are several listed medications in supplement file, and dexamethasone was proved effective treatment in COVID-19, except remdesvir. Could you provide the proportion of dexamethasone used in two arms? I think the data would impact the outcome.

Author: We have listed the medications in the supplement file that were accepted as standard of care according to the guidelines for treatment issued by Indian Council of Medical Research and Ministry of Health, Government of India during the pandemic. This is referenced in the paper. However, the drugs were to be used as per severity of the illness and clinical discretion. There were differences in the use of drugs at study sites. Dexamethasone was only used in one subject who developed an acute onset of breathlessness and drop in arterial oxygen; withdrawn from the study.

3. In Discussion, strength and limitation, line 566: A convenience study sample of 140 participants was felt to be adequate by AC (first author) and SS (Biostatistician co-author)”, and no formal estimation of required sample size for this study was attempted. I think that the authors might write in paragraph of limitations of conclusion, because sampling bias or selection bias is possible. Moreover, the authors should list some bias in terms of limitations, not to describe the chaos situation when the study was conducted during the pandemic.

Author: We agree with the comment and accordingly modified the section on limitations and conclusion. We have mentioned the possibility of a selection bias as described in the comment above also/

Minor revisions:

1). Discussion, line 470: completer analysis should be corrected as per protocol analysis.

Author: We have corrected the term

2. Reference 50 and 52, line 925 and 935: volume and page are missed.

Author: The references have been corrected as per the citation provided by the published paper and conforming to PLOS One.

Attachment

Submitted filename: Response to Reviewers_0922.docx

Decision Letter 2

Shu-Hsing Cheng

10 Oct 2022

PONE-D-21-24749R2Coadministration of AYUSH 64 as an adjunct to Standard of Care in mild and moderate COVID-19: A randomized, controlled, multicentric clinical trialPLOS ONE

Dear Dr. Chopra,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

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Shu-Hsing Cheng, Ph.D.

Guest Editor

PLOS ONE

Journal Requirements:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

Additional Editor Comments (if provided):

The whole manuscript still contained many grammar errors and missing notes. For examples:

1. At line 39, “Significance p <0.05, two sided.” This is not a complete sentence

2. In the abstract, “App.”, “CI”, “PP”, abbreviations were presented without preceding full names.

3. At line 61, “ the World” should the “the world”

4. At line 97, HCQS without full names

5. At line 163, the meanings of “The patients did not assess the burden or the outcome of the intervention.” was not clear.

6. At line 171, “ real life PCR” must be “real time”

7. At line 293, CRO were presented without preceding full name.

8. For figures and tables:

Table 1 Footnote: (p,0.05) may be p<0.05, like other footnotes in table 2-5.

Table 2 # was not explained in the footnote.

Table 3: * did not explain the comparison groups or arms. Is it significant?

Table 4: ** was not explained in the footnote.

Table 5: In Column 1, is “Investigation” represented anything?

Figure 2: “completer” was suggested change to “per protocol”

9. At line 417-418, “there was a significant reduction in serum biomarkers of COVID-19 in each of the study groups without any significant difference (Table 3).” This sentence was not clear.

10. At line 430-432, “ In comparison to SOC, AYUSH Plus showed significant improvement in several domains (physical health, psychological health, social relationship, and environmental well-being) in the WHO QOL BREF and the total HR-BHF score the time of clinical recovery and pre-determined follow-up time points (Table 4).” May the authors check again the completeness of the sentences?

Most of the contents had been revised according to previous 3 reviewers’ comments. However, the whole manuscript needs dedicated edition to improve the readability and quality.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

PLoS One. 2023 Mar 16;18(3):e0282688. doi: 10.1371/journal.pone.0282688.r006

Author response to Decision Letter 2


21 Oct 2022

Additional Editor Comments (if provided):

The whole manuscript still contained many grammar errors and missing notes. For examples:

Response: My apologies for these errors. The manuscript has been rechecked by a profession in use of English language and medical writing.

Editor:

1. At line 39, “Significance p <0.05, two sided.” This is not a complete sentence

Response: Corrected

2. In the abstract, “App.”, “CI”, “PP”, abbreviations were presented without preceding full names.

Response: All abbreviations are rechecked and full name provided

3. At line 61, “ the World” should the “the world”

Response: corrected

4. At line 97, HCQS without full names

Response: corrected

5. At line 163, the meanings of “The patients did not assess the burden or the outcome of the intervention.” was not clear

Response: This is deleted and the sections rewritten.

6. At line 171, “ real life PCR” must be “real time”

Response: corrected

7. At line 293, CRO were presented without preceding full name.

Response: A full form was provided in the earlier text

8. For figures and tables:

Table 1 Footnote: (p,0.05) may be p<0.05, like other footnotes in table 2-5.

Table 2 # was not explained in the footnote.

Table 3: * did not explain the comparison groups or arms. Is it significant?

Table 4: ** was not explained in the footnote.

Table 5: In Column 1, is “Investigation” represented anything?

Figure 2: “completer” was suggested change to “per protocol”

Response: All Tables are rechecked and corrections made. Figure 2 is revised

9. At line 417-418, “there was a significant reduction in serum biomarkers of COVID-19 in each of the study groups without any significant difference (Table 3).” This sentence was not clear.

Response: Though the difference from baseline was significant in each of the two groups, there was no significant difference between the groups. This is now further clarified

10. At line 430-432, “ In comparison to SOC, AYUSH Plus showed significant improvement in several domains (physical health, psychological health, social relationship, and environmental well-being) in the WHO QOL BREF and the total HR-BHF score the time of clinical recovery and pre-determined follow-up time points (Table 4).” May the authors check again the completeness of the sentences?

Response: The sentence is further made clear. It now reads ‘In comparison to SOC, AYUSH Plus showed significant improvement in several domains (physical health, psychological health, social relationship, and environmental well-being) in the WHO QOL BREF and the total HR-BHF score at the time of clinical recovery and during follow-up (Table 4).’

Attachment

Submitted filename: PLOS One_Author reponse 201022.docx

Decision Letter 3

Shu-Hsing Cheng

22 Feb 2023

Coadministration of AYUSH 64 as an adjunct to Standard of Care in mild and moderate COVID-19: A randomized, controlled, multicentric clinical trial

PONE-D-21-24749R3

Dear Dr. Arvind Chopra

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Kind regards,

Shu-Hsing Cheng, Ph.D.

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PLOS ONE

Additional Editor Comments (optional):

This version is comprehensive, and previleged to be accepted.

Reviewers' comments:

Acceptance letter

Shu-Hsing Cheng

6 Mar 2023

PONE-D-21-24749R3

Co-administration of AYUSH 64 as an adjunct to Standard of Care in mild and moderate COVID-19: A randomized, controlled, multicentric clinical trial

Dear Dr. Chopra:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

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Kind regards,

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on behalf of

Dr. Shu-Hsing Cheng

Guest Editor

PLOS ONE

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    S1 File. CONSORT check list.

    (DOC)

    S2 File. Study protocol.

    (DOCX)

    S3 File. Composition, chemistry, manufacturing, and controls of AYUSH 64.

    (DOCX)

    S4 File. Health and quality of life questionnaires (WHO-QOL & HR-BHF).

    (DOCX)

    S5 File. Additional data–standard of care drugs, site specific drugs & timelines, general linear model output, intention to treat analysis, and radiological data.

    (DOCX)

    S6 File. Additional data- adverse events.

    (DOCX)

    S7 File. Additional data- laboratory results.

    (DOCX)

    S8 File. Selected raw data—efficacy, withdrawals, adverse events.

    (DOCX)

    Attachment

    Submitted filename: Response to Editor_Referee.docx

    Attachment

    Submitted filename: comments of AYUSH 64 in COVID-19.docx

    Attachment

    Submitted filename: Response to Reviewers_0922.docx

    Attachment

    Submitted filename: PLOS One_Author reponse 201022.docx

    Data Availability Statement

    Several relevant data are within the manuscript and its Supporting Information files (S8F).All relevant data on primary efficacy, adverse events and withdrawals is available enclosed with the manuscript as a Supporting Information file (S8 File). The full data set is archived by the CCRAS, Government of India (http://www.ccras.nic.in), as an electronic data base and access will be provided after approval by Director General, CCRAS as explained below. Access to full data set will be available for any kind of non-commercial purpose and without any other restriction after approval by the sponsor (Director General, Central Council for Research in Ayurvedic Sciences/ CCRAS, Government of India) six months after publication. The latter will require a formal request from the applicant stating the reason for access and accompanied with a CV (applicant) and may be sent Email (crdp5624@gmail.com) to Arvind Chopra (first author) for further processing by CCRAS.


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