Dataset Information

An Ayurvedic personalized prophylactic protocol in COVID-19.

ABSTRACT: The current COVID-19 pandemic brought about by the SARS-CoV-2, a novel β coronavirus is creating intense health havoc globally. Researchers suspect the situation to stay for long in the community, considering this virus's pathogenesis, high rate transmission and tendency to provoke uncontrolled immune response activation. Immune mechanisms are highly individualistic. We put forward a hypothetical model of prakruti (Ayurvedic body phenotyping character) based personalized prophylactic-therapeutic strategies aiming at a better immunomodulation and quicker resolution of host immune mechanisms. We propose this model in symptomatic, mild to moderate, COVID-19 diagnosed cases and in cases quarantined for high to low risk primary contact with a positive case. We also suggest a community level personalized Ayurvedic prophylactic-therapeutic strategy based on the DOTS model. Person-centered body purificatory measures (panchakarma procedures) like therapeutic purgation (virechana) and medicated enema (basti) are suggested in this hypothetical protocol with justification on evidence-based links between immune responses and prakruti along with specific jwara (fevers of varied origin as per Ayurvedic sciences) and COVID-19 symptomatology. The paper also appraises the importance of pitta dosha/ama dosha in the manifestation of inflammation driven destructive phase of immune responses along with its stage-wise intervention. This hypothetical model intends to open up discussions on significance of prakruti assessment as a predictive marker to screen people who are at risk of succumbing into deteriorating states if infected with COVID-19. It also intends to discuss the predictive personalized medicine measures based on prakruti in yielding individual host immune homeostasis which may positively reduce the chances of untoward events of an aggravated immune responsiveness and subsequent inflammation driven tissue destruction - the candidate causes for COVID-19 related casualties. Testing this model may give insight towards emphasizing personalized host immune coping mechanisms that may prove crucial in any infectious outbreaks in near future too.

SUBMITTER: Nair PP

PROVIDER: S-EPMC7834287 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundWhile Molnupiravir and Paxlovid have recently been approved for use in some countries, there are no widely available treatments for COVID-19, the disease caused by SARS-CoV-2 infection. Herbal extracts have been used to treat respiratory clinical indications by Ayurvedic medicine practitioners with minimal adverse reactions and intense research efforts are currently under way to develop some of these formulations for COVID-19 treatment.MethodsLiterature search for in silico, in vitro, in vivo, and clinical studies on the topic of Ayurvedic formulations for potential COVID-19 treatment, in order to present the current state of current knowledge by integrating information across all systems.ResultsThe search yielded 20 peer reviewed articles on in silico studies examining the interaction of phytoconstituents of popular Ayurvedic formulations with SARS-CoV-2 components and its receptors; five articles on preclinical investigations of the ability of selected Ayurvedic formulations to inhibit functions of SARS-CoV-2 proteins; and 51 completed clinical trials on the efficacy of using Ayurvedic formulations for treatment of mild to moderate COVID-19. Clinical data was available from 17 of the 51 trials. There was a considerable overlap between formulations used in the in silico studies and the clinical trials. This finding was unexpected as there is no clearly stated alignment between studies and the traditional pathway to drug discovery- basic discovery leading to in vitro and in vivo proof of concept, followed by validation in clinical trials. This was further demonstrated in the majority of the in silico studies where focus was on potential antiviral mechanisms, while the clinical trials were focused on patient recovery using oral treatments. In all 17 clinical trials where data was available, Ayurvedic treatments lead to a shorter period to recovery in participants with COVID-19.ConclusionThe most commonly used Ayurvedic treatments for management of respiratory symptoms associated with SARS-CoV-2 infection appear to have prophylactic and/or therapeutic properties. It would be of particular interest to assess synergistic and concomitant systemic effects and antiviral activities of individual phytoconstituents and their combinations in the Ayurvedic treatments.

Project description:BackgroundAyurvedic clinical profiling of COVID-19 is a pre-requisite to develop standalone and integrative treatment approaches. At present, Ayurvedic clinicians do not have access to COVID-19 patients in clinical settings. In these circumstances, a preliminary clinical profiling of COVID-19 based on review of modern medical and classical Ayurvedic literature with inputs from Allopathic clinicians treating COVID-19 patients assumes significance.ObjectivesThis paper aims to develop an Ayurvedic clinical profile of COVID-19 by literature review supported by analysis of clinical data of a cohort of COVID-19 patients.MethodsThe typical clinical presentation of COVID-19 was categorized based on a cluster of symptoms with reference to "Interim Clinical Guidance for Management of Patients with confirmed corona virus disease (COVID-19)" released by the US CDC. As the clinical presentation is found to vary widely, research papers reporting clinical symptoms of patient samples from different parts of the world were also reviewed to identify outliers and atypical presentations. Case records of fourteen COVID-19 patients treated at Medanta Hospital, Gurgaon were analyzed to compare symptomatology with data obtained from published literature. Further, a careful correlation was done with the data collected from selected Ayurvedic classical texts and expert views of clinical practitioners to arrive at a preliminary Ayurvedic clinical profile of COVID-19.ResultsCOVID-19 can be understood from the Ayurvedic perspective as vātakapha dominant sannipātajvara of āgantu origin with pittānubandha. The asymptomatic, presymptomatic, mild, moderate, severe and critical stages of COVID-19 with varying clinical presentations have been analysed on the basis of nidāna, doṣa, dūṣya, nidānapañcaka and ṣaṭkriyākāla to present a preliminary clinical profile of the disease.ConclusionIn this paper, we have demonstrated that a preliminary clinical profiling of COVID-19 from the Ayurvedic perspective is possible through literature review supported by discussions with Allopathic clinicians as well as examination of patient case records. The provisional diagnosis proposed can be further developed with continued review of literature, wider cooperation and teamwork with Allopathic physicians and access to clinical data as well as direct clinical assessment of COVID-19 patients.

Project description:IntroductionCOVID-19 induces venous, arterial and microvascular thrombosis, involving several pathophysiological processes. In patients with severe COVID-19 without macrovascular thrombosis, escalating into high-dose prophylactic anticoagulation (HD-PA) or therapeutic anticoagulation (TA) could be beneficial in limiting the extension of microvascular thrombosis and forestalling the evolution of lung and multiorgan microcirculatory dysfunction. In the absence of data from randomised trials, clinical practice varies widely.Methods and analysisThis is a French multicentre, parallel-group, open-label, randomised controlled superiority trial to compare the efficacy and safety of three anticoagulation strategies in patients with COVID-19. Patients with oxygen-treated COVID-19 showing no pulmonary artery thrombosis on computed tomography with pulmonary angiogram will be randomised to receive either low-dose PA, HD-PA or TA for 14 days. Patients attaining the extremes of weight and those with severe renal failure will not be included. We will recruit 353 patients. Patients will be randomised on a 1:1:1 basis, and stratified by centre, use of invasive mechanical ventilation, D-dimer levels and body mass index. The primary endpoint is a hierarchical criterion at day 28 including all-cause mortality, followed by the time to clinical improvement defined as the time from randomisation to an improvement of at least two points on the ordinal clinical scale. Secondary outcomes include thrombotic and major bleeding events at day 28, individual components of the primary endpoint, number of oxygen-free, ventilator-free and vasopressor-free days at day 28, D-dimer and sepsis-induced coagulopathy score at day 7, intensive care unit and hospital stay at day 28 and day 90, and all-cause death and quality of life at day 90.Ethics and disseminationThe study has been approved by an ethical committee (Ethics Committee, Ile de France VII, Paris, France; reference 2020-A03531-38). Patients will be included after obtaining their signed informed consent. The results will be submitted for publication in peer-reviewed journals.Trial registration numberNCT04808882.

Project description:BackgroundDuring the COVID-19 pandemic, novel digital health technologies have the potential to improve our understanding of SARS-CoV-2 and COVID-19, improve care delivery, and produce better health outcomes. The National Institutes of Health called on digital health leaders to contribute to a high-quality data repository that will support researchers to make discoveries that are otherwise not possible with small, limited data sets.ObjectiveTo this end, we seek to develop a COVID-19 digital biomarker for early detection of physiological exacerbation or decompensation. We propose the development and validation of a COVID-19 decompensation Index (CDI) in a 2-phase study that builds on existing wearable biosensor-derived analytics generated by physIQ's end-to-end cloud platform for continuous physiological monitoring with wearable biosensors. This effort serves to achieve two primary objectives: (1) to collect adequate data to help develop the CDI and (2) to collect rich deidentified clinical data correlating with outcomes and symptoms related to COVID-19 progression. Our secondary objectives include evaluation of the feasibility and usability of pinpointIQ, a digital platform through which data are gathered, analyzed, and displayed.MethodsThis is a prospective, nonrandomized, open-label, 2-phase study. Phase I will involve data collection for the digital data hub of the National Institutes of Health as well as data to support the preliminary development of the CDI. Phase II will involve data collection for the hub and contribute to continued refinement and validation of the CDI. While this study will focus on the development of a CDI, the digital platform will also be evaluated for feasibility and usability while clinicians deliver care to continuously monitored patients enrolled in the study.ResultsOur target CDI will be a binary classifier trained to distinguish participants with and those without decompensation. The primary performance metric for CDI will be the area under the receiver operating characteristic curve with a minimum performance criterion of ≥0.75 (α=.05; power [1-β]=0.80). Furthermore, we will determine the sex or gender and race or ethnicity of the participants, which would account for differences in the CDI performance, as well as the lead time-time to predict decompensation-and its relationship with the ultimate disease severity based on the World Health Organization COVID-19 ordinal scale.ConclusionsUsing machine learning techniques on a large data set of patients with COVID-19 could provide valuable insights into the pathophysiology of COVID-19 and a digital biomarker for COVID-19 decompensation. Through this study, we intend to develop a tool that can uniquely reflect physiological data of a diverse population and contribute to high-quality data that will help researchers better understand COVID-19.Trial registrationClinicalTrials.gov NCT04575532; https://www.clinicaltrials.gov/ct2/show/NCT04575532.International registered report identifier (irrid)DERR1-10.2196/27271.

Dataset Information

An Ayurvedic personalized prophylactic protocol in COVID-19.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets