Directorate of AYUSH, Health and Family Welfare Department, Government of NCT of Delhi, New Delhi, India.
Department of Psychology and Pedogogic Science, St Mary's University, London, UK.
Homeopathy. 2023 Feb;112(1):22-29. doi: 10.1055/s-0042-1746196. Epub 2022 Aug 21.
Most of the symptoms of coronavirus disease 2019 (COVID-19) are covered by large repertory rubrics and hence many remedies have been proposed as "genus epidemicus". The aim of this study was to combine the information from various data collections to prepare a COVID-19 Bayesian mini-repertory/an algorithm-based application (app) and test it.
In July 2021, 1,161 COVID-19 cases from 100 practitioners globally were combined. These data were used to calculate "condition-confined" likelihood ratios (LRs) for 59 symptoms of COVID-19. Out of these, 35 symptoms of the 11 medicines that had at least 20 cases each were considered. The information was entered in a spreadsheet (algorithm) to calculate combined LRs of specific combinations of symptoms. The algorithm contained the medicines , , , , , , , , , and . To test concordance, the doctors were then invited to re-enter the symptoms of their cases into this algorithm.
The algorithm was re-tested on 358 cases, and concordance was seen in 288 cases. On analysis of the data, bias was noticed in the group, which was therefore excluded from the algorithm. The remaining 10 medicines, representing 81.8% of all cases, were included in the preparation of the next version of the homeopathic mini-repertory and app.
The Bayesian mini-repertory and app is based on qualitative clinical experiences of various doctors in COVID-19 and gives indications for specific medicines for common COVID-19 symptoms. It is freely available [English: https://hpra.co.uk/; Spanish: https://hpra.co.uk/es ] for further testing and utilization by the profession.
新型冠状病毒病 2019（COVID-19）的大多数症状都包含在大型药物纲要中，因此有许多药物被提出作为“传染病通用药物”。本研究的目的是结合来自各种数据收集的信息，准备一个 COVID-19 贝叶斯迷你纲要/基于算法的应用程序（应用程序）并对其进行测试。
2021 年 7 月，我们将全球 100 名医生的 1161 例 COVID-19 病例进行了合并。这些数据用于计算 COVID-19 的 59 个症状的“病症限定”似然比（LR）。其中，有 35 个症状来自至少有 20 例的 11 种药物。将这些信息输入电子表格（算法），以计算特定症状组合的综合 LR。该算法包含药物 、 、 、 、 、 、 、 、 。为了测试一致性，然后邀请医生将他们病例的症状重新输入到该算法中。
该算法在 358 例病例中进行了重新测试，在 288 例病例中发现了一致性。在数据分析中，注意到 组存在偏差，因此该组被排除在算法之外。算法中保留了 10 种药物，它们代表了所有病例的 81.8%，用于制备下一个版本的顺势迷你纲要和应用程序。
贝叶斯迷你纲要和应用程序基于不同医生在 COVID-19 方面的定性临床经验，为常见 COVID-19 症状提供了特定药物的指示。它可免费获得 [英文：https://hpra.co.uk/；西班牙文：https://hpra.co.uk/es ]，以供专业人士进一步测试和使用。
