A Bayesian Materia Medica of Pulsatilla nigricans

Abstract Homeopathic treatment is guided by the patient's symptoms and signs, which serve as medicines' indicators. A precise knowledge and understanding of the indicators of each medicine is therefore essential for therapeutic success. Following a Bayesian concept, it is now apparent that a symptom indicates a medicine when its likelihood ratio (LR) for that medicine is greater than 1—that is, when the symptom is more prevalent in patients who respond to the medicine than in the remainder of the population. For the past 8 years, the ‘Best Chronic Homeopathic Cases’ and the ‘Bayesian Homeopathic Repertory’ projects have been systematically evaluating the LRs of symptom–medicine relationships based on data from the best available cases. This article presents a provisional Bayesian Materia Medica of Pulsatilla nigricans, developed following this novel approach. Fifty-two statistically validated Pulsatilla-indicating symptoms, including 17 keynotes, are reported, along with their prevalence in the general and pulsatilla responding populations and their LRs. The resulting picture aligns closely with the core traditional clinical knowledge experienced homeopaths have of Pulsatilla, and the research methodology appears promising for the development of a more reliable homeopathic materia medica and repertory.