Background/Objective Coronavirus disease 2019 (COVID-19) is a new disease; its clinical profile and natural history are evolving. Each well-recorded case in homeopathic practice is important for deciding the future course of action. This study aims at identifying clinically useful homeopathic remedies and their prescribing symptoms using the prognostic factor research model. Methods This was an open-label, multi-centric, observational study performed from April 2020 to July 2020 at various public health care clinics. The data were collected prospectively from clinical practice at integrated COVID-19 care facilities in India. Good-quality cases were selected using a specific set of criteria. These cases were analyzed for elucidating prognostic factors by calculating the likelihood ratio (LR) of each frequently occurring symptom. The symptoms with high LR values (>1) were considered as prescribing indications of the specific remedy. Results Out of 327 COVID-19 cases reported, 211 met the selection criteria for analysis. The most common complaints were fatigue, sore throat, dry cough, myalgia, fever, dry mouth and throat, increased thirst, headache, decreased appetite, anxiety, and altered taste. Twenty-seven remedies were prescribed and four of them—Arsenicum album, Bryonia alba, Gelsemium sempervirens, and Pulsatilla nigricans—were the most frequently used. A high LR was obtained for certain symptoms, which enabled differentiation between the remedies for a given patient. Conclusion Homeopathic medicines were associated with improvement in symptoms of COVID-19 cases. Characteristic symptoms of four frequently indicated remedies have been identified using prognostic factor research, findings that can contribute to accurate homeopathic prescribing during future controlled research in COVID-19.
Background Dengue is an emerging threat to public health. At present, no clear modalities are available for the prevention and management of thrombocytopenia due to dengue. This article reports the clinical outcomes of integrative homeopathic care in a hospital setting during a severe outbreak of dengue in New Delhi, India, during the period September to December 2015. Methods Based on preference, 138 patients received a homeopathic medicine along with usual care (H+UC), and 145 patients received usual care (UC) alone. Assessment of thrombocytopenia (platelet count < 100,000/mm3) was the main outcome measure. Kaplan–Meier analysis enabled comparison of the time taken to reach a platelet count of 100,000/mm3. Results There was a statistically significantly greater rise in platelet count on day 1 of follow-up in the H+UC group compared with UC alone (mean difference = 12,337; 95% confidence interval [CI], 5,421 to 19,252; p = 0.001). This trend persisted until day 5 (mean difference = 14,809; 95% CI, 1,615 to 28,004; p = 0.02). The time taken to reach a platelet count of 100,000/mm3 was nearly 2 days earlier in the H+UC group compared with UC alone (H+UC: 3.44 days ± standard error of the mean [SEM] 0.18; 95% CI, 3.08 to 3.80; UC: 5.28 days ± SEM 0.29; 95% CI, 4.71 to 5.86; p < 0.001). Conclusion These results suggest a positive role of adjuvant homeopathy in thrombocytopenia due to dengue. Randomized controlled trials may be conducted to obtain more insight into the comparative effectiveness of this integrative approach.
Background/Objective Prognostic factor research (PFR), prevalence of symptoms and likelihood ratio (LR) play an important role in identifying prescribing indications of useful homeopathic remedies. It involves meticulous unbiased collection and analysis of data collected during clinical practice. This paper is an attempt to identify causes of bias and suggests ways to mitigate them for improving the accuracy in prescribing for better clinical outcomes and execution of randomized controlled studies. Methods A prospective, open label, observational study was performed from April 2020 to December 2020 at two COVID Health Centers. A custom-made Excel spreadsheet containing 71 fields covering a spectrum of COVID-19 symptoms was shared with doctors for regular reporting. Cases suitable for PFR were selected. LR was calculated for commonly occurring symptoms. Outlier values with LR ≥5 were identified and variance of LRs was calculated. Results Out of 1,889 treated cases of confirmed COVID-19, 1,445 cases were selected for pre-specified reasons. Nine medicines, Arsenicum album, Bryonia alba, Gelsemium sempervirens, Pulsatilla nigricans, Hepar sulphuricus, Magnesia muriaticum, Phosphorus, Nux vomica and Belladonna, were most frequently prescribed. Outlier values and large variance for Hepar sulphuricus and Magnesia muriaticum were noticed as indication of bias. Confirmation bias leading to lowering of symptom threshold, keynote prescribing, and deficiency in checking of all symptoms in each case were identified as the most important sources of bias. Conclusion Careful identification of biases and remedial steps such as training of doctors, regular monitoring of data, checking of all pre-defined symptoms, and multicenter data collection are important steps to mitigate biases.
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