Hydroxychloroquine: A Potential Ethical Dilemma for Rheumatologists during the COVID-19 Pandemic
Bibliographic record
Abstract
Two antimalarial agents, chloroquine (CQ) and hydroxychloroquine (HCQ), have been trusted treatments for a range of rheumatic diseases over the past 70 years1. These agents have attracted intense media attention in the past few weeks with suggestions that this category of drugs may have potential in the management of the coronavirus (SARS-CoV2)–associated disease called COVID-192,3. In this unprecedented time of a world viral pandemic that is associated with considerable mortality, rheumatologists can anticipate challenges in clinical care. We must counsel patients about the appropriate use of HCQ (CQ is not currently available in Canada) in the management of rheumatic diseases, provide valid scientific information regarding the current evidence for effect in COVID-19 disease, and be poised to provide alternative drug treatment in the event that HCQ may be allocated away from routine rheumatology clinical care to treat seriously ill viral-infected patients. These issues are pertinent and imminent for the rheumatologist and require an understanding of the current available knowledge, and consideration of a possible ethical dilemma in the event that drug supply is limited. Antimalarial therapy began in the mid-17th century with observations by Jesuit missionaries in Peru that the bark of a specific tree, later named Cinchona, could be used to treat the severe febrile illness now know to be malaria4. In the late 17th century, the Peruvian bark, mixed with rose leaves, lemon juice, and wine was a widely used secret treatment for fever in the malarial regions of England4. Quinine is a complex structured alkaloid and the active therapeutic component of the Cinchona tree. It was isolated and named in 1820 by 2 French chemists, Pelletier and Caventou4. Until the 1850s all the Cinchona bark came from the wild forests of the Andean republics of … Address correspondence to Dr. M.A. Fitzcharles, Montreal General Hospital, McGill University Health Centre, 1650 Cedar Ave., Montreal, Quebec H3G 1A4, Canada. E-mail: mfitzcharles{at}sympatico.ca
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.050 | 0.114 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.024 |
| Scholarly communication | 0.011 | 0.011 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.038 | 0.049 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".