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Enregistrement W3189039592 · doi:10.37901/jcphp20-00023

Ethical Considerations of Hydroxychloroquine During the COVID-19 Pandemic

2021· article· en· W3189039592 sur OpenAlexaboutno aff
Amy L. Reese

Notice bibliographique

RevueJournal of Contemporary Pharmacy Practice · 2021
Typearticle
Langueen
DomaineMedicine
ThématiquePharmaceutical Practices and Patient Outcomes
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésHydroxychloroquineMedicinePandemicDistributive justiceMedical prescriptionPharmacyCoronavirus disease 2019 (COVID-19)Economic JusticeFamily medicineIntensive care medicineLawPharmacologyPolitical scienceInternal medicine

Résumé

récupéré en direct d'OpenAlex

The SARS-CoV-2 pandemic has greatly affected almost every aspect of our lives. Like many community pharmacists, I struggled with the shortage of hydroxychloroquine shortly after the FDA issued an Emergency Use Authorization (EUA) in March of 2020 to be used to treat COVID-19. Pharmacists who already dispensed hydroxychloroquine to lupus and rheumatoid arthritis patients scrambled to find enough drug to dispense to the expected influx of COVID-19 patients. Some chose to fill only 30-day supplies for any patient, no matter their diagnosis and some declined new patients. Long-term patients reportedly were unable to fill their prescriptions for hydroxychloroquine. Due to the dire situation many pharmacists faced, an ethical question arose: Is off-label prescribing of a medication ethically permissible during a drug shortage?It is ethically permissible to use medications to treat the off-label indications. The risks to the patients who regularly receive the medication versus the benefits to the new group of patients receiving the medication must be weighed and distributive justice must be considered. Distributive justice is equitable, fair, and appropriate distribution that is justified by structural norms of social cooperation.(1) Distributive justice is essential to ethically distributing a scarce resource such as hydroxychloroquine because it determines who receives the medication and how much. The normal global demand for hydroxychloroquine is 300 metric tons(2); if only 2% of COVID-19 patients were treated with hydroxychloroquine, the demand would increase more than three-fold to 1,000 metric tons.(2) The increase in demand without the ability to increase supply as quickly puts a strain on the healthcare system. The American Society of Health-System Pharmacists (ASHP) published on the Drug Shortages reference website stating the drug shortage indicated many generic-manufacturers could not keep up with the demand.(3) When dealing with a drug shortage, how does a pharmacist ethically allocate a medication that is in short supply in order to provide for all patients of the pharmacy?There are four fundamentals of allocation: maximize the benefits produced by scarce resources, treat people equally, promote and reward instrumental value, and give priority to the worst off.(4) Maximizing the benefits of the scarce resource can be translated to mean make the supply last as long as possible: instead of giving one patient a 90-day supply of hydroxychloroquine (180 tablets), give three patients 30-day supplies (60 tablets for each patient). The fundamental of treating people equally is explicated through the triage process. The triage process can determine who ought to receive care based on the patient’s prognosis: a first come, first serve method can be used in triage or a random selection of patients who have similar prognosis.(4) A first come, first served method of triage should not be used due to the disparities it could create. (4) People who have the means to arrive at the pharmacy faster and easier receive treatment before people who lack those means. A random selection of patients who have similar prognosis would be the most ethical because it would give all patients in the same severity a chance at receiving the medication. Often times, a first come, first serve basis is used to distribute medication in the pharmacy despite it not being the most ethical allocation of medication. Promoting and rewarding instrumental value can be performed either retrospectively or prospectively: a retrospective system prioritizes people who have contributed to the efforts against the COVID-19 such as researchers and healthcare workers while a prospective system prioritizes people who will directly contribute to efforts of mitigating the pandemic such as healthcare professionals.(4) In terms of allocation of scarce drugs, people who have positively impacted the COVID-19 pandemic such as research or healthcare professions would receive medication therapy before other patients. Giving priority to the worst off maximizes utility by treating the sickest first(4); the patients who are the sickest but would still benefit from the treatment would receive it over patient who is not as ill. Priority to the worst off also provides treatment to younger patients before older patients because they would usually fare better long term. In this manner, pharmacists would analyze the severity of each patient’s illness and age to dispense the medication to the most ill and the youngest.The issue of distributive justice is not only an ethical issue of proper allocation. Hydroxychloroquine was being used off-label to treat COVID-19 while supply of the medication was being taken from patients who rely on the drug to stave off their autoimmune diseases (rheumatoid arthritis and lupus erythematosus). Clinical trials indicated that hydroxychloroquine effectively treats disease manifestations in rheumatoid arthritis such as joint pain and rashes(5); withdrawal of the medication can put the patient at risk of flares which could be life-threatening such as lupus nephritis.(5) The drug shortage caused concern for patients, rheumatologists, and pharmacists due to this evidence.(5)Researchers around the world conducted clinical research to determine whether the off-label use of hydroxychloroquine was appropriate for treatment and prophylaxis of COVID-19. Many of the studies could not determine whether hydroxychloroquine was effective in treating or preventing COVID-19. A study published in the New England Journal of Medicine from Brazil by Cavalcanti et. al. stated that hydroxychloroquine did not improve mild-to-moderate hospitalized patients with or without azithromycin.(6) Another study performed throughout the United States and Canada by Boulware et. al. randomized patients to determine whether hydroxychloroquine was effective in staving off COVID-19 through postexposure prophylaxis.(7) Essentially, a patient population who have been shown to benefit from hydroxychloroquine faced devastating shortages due to experimentation with the drug which ended up inconclusive. Is this an ethical utilization of scarce medications? If hydroxychloroquine was proven effective, then it would be ethically permissible to deny patients of a chronic illness for a few months to treat patients with COVID-19 because it is a more critical and life-threatening disease. Depriving a patient maintenance medication would be justified if that medication was proven to save the lives of other patients who are fighting for life (life-or-death situation). But because hydroxychloroquine could not be demonstrated to be effective in preventing or treating COVID-19, it is unethical to deny patients of a chronic illness their medication which alleviates their symptoms and mitigates their autoimmune disease.The FDA rescinded the EUA for hydroxychloroquine on June 15, 2020(8), and the shortage resolved quickly to the benefit of patients suffering from autoimmune diseases. The ethical questions remain. As pharmacists, we must act ethically in all we do–even pertaining to the distribution of medication from the pharmacy. Pharmacists must allot essential medication according to the four fundamentals of allocation when faced with a paucity. We must also analyze the data to determine whether the data support depriving life-sustaining medication from one patient population to distribute it to another patient population. We can take the lessons we have learned from the unprecedented situations we faced during this COVID-19 pandemic and use them for the future. Hopefully we will not experience such a devastating pandemic in the future, but it is best to be prepared for possibilities than to face another situation like the one we have seen without pondering the ethical implications of our actions.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,108
score de la tête « metaresearch » (Gemma)0,133
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Commentaire · Signal consensuel: Commentaire
Score de désaccord entre enseignants0,108
Score d'incertitude au seuil0,572

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,1080,133
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0020,001
Bibliométrie0,0010,000
Études des sciences et des technologies0,0160,037
Communication savante0,0140,009
Science ouverte0,0030,010
Intégrité de la recherche0,0350,039
Charge utile insuffisante (le modèle a refusé de juger)0,0040,001

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,330
Tête enseignante GPT0,498
Écart entre enseignants0,168 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreCommentaire

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2021
Routes d'admission1
Résumé présentoui

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