Hydroxychloroquine in Nonhospitalized Adults With Early COVID-19
Bibliographic record
Abstract
LettersMarch 2021Hydroxychloroquine in Nonhospitalized Adults With Early COVID-19FREEAnusuya Bhattacharyya, MBBS, DO, DNB (Ophthalmology), Phulen Sarma, MBBS, MD, DM (Clinical Pharmacology), PDCR, Hardeep Kaur, MSc, Bikash Medhi, MBBS, MD, MAMSAnusuya Bhattacharyya, MBBS, DO, DNB (Ophthalmology)Government Medical College & Hospital, Chandigarh, IndiaSearch for more papers by this author, Phulen Sarma, MBBS, MD, DM (Clinical Pharmacology), PDCRPostgraduate Institute of Medical Education and Research, Chandigarh, IndiaSearch for more papers by this author, Hardeep Kaur, MScPostgraduate Institute of Medical Education and Research, Chandigarh, IndiaSearch for more papers by this author, Bikash Medhi, MBBS, MD, MAMSPostgraduate Institute of Medical Education and Research, Chandigarh, IndiaSearch for more papers by this authorAuthor, Article, and Disclosure Informationhttps://doi.org/10.7326/L21-0001 SectionsAboutVisual AbstractPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinkedInRedditEmail TO THE EDITOR: Skipper and colleagues' multicenter trial (1) was conducted in 2 locations (the United States and Canada) with the intention of evaluating the absolute therapeutic efficacy of HCQ in symptomatic, nonhospitalized adults with COVID-19. Patients were randomly assigned to either the HCQ or placebo group. While evaluating the composition of the placebo regimen, we noted that a folic acid tablet, 400 mcg, was used as placebo in the U.S. population and a lactose tablet in the Canadian population.In in silico studies, folic acid acted as a good binder against severe acute respiratory syndrome coronavirus 2 furin (which is required for viral entry to the host cell) (2). In clinical studies, Itelman and associates (3) reported lower blood folic acid levels among patients with severe disease than in their counterparts with mild disease. Pregnant women seem to be less likely to require hospitalization for COVID-19 (4), and Acosta-Elias and Espinosa-Tanguma (4) postulated that folic acid uptake may be the protective factor. Use of Angiovit (Altayvitaminy), an agent containing folic acid and vitamin B12, has been associated with a shorter duration of “hospital stay” and “fever” compared with mainstay therapy (5). Several trials evaluating folic acid as a therapeutic agent in COVID-19 are currently under way (https://clinicaltrials.gov/ct2/show/NCT04354428 and https://covid-19.cochrane.org/studies/crs-15322074).Skipper and colleagues concluded that there was no statistically significant difference in “COVID-19–related symptoms,” “incidence of hospitalization,” and “death” between both groups. This comparable efficacy does not indicate the absolute efficacy of HCQ; rather, it indicates the comparative efficacy between HCQ and folic acid, and both performed equally. Again, rather than describing this trial as “placebo controlled,” it would be better classified as a “head-on” comparison between HCQ and folic acid.References1. Skipper CP, Pastick KA, Engen NW, et al. Hydroxychloroquine in nonhospitalized adults with early COVID-19. A randomized trial. Ann Intern Med. 2020;173:623-31. doi:10.7326/M20-4207 LinkGoogle Scholar2. Sheybani Z, Dokoohaki MH, Negahdaripour M, et al. The role of folic acid in the management of respiratory disease caused by COVID-19. ChemRxiv. Preprint posted online 30 March 2020. doi:10.26434/chemrxiv.12034980.v1 Google Scholar3. Itelman E, Wasserstrum Y, Segev A, et al. Clinical characterization of 162 COVID-19 patients in Israel: preliminary report from a large tertiary center. Isr Med Assoc J. 2020;22:271-4. [PMID: 32378815] MedlineGoogle Scholar4. Acosta-Elias J, Espinosa-Tanguma R. The folate concentration and/or folic acid metabolites in plasma as factor for COVID-19 infection. Front Pharmacol. 2020;11:1062. [PMID: 32765270] doi:10.3389/fphar.2020.01062 CrossrefMedlineGoogle Scholar5. Boyko AN, Shamalov NA, Boyko OV, et al. The first experience with Angiovit in the combination treatment of acute COVID-19 infection. Neurology, Neuropsychiatry, Psychosomatics. 2020;12:82-6. doi:10.14412/2074-2711-2020-3-82-86 Google Scholar Comments 0 Comments Sign In to Submit A Comment Author, Article, and Disclosure InformationAuthors: Anusuya Bhattacharyya, MBBS, DO, DNB (Ophthalmology); Phulen Sarma, MBBS, MD, DM (Clinical Pharmacology), PDCR; Hardeep Kaur, MSc; Bikash Medhi, MBBS, MD, MAMSAffiliations: Government Medical College & Hospital, Chandigarh, IndiaPostgraduate Institute of Medical Education and Research, Chandigarh, IndiaDisclosures: Authors have disclosed no conflicts of interest. Forms can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=L21-0001. PreviousarticleNextarticle Advertisement FiguresReferencesRelatedDetailsSee AlsoHydroxychloroquine in Nonhospitalized Adults With Early COVID-19 Caleb P. Skipper , Katelyn A. Pastick , Nicole W. Engen , Ananta S. Bangdiwala , Mahsa Abassi , Sarah M. Lofgren , Darlisha A. Williams , Elizabeth C. Okafor , Matthew F. Pullen , Melanie R. Nicol , Alanna A. Nascene , Kathy H. Hullsiek , Matthew P. Cheng , Darlette Luke , Sylvain A. Lother , Lauren J. MacKenzie , Glen Drobot , Lauren E. Kelly , Ilan S. Schwartz , Ryan Zarychanski , Emily G. McDonald , Todd C. Lee , Radha Rajasingham , and David R. Boulware Hydroxychloroquine in Nonhospitalized Adults With Early COVID-19 Claudia N. Paiva , Daniel V. Tausk Hydroxychloroquine in Nonhospitalized Adults With Early COVID-19 Bruno Luís de Castro Araujo Hydroxychloroquine in Nonhospitalized Adults With Early COVID-19 Caleb P. Skipper , David R. 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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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".