Abstract
Background
COVID-19, caused by the virus SARS-CoV-2, has brought extensive challenges to the scientific community in recent months. Several studies have been undertaken in an attempt to minimize the impact of the disease worldwide. Although new knowledge has been quickly disseminated, including viral mechanisms, pathophysiology, and clinical findings, there is a lack of information on the effective pharmacological management of this disease. In vitro studies have shown some benefits related to the use of antimalarials (chloroquine and hydroxychloroquine) for inhibiting SARS-CoV-2. However, the data from open clinical trials on COVID-19 patients are controversial.
Objective
We present the protocol for a research project that compares the potential protective effect of antimalarials in preventing moderate-to-severe forms of COVID-19 in two groups: (1) patients treated chronically with antimalarials for rheumatic diseases and (2) other members of the patients’ household who have not been diagnosed with rheumatic diseases and are not taking antimalarials.
Methods
This is a 24-week, prospective, observational cohort study comprising patients from public and private health services across Brazil, who chronically use antimalarials for the treatment of immune-mediated rheumatic diseases, osteoarthritis, or chikungunya-related arthropathy. A total of six sequential phone interviews were scheduled during the COVID-19 outbreak in five different regions of Brazil. Information regarding social, epidemiological, and demographic data, as well as details about rheumatic diseases, antimalarials, comorbidities, and concomitant medication, is being recorded using a specific online form in the REDCap database. Symptoms suggestive of COVID-19, including fever, cough, dyspnea, anosmia, and dysgeusia, are being self-reported and collected via phone interviews. Our main outcomes are hospitalization, need of intensive care unit, and death.
Results
Recruitment began at the end of March 2020, and the inclusion was done during an 8-week period (from March 29 to May 17) with a total of 10,443 individuals enrolled at baseline, 5166 of whom have rheumatic diseases, from 23 tertiary rheumatology centers across 97 Brazilian cities. Data analysis is scheduled to begin after all inclusion data have been collected.
Conclusions
This study, which includes a large sample of chronic antimalarial users, will allow us to explore whether SARS-CoV-2 infection may be associated with immune-mediated rheumatic diseases and long-term antimalarial usage.
Trial Registration
Brazilian Registry of Clinical Trials RBR–9KTWX6; http://www.ensaiosclinicos.gov.br/rg/RBR-9ktwx6/
International Registered Report Identifier (IRRID)
DERR1-10.2196/23532
Keywords: COVID-19, SARS-CoV-2, coronavirus, antimalarial, rheumatic diseases, mortality, immune system, immunology, protocol, observational, pharmacological, drug
Introduction
COVID-19, which originated from Wuhan, China, in December 2019, remains a major challenge for scientists and the medical community as it continues to spread rapidly across the world [1,2]. The rapid transmission of the disease, which is caused by the novel coronavirus SARS-CoV-2, and the need to minimize its impact have caused scientific research and information to emerge at a record speed, but there are still numerous knowledge gaps [3-6].
In recent months, a marked information revolution has been observed, relating to viral mechanisms, pathophysiology, and heterogeneous clinical findings with different severity grades. Those infected with COVID-19 range from asymptomatic individuals to critically ill patients with outcomes like severe acute respiratory syndrome, coagulopathy (a prothrombotic state triggered by inflammation and other factors), and death [7-13]. Age and concomitant diseases, especially hypertension, diabetes, and heart, kidney, and lung diseases, are associated with poor outcomes [14-18].
Considering there is no specific, effective pharmacological treatment for COVID-19, several drugs have been tested, such as antivirals (lopinavir-ritonavir, remdesivir, favipiravir); antimalarials alone or combined with azithromycine; interleukin 6 (IL-6) antagonists; Janus kinase inhibitors and interferon, as well as other procedures (extracorporeal membrane oxygenation and convalescent plasma). However, to date, there are no data on the potential preventive effect of any of these, regardless of timing (pre-exposure, symptomatic period, or inflammatory phase) [19-27].
The role of chloroquine and hydroxychloroquine in treating patients with malaria and immune-mediated rheumatic diseases (IMRD) is well-known, especially in cases of systemic lupus erythematous and rheumatoid arthritis. In vitro studies have shown antimalarials have an antiviral effect against some viruses, such as SARS-CoV (severe acute respiratory syndrome–associated coronavirus), MERS-CoV (Middle East respiratory syndrome coronavirus), SARS-CoV-2, HIV, Zika, and influenza A(H5N1), especially in relation to endosomal membrane pH changes and an inhibitory mechanism to hamper the viral entry inside the cells. However, clinical trials are controversial and present many methodological problems, including randomization, dosage, time of use, endpoint definitions, outcomes, and safety issues [28-35].
Among rheumatologists, antimalarials have been used safely and effectively for several decades in patients with rheumatic diseases [36]. For this reason, rheumatologists and rheumatic patients who are long-term users of antimalarials were involved in COVID-19–related discussions and research [37-39]. Our main hypothesis is that patients with rheumatic diseases who chronically use antimalarials could have a lower rate of moderate-to-severe forms of COVID-19 since these drugs work as immune modulators in mitigating cytokine storm and poor prognosis.
Objectives
Our primary aim is to assess the potential preventive effects of antimalarials in reducing the incidence of moderate-to-severe forms of COVID-19 in patients with rheumatic diseases. Secondarily, we aim to determine the frequency of SARS-CoV-2 infection in patients with rheumatic diseases who are chronic users of antimalarials. For both objectives, patients with rheumatic diseases will be compared with members of their household who are not taking antimalarials.
Methods
Design
The study design will be a prospective, multicentric, observational cohort study with a control group.
Sample Size
Considering a moderate-to-severe COVID-19 rate as the dependent variable, a rate which the current literature estimates to be 20% [4,6,10-18,40-42] as well as the proportion of 1 case for every 2 controls, the sample calculation was approximately 3000 antimalarial users and 6000 nonusers, with an error α=5% and β=20%.
Inclusion Criteria
The inclusion criteria are as follows:
Men and women;
>18 years of age;
Use of antimalarials for at least 30 days before inclusion in the study;
Diagnosis of IMRD (according to the criteria of the American College of Rheumatology or European League Against Rheumatism), rheumatoid arthritis [43], systemic lupus erythematosus [44], Sjögren's syndrome [45], systemic sclerosis [46], inflammatory myopathies [47], and mixed connective tissue disease [48];
Diagnosis of osteoarthritis (subgroup) [49];
Diagnosis of chikungunya-related arthropathy (subgroup).
Exclusion Criteria
The exclusion criteria, which apply to both patients and controls, are as follows:
Previous use of chloroquine or equivalent that was not in the past 6 months;
History of solid organ or bone marrow transplantation;
Neoplasm of solid organs or lymphatic or myeloproliferative lineage in the past 12 months with or without adjuvant chemotherapy;
Positive HIV status, regardless of highly active antiretroviral therapy;
Use of intravenous human immunoglobulin in the past 30 days;
End-stage renal disease on peritoneal dialysis and hemodialysis.
Control Group
The control group will consist of healthy individuals aged >18 years, who are household cohabitants or work colleagues of patients with rheumatic diseases in the intervention group.
Contact with a suspected or confirmed case of COVID-19 is defined as an individual sharing accommodations with a patient with a rheumatic disease (eg, residing in the same house or environment as roommates, occupational colleagues, etc). The exposure grade assessment is individualized, considering the type of environment and the exposure time.
For each case, two household and/or professional contact individuals will be selected as controls. The choice of the first control is prioritized by flu-like symptoms and defined as the “symptomatic group,” including suspected or confirmed cases. Those without symptoms will comprise the “asymptomatic group;” both household and/or contact individuals can be selected, preferably paired for age and sex.
The household and/or workplace contacts were chosen to characterize the control group because of their high epidemiological value during community viral transmissions worldwide, instead of including nonusers of antimalarials with rheumatic diseases. Moreover, lupus patients without antimalarial treatment are quite uncommon, except in those with previous toxicity (maculopathy, allergy, long-term remission, etc).
Data Collection
Data are being collected regarding social, epidemiological, and demographic characteristics, as well as detailed information on antimalarials (type of salt, dosage, frequency, adherence during the pandemic) and rheumatic disease (diagnosis, disease activity). In addition, aspects related to comorbidities, smoking, alcohol intake, and concomitant medications are being recorded, as well as specific information about COVID-19 symptoms and main outcomes (hospitalization, need for intensive care unit, and death) in both groups (Multimedia Appendix 1).
All phone interviews are being conducted by health care professionals (eg, volunteer medical students), all previously trained by the principal investigator or subinvestigator from each rheumatology center (Figure 1). This training included a tutorial in PDF and video formats about each step of the study protocol. In addition, several WhatsApp-based groups were formed and supervised by the principal investigator, subinvestigator, or study coordinators to find the best solution for minimizing eventual problems.
Figure 1.

Centers participating in the study.
All patients and controls gave a verbal informed consent before participating in this cohort study. The need for signed informed consent was waived by the Brazilian National Ethics Committee (CONEP) due to the urgency of the pandemic. However, it is worth emphasizing that participation was voluntary for both groups. Research subjects will not be identified by their full name at any time and will not have their personal data disclosed.
The data are being stored on the REDCap platform, with telephone interviews performed as shown in Figure 2. Interviews with patients with invalid contact information or who did not answer the telephone after three consecutive calls at intervals of 3 days were canceled, although patients were not removed from the study. All patients will be evaluated during the closing visit (V6), unless they decline to participate, regardless of whether intermediary visits were missed (V2 to V5).
Figure 2.

Telephone interview schedule.
A clinically confirmed case of COVID-19 was defined according to the Brazilian Ministry of Health criteria [50] that included self-reported symptoms (fever, cough, nasal congestion, shortness of breath, malaise, myalgia, decline in general condition, and sudden anosmia and/or dysgeusia) and/or have been in contact with someone with a confirmed or suspected case of COVID-19. A positive PCR (polymerase chain reaction) test for SARS-CoV-2, via oropharyngeal and nasopharyngeal sampling or a specific confirmatory serology (immunoglobulin G and/or immunoglobulin M), is needed to test for infection, according to the Brazilian Ministry of Health [50] (Figure 3).
Figure 3.

Suspected vs confirmed cases of COVID-19. RT-PCR: real-time polymerase chain reaction, IgM: immunoglobulin M, IgA: immunoglobulin A, IgG: immunoglobulin G, ELISA: enzyme-linked immunosorbent assay, IC: ion channel, ECLIA: electrochemiluminescence immunoassay.
Moderate-to-severe cases are defined as those that require hospitalization, mechanical ventilation, or result in death. Through direct contact with hospitals, hospitalized patients are being clinically evaluated in terms of longitudinal follow-up and treatment outcome, infection severity, length of stay, need for intensive care, mechanical ventilation, and cause of death.
Considering the heterogeneous community viral transmission in Brazil, some epidemiological approaches were developed to assure a similar path involving patients with rheumatic diseases and controls, such as the same pandemic COVID-19 curve in each city and region [41]. Therefore, after initial contact (V1), two strategies were adopted to maintain the follow-up of patients and to optimize the capture of main outcomes. Firstly, an active strategy is addressed in cases of flu-like syndrome and symptoms suggestive of COVID-19. For this strategy, the patient or household member is shown how to provide clinical data on the patient or his/her control through a toll-free telephone number (the 0800 system). Secondly, the patient is contacted every week by the REDCap team to gather relevant data on infection. An additional visit is conducted if the patient or control provides information about flu symptoms or disease activity via an unscheduled phone call or contact through the toll-free number. In both cases the individual will be advised to stay home and use painkillers or an antipyretic. In case of worsening/severe symptoms (eg, persistent cough or fever and shortness of breath), they will be advised to visit a hospital or to make an appointment with a physician involved in our study.
Outcomes
Primary outcomes (at baseline and during the 24-week study period) are as follows:
SARS-CoV-2 infection (illness): suspected, suggestive, or confirmed
Death
Hospitalization
Need for intensive care unit
Need for mechanical ventilation
Total hospitalization time
Date of occurrence of an adverse event (eg, death, hospitalization)
Secondary outcomes are as follows:
General clinical differences in COVID-19 course severity between rheumatic patients and nonrheumatic controls;
Initial clinical differences and progression to moderate or severe course of disease between the two groups.
Confounding and adjustment variables are age, sex, comorbidities, concomitant medications, and flu vaccine.
Ethics
This project was registered with the Brazilian Registry of Clinical Trials (ID RBR-9KTWX6).
The project, which is currently in the data collection phase, was approved by the Brazilian Committee of Ethics in Human Research–CONEP (CAAE 30246120.3.1001.5505).
Statistical Analysis
The data will be analyzed using descriptive statistics—absolute and relative frequencies for categorical variables and quantitative measures (mean, quartiles, minimum, maximum, and standard deviation) for numerical variables. The normality of the data will be verified using the Kolmogorov-Smirnov test.
A chi-square test will be used to assess the association between categorical variables with standardized adjusted residual calculation; Fisher exact test will be used for small samples. The linear associations between two variables of a numerical nature will be evaluated using Pearson correlation.
To evaluate the behavior of clinical variables between two points in time by group, analysis of variance (ANOVA) will be used, with repeated measures. In the case of nonnormality of data, the means of the groups at each time point will be compared using the Kruskal-Wallis nonparametric test. To compare the means between phone visits in each group, the Wilcoxon nonparametric test will be used.
The comparison between the means of numerical variables with normal distribution will be verified through the Student t test. If the assumption of normality is violated, the Mann-Whitney nonparametric test will be used.
Adjusted multiple linear regression models will be used to assess the simultaneous effects of sex, age, duration of illness, comorbidities, concomitant medications, and other confounding variables, according to group and predefined outcomes. For dichotomous dependent variables, a logistic regression model will be preferred. Survival analysis models, including log rank and Kaplan-Meier tests, adjusted for confounding variables, will be developed to assess the main outcomes over time. The time defined as the end date will be the date of a major event, such as illness with confirmation or suspicion of infection, hospitalization, or death.
Correlation analysis will be performed using the Pearson test to assess the relationship between the incidence rate of confirmed COVID-19 cases per 100,000 inhabitants and the proportion of symptomatic patients and controls in municipalities. Data of confirmed cases per municipality are available through the Brasil.io project [51]. The QGIGS Desktop 3.6.0 (Open Source Geospatial Foundation) will be used for map plotting.
SPSS, version 20 (IMB Corp) will be used in all analyses, and a P value <.05 will be considered significant.
Results
This study is in the data collection phase. Study recruitment opened in March 2020. In an 8-week period (from March 29 to May 17), a total of 10,443 individuals enrolled at baseline (including 5166 patients with rheumatic diseases) from 23 tertiary rheumatology centers in 97 Brazilian cities. Data analysis is scheduled to start after all relevant data have been collected.
Discussion
This study’s novel design, with its large sample of chronic antimalarial users, will enable us to perform a thorough prospective assessment (every 2 weeks) to explore whether vulnerability to SARS-CoV-2 infection may be associated with IMRD or to hydroxychloroquine after adjustments for cofounders, especially those related to other immunosuppressive drugs and comorbidities. On the other hand, it has some limitations, such as compliance and adherence; a potential shortage of HCQ (hydroxychloroquine) in some parts of our country; possible biases associated with recalling symptoms; inability to answer the phone (due to hospitalization or death), and lack of confirmatory tests (PCR tests for SARS-CoV-2 or antibody-based RNA [ribonucleic acid]) for all enrolled patients and controls, especially in those with nonsevere forms. Future randomized controlled trials may provide a better understanding of these differences.
Abbreviations
- ANOVA
analysis of variance
- CONEP
Brazilian National Ethics Committee
- IL-6
interleukin 6
- IMRD
immune-mediated rheumatic diseases
- MERS-CoV
Middle East respiratory syndrome coronavirus
- PCR
polymerase chain reaction
- RNA
ribonucleic acid
- SARS-CoV
severe acute respiratory syndrome–associated coronavirus
- V
visit
Appendix
Data collection form.
Footnotes
Conflicts of Interest: LM has received personal or institutional support from Abbvie, Janssen, Pfizer and Roche, and has delivered speeches at events related to this work and sponsored by Abbvie, Boehringer Ingelheim, GSK, Janssen, Libbs, Lilly, Novartis, Pfizer, Roche, Sandoz, and UCB. AG has received personal or institutional support from Pfizer and Abbvie.
References
- 1.Salata C, Calistri A, Parolin C, Palù Giorgio. Coronaviruses: a paradigm of new emerging zoonotic diseases. Pathog Dis. 2019 Dec 01;77(9):a. doi: 10.1093/femspd/ftaa006. http://europepmc.org/abstract/MED/32065221. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Li X, Wang W, Zhao X, Zai J, Zhao Q, Li Y, Chaillon A. Transmission dynamics and evolutionary history of 2019-nCoV. J Med Virol. 2020 May 14;92(5):501–511. doi: 10.1002/jmv.25701. http://europepmc.org/abstract/MED/32027035. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Bonini S, Maltese G. COVID-19 Clinical trials: Quality matters more than quantity. Allergy. 2020 May 20; doi: 10.1111/all.14409. http://europepmc.org/abstract/MED/32434272. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Teymoori-Rad M, Samadizadeh S, Tabarraei A, Moradi A, Shahbaz MB, Tahamtan A. Ten challenging questions about SARS-CoV-2 and COVID-19. Expert Rev Respir Med. 2020 Jun 30;:1–8. doi: 10.1080/17476348.2020.1782197. [DOI] [PubMed] [Google Scholar]
- 5.Khatami A. Filling in the gaps. J Paediatr Child Health. 2020 Aug 29;56(8):1172–1172. doi: 10.1111/jpc.15026. [DOI] [PubMed] [Google Scholar]
- 6.Fidahic M, Nujic D, Runjic R, Civljak M, Markotic F, Lovric Makaric Z, Puljak L. Research methodology and characteristics of journal articles with original data, preprint articles and registered clinical trial protocols about COVID-19. BMC Med Res Methodol. 2020 Jun 22;20(1):161. doi: 10.1186/s12874-020-01047-2. https://bmcmedresmethodol.biomedcentral.com/articles/10.1186/s12874-020-01047-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Polak SB, Van Gool IC, Cohen D, von der Thüsen Jan H, van Paassen J. A systematic review of pathological findings in COVID-19: a pathophysiological timeline and possible mechanisms of disease progression. Mod Pathol. 2020 Jun 22; doi: 10.1038/s41379-020-0603-3. http://europepmc.org/abstract/MED/32572155. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Chang D, Zhao P, Zhang D, Dong J, Xu Z, Yang G, Li B, Liu H, Li B, Qin C, Peng X, Wang F, Xie L, Chen Z, Dela Cruz CS, Sharma L, Qin E. Persistent Viral Presence Determines the Clinical Course of the Disease in COVID-19. J Allergy Clin Immunol Pract. 2020 Sep;8(8):2585–2591.e1. doi: 10.1016/j.jaip.2020.06.015. http://europepmc.org/abstract/MED/32574840. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Cleary S, Pitchford S, Amison R, Carrington R, Robaina CC, Magnen M. Animal models of mechanisms of SARS-CoV-2 infection and COVID-19 pathology. Br J Pharmacol. 2020:e. doi: 10.22541/au.158861365.54417186. https://www.authorea.com/users/317432/articles/447533-animal-models-of-sars-cov-2-infection-and-mechanisms-of-covid-19?commit=9720d3d8f3f06302b708c390507c2735e26884a7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Tu H, Tu S, Gao S, Shao A, Sheng J. Current epidemiological and clinical features of COVID-19; a global perspective from China. J Infect. 2020 Jul;81(1):1–9. doi: 10.1016/j.jinf.2020.04.011. http://europepmc.org/abstract/MED/32315723. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Hassan S, Sheikh F, Jamal S, Ezeh J, Akhtar A. Coronavirus (COVID-19): A Review of Clinical Features, Diagnosis, and Treatment. Cureus. 2020 Mar 21;12(3):e7355. doi: 10.7759/cureus.7355. http://europepmc.org/abstract/MED/32328367. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Park J, Jang W, Kim S, Lee J, Lim Y, Cho C, Park Seok-Won, Kim Bo Hae. The Clinical Manifestations and Chest Computed Tomography Findings of Coronavirus Disease 2019 (COVID-19) Patients in China: A Proportion Meta-Analysis. Clin Exp Otorhinolaryngol. 2020 May;13(2):95–105. doi: 10.21053/ceo.2020.00570. http://e-ceo.org/DOIx.php?id=10.21053/ceo.2020.00570. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Gulati A, Pomeranz C, Qamar Z, Thomas S, Frisch D, George G, Summer R, DeSimone J, Sundaram B. A Comprehensive Review of Manifestations of Novel Coronaviruses in the Context of Deadly COVID-19 Global Pandemic. Am J Med Sci. 2020 Jul;360(1):5–34. doi: 10.1016/j.amjms.2020.05.006. http://europepmc.org/abstract/MED/32620220. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Yang R, Gui X, Zhang Y, Xiong Y. The role of essential organ-based comorbidities in the prognosis of COVID-19 infection patients. Expert Rev Respir Med. 2020 Aug 28;14(8):835–838. doi: 10.1080/17476348.2020.1761791. http://europepmc.org/abstract/MED/32345072. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Asfahan S, Deokar K, Dutt N, Niwas R, Jain P, Agarwal M. Extrapolation of mortality in COVID-19: Exploring the role of age, sex, co-morbidities and health-care related occupation. Monaldi Arch Chest Dis. 2020 May 21;90(2) doi: 10.4081/monaldi.2020.1325. doi: 10.4081/monaldi.2020.1325. [DOI] [PubMed] [Google Scholar]
- 16.Singh AK, Gillies CL, Singh R, Singh A, Chudasama Y, Coles B, Seidu S, Zaccardi F, Davies MJ, Khunti K. Prevalence of co-morbidities and their association with mortality in patients with COVID-19: A systematic review and meta-analysis. Diabetes Obes Metab. 2020 Jun 23; doi: 10.1111/dom.14124. http://europepmc.org/abstract/MED/32573903. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Ji W, Huh K, Kang M, Hong J, Bae GH, Lee R, Na Y, Choi H, Gong SY, Choi Y, Ko K, Im J, Jung J. Effect of Underlying Comorbidities on the Infection and Severity of COVID-19 in Korea: a Nationwide Case-Control Study. J Korean Med Sci. 2020 Jun 29;35(25):e237. doi: 10.3346/jkms.2020.35.e237. https://jkms.org/DOIx.php?id=10.3346/jkms.2020.35.e237. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Ye C, Zhang S, Zhang X, Cai H, Gu J, Lian J, Lu Y, Jia H, Hu J, Jin C, Yu G, Zhang Y, Sheng J, Yang Y. Impact of comorbidities on patients with COVID-19: A large retrospective study in Zhejiang, China. J Med Virol. 2020 Jun 16; doi: 10.1002/jmv.26183. http://europepmc.org/abstract/MED/32543710. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Rabby Md Insiat Islam. Current Drugs with Potential for Treatment of COVID-19: A Literature Review. J Pharm Pharm Sci. 2020 Apr 04;23(1):58–64. doi: 10.18433/jpps31002. doi: 10.18433/jpps31002. [DOI] [PubMed] [Google Scholar]
- 20.Xu X, Ong YK, Wang DY. Role of adjunctive treatment strategies in COVID-19 and a review of international and national clinical guidelines. Mil Med Res. 2020 May 05;7(1):22. doi: 10.1186/s40779-020-00251-x. https://mmrjournal.biomedcentral.com/articles/10.1186/s40779-020-00251-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Luo P, Liu Y, Qiu L, Liu X, Liu D, Li J. Tocilizumab treatment in COVID-19: A single center experience. J Med Virol. 2020 Jul 15;92(7):814–818. doi: 10.1002/jmv.25801. http://europepmc.org/abstract/MED/32253759. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Zumla A, Hui DS, Azhar EI, Memish ZA, Maeurer M. Reducing mortality from 2019-nCoV: host-directed therapies should be an option. The Lancet. 2020 Feb;395(10224):e35–e36. doi: 10.1016/s0140-6736(20)30305-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Hung I, Lung K, Tso E, Liu R, Chung T, Chu M, Ng Y, Lo J, Chan J, Tam Ar, Shum H, Chan V, Wu Ak, Sin K, Leung W, Law W, Lung Dc, Sin S, Yeung P, Yip Cc, Zhang Rr, Fung Ay, Yan Ey, Leung K, Ip Jd, Chu Aw, Chan W, Ng Ac, Lee R, Fung K, Yeung A, Wu T, Chan Jw, Yan W, Chan W, Chan Jf, Lie Ak, Tsang Ot, Cheng Vc, Que T, Lau C, Chan K, To Kk, Yuen K. Triple combination of interferon beta-1b, lopinavir–ritonavir, and ribavirin in the treatment of patients admitted to hospital with COVID-19: an open-label, randomised, phase 2 trial. The Lancet. 2020 May;395(10238):1695–1704. doi: 10.1016/S0140-6736(20)31042-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Venkatasubbaiah M, Dwarakanadha Reddy P, Satyanarayana SV. Literature-based review of the drugs used for the treatment of COVID-19. Curr Med Res Pract. 2020 May;10(3):100–109. doi: 10.1016/j.cmrp.2020.05.013. http://europepmc.org/abstract/MED/32572376. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Zhang L, Liu Y. Potential interventions for novel coronavirus in China: A systematic review. J Med Virol. 2020 May 03;92(5):479–490. doi: 10.1002/jmv.25707. http://europepmc.org/abstract/MED/32052466. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Juul S, Nielsen N, Bentzer P, Veroniki AA, Thabane L, Linder A, Klingenberg S, Gluud C, Jakobsen JC. Interventions for treatment of COVID-19: a protocol for a living systematic review with network meta-analysis including individual patient data (The LIVING Project) Syst Rev. 2020 May 09;9(1):108. doi: 10.1186/s13643-020-01371-0. https://systematicreviewsjournal.biomedcentral.com/articles/10.1186/s13643-020-01371-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Jean S, Lee P, Hsueh P. Treatment options for COVID-19: The reality and challenges. J Microbiol Immunol Infect. 2020 Jun;53(3):436–443. doi: 10.1016/j.jmii.2020.03.034. https://linkinghub.elsevier.com/retrieve/pii/S1684-1182(20)30094-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Pastick K, Okafor E, Wang F, Lofgren S, Skipper C, Nicol M, Pullen Matthew F, Rajasingham Radha, McDonald Emily G, Lee Todd C, Schwartz Ilan S, Kelly Lauren E, Lother Sylvain A, Mitjà Oriol, Letang Emili, Abassi Mahsa, Boulware David R. Review: Hydroxychloroquine and Chloroquine for Treatment of SARS-CoV-2 (COVID-19) Open Forum Infect Dis. 2020 Apr;7(4):ofaa130. doi: 10.1093/ofid/ofaa130. http://europepmc.org/abstract/MED/32363212. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Saqrane S, El Mhammedi M. Review on the global epidemiological situation and the efficacy of chloroquine and hydroxychloroquine for the treatment of COVID-19. New Microbes New Infect. 2020 May;35:100680. doi: 10.1016/j.nmni.2020.100680. https://linkinghub.elsevier.com/retrieve/pii/S2052-2975(20)30032-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Sun J, Chen Y, Fan X, Wang X, Han Q, Liu Z. Advances in the use of chloroquine and hydroxychloroquine for the treatment of COVID-19. Postgrad Med. 2020 Jun 21;:1–10. doi: 10.1080/00325481.2020.1778982. http://europepmc.org/abstract/MED/32496926. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Meo S, Klonoff D, Akram J. Efficacy of chloroquine and hydroxychloroquine in the treatment of COVID-19. Eur Rev Med Pharmacol Sci. 2020 Apr;24(8):4539–4547. doi: 10.26355/eurrev_202004_21038. https://www.europeanreview.org/article/21038. [DOI] [PubMed] [Google Scholar]
- 32.Al-Bari MAA. Facts and myths: Efficacies of repurposing chloroquine and hydroxychloroquine for the treatment of COVID-19. Curr Drug Targets. 2020 Jun 17;21 doi: 10.2174/1389450121666200617133142. [DOI] [PubMed] [Google Scholar]
- 33.Shukla AM, Archibald LK, Wagle Shukla A, Mehta HJ, Cherabuddi K. Chloroquine and hydroxychloroquine in the context of COVID-19. Drugs Context. 2020 Apr 28;9:1–8. doi: 10.7573/dic.2020-4-5. doi: 10.7573/dic.2020-4-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Sarma P, Kaur H, Kumar H, Mahendru D, Avti P, Bhattacharyya A, Prajapat M, Shekhar N, Kumar S, Singh R, Singh A, Dhibar DP, Prakash A, Medhi B. Virological and clinical cure in COVID-19 patients treated with hydroxychloroquine: A systematic review and meta-analysis. J Med Virol. 2020 Jul 03;92(7):776–785. doi: 10.1002/jmv.25898. http://europepmc.org/abstract/MED/32297988. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Liu W, Zhou P, Chen K, Ye Z, Liu F, Li X, He N, Wu Z, Zhang Q, Gong X, Tang Q, Du X, Ying Y, Xu X, Zhang Y, Liu J, Li Y, Shen N, Couban RJ, Ibrahim QI, Guyatt G, Zhai S. Efficacy and safety of antiviral treatment for COVID-19 from evidence in studies of SARS-CoV-2 and other acute viral infections: a systematic review and meta-analysis. CMAJ. 2020 Jul 06;192(27):E734–E744. doi: 10.1503/cmaj.200647. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Dos Reis Neto Edgard Torres, Kakehasi AM, de Medeiros Pinheiro M, Ferreira GA, Marques CDL, da Mota LMH, Dos Santos Paiva Eduardo, Pileggi GCS, Sato EI, Reis APMG, Xavier RM, Provenza JR. Revisiting hydroxychloroquine and chloroquine for patients with chronic immunity-mediated inflammatory rheumatic diseases. Adv Rheumatol. 2020 Jun 09;60(1):32. doi: 10.1186/s42358-020-00134-8. http://europepmc.org/abstract/MED/32517786. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Graef ER, Liew JW, Putman MS, Simard JF, Sirotich E, Berenbaum F, Duarte-García Alí, Grainger R, Harrison C, Konig MF, Korsten P, Proulx L, Richards DP, Robinson PC, Sattui SE, Ugarte-Gil MF, Young KJ, Kim AH, Sparks JA, COVID-19 Global Rheumatology Alliance : hydroxychloroquine, COVID-19 and the role of the rheumatologist. Ann Rheum Dis. 2020 Jun 15;79(6):734–736. doi: 10.1136/annrheumdis-2020-217480. http://europepmc.org/abstract/MED/32295786. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38.Misra DP, Agarwal V, Gasparyan AY, Zimba O. Rheumatologists' perspective on coronavirus disease 19 (COVID-19) and potential therapeutic targets. Clin Rheumatol. 2020 Jul 10;39(7):2055–2062. doi: 10.1007/s10067-020-05073-9. http://europepmc.org/abstract/MED/32277367. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39.Felten R, Chatelus E, Arnaud L. How and why are rheumatologists relevant to COVID-19? Joint Bone Spine. 2020 Jul;87(4):279–280. doi: 10.1016/j.jbspin.2020.04.006. http://europepmc.org/abstract/MED/32451147. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40.Coronavirus disease 2019 (COVID-19) — Situation Report – 51. World Health Organization. 2020. [2020-06-01]. https://www.who.int/docs/default-source/coronaviruse/situation-reports/20200311-sitrep-51-covid-19.pdf?sfvrsn=1ba62e57_10.
- 41.Candido DS, Claro IM, de Jesus JG, Souza WM, Moreira FRR, Dellicour S, Mellan TA, du Plessis L, Pereira RHM, Sales FCS, Manuli ER, Thézé Julien, Almeida L, Menezes MT, Voloch CM, Fumagalli MJ, Coletti TM, da Silva CAM, Ramundo MS, Amorim MR, Hoeltgebaum HH, Mishra S, Gill MS, Carvalho LM, Buss LF, Prete CA, Ashworth J, Nakaya HI, Peixoto PS, Brady OJ, Nicholls SM, Tanuri A, Rossi AD, Braga CKV, Gerber AL, de C Guimarães Ana Paula, Gaburo N, Alencar CS, Ferreira ACS, Lima CX, Levi JE, Granato C, Ferreira GM, Francisco RS, Granja F, Garcia MT, Moretti ML, Perroud MW, Castiñeiras Terezinha M P P, Lazari CS, Hill SC, de Souza Santos AA, Simeoni CL, Forato J, Sposito AC, Schreiber AZ, Santos MNN, de Sá Camila Zolini, Souza RP, Resende-Moreira LC, Teixeira MM, Hubner J, Leme PAF, Moreira RG, Nogueira ML, Brazil-UK Centre for Arbovirus Discovery‚ Diagnosis‚ GenomicsEpidemiology (CADDE) Genomic Network. Ferguson Neil M, Costa Silvia F, Proenca-Modena José Luiz, Vasconcelos Ana Tereza R, Bhatt Samir, Lemey Philippe, Wu Chieh-Hsi, Rambaut Andrew, Loman Nick J, Aguiar Renato S, Pybus Oliver G, Sabino Ester C, Faria Nuno Rodrigues. Evolution and epidemic spread of SARS-CoV-2 in Brazil. Science. 2020 Sep 04;369(6508):1255–1260. doi: 10.1126/science.abd2161. http://europepmc.org/abstract/MED/32703910. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42.Michaud K, Wipfler K, Shaw Y, Simon TA, Cornish A, England BR, Ogdie A, Katz P. Experiences of Patients With Rheumatic Diseases in the United States During Early Days of the COVID-19 Pandemic. ACR Open Rheumatol. 2020 Jun 09;2(6):335–343. doi: 10.1002/acr2.11148. doi: 10.1002/acr2.11148. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43.Aletaha Daniel, Neogi Tuhina, Silman Alan J, Funovits Julia, Felson David T, Bingham Clifton O, Birnbaum Neal S, Burmester Gerd R, Bykerk Vivian P, Cohen Marc D, Combe Bernard, Costenbader Karen H, Dougados Maxime, Emery Paul, Ferraccioli Gianfranco, Hazes Johanna M W, Hobbs Kathryn, Huizinga Tom W J, Kavanaugh Arthur, Kay Jonathan, Kvien Tore K, Laing Timothy, Mease Philip, Ménard Henri A, Moreland Larry W, Naden Raymond L, Pincus Theodore, Smolen Josef S, Stanislawska-Biernat Ewa, Symmons Deborah, Tak Paul P, Upchurch Katherine S, Vencovský Jirí, Wolfe Frederick, Hawker Gillian. 2010 Rheumatoid arthritis classification criteria: an American College of Rheumatology/European League Against Rheumatism collaborative initiative. Arthritis Rheum. 2010 Sep 10;62(9):2569–81. doi: 10.1002/art.27584. doi: 10.1002/art.27584. [DOI] [PubMed] [Google Scholar]
- 44.Aringer M, Costenbader KH, Daikh David, Brinks Ralph, Mosca Marta, Ramsey-Goldman Rosalind, Smolen Josef S, Wofsy David, Boumpas Dimitrios T, Kamen Diane L, Jayne David, Cervera Ricard, Costedoat-Chalumeau Nathalie, Diamond Betty, Gladman Dafna D, Hahn Bevra, Hiepe Falk, Jacobsen Søren, Khanna Dinesh, Lerstrøm Kirsten, Massarotti Elena, McCune Joseph, Ruiz-Irastorza Guillermo, Sanchez-Guerrero Jorge, Schneider Matthias, Urowitz Murray, Bertsias George, Hoyer Bimba F, Leuchten Nicolai, Tani Chiara, Tedeschi Sara K, Touma Zahi, Schmajuk Gabriela, Anic Branimir, Assan Florence, Chan Tak Mao, Clarke Ann Elaine, Crow Mary K, Czirják László, Doria Andrea, Graninger Winfried, Halda-Kiss Bernadett, Hasni Sarfaraz, Izmirly Peter M, Jung Michelle, Kumánovics Gábor, Mariette Xavier, Padjen Ivan, Pego-Reigosa José M, Romero-Diaz Juanita, Rúa-Figueroa Fernández Íñigo, Seror Raphaèle, Stummvoll Georg H, Tanaka Yoshiya, Tektonidou Maria G, Vasconcelos Carlos, Vital Edward M, Wallace Daniel J, Yavuz Sule, Meroni Pier Luigi, Fritzler Marvin J, Naden Ray, Dörner Thomas, Johnson Sindhu R. 2019 European League Against Rheumatism/American College of Rheumatology Classification Criteria for Systemic Lupus Erythematosus. Arthritis Rheumatol. 2019 Sep 04;71(9):1400–1412. doi: 10.1002/art.40930. doi: 10.1002/art.40930. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 45.Shiboski CH, Shiboski SC, Seror R, Criswell LA, Labetoulle M, Lietman TM, Rasmussen A, Scofield H, Vitali C, Bowman SJ, Mariette X, International Sjögren's Syndrome Criteria Working Group 2016 American College of Rheumatology/European League Against Rheumatism classification criteria for primary Sjögren's syndrome: A consensus and data-driven methodology involving three international patient cohorts. Ann Rheum Dis. 2017 Jan 26;76(1):9–16. doi: 10.1136/annrheumdis-2016-210571. [DOI] [PubMed] [Google Scholar]
- 46.van den Hoogen Frank, Khanna D, Fransen J, Johnson S, Baron M, Tyndall Alan, Matucci-Cerinic Marco, Naden Raymond P, Medsger Thomas A, Carreira Patricia E, Riemekasten Gabriela, Clements Philip J, Denton Christopher P, Distler Oliver, Allanore Yannick, Furst Daniel E, Gabrielli Armando, Mayes Maureen D, van Laar Jacob M, Seibold James R, Czirjak Laszlo, Steen Virginia D, Inanc Murat, Kowal-Bielecka Otylia, Müller-Ladner Ulf, Valentini Gabriele, Veale Douglas J, Vonk Madelon C, Walker Ulrich A, Chung Lorinda, Collier David H, Csuka Mary Ellen, Fessler Barri J, Guiducci Serena, Herrick Ariane, Hsu Vivien M, Jimenez Sergio, Kahaleh Bashar, Merkel Peter A, Sierakowski Stanislav, Silver Richard M, Simms Robert W, Varga John, Pope Janet E. 2013 classification criteria for systemic sclerosis: an American College of Rheumatology/European League against Rheumatism collaborative initiative. Arthritis Rheum. 2013 Nov;65(11):2737–47. doi: 10.1002/art.38098. doi: 10.1002/art.38098. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 47.Lundberg Ingrid E, Tjärnlund Anna, Bottai Matteo, Werth Victoria P, Pilkington Clarissa, de Visser Marianne, Alfredsson Lars, Amato Anthony A, Barohn Richard J, Liang Matthew H, Singh Jasvinder A, Aggarwal Rohit, Arnardottir Snjolaug, Chinoy Hector, Cooper Robert G, Dankó Katalin, Dimachkie Mazen M, Feldman Brian M, Garcia-De La Torre Ignacio, Gordon Patrick, Hayashi Taichi, Katz James D, Kohsaka Hitoshi, Lachenbruch Peter A, Lang Bianca A, Li Yuhui, Oddis Chester V, Olesinska Marzena, Reed Ann M, Rutkowska-Sak Lidia, Sanner Helga, Selva-O'Callaghan Albert, Song Yeong-Wook, Vencovsky Jiri, Ytterberg Steven R, Miller Frederick W, Rider Lisa G, International Myositis Classification Criteria Project Consortium‚ the Euromyositis Register‚the Juvenile Dermatomyositis Cohort Biomarker StudyRepository (UKIreland) 2017 European League Against Rheumatism/American College of Rheumatology Classification Criteria for Adult and Juvenile Idiopathic Inflammatory Myopathies and Their Major Subgroups. Arthritis Rheumatol. 2017 Dec 10;69(12):2271–2282. doi: 10.1002/art.40320. doi: 10.1002/art.40320. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 48.Kasukawa R. Mixed connective tissue disease. Intern Med. 1999 May;38(5):386–93. doi: 10.2169/internalmedicine.38.386. https://joi.jlc.jst.go.jp/JST.Journalarchive/internalmedicine1992/38.386?from=PubMed. [DOI] [PubMed] [Google Scholar]
- 49.Altman R, Alarcón G, Appelrouth D, Bloch D, Borenstein D, Brandt K, Brown C, Cooke TD, Daniel W, Gray R. The American College of Rheumatology criteria for the classification and reporting of osteoarthritis of the hand. Arthritis Rheum. 1990 Nov;33(11):1601–10. doi: 10.1002/art.1780331101. [DOI] [PubMed] [Google Scholar]
- 50.Ministry of Health (BR) Health Surveillance Secretariat. Public Health Emergency Operations Center Coronavirus disease 2019: expansion of surveillance, non-pharmacological measures and decentralization of laboratory diagnosis. 2020. Mar, [2020-06-01]. http://maismedicos.gov.br/images/PDF/2020_03_13_Boletim-Epidemiologico-05.pdf.
- 51.Especial COVID-19: Dados Por Município. Brasil.io. 2020. [2020-06-01]. https://brasil.io/home/
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