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COVID-19 Pandemic and Virtual Clinics for Diabetes Care

2021; Mary Ann Liebert, Inc.; Volume: 23; Issue: S2 Linguagem: Inglês

10.1089/dia.2021.2501

1557-8593

Satish K. Garg, Trenton Reinicke,

SARS-CoV-2 and COVID-19 Research

Diabetes Technology & TherapeuticsVol. 23, No. S2 Original ArticlesOpen AccessCOVID-19 Pandemic and Virtual Clinics for Diabetes CareSatish K. Garg and Trenton ReinickeSatish K. GargBarbara Davis Center for Diabetes, University of Colorado, Denver, COSearch for more papers by this author and Trenton ReinickeBarbara Davis Center for Diabetes, University of Colorado, Denver, COSearch for more papers by this authorPublished Online:31 May 2021https://doi.org/10.1089/dia.2021.2501AboutSectionsPDF/EPUB Permissions & CitationsPermissionsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookXLinked InRedditEmail IntroductionWe are delighted to author this critical article on COVID-19 and diabetes in the ATTD 2020 Yearbook. It is thought-provoking to remember the last conference (13th International Conference on Advanced Technologies & Treatments for Diabetes in February 2020) held in Madrid, Spain. It is especially hard to believe that it was the last sizable (attended by nearly 4000 participants) international in-person conference. It is shocking to witness the venue utilized for the 2020 ATTD Conference being converted into a makeshift hospital for COVID-19 patients just a few months later. At the time of this writing, it is still unknown whether we will have an in-person meeting for the next ATTD Conference to be held in February 2021 in Paris, France. All the data presented in this article will be outdated by the time this manuscript is read. The data in this manuscript was collected in August 2020, and many of the findings will be quite different by February 2021.Coronaviruses are a large family of viruses that are enveloped-positive-strain RNA viruses. There are many pathogenic coronaviruses found in humans, specifically severe acute respiratory syndrome coronavirus (SARS-CoV), Middle East respiratory virus coronavirus (MERS-CoV), and the current novel SARS-CoV-2 virus, commonly referred to as COVID-19, which has caused a global pandemic. The primary mode of transmission for COVID-19 is human-to-human contact, and it is frequently spread by asymptomatic carriers, some of which are found to be “super spreaders.” The COVID-19 infection started in Wuhan, China, in December 2019 and later spread to Europe, the United States, and the rest of the world.Since December 2019, the COVID-19 outbreak has affected more than 212 countries, translating to more than 20 million cases of the virus worldwide at the time of this writing, with >5 million cases in the United States alone. Other countries reporting higher numbers of COVID-19 patients are Brazil and India. More than 700,000 people have died from COVID-19 across the globe; specifically, in the United States and South America there have been more than 8 million cases reported, with a total of 370,000 deaths due to the virus. The exact prevalence of the infection is currently unknown. However, it is commonly believed that ∼60%–70% of the population will need to be infected for herd immunity to be effective.Research demonstrates that nearly one-third of patients with severe COVID-19 who are admitted to the intensive care units (ICUs) in the United States have diabetes. The incidence of diabetes and hypertension in ICU patients with COVID-19 is about two-fold higher than in non-ICU patients. Specifically, the prevalence of diabetes is about three-fold higher in COVID-19 patients with severe complications than that of nonsevere cases (about 16% vs. 5.7%, respectively). Patients with diabetes (both type 1 and type 2) face a higher risk of morbidity and mortality associated with COVID-19. Recent United Kingdom National Health Service (UK NHS) data illustrate that people with type 1 diabetes and poor glucose control (HbA1c above 8.5%) have a 3.5-fold higher risk of death from COVID-19 than those without diabetes, whereas among individuals with type 2 diabetes and poor glucose control there is a two-time higher risk of death from COVID-19 than those without diabetes.The COVID-19 global pandemic has affected healthcare (clinical and research) enormously, with devastating consequences physically, socially, and economically. The global economic impact of COVID-19 is unspeakable, with the world seeing drastically reduced gross domestic product growth, recession-level impacts, and the possibility of entering another depression. The healthcare impact, as it relates to diabetes, has been enormous, in turn, affecting not only clinical care but clinical research as well. Since many localities had stay-at-home, safer-at-home, or other lockdown orders, most of the economy came to a screeching halt. Unfortunately, these social distancing restrictions have affected many chronic conditions, like diabetes, adversely. Of all the catastrophic results from the pandemic, a silver lining may be the emergence of telehealth and virtual care as an alternative way to deliver ongoing and efficient care to patients with diabetes.As one can imagine, it has been difficult to choose only a handful of abstracts for this article, as there have been thousands of manuscripts written since the pandemic started. In this opening article of the ATTD 2020 Yearbook on the COVID-19 pandemic and diabetes, we plan to discuss the following topics: 1.Testing for the virus (antigens, reverse-transcription polymerase chain reaction [RT-PCR], and antibodies)2.Associated morbidity and mortality with COVID-193.Emerging medications for possible use in COVID-19 patients4.The role of virtual or telehealth through emerging technologies like continuous glucose monitors (CGM), insulin pumps, and hybrid closed-loop systems5.Treatment options with convalescent serum from patients who recovered from COVID-19 infections6.Possible COVID-19 vaccinationsKey Articles Reviewed for the ArticleDiagnostic performance of COVID-19 serology assayZainol Rashid Z, Othman SN, Abdul Samat MN, Ali UK, Wong KKMalays J Pathol 2020;42: 13–21Antibody detection and dynamic characteristics in patients with COVID-19Xiang F, Wang X, He X, Peng Z, Yang B, Zhang J, Zhou Q, Ye H, Ma Y, Li H, Wei X, Cai P, Ma W-LClin Infect Dis 2020;71: 1930–1934Antibody tests for identification of current and past infection with SARS-CoV-2Deeks JJ, Dinnes J, Takwoingi Y, Davenport C, Spijker R, Taylor-Phillips S, Adriano A, Beese S, Dretzke J, Ferrante di Ruffano L, Harris IM, Price MJ, Dittrich S, Emperador D, Hooft L, Leeflang MM, Van den Bruel A, Cochrane COVID-19 Diagnostic Test Accuracy GroupCochrane Database Syst Rev 2020;6: CD013652Convergent antibody responses to SARS-CoV-2 in convalescent individualsRobbiani DF, Gaebler C, Muecksch F, Lorenzi JCC, Wang Z, Cho A, Agudelo M, Barnes CO, Gazumyan A, Finkin S, Hagglof T, Oliveira TY, Viant C, Hurley A, Hoffmann HH, Millard KG, Kost RG, Cipolla M, Gordon K, Bianchini F, Chen ST, Ramos V, Patel R, Dizon J, Shimeliovich I, Mendoza P, Hartweger H, Nogueira L, Pack M, Horowitz J, Schmidt F, Weisblum Y, Michailidis E, Ashbrook AW, Waltari E, Pak JE, Huey-Tubman KE, Koranda N, Hoffman PR, West AP Jr, Rice CM, Hatziioannou T, Bjorkman PJ, Bieniasz PD, Caskey M, Nussenzweig MCNature 2020;584: 437–442The silver lining to COVID-19: avoiding diabetic ketoacidosis admissions with telehealthPeters AL, Garg SKDiabetes Technol Ther 2020;22: 449–453Hypoglycemia at the time of Covid-19 pandemicShah K, Tiwaskar M, Chawla P, Kale M, Deshmane R, Sowani ADiabetes Metab Syndr 2020;14: 1143–1146Kawasaki-like multisystem inflammatory syndrome in children during the Covid-19 pandemic in Paris, France: prospective observational studyToubiana J, Poirault C, Corsia A, Bajolle F, Fourgeaud J, Angoulvant F, Debray A, Basmaci R, Salvador E, Biscardi S, Frange P, Chalumeau M, Casanova J-L, Cohen JF, Slimane ABMJ 2020;369: m2094An outbreak of severe Kawasaki-like disease at the Italian epicentre of the SARS-CoV-2 epidemic: an observational cohort studyVerdoni L, Mazza A, Gervasoni A, Martelli L, Ruggeri M, Ciuffreda M, Bonanomi E, D'Antiga LLancet 2020;395: 1771–1778Observational study of hydroxychloroquine in hospitalized patients with Covid-19Galerius J, Sun Y, Platt J, Zucker J, Baldwin M, Hripcsak G, Labella A, Manson DK, Kubin C, Barr RG, Sobieszczyk ME, Schluger NWN Engl J Med 2020;382: 2411–2418Renin-angiotensin-aldosterone system inhibitors and risk of Covid-19Reynolds HR, Adhikari S, Pulgarin C, Troxel AB, Iturrate E, Johnson SB, Hausvater A, Newman JD, Berger JS, Bangalore S, Katz SD, Fishman GI, Kunichoff D, Chen Y, Ogedegbe G, Hochman JSN Engl J Med 2020;382: 2441–2448Compassionate use of remdesivir for patients with severe Covid-19Grein J, Ohmagari N, Shin D, Diaz G, Asperges E, Castagna A, Feldt T, Green G, Green ML, Lescure F-X, Nicastri E, Oda R, Yo K, Quiros-Roldan E, Studemeister A, Redinski J, Ahmed S, Bernett J, Chelliah D, Chen D, Chihara S, Cohen SH, Cunningham J, D'Arminio Monforte A, Ismail S, Kato H, Lapadula G, L'Her E, Maeno T, Majumder S, Massari M, Mora-Rillo M, Mutoh Y, Nguyen D, Verweij E, Zoufaly A, Osinusi AO, DeZure A, Zhao Y, Zhong L, Chokkalingam A, Elboudwarej E, Telep L, Timbs L, Henne I, Sellers S, Cao H, Tan SK, Winterbourne L, Desai P, Mera R, Gaggar A, Myers RP, Brainard DM, Childs R, Flanigan TN Engl J Med 2020;382: 2327–2336Short-term dexamethasone in Sars-CoV-2 patientsSelvaraj V, Dapaah-Afriyie K, Finn A, Flanigan TPR I Med J (2013) 2020;103: 39–43Managing diabetes in pregnancy before, during, and after COVID-19Murphy HRDiabetes Technol Ther 2020;22: 454–461Managing new-onset type 1 diabetes during the COVID-19 pandemic: challenges and opportunitiesGarg SK, Rodbard D, Hirsch IB, Forlenza GPDiabetes Technol Ther 2020;22: 431–439Inpatient transition to virtual care during COVID-19 pandemicJones MS, Goley AL, Alexander BE, Keller SB, Caldwell MM, Buse JBDiabetes Technol Ther 2020;22: 444–448Diagnostic performance of COVID-19 serology assayZainol Rashid Z, Othman SN, Abdul Samat MN, Ali UK, Wong KKUniversiti Kebangsaan Malaysia Medical Centre, Faculty of Medicine, Department of Medical Microbiology & Immunology, Kuala Lumpur, MalaysiaMalays J Pathol 2020;42: 13–21BackgroundThe World Health Organization (WHO) declared COVID-19 a world pandemic on March 12, 2020. Using respiratory samples, suspected cases can be confirmed by nucleic acid assays with real-time PCR. Serology tests are comparatively easier to perform, but their usefulness may be limited by their performance and because antibodies can appear later in the course of the disease. The goal of this paper is to describe the performance data on serological assays for COVID-19.MethodsWe reviewed multiple reports and kit inserts on the diagnostic performance of commercially available rapid tests from various manufacturers. Only preliminary data are currently available.ResultsFrom a total of nine rapid detection test (RDT) kits, three kits offer total antibody detection while six kits offer combination SARS-CoV-2 IgM and IgG detection in two separate test lines. All kits use whole blood, serum, or plasma samples and are based on colloidal gold-labeled immunochromatography principle and one-step method, with results obtained within 15 minutes. The sensitivity for both IgM and IgG tests ranges between 72.7% and 100%, while specificity ranges between 98.7% and 100%. Also reviewed in this paper are two immunochromatography processes using nasopharyngeal or throat swab for detection of COVID-19 specific antigen.ConclusionsThere is a great deal to determine regarding the value of serological testing in COVID-19 diagnosis and monitoring. More comprehensive evaluations of this form of testing are rapidly under way. The use of serology methods requires appropriate interpretation of the results and understanding of the strengths and limitations of such tests.Antibody detection and dynamic characteristics in patients with COVID-19Xiang F1, Wang X1, He X1, Peng Z2, Yang B1, Zhang J1, Zhou Q1, Ye H3, Ma Y1, Li H1, Wei X1, Cai P4, Ma W-L11Department of Respiratory and Critical Care Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; 2School of Urban Design, Wuhan University, Wuhan, China; 3Department of Pathophysiology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; 4Department of Clinical Laboratory, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, ChinaClin Infect Dis 2020;71: 1930–1934BackgroundThe corona virus disease 2019 (COVID-19), which is caused by the corona virus 2 (SARS-CoV-2), has been rapidly spreading nationwide and abroad. A serologic test to identify antibody dynamics and response to SARS-CoV-2 was developed.MethodsNucleic acid testing by RT-PCR for SARS-CoV-2 was the gold standard for COVID-19 diagnosis. At 3–40 days after symptom onset, the antibodies against SARS-CoV-2 were detected by an enzyme-linked immunosorbent assay (ELISA) based on the recombinant nucleocapsid protein of SARS-CoV-2 in patients with confirmed or suspected COVID-19. The serodiagnostic power of the specific IgM and IgG antibodies against SARS-CoV-2 was investigated in terms of sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and consistency rate.ResultsAs early as the fourth day after symptom onset, the seroconversion of specific IgM and IgG antibodies was observed. In patients confirmed with COVID-19, sensitivity, specificity, PPV, NPV, and consistency rate of IgM were 77.3% (51/66), 100%, 100%, 80.0%, and 88.1%, respectively, and those of IgG were 83.3.3% (55/66), 95.0%, 94.8%, 83.8%, and 88.9%, respectively. In patients suspected with COVID-19, sensitivity, specificity, PPV, NPV, and consistency rate of IgM were 87.5% (21/24), 100%, 100%, 95.2%, and 96.4%, respectively, and those of IgG were 70.8% (17/24), 96.6%, 85.0%, 89.1%, and 88.1%, respectively. Both antibodies that performed well in serodiagnosis for COVID-19 rely on great specificity.ConclusionsThe antibodies against SARS-CoV-2 can be detected in the middle and later stage of the illness. Antibody detection may play an important role in the diagnosis of COVID-19 as an approach that complements viral nucleic acid assays.Antibody tests for identification of current and past infection with SARS-CoV-2Deeks JJ1,2, Dinnes J1,2, Takwoingi Y1,2, Davenport C1,2, Spijker R3,4, Taylor-Phillips S1,5, Adriano A1, Beese S1, Dretzke J1, Ferrante di Ruffano L1, Harris IM1, Price MJ1,2, Dittrich S6, Emperador D6, Hooft L4, Leeflang MM7,8, Van den Bruel A9; Cochrane COVID-19 Diagnostic Test Accuracy Group1Test Evaluation Research Group, Institute of Applied Health Research, University of Birmingham, Birmingham, UK; 2 NIHR Birmingham Biomedical Research Centre, University Hospitals Birmingham NHS Foundation Trust and University of Birmingham, Birmingham, UK; 3Medical Library, Amsterdam UMC, University of Amsterdam, Amsterdam Public Health, Amsterdam, Netherlands; 4Cochrane Netherlands, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands; 5Division of Health Sciences, Warwick Medical School, University of Warwick, Coventry, UK; 6FIND, Geneva, Switzerland; 7Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, Netherlands; 8Biomarker and Test Evaluation Programme (BiTE), Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands; 9Department of Public Health and Primary Care, KU Leuven, Leuven, BelgiumCochrane Database Syst Rev 2020;6: CD013652BackgroundSARS-CoV-2 virus and the resulting COVID-19 pandemic pose important diagnostic concerns. Several strategies are available to diagnose current infection, rule out infection, identify patients in need of care escalation, or test for previous infection and immune response. Serology tests that detect the antibodies to SARS-CoV-2 aim to identify prior SARS-CoV-2 infection and may help confirm current infection.MethodsThis paper aims to assess the diagnostic accuracy of antibody tests to determine if a person in the community or in primary or secondary care has SARS-CoV-2 infection, or has had SARS-CoV-2 infection in the past, as well as the accuracy of antibody tests for use in seroprevalence surveys. We performed electronic searches in both the Cochrane COVID-19 Study Register and the COVID-19 Living Evidence Database from the University of Bern, which is updated daily with published articles from PubMed and Embase and with preprints from medRxiv and bioRxiv. In addition, we looked at repositories of COVID-19 publications and did not apply any language restrictions. We ran searches for this review iteration until April 27, 2020. We included test accuracy studies of any design that evaluated antibody tests (including enzyme-linked immunosorbent assays, chemiluminescence immunoassays, and lateral flow assays) in patients suspected of current or previous SARS-CoV-2 infection, or wherever tests were used to detect infection. We also included studies of patients either known to have, or not to have, SARS-CoV-2 infection. We included all reference standards to define the presence or absence of SARS-CoV-2 (including RT-PCR and clinical diagnostic criteria). We assessed potential bias and applicability of the studies using the QUADAS-2 tool. We extracted two-by-two contingency table data and presented sensitivity and specificity for each antibody (or combination of antibodies) using paired forest plots. We pooled data with random-effects logistic regression as appropriate, stratifying by time since post-symptom onset. We tabulated available data by test manufacturer. We have presented uncertainty in estimates of sensitivity and specificity using 95% confidence intervals (CIs).ResultsWe included 57 publications reporting on a total of 54 study cohorts with 15,976 samples, of which 8526 were from cases of SARS-CoV-2 infection. Studies were conducted in Asia (n=38), Europe (n=15), and the United States and China (n=1). We identified data from 25 commercial tests and numerous in-house assays, a small fraction of the 279 antibody assays listed by the Foundation for Innovative Diagnostics. More than half (n=28) of the studies included were only available as preprints. Our concerns included risk of bias as well as applicability. Common issues included the following: use of multigroup designs (n=29); inclusion of only COVID-19 cases (n=19); lack of blinding of the index test (n=49) and reference standard (n=29); differential verification (n=22); and the lack of clarity about participant numbers, characteristics, and study exclusions (n=47). Most studies (n=44) only included patients who were hospitalized because of suspected or confirmed COVID-19 infection. There were no studies exclusively in asymptomatic participants. Two-thirds of the studies (n=33) defined COVID-19 cases based on RT-PCR results alone, disregarding the potential for false-negative RT-PCR results. We perceived evidence of the selective publication of study findings by omission of the identity of tests (n=5). We observed substantial heterogeneity in sensitivities of IgA, IgM, and IgG antibodies, or combinations thereof, for results aggregated across various time periods post-symptom onset (range 0% to 100% for all target antibodies). Therefore, we based our main results on the 38 studies that stratified results by the time since symptom onset. The numbers of individuals contributing data to each study each week are small and are usually not based on tracking the same groups of patients over time. Pooled results for IgG, IgM, IgA, total antibodies, and IgG/IgM all showed low sensitivity during the first week since onset of symptoms (all less than 30.1%), rising in the second week and reaching their highest values in the third week. The combination of IgG/IgM had a sensitivity of 30.1% (95% CI 21.4 to 40.7) for 1 to 7 days, 72.2% (95% CI 63.5 to 79.5) for 8 to 14 days, and 91.4% (95% CI 87.0 to 94.4) for 15 to 21 days. Estimates of accuracy beyond 3 weeks are based on smaller sample sizes and fewer studies. For 21 to 35 days, pooled sensitivities for IgG/IgM were 96.0% (95% CI 90.6 to 98.3). Insufficient studies exist to estimate sensitivity of tests beyond 35 days post-symptom onset. Summary specificities (provided in 35 studies) exceeded 98% for all target antibodies with confidence intervals no more than 2 percentage points wide. False-positive results were more common where COVID-19 had been suspected and ruled out, but numbers were small and the difference was within the range of chance. Assuming a prevalence of 50%, a value considered possible in healthcare workers who have suffered respiratory symptoms, we would anticipate that 43 (28 to 65) would be missed and 7 (3 to 14) would be falsely positive in 1000 people undergoing IgG/IgM testing at days 15 to 21 post-symptom onset. At a prevalence of 20%, a likely value in surveys in high-risk settings, 17 (11 to 26) would be missed per 1000 people tested and 10 (5 to 22) would be falsely positive. At a lower prevalence of 5%, a likely value in national surveys, 4 (3 to 7) would be missed per 1000 tested, and 12 (6 to 27) would be falsely positive. Analyses showed small differences in sensitivity among assay type, but methodological concerns and sparse data prevent comparisons among test brands.ConclusionsThe sensitivity of antibody tests is too low in the first week since symptom onset to have a primary role for the diagnosis of COVID-19, but they may still have a role complementing other testing in individuals presenting later, when RT-PCR tests are negative or are not done. Antibody tests are likely to have a useful role for detecting previous SARS-CoV-2 infection if used 15 or more days after symptom onset. However, the duration of antibody rises is currently unknown, and we discovered very little data beyond 35 days post-symptom onset. Therefore, we are uncertain about the usefulness of these tests for seroprevalence surveys for public health management purposes. Concerns about high risk of bias and applicability make it likely that the accuracy of tests when used in clinical care will be lower than reported in the included studies. Sensitivity has mainly been evaluated in hospitalized patients, so it is unclear whether the tests are able to detect lower antibody levels likely seen with milder and asymptomatic COVID-19 disease. The design, execution, and reporting of studies of the accuracy of COVID-19 tests necessitates considerable improvement. Studies must report data on sensitivity disaggregated by time since symptom onset. COVID-19-positive cases that are RT-PCR-negative should be included as well as those confirmed RT-PCR, in accordance with the World Health Organization (WHO) and China National Health Commission of the People's Republic of China (CDC) case definitions. We were only able to obtain data from a small proportion of available tests, and action is needed to ensure that all results of test evaluations are accessible in the public domain to prevent selective reporting. This is a fast-moving field, and we plan ongoing updates of this living systematic review.Convergent antibody responses to SARS-CoV-2 in convalescent individualsRobbiani DF1, Gaebler C1, Muecksch F2, Lorenzi JCC1, Wang Z1, Cho A1, Agudelo M1, Barnes CO3, Gazumyan A1, Finkin S1, Hagglof T1, Oliveira TY1, Viant C1, Hurley A4, Hoffmann HH5, Millard KG1, Kost RG6, Cipolla M1, Gordon K1, Bianchini F1, Chen ST1, Ramos V1, Patel R1, Dizon J1, Shimeliovich I1, Mendoza P1, Hartweger H1, Nogueira L1, Pack M1, Horowitz J1, Schmidt F2, Weisblum Y2, Michailidis E5, Ashbrook AW5, Waltari E7, Pak JE7, Huey-Tubman KE3, Koranda N3, Hoffman PR3, West AP Jr3, Rice CM5, Hatziioannou T2, Bjorkman PJ3, Bieniasz PD2,8, Caskey M1, Nussenzweig MC1,81Laboratory of Molecular Immunology, The Rockefeller University, New York, NY; 2Laboratory of Retrovirology, The Rockefeller University, New York, NY; 3Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA; 4Hospital Program Direction, The Rockefeller University, New York, NY; 5Laboratory of Virology and Infectious Disease, The Rockefeller University, New York, NY; 6Hospital Clinical Research Office, The Rockefeller University, New York, NY; 7Chan Zuckerberg Biohub, San Francisco, CA; 8Howard Hughes Medical Institute, The Rockefeller University, New York, NYNature 2020;584: 437–442.BackgroundDuring the COVID-19 pandemic, SARS-CoV-2 infected millions of people and claimed hundreds of thousands of lives. Virus entry into cells depends on the receptor binding domain (RBD) of the SARS-CoV-2 spike protein (S). Although there is no vaccine, it is likely that antibodies will be essential for protection. However, little is known about the human antibody response to SARS-CoV-2.MethodsHere we report on 149 COVID-19 convalescent individuals.ResultsPlasmas collected an average of 39 days after the onset of symptoms had variable half-maximal pseudovirus neutralizing titers: less than 1:50 in 33% and below 1:1000 in 79%, while only 1% showed titers above 1:5000. Antibody sequencing revealed expanded clones of RBD-specific memory B cells expressing closely related antibodies in different individuals. Despite low plasma titers, antibodies to three distinct epitopes on RBD neutralized at half-maximal inhibitory concentrations (IC50 values) as low as single-digit nanograms per milliliter.ConclusionsThus, most convalescent plasmas obtained from individuals who recover from COVID-19 do not contain high levels of neutralizing activity. Nevertheless, rare but recurring RBD-specific antibodies with potent antiviral activity were found in all individuals tested, suggesting that a vaccine designed to elicit such antibodies could be broadly effective.CommentThe above four abstracts describe different serological assays for COVID-19 antibodies. There are currently two antibody assays against SARS-CoV-2–IgM and IgG. In the early stages of COVID-19 pathogenesis, the antibody response may not be significantly detected; however, after 10–14 days of infection, there is a significant IgG antibody observed in patients who are COVID-19 positive via RT-PCR. At the time of this writing, the definitive test for diagnosing a patient with COVID-19 is the RT-PCR test for the virus. Yet, after a few days, the presence of COVID-19 antibodies indirectly reflects past infection (symptomatic or asymptomatic). There are numerous antibody assays available in the marketplace, many of which have not been vetted by proper studies even though approved by the U.S. Food and Drug Administration (FDA), as they were authorized on an emergency basis. Thus, the sensitivity and specificity of these assays are currently being challenged. Also, we do not currently know the duration of the neutralizing antibody response as measured by the assays because most of the studies have recorded only up to two or three months past the initial infection. It is possible that by the end of 2020, we will learn more about this antibody response and duration within the system.The silver lining to COVID-19: avoiding diabetic ketoacidosis admissions with telehealthPeters AL1, Garg SK21Keck School of Medicine of the University of Southern California, Los Angeles, CA; 2Barbara Davis Center for Diabetes, University of Colorado Denver, Aurora, CODiabetes Technol Ther 2020;22: 449–453BackgroundThe Stay at Home order in Colorado and The Stay Safe at Home order in California during the COVID-19 pandemic have compelled most endocrinologists/diabetologists to provide diabetes care remotely via telehealth. This could ultimately provide better access to diabetes healthcare in certain circumstances. However, healthcare disparities continue to challenge the availability of diabetes technology for underserved communities. We report our experiences using telehealth to effectively provide diabetes care to two patients and subsequently prevent hospital admissions.MethodsTwo adult patients with type 1 diabetes (T1D)–one new onset and the other with established T1D–are presented using telehealth facilitated by Clarity Software and the “Share” feature with the use of Dexcom G6 continuous glucose monitoring (CGM) for management of diabetic ketosis and hyperglycemia.ResultsBoth patients were managed effectively via remote services despite having a higher risk of diabetic ketoacidosis (DKA). Glucose data shared through CGM facilitated frequent adjustments to insulin doses, increased fluid and carbohydrate intake, and prevention of hospital admissions in both cases. In the case of a patient with new-onset T1D, most of the education was handled remotely by certified diabetes care and education specialists.ConclusionsAcute diabetes complications like DKA increase morbidity and mortality and add to the costs of the healthcare system. The current pandemic of COVID-19 has allowed newer ways (with the help of newer technologies) to manage high-risk patients with T1D and DKA via telehealth and may result in lasting benefits to patients with T1D.Hypoglycemia at the time of Covid-19 pandemicShah K1, Tiwaskar M2, Chawla P3, Kale M4, Deshmane R5, Sowani A61Diabetes & Thyroid Care Center, India; 2Shilpa Medical Research Centre, India; 3Lina Diabetes Care and Mumbai Diabetes Research Centre, India; 4Dr Kale's Diabetes and Psychiatry Clinic, India; 5Shree Mahalaxmi Diabetic Care Centre, India; 6Diabetes Specialty Centre, IndiaDiabetes Metab Syndr 2020;14: 1143–1146BackgroundHypoglycemia is the most critical factor to be addressed in glycemic management of diabetes in order to avoid further complications. The new coronavirus strain (COVID-19) pandemic has resulted in lockdowns that have further complicated concerns surrounding hypoglycemia due to limited access to food, outpatient clinics, pathological services, and medicines.AimTo assess the contributing facto