Heterologous versus homologous boosting elicits qualitatively distinct, BA.5-cross-reactive T cells in transplant recipients.

BackgroundThe SARS-CoV-2 Omicron BA.5 subvariant escapes vaccination-induced neutralizing antibodies because of mutations in the spike (S) protein. Solid organ transplant recipients (SOTRs) develop high COVID-19 morbidity and poor Omicron variant recognition after COVID-19 vaccination. T cell responses may provide a second line of defense. Therefore, understanding which vaccine regimens induce robust, conserved T cell responses is critical.MethodsWe evaluated anti-S IgG titers, subvariant pseudo-neutralization, and S-specific CD4+ and CD8+ T cell responses from SOTRs in a national, prospective, observational trial (n = 75). Participants were selected if they received 3 doses of mRNA (homologous boosting) or 2 doses of mRNA followed by Ad26.COV2.S (heterologous boosting).ResultsHomologous boosting with 3 mRNA doses induced the highest anti-S IgG titers. However, antibodies induced by both vaccine regimens demonstrated lower pseudo-neutralization against BA.5 compared with the ancestral strain. In contrast, vaccine-induced S-specific T cells maintained cross-reactivity against BA.5 compared with ancestral recognition. Homologous boosting induced higher frequencies of activated polyfunctional CD4+ T cell responses, with polyfunctional IL-21+ peripheral T follicular helper cells increased in mRNA-1273 compared with BNT162b2. IL-21+ cells correlated with antibody titers. Heterologous boosting with Ad26.COV2.S did not increase CD8+ responses compared to homologous boosting.ConclusionBoosting with the ancestral strain can induce cross-reactive T cell responses against emerging variants in SOTRs, but alternative vaccine strategies are required to induce robust CD8+ T cell responses.FundingBen-Dov Family; NIH National Institute of Allergy and Infectious Diseases (NIAID) K24AI144954, NIAID K08AI156021, NIAID K23AI157893, NIAID U01AI138897, National Institute of Diabetes and Digestive and Kidney Diseases T32DK007713, and National Cancer Institute 1U54CA260492; Johns Hopkins Vice Dean of Research Support for COVID-19 Research in Immunopathogenesis; and Emory COVID-19 research repository.

Validity of Coronavirus Disease 2019 International Classification of Diseases, Tenth Revision in the Urgent Care Setting and Impact on Antibiotic Prescribing Rates.

We validated  different coronavirus disease 2019 (COVID-19) International Classification of Diseases, Tenth Edition (ICD-10) encounter definitions across 2 urgent care clinics. Sensitivity of definitions varied throughout the pandemic. Inclusion of COVID-19 and COVID-19-like illness (CLI) ICD-10s rendered highest sensitivity but lowest specificity. Antibiotic prescribing rates were low for COVID-19 ICD-10 encounters, increasing with CLI ICD-10 encounters.

Impact of different COVID-19 encounter definitions on antibiotic prescribing rates in urgent care

Background: Billing data have been used in the outpatient setting to identify targets for antimicrobial stewardship. However, COVID-19 ICD-10 codes are new, and the validity of using COVID-19 ICD-10 codes to accurately identify COVID-19 encounters is unknown. We investigated COVID-19 ICD-10 utilization in our urgent care clinics during the pandemic and the impact of using different COVID-19 encounter definitions on antibiotic prescribing rates (APRs). Methods: We included all telemedicine and office visits at 2 academic urgent-care clinics from January 2020 to September 2021. We extracted ICD-10 encounter codes and testing data from the electronic medical record. We compared encounters for which COVID-19 ICD-10 codes were present with encounters for which SARS-CoV-2 nucleic acid amplification testing (NAAT) was performed within 5 days of and up to 2 days after the encounter (Fig. 1). We calculated the sensitivity of the use of COVID-19 ICD-10 codes against a positive NAAT. We calculated the APR as the proportion of encounters in which an antibacterial drug was prescribed. This quality improvement project was deemed non–human-subjects research by the Stanford Panel on Human Subjects in Medical Research.Funding: NoneDisclosures: None

Outpatient hydroxychloroquine prescribing at a large academic health system during the COVID-19 pandemic

To the Editor—The coronavirus disease 2019 (COVID-19) pandemic has attracted widespread attention to experimental treatments, including the antirheumatic drug hydroxychloroquine, raising concerns about its supply for patients already taking the drug for non–COVID-19 indications.1 Currently, multiple manufacturers have reported shortages of hydroxychloroquine.2 We report an exploratory analysis of hydroxychloroquine prescribing in outpatient and urgent care clinics of a large academic health system in northern California. The CDC guidance has recommended that patients request larger prescription drug quantities to minimize pharmacy visits.3 However, the American College of Rheumatology has suggested limiting outpatient prescription refills of hydroxychloroquine to a 30-day supply as a potential mitigation strategy for any supply disruptions in select circumstances.4 Our analysis was observational in nature, and further interpretation is limited by several factors. [...]these results are unique to practice paradigms of a single health system and are subject to regional epidemiology of COVID-19.

Predicting a Positive Antibody Response After 2 SARS-CoV-2 mRNA Vaccines in Transplant Recipients: A Machine Learning Approach With External Validation.

BACKGROUND: Solid organ transplant recipients (SOTRs) are less likely to mount an antibody response to SARS-CoV-2 mRNA vaccines. Understanding risk factors for impaired vaccine response can guide strategies for antibody testing and additional vaccine dose recommendations. METHODS: Using a nationwide observational cohort of 1031 SOTRs, we created a machine learning model to explore, identify, rank, and quantify the association of 19 clinical factors with antibody responses to 2 doses of SARS-CoV-2 mRNA vaccines. External validation of the model was performed using a cohort of 512 SOTRs at Houston Methodist Hospital. RESULTS: Mycophenolate mofetil use, a shorter time since transplant, and older age were the strongest predictors of a negative antibody response, collectively contributing to 76% of the model's prediction performance. Other clinical factors, including transplanted organ, vaccine type (mRNA-1273 versus BNT162b2), sex, race, and other immunosuppressants, showed comparatively weaker associations with an antibody response. This model showed moderate prediction performance, with an area under the receiver operating characteristic curve of 0.79 in our cohort and 0.67 in the external validation cohort. An online calculator based on our prediction model is available at http://transplantmodels.com/covidvaccine/ . CONCLUSIONS: Our machine learning model helps understand which transplant patients need closer follow-up and additional doses of vaccine to achieve protective immunity. The online calculator based on this model can be incorporated into transplant providers' practice to facilitate patient-centric, precision risk stratification and inform vaccination strategies among SOTRs.

Sustained Reduction in Urgent Care Antibiotic Prescribing During the Coronavirus Disease 2019 Pandemic: An Academic Medical Center's Experience.

We compared antibiotic prescribing before and during the -coronavirus disease 2019 (COVID-19) pandemic at 2 academic urgent care clinics and found a sustained decrease in prescribing driven by respiratory encounters and despite transitioning to telemedicine. Antibiotics were rarely prescribed during encounters for COVID-19 or COVID-19 symptoms. COVID-19 revealed opportunities for outpatient stewardship programs.

Correction to: Cardiovascular Complications in Patients with COVID-19: Consequences of Viral Toxicities and Host Immune Response.

It has been pointed out that the second paragraph of the section "Treatments for SARS-CoV-2 Infection" contains an error. The original article has been corrected.

Cardiovascular Complications in Patients with COVID-19: Consequences of Viral Toxicities and Host Immune Response.

PURPOSE OF REVIEW: Coronavirus disease of 2019 (COVID-19) is a cause of significant morbidity and mortality worldwide. While cardiac injury has been demonstrated in critically ill COVID-19 patients, the mechanism of injury remains unclear. Here, we review our current knowledge of the biology of SARS-CoV-2 and the potential mechanisms of myocardial injury due to viral toxicities and host immune responses. RECENT FINDINGS: A number of studies have reported an epidemiological association between history of cardiac disease and worsened outcome during COVID infection. Development of new onset myocardial injury during COVID-19 also increases mortality. While limited data exist, potential mechanisms of cardiac injury include direct viral entry through the angiotensin-converting enzyme 2 (ACE2) receptor and toxicity in host cells, hypoxia-related myocyte injury, and immune-mediated cytokine release syndrome. Potential treatments for reducing viral infection and excessive immune responses are also discussed. COVID patients with cardiac disease history or acquire new cardiac injury are at an increased risk for in-hospital morbidity and mortality. More studies are needed to address the mechanism of cardiotoxicity and the treatments that can minimize permanent damage to the cardiovascular system.