Nirmatrelvir Plus Ritonavir for Early COVID-19 in a Large U.S. Health System : A Population-Based Cohort Study.

BACKGROUND: In the EPIC-HR (Evaluation of Protease Inhibition for Covid-19 in High-Risk Patients) trial, nirmatrelvir plus ritonavir led to an 89% reduction in hospitalization or death among unvaccinated outpatients with early COVID-19. The clinical impact of nirmatrelvir plus ritonavir among vaccinated populations is uncertain. OBJECTIVE: To assess whether nirmatrelvir plus ritonavir reduces risk for hospitalization or death among outpatients with early COVID-19 in the setting of prevalent SARS-CoV-2 immunity and immune-evasive SARS-CoV-2 lineages. DESIGN: Population-based cohort study analyzed to emulate a clinical trial using inverse probability-weighted models to account for anticipated bias in treatment. SETTING: A large health care system providing care for 1.5 million patients in Massachusetts and New Hampshire during the Omicron wave (1 January to 17 July 2022). PATIENTS: 44 551 nonhospitalized adults (90.3% with ≥3 vaccine doses) aged 50 years or older with COVID-19 and no contraindications for nirmatrelvir plus ritonavir. MEASUREMENTS: The primary outcome was a composite of hospitalization within 14 days or death within 28 days of a COVID-19 diagnosis. RESULTS: During the study period, 12 541 (28.1%) patients were prescribed nirmatrelvir plus ritonavir, and 32 010 (71.9%) were not. Patients prescribed nirmatrelvir plus ritonavir were more likely to be older, have more comorbidities, and be vaccinated. The composite outcome of hospitalization or death occurred in 69 (0.55%) patients who were prescribed nirmatrelvir plus ritonavir and 310 (0.97%) who were not (adjusted risk ratio, 0.56 [95% CI, 0.42 to 0.75]). Recipients of nirmatrelvir plus ritonavir had lower risk for hospitalization (adjusted risk ratio, 0.60 [CI, 0.44 to 0.81]) and death (adjusted risk ratio, 0.29 [CI, 0.12 to 0.71]). LIMITATION: Potential residual confounding due to differential access to COVID-19 vaccines, diagnostic tests, and treatment. CONCLUSION: The overall risk for hospitalization or death was already low (1%) after an outpatient diagnosis of COVID-19, but nirmatrelvir plus ritonavir reduced this risk further. PRIMARY FUNDING SOURCE: National Institutes of Health.

Leveraging the virtual learning environment to enhance medical student engagement with interventional radiology.

PURPOSE: To evaluate medical student engagement with Interventional Radiology (IR) before and after a virtual elective course. METHODS: The elective was nine, one-hour lectures over ten weeks. An anonymous pre and post-course survey was administered to students. The hypothesis was that this course would increase student engagement with IR. Respondents answered nine questions to score their interest in, exposure to, familiarity with, and understanding of IR using a five-point Likert scale. Demographics were reported for the pre-course group only. A Wilcoxon signed-ranked test was performed to assess for significant mean change in pre and post-course responses. Among the 276 registered students, there were 144 individual, complete responses for the pre-course survey, and 60 paired responses for both surveys. RESULTS: Thirty-seven percent of respondents were first or second year medical students. Thirty percent of participants were enrolled at an institution outside of the United States, 26% are the first in their family to attend college, and 41% identified as female. Thirty-six percent reported this virtual course was one of their earliest experiences with IR. There was a significant increase in student exposure to IR generally, familiarity with IR compared to other specialties, familiarity with the IR training pathway(s), understanding of what an Interventional Radiologist does, understanding of the difference between IR and Diagnostic Radiology, and understanding of when to consult IR for patient care after completion of the course. CONCLUSION: A virtual IR elective is an effective means to increase exposure to, familiarity with, and understanding of IR.

Feasibility and lessons learned on remote trial implementation from TestBoston, a fully remote, longitudinal, large-scale COVID-19 surveillance study.

Longitudinal clinical studies traditionally require in-person study visits which are well documented to pose barriers to participation and contribute challenges to enrolling representative samples. Remote trial models may reduce barriers to research engagement, improve retention, and reach a more representative cohort. As remote trials become more common following the COVID-19 pandemic, a critical evaluation of this approach is imperative to optimize this paradigm shift in research. The TestBoston study was launched to understand prevalence and risk factors for COVID-19 infection in the greater Boston area through a fully remote home-testing model. Participants (adults, within 45 miles of Boston, MA) were recruited remotely from patient registries at Brigham and Women's Hospital and the general public. Participants were provided with monthly and "on-demand" at-home SARS-CoV-2 RT-PCR and antibody testing using nasal swab and dried blood spot self-collection kits and electronic surveys to assess symptoms and risk factors for COVID-19 via an online dashboard. Between October 2020 and January 2021, we enrolled 10,289 participants reflective of Massachusetts census data. Mean age was 47 years (range 18-93), 5855 (56.9%) were assigned female sex at birth, 7181(69.8%) reported being White non-Hispanic, 952 (9.3%) Hispanic/Latinx, 925 (9.0%) Black, 889 (8.6%) Asian, and 342 (3.3%) other and/or more than one race. Lower initial enrollment among Black and Hispanic/Latinx individuals required an adaptive approach to recruitment, leveraging connections to the medical system, coupled with community partnerships to ensure a representative cohort. Longitudinal retention was higher among participants who were White non-Hispanic, older, working remotely, and with lower socioeconomic vulnerability. Implementation highlighted key differences in remote trial models as participants independently navigate study milestones, requiring a dedicated participant support team and robust technology platforms, to reduce barriers to enrollment, promote retention, and ensure scientific rigor and data quality. Remote clinical trial models offer tremendous potential to engage representative cohorts, scale biomedical research, and promote accessibility by reducing barriers common in traditional trial design. Barriers and burdens within remote trials may be experienced disproportionately across demographic groups. To maximize engagement and retention, researchers should prioritize intensive participant support, investment in technologic infrastructure and an adaptive approach to maximize engagement and retention.

Variant Analysis and Strategic Clustering to Sub-Lineage of Double Mutant Strain B.1.617 of SARS-CoV-2

SARS-CoV-2 is an RNA coronavirus responsible for Acute Respiratory Syndrome (COVID-19). In January 2021, the re-occurrence of COVID-19 infection was at its peak, considered the second wave of epidemics. In the initial stage, it was considered a double mutant strain due to two significant mutations observed in their Spike protein (E484Q and L452R). Although it was first detected in India later on, it was spread to several countries worldwide, causing high fatality due to this strain. In the present study, we investigated the spreading of B.1.617 strain worldwide through 822 genome sequences submitted in GISAID on 21 April 2021. All genome sequences were analyzed for variations in genome sequences based on their effects due to changes in nucleotides. At Allele frequency 0.05, there were a total of 47 variations in ORF1ab, 22 in Spike protein gene, 6 variations in N gene, 5 in ORF8 and M gene, four mutations in Orf7a, and one nucleotide substitution observed for ORF3a, ORF6 and ORF7b gene. The clustering for similar mutations mentioned B.1.617 sub-lineages. The outcome of this study established relative occurrence and spread worldwide. The study's finding represented that 'double mutant';strain is not only spread through traveling but it is also observed to evolve naturally with different mutations observed in B.1.617 lineage. The information extracted from the study helps to understand viral evolution and genome variations of B.1.617 lineage. The results support the need of separating B.1.617 into sub-lineages.

Association of Self-reported High-Risk Allergy History With Allergy Symptoms After COVID-19 Vaccination.

Importance: Allergic history in individuals with confirmed anaphylaxis to a messenger RNA (mRNA) COVID-19 vaccine is common. However, the risk factors for allergy symptoms after receiving the vaccine are unknown. Objective: To assess the association between self-reported history of high-risk allergy and self-reported allergic reactions after mRNA COVID-19 vaccination of health care employees. Design, Setting, and Participants: This cohort study obtained demographic, medical, and vaccine administration data of employees of Mass General Brigham from the institutional electronic health record. Employees who received at least 1 dose of an mRNA COVID-19 vaccine between December 14, 2020, and February 1, 2021, and who completed at least 1 postvaccination symptom survey in the 3 days after vaccination were included. Exposures: Self-reported history of high-risk allergy, defined as a previous severe allergic reaction to a vaccine, an injectable medication, or other allergen. Main Outcomes and Measures: The primary outcome was 1 or more self-reported allergic reactions in the first 3 days after dose 1 or dose 2 of an mRNA COVID-19 vaccine. Multivariable log binomial regression was used to assess the association between allergic reactions and high-risk allergy status. Results: A total of 52 998 health care employees (mean [SD] age, 42 [14] years; 38 167 women [72.0%]) were included in the cohort, of whom 51 706 (97.6%) received 2 doses of an mRNA COVID-19 vaccine and 474 (0.9%) reported a history of high-risk allergy. Individuals with vs without a history of high-risk allergy reported more allergic reactions after receiving dose 1 or 2 of the vaccine (11.6% [n = 55] vs 4.7% [n = 2461]). In the adjusted model, a history of high-risk allergy was associated with an increased risk of allergic reactions (adjusted relative risk [aRR], 2.46; 95% CI, 1.92-3.16), with risk being highest for hives (aRR, 3.81; 95% CI, 2.33-6.22) and angioedema (aRR, 4.36; 95% CI, 2.52-7.54). Conclusions and Relevance: This cohort study found that self-reported history of high-risk allergy was associated with an increased risk of self-reported allergic reactions within 3 days of mRNA COVID-19 vaccination. However, reported allergy symptoms did not impede the completion of the 2-dose vaccine protocol among a cohort of eligible health care employees, supporting the overall safety of mRNA COVID-19 vaccine.

Digital triage: Novel strategies for population health management in response to the COVID-19 pandemic.

The COVID-19 pandemic has created unique challenges for the U.S. healthcare system due to the staggering mismatch between healthcare system capacity and patient demand. The healthcare industry has been a relatively slow adopter of digital innovation due to the conventional belief that humans need to be at the center of healthcare delivery tasks. However, in the setting of the COVID-19 pandemic, artificial intelligence (AI) may be used to carry out specific tasks such as pre-hospital triage and enable clinicians to deliver care at scale. Recognizing that the majority of COVID-19 cases are mild and do not require hospitalization, Partners HealthCare (now Mass General Brigham) implemented a digitally-automated pre-hospital triage solution to direct patients to the appropriate care setting before they showed up at the emergency department and clinics, which would otherwise consume resources, expose other patients and staff to potential viral transmission, and further exacerbate supply-and-demand mismatching. Although the use of AI has been well-established in other industries to optimize supply and demand matching, the introduction of AI to perform tasks remotely that were traditionally performed in-person by clinical staff represents a significant milestone in healthcare operations strategy.

COVID-19 Complicated by Acute Pulmonary Embolism and Right-Sided Heart Failure.

A patient with coronavirus disease-2019 (COVID-19) developed sudden shortness of breath and hypoxia. She received a diagnosis of massive pulmonary embolism complicated by right-sided heart failure, which was successfully managed conservatively. This case marks the first report of COVID-19-induced pulmonary embolism in association with acute heart failure. (Level of Difficulty: Beginner.).