Research unit network (RUN) as a learning research system.

The clinical research units (CRUs) are one of the main spaces where both translational research and science take place. However, there is a lack of information about both best practices for CRU operations and, ultimately, benchmarks to evaluate CRU performance. The Research Unit Network (RUN) was created with the purpose to enable direct communication and collaboration among CRUs. An online survey was administered to further illustrate the functionality and impact of RUN. Thirty-one individual survey responses (39.2%) were included in the final analysis. The members value RUN monthly meetings (87.1%) as the most useful aspect of this network and CRU budgeting (67.7%) and staffing (61.3%) were the most relevant topics discussed. This is followed by EPIC - Research (58.1%), delegation of authority logs, unit signatures, and policies (51.6%), COVID-19 pandemic response (41.9%), the implementation of clinical trial management system (29.0%), and protocol deviations (19.4%). The intermediate goal of RUN is to identify best practices CRUs are establishing, implementing, and sharing these experiences with the goal to adopt them in different CRUs. The network's long-term goal is to establish standard benchmarks that can be used for evaluating the performance of CRUs across the nation.

Patient Experiences with a Tertiary Care Post-COVID-19 Clinic.

Post-acute sequelae of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (PASC) is a complex condition with multisystem involvement. We assessed patients' experience with a PASC clinic established at University of Iowa in June 2020. A survey was electronically mailed in June 2021 asking about (1) symptoms and their impact on functional domains using the Patient-Reported Outcomes Measurement Information System (PROMIS) measures (Global Health and Cognitive Function Abilities) (2) satisfaction with clinic services, referrals, barriers to care, and recommended support resources. Survey completion rate was 35% (97/277). Majority were women (67%), Caucasian (93%), and were not hospitalized (76%) during acute COVID-19. As many as 50% reported wait time between 1 and 3 months, 40% traveled >1 h for an appointment and referred to various subspecialities. Participants reported high symptom burden-fatigue (77%), "brain fog" (73%), exercise intolerance (73%), anxiety (63%), sleep difficulties (56%) and depression (44%). On PROMIS measures, some patients scored significantly low (≥1.5 SD below mean) in physical (22.7%), mental (15.9%), and cognitive (17.6%) domains. Approximately 61% to 93% of participants were satisfied with clinical services. Qualitative analysis added insight to their experience with healthcare. Participants suggested potential strategies for optimizing recovery, including continuity of care, a co-located multispecialty clinic, and receiving timely information from emerging research. Participants appreciated that physicians validated their symptoms and provided continuity of care and access to specialists.

Patient Experiences with a Tertiary Care Post-COVID-19 Clinic

Post-acute sequelae of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (PASC) is a complex condition with multisystem involvement. We assessed patients' experience with a PASC clinic established at University of Iowa in June 2020. A survey was electronically mailed in June 2021 asking about (1) symptoms and their impact on functional domains using the Patient-Reported Outcomes Measurement Information System (PROMIS) measures (Global Health and Cognitive Function Abilities) (2) satisfaction with clinic services, referrals, barriers to care, and recommended support resources. Survey completion rate was 35% (97/277). Majority were women (67%), Caucasian (93%), and were not hospitalized (76%) during acute COVID-19. As many as 50% reported wait time between 1 and 3 months, 40% traveled >1 h for an appointment and referred to various subspecialities. Participants reported high symptom burden-fatigue (77%), "brain fog” (73%), exercise intolerance (73%), anxiety (63%), sleep difficulties (56%) and depression (44%). On PROMIS measures, some patients scored significantly low (≥1.5 SD below mean) in physical (22.7%), mental (15.9%), and cognitive (17.6%) domains. Approximately 61% to 93% of participants were satisfied with clinical services. Qualitative analysis added insight to their experience with healthcare. Participants suggested potential strategies for optimizing recovery, including continuity of care, a co-located multispecialty clinic, and receiving timely information from emerging research. Participants appreciated that physicians validated their symptoms and provided continuity of care and access to specialists.

Brain Fog and Fatigue following COVID-19 Infection: An Exploratory Study of Patient Experiences of Long COVID.

Post-acute sequelae of SARS-CoV-2 (PASC) is a poorly understood condition with significant impact on quality of life. We aimed to better understand the lived experiences of patients with PASC, focusing on the impact of cognitive complaints ("brain fog") and fatigue on (1) daily activities, (2) work/employment, and (3) interpersonal relationships. We conducted semi-structured qualitative interviews with 15 patients of a Midwestern academic hospital's post-COVID-19 clinic. We audio-recorded, transcribed, and analyzed interviews thematically using a combined deductive-inductive approach and collected participants' characteristics from chart review. Participants frequently used descriptive and metaphorical language to describe symptoms that were relapsing-remitting and unpredictable. Fatigue and brain fog affected all domains and identified subthemes included symptoms' synergistic effects, difficulty with multitasking, lack of support, poor self-perception, and fear of loss of income and employment. Personal relationships were affected with change of responsibilities, difficulty parenting, social isolation, and guilt due to the burdens placed on family. Furthermore, underlying social stigma contributed to negative emotions, which significantly affected emotional and mental health. Our findings highlight PASC's negative impact on patients' daily lives. Providers can better support COVID-19 survivors during their recovery by identifying their needs in a sensitive and timely manner.

Contrastive learning and subtyping of post-COVID-19 lung computed tomography images.

Patients who recovered from the novel coronavirus disease 2019 (COVID-19) may experience a range of long-term symptoms. Since the lung is the most common site of the infection, pulmonary sequelae may present persistently in COVID-19 survivors. To better understand the symptoms associated with impaired lung function in patients with post-COVID-19, we aimed to build a deep learning model which conducts two tasks: to differentiate post-COVID-19 from healthy subjects and to identify post-COVID-19 subtypes, based on the latent representations of lung computed tomography (CT) scans. CT scans of 140 post-COVID-19 subjects and 105 healthy controls were analyzed. A novel contrastive learning model was developed by introducing a lung volume transform to learn latent features of disease phenotypes from CT scans at inspiration and expiration of the same subjects. The model achieved 90% accuracy for the differentiation of the post-COVID-19 subjects from the healthy controls. Two clusters (C1 and C2) with distinct characteristics were identified among the post-COVID-19 subjects. C1 exhibited increased air-trapping caused by small airways disease (4.10%, p = 0.008) and diffusing capacity for carbon monoxide %predicted (DLCO %predicted, 101.95%, p < 0.001), while C2 had decreased lung volume (4.40L, p < 0.001) and increased ground glass opacity (GGO%, 15.85%, p < 0.001). The contrastive learning model is able to capture the latent features of two post-COVID-19 subtypes characterized by air-trapping due to small airways disease and airway-associated interstitial fibrotic-like patterns, respectively. The discovery of post-COVID-19 subtypes suggests the need for different managements and treatments of long-term sequelae of patients with post-COVID-19.

Bronchodilators in Tobacco-Exposed Persons with Symptoms and Preserved Lung Function.

BACKGROUND: Many persons with a history of smoking tobacco have clinically significant respiratory symptoms despite an absence of airflow obstruction as assessed by spirometry. They are often treated with medications for chronic obstructive pulmonary disease (COPD), but supporting evidence for this treatment is lacking. METHODS: We randomly assigned persons who had a tobacco-smoking history of at least 10 pack-years, respiratory symptoms as defined by a COPD Assessment Test score of at least 10 (scores range from 0 to 40, with higher scores indicating worse symptoms), and preserved lung function on spirometry (ratio of forced expiratory volume in 1 second [FEV1] to forced vital capacity [FVC] ≥0.70 and FVC ≥70% of the predicted value after bronchodilator use) to receive either indacaterol (27.5 µg) plus glycopyrrolate (15.6 µg) or placebo twice daily for 12 weeks. The primary outcome was at least a 4-point decrease (i.e., improvement) in the St. George's Respiratory Questionnaire (SGRQ) score (scores range from 0 to 100, with higher scores indicating worse health status) after 12 weeks without treatment failure (defined as an increase in lower respiratory symptoms treated with a long-acting inhaled bronchodilator, glucocorticoid, or antibiotic agent). RESULTS: A total of 535 participants underwent randomization. In the modified intention-to-treat population (471 participants), 128 of 227 participants (56.4%) in the treatment group and 144 of 244 (59.0%) in the placebo group had at least a 4-point decrease in the SGRQ score (difference, -2.6 percentage points; 95% confidence interval [CI], -11.6 to 6.3; adjusted odds ratio, 0.91; 95% CI, 0.60 to 1.37; P = 0.65). The mean change in the percent of predicted FEV1 was 2.48 percentage points (95% CI, 1.49 to 3.47) in the treatment group and -0.09 percentage points (95% CI, -1.06 to 0.89) in the placebo group, and the mean change in the inspiratory capacity was 0.12 liters (95% CI, 0.07 to 0.18) in the treatment group and 0.02 liters (95% CI, -0.03 to 0.08) in the placebo group. Four serious adverse events occurred in the treatment group, and 11 occurred in the placebo group; none were deemed potentially related to the treatment or placebo. CONCLUSIONS: Inhaled dual bronchodilator therapy did not decrease respiratory symptoms in symptomatic, tobacco-exposed persons with preserved lung function as assessed by spirometry. (Funded by the National Heart, Lung, and Blood Institute and others; RETHINC ClinicalTrials.gov number, NCT02867761.).

The Research Unit Network (RUN) as a Learning Research System

OBJECTIVES/GOALS: CTRUs support clinical research. RUN is a Learning Research System that is created to enhance CTSA and non-CTSA research units capacity through implementing, assessing, and disseminating discoveries in methods, approaches, education, and training in clinical and translational science. METHODS/STUDY POPULATION: The RUN association began in July 2018 with eight universities. The association has grown to 44 hospitals, research, and academic institutions (including 36 CTSA institutions). A RUN Discussion Forum has been approved by the National Center for Advancing Science (NCATS) and utilized by RUN. The Discussion Forums are created with the goal of advancing CTSA Program objectives in high priority areas of clinical and translational science. RUN actively engages members through in depth scheduled monthly meeting discussions with various relevant topics regarding the development and evaluation of clinical trials metrics, benchmarks, and scholarly publication and presentation activities. RESULTS/ANTICIPATED RESULTS: Topics covered in RUN monthly meetings include research units general budget guidelines, staff recruitment and retainment strategies, EPIC use in scheduling CRU research visits, and PPE for investigational drugs in context of USP800 requirements. RUN members vary in geographic location, type of clinical research (outpatient vs inpatient), resources, and research subject volume. They are engaged in online discussion and learning opportunities to improve translational science practices. A recent article titled “Impact of COVID-19 on Clinical Research Units (CRUs)” in JCTS is an example of best practices learned by RUN members and shared with the broader research community. DISCUSSION/SIGNIFICANCE: RUN as a Learning Research System enhances clinical and translational research unit capacity and efficiency, encouraging collaboration to contribute with improving public health. This network is aligned with the CTSAs mission of developing innovative solutions to improve translational science.

Quantitative Chest CT Assessment of Small Airways Disease in Post-Acute SARS-CoV-2 Infection.

Background The long-term effects of SARS-CoV-2 infection on pulmonary structure and function remain incompletely characterized. Purpose To test whether SARS-CoV-2 infection leads to small airways disease in patients with persistent symptoms. Materials and Methods In this single-center study at a university teaching hospital, adults with confirmed COVID-19 who remained symptomatic more than 30 days following diagnosis were prospectively enrolled from June to December 2020 and compared with healthy participants (controls) prospectively enrolled from March to August 2018. Participants with post-acute sequelae of COVID-19 (PASC) were classified as ambulatory, hospitalized, or having required the intensive care unit (ICU) based on the highest level of care received during acute infection. Symptoms, pulmonary function tests, and chest CT images were collected. Quantitative CT analysis was performed using supervised machine learning to measure regional ground-glass opacity (GGO) and using inspiratory and expiratory image-matching to measure regional air trapping. Univariable analyses and multivariable linear regression were used to compare groups. Results Overall, 100 participants with PASC (median age, 48 years; 66 women) were evaluated and compared with 106 matched healthy controls; 67% (67 of 100) of the participants with PASC were classified as ambulatory, 17% (17 of 100) were hospitalized, and 16% (16 of 100) required the ICU. In the hospitalized and ICU groups, the mean percentage of total lung classified as GGO was 13.2% and 28.7%, respectively, and was higher than that in the ambulatory group (3.7%, P < .001 for both comparisons). The mean percentage of total lung affected by air trapping was 25.4%, 34.6%, and 27.3% in the ambulatory, hospitalized, and ICU groups, respectively, and 7.2% in healthy controls (P < .001). Air trapping correlated with the residual volume-to-total lung capacity ratio (ρ = 0.6, P < .001). Conclusion In survivors of COVID-19, small airways disease occurred independently of initial infection severity. The long-term consequences are unknown. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Elicker in this issue.

Urban Particulate Matter Impairment of Airway Surface Liquid-Mediated Coronavirus Inactivation.

Air pollution particulate matter (PM) is associated with SARS-CoV-2 infection and severity, although mechanistic studies are lacking. We tested whether airway surface liquid (ASL) from primary human airway epithelial cells is antiviral against SARS-CoV-2 and human alphacoronavirus 229E (CoV-229E) (responsible for common colds), and whether PM (urban, indoor air pollution [IAP], volcanic ash) affected ASL antiviral activity. ASL inactivated SARS-CoV-2 and CoV-229E. Independently, urban PM also decreased SARS-CoV-2 and CoV-229E infection, and IAP PM decreased CoV-229E infection. However, in combination, urban PM impaired ASL's antiviral activity against both viruses, and the same effect occurred for IAP PM and ash against SARS-CoV-2, suggesting that PM may enhance SARS-CoV-2 infection.

Impact of COVID-19 on Clinical Research Units (CRUs).

Few studies have explored the challenges that the COVID-19 pandemic has presented for Clinical Research Units (CRUs), the solutions that have been implemented, and the changes that have been made in the operational guidelines for these entities. This study sought to identify and document common practices implemented by CRUs around the United States of America (USA) when addressing the unique challenges posed by the COVID-19 pandemic. This descriptive study utilized a non-experimental mixed-methods approach and gathered data from representatives of 43 CRUs across the USA. An online survey was followed by in-depth interviews. The findings show that challenges faced from the COVID-19 pandemic, changes made to daily operations, and lessons learned are very similar across CRUs. Although most CRUs never stopped performing essential clinical research, many adapted to the pandemic by engaging in virtual visits, and many played key roles in administering and supporting both COVID-19 therapeutic and vaccine trials. Follow-up interviews showed that processes for formal approval and reopening were similar across CRUs. In addition to highlighting the significance of the role played by CRUs during the COVID-19 pandemic, this study addresses the relevance of CRUs and lays the groundwork for future conversations on the importance of these units.

Post-acute COVID-19 functional movement disorder.

Movement disorders are rare compared to other neurological manifestations of COVID-19. Patients who have recovered from acute severe acute respiratory syndrome coronavirus-2 infection continue to have multiple debilitating symptoms months later. We report a case of 54-year-old man who presented with repetitive flexion movement of head which started 2 months after severe acute respiratory syndrome coronavirus-2 infection. Extensive work-up including neurological examination, neuroimaging, cerebrospinal fluid analysis, and electroencephalogram were normal. The self-reported questionnaires for depression and anxiety were suggestive of severe anxiety and depression. The patient continued to have the jerky movements besides cognitive impairment, frequent headaches, intermittent shortness of breath, sleeping difficulties, fatigue, and dizziness at 1-year follow-up. This case highlights the presentation of functional movement disorder as one of the manifestations of underlying neuropsychiatric condition. Our patient had significant effect on quality of life with high symptom burden which further highlights the struggle and unmet needs of the patients with multiple symptoms after severe acute respiratory syndrome coronavirus-2 infection.

Case Studies in Physiology: Temporal variations of the lung parenchyma and vasculature in asymptomatic COVID-19 pneumonia: a multispectral CT assessment.

This study reports systematic longitudinal pathophysiology of lung parenchymal and vascular effects of asymptomatic COVID-19 pneumonia in a young, healthy never-smoking male. Inspiratory and expiratory noncontrast along with contrast dual-energy computed tomography (DECT) scans of the chest were performed at baseline on the day of acute COVID-19 diagnosis (day 0), and across a 90-day period. Despite normal vital signs and pulmonary function tests on the day of diagnosis, the CT scans and corresponding quantification metrics detected abnormalities in parenchymal expansion based on image registration, ground-glass (GGO) texture (inflammation) as well as DECT-derived pulmonary blood volume (PBV). Follow-up scans on day 30 showed improvement in the lung parenchymal mechanics as well as reduced GGO and improved PBV distribution. Improvements in lung PBV continued until day 90. However, the heterogeneity of parenchymal mechanics and texture-derived GGO increased on days 60 and 90. We highlight that even asymptomatic COVID-19 infection with unremarkable vital signs and pulmonary function tests can have measurable effects on lung parenchymal mechanics and vascular pathophysiology, which may follow apparently different clinical courses. For this asymptomatic subject, post COVID-19 regional mechanics demonstrated persistent increased heterogeneity concomitant with return of elevated GGOs, despite early improvements in vascular derangement.NEW & NOTEWORTHY We characterized the temporal changes of lung parenchyma and microvascular pathophysiology from COVID-19 infection in an asymptomatic young, healthy nonsmoking male using dual-energy CT. Lung parenchymal mechanics and microvascular disease followed different clinical courses. Heterogeneous perfused blood volume became more uniform on follow-up visits up to 90 days. However, post COVID-19 mechanical heterogeneity of the lung parenchyma increased after apparent improvements in vascular abnormalities, even with normal spirometric indices.

Genetic and non-genetic factors affecting the expression of COVID-19-relevant genes in the large airway epithelium.

BACKGROUND: The large airway epithelial barrier provides one of the first lines of defense against respiratory viruses, including SARS-CoV-2 that causes COVID-19. Substantial inter-individual variability in individual disease courses is hypothesized to be partially mediated by the differential regulation of the genes that interact with the SARS-CoV-2 virus or are involved in the subsequent host response. Here, we comprehensively investigated non-genetic and genetic factors influencing COVID-19-relevant bronchial epithelial gene expression. METHODS: We analyzed RNA-sequencing data from bronchial epithelial brushings obtained from uninfected individuals. We related ACE2 gene expression to host and environmental factors in the SPIROMICS cohort of smokers with and without chronic obstructive pulmonary disease (COPD) and replicated these associations in two asthma cohorts, SARP and MAST. To identify airway biology beyond ACE2 binding that may contribute to increased susceptibility, we used gene set enrichment analyses to determine if gene expression changes indicative of a suppressed airway immune response observed early in SARS-CoV-2 infection are also observed in association with host factors. To identify host genetic variants affecting COVID-19 susceptibility in SPIROMICS, we performed expression quantitative trait (eQTL) mapping and investigated the phenotypic associations of the eQTL variants. RESULTS: We found that ACE2 expression was higher in relation to active smoking, obesity, and hypertension that are known risk factors of COVID-19 severity, while an association with interferon-related inflammation was driven by the truncated, non-binding ACE2 isoform. We discovered that expression patterns of a suppressed airway immune response to early SARS-CoV-2 infection, compared to other viruses, are similar to patterns associated with obesity, hypertension, and cardiovascular disease, which may thus contribute to a COVID-19-susceptible airway environment. eQTL mapping identified regulatory variants for genes implicated in COVID-19, some of which had pheWAS evidence for their potential role in respiratory infections. CONCLUSIONS: These data provide evidence that clinically relevant variation in the expression of COVID-19-related genes is associated with host factors, environmental exposures, and likely host genetic variation.

Quantitative CT imaging and advanced visualization methods: potential application in novel coronavirus disease 2019 (COVID-19) pneumonia.

Increasingly, quantitative lung computed tomography (qCT)-derived metrics are providing novel insights into chronic inflammatory lung diseases, including chronic obstructive pulmonary disease, asthma, interstitial lung disease, and more. Metrics related to parenchymal, airway, and vascular anatomy together with various measures associated with lung function including regional parenchymal mechanics, air trapping associated with functional small airways disease, and dual-energy derived measures of perfused blood volume are offering the ability to characterize disease phenotypes associated with the chronic inflammatory pulmonary diseases. With the emergence of COVID-19, together with its widely varying degrees of severity, its rapid progression in some cases, and the potential for lengthy post-COVID-19 morbidity, there is a new role in applying well-established qCT-based metrics. Based on the utility of qCT tools in other lung diseases, previously validated supervised classical machine learning methods, and emerging unsupervised machine learning and deep-learning approaches, we are now able to provide desperately needed insight into the acute and the chronic phases of this inflammatory lung disease. The potential areas in which qCT imaging can be beneficial include improved accuracy of diagnosis, identification of clinically distinct phenotypes, improvement of disease prognosis, stratification of care, and early objective evaluation of intervention response. There is also a potential role for qCT in evaluating an increasing population of post-COVID-19 lung parenchymal changes such as fibrosis. In this work, we discuss the basis of various lung qCT methods, using case-examples to highlight their potential application as a tool for the exploration and characterization of COVID-19, and offer scanning protocols to serve as templates for imaging the lung such that these established qCT analyses have the best chance at yielding the much needed new insights.

The Cardiovascular Effects of Treatment with Hydroxychloroquine and Azithromycin.

Hydroxychloroquine combined with azithromycin has been investigated for activity against coronavirus disease 2019 (COVID-19), but concerns about adverse cardiovascular (CV) effects have been raised. This study evaluated claims data to determine if risks for CV events were increased with hydroxychloroquine alone or combined with azithromycin. We identified data from 43,752 enrollees that qualified for analysis. The number of CV events increased by 25 (95% confidence interval [CI]: 8, 42, p=0.005) per 1000 people per year of treatment with hydroxychloroquine alone compared with pretreatment levels and by 201 (95% CI: 145, 256, p<0.001) events per 1000 people per year when individuals took hydroxychloroquine and azithromycin. These rates translate to an additional 0.34 (95% CI: 0.11, 0.58) CV events per 1000 patients placed on a 5-day treatment with hydroxychloroquine monotherapy and 2.75 (95% CI: 1.99, 3.51) per 1000 patients on a 5-day treatment with both hydroxychloroquine and azithromycin. The rate of adverse events increased with age following exposure to hydroxychloroquine alone and combined with azithromycin. For females aged 60 to 79 years prescribed hydroxychloroquine, the rate of adverse CV events was 0.92 per 1000 patients on 5 days of therapy, but it increased to 4.78 per 1000 patients when azithromycin was added. The rate of adverse CV events did not differ significantly from zero for patients 60 years of age or younger. These data suggest that hydroxychloroquine with or without azithromycin is likely safe in individuals under 60 years of age if they do not have additional CV risks. However, the combination of hydroxychloroquine and azithromycin should be used with extreme caution in older patients.