Clinically stable covid-19 patients presenting to acute unscheduled episodic care venues have increased risk of hospitalization: secondary analysis of a randomized control trial.

BACKGROUND: Assessment for risks associated with acute stable COVID-19 is important to optimize clinical trial enrollment and target patients for scarce therapeutics. To assess whether healthcare system engagement location is an independent predictor of outcomes we performed a secondary analysis of the ACTIV-4B Outpatient Thrombosis Prevention trial. METHODS: A secondary analysis of the ACTIV-4B trial that was conducted at 52 US sites between September 2020 and August 2021. Participants were enrolled through acute unscheduled episodic care (AUEC) enrollment location (emergency department, or urgent care clinic visit) compared to minimal contact (MC) enrollment (electronic contact from test center lists of positive patients).We report the primary composite outcome of cardiopulmonary hospitalizations, symptomatic venous thromboembolism, myocardial infarction, stroke, transient ischemic attack, systemic arterial thromboembolism, or death among stable outpatients stratified by enrollment setting, AUEC versus MC. A propensity score for AUEC enrollment was created, and Cox proportional hazards regression with inverse probability weighting (IPW) was used to compare the primary outcome by enrollment location. RESULTS: Among the 657 ACTIV-4B patients randomized, 533 (81.1%) with known enrollment setting data were included in this analysis, 227 from AUEC settings and 306 from MC settings. In a multivariate logistic regression model, time from COVID test, age, Black race, Hispanic ethnicity, and body mass index were associated with AUEC enrollment. Irrespective of trial treatment allocation, patients enrolled at an AUEC setting were 10-times more likely to suffer from the adjudicated primary outcome, 7.9% vs. 0.7%; p < 0.001, compared with patients enrolled at a MC setting. Upon Cox regression analysis adjustment patients enrolled at an AUEC setting remained at significant risk of the primary composite outcome, HR 3.40 (95% CI 1.46, 7.94). CONCLUSIONS: Patients with clinically stable COVID-19 presenting to an AUEC enrollment setting represent a population at increased risk of arterial and venous thrombosis complications, hospitalization for cardiopulmonary events, or death, when adjusted for other risk factors, compared with patients enrolled at a MC setting. Future outpatient therapeutic trials and clinical therapeutic delivery programs of clinically stable COVID-19 patients may focus on inclusion of higher-risk patient populations from AUEC engagement locations. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT04498273.

Design of Lung Transplant Go (LTGO): A randomized controlled trial evaluating the efficacy of a telerehabilitation behavioral exercise intervention to improve physical activity, physical function, and blood pressure control after lung transplantation☆

Background Lung transplantation is an established treatment option for persons with advanced lung disease. After transplantation, lung function typically returns to near normal levels, however exercise capacity remains low due to chronic deconditioning, limited physical function, and inactive lifestyles which undermine the intended benefits of the highly selective, resource-intensive transplant procedure. Pulmonary rehabilitation is recommended to improve fitness and activity tolerance, however due to multiple barriers, lung transplant recipients either never participate, or fail to complete, pulmonary rehabilitation programs. Purpose To describe the design of Lung Transplant Go (LTGO), a trial modified for the remote environment based on recommendations to preserve trial integrity during COVID. The aims are to evaluate a behavioral exercise intervention to improve physical function, physical activity, and blood pressure control in lung transplant recipients conducted safely and effectively using a telerehabilitation (telerehab) platform, and to explore the role of potential mediators and moderators of the relationship between LTGO and outcomes. Methods Single-site, 2-group randomized controlled trial with lung transplant recipients randomized 1:1 to either the LTGO intervention (a 2-phased, supervised, telerehab behavioral exercise program), or to enhanced usual care (activity tracking and monthly newsletters). All study activities, including intervention delivery, recruitment, consenting, assessment, and data collection, will be performed remotely. Conclusion If efficacious, this fully scalable and replicable telerehab intervention could be efficiently translated to reach large numbers of lung recipients to improve and sustain self-management of exercise habits by overcoming barriers to participation in existing, in-person pulmonary rehabilitation programs.

Design of Lung Transplant Go (LTGO): A randomized controlled trial evaluating the efficacy of a telerehabilitation behavioral exercise intervention to improve physical activity, physical function, and blood pressure control after lung transplantation.

Background: Lung transplantation is an established treatment option for persons with advanced lung disease. After transplantation, lung function typically returns to near normal levels, however exercise capacity remains low due to chronic deconditioning, limited physical function, and inactive lifestyles which undermine the intended benefits of the highly selective, resource-intensive transplant procedure. Pulmonary rehabilitation is recommended to improve fitness and activity tolerance, however due to multiple barriers, lung transplant recipients either never participate, or fail to complete, pulmonary rehabilitation programs. Purpose: To describe the design of Lung Transplant Go (LTGO), a trial modified for the remote environment based on recommendations to preserve trial integrity during COVID. The aims are to evaluate a behavioral exercise intervention to improve physical function, physical activity, and blood pressure control in lung transplant recipients conducted safely and effectively using a telerehabilitation (telerehab) platform, and to explore the role of potential mediators and moderators of the relationship between LTGO and outcomes. Methods: Single-site, 2-group randomized controlled trial with lung transplant recipients randomized 1:1 to either the LTGO intervention (a 2-phased, supervised, telerehab behavioral exercise program), or to enhanced usual care (activity tracking and monthly newsletters). All study activities, including intervention delivery, recruitment, consenting, assessment, and data collection, will be performed remotely. Conclusion: If efficacious, this fully scalable and replicable telerehab intervention could be efficiently translated to reach large numbers of lung recipients to improve and sustain self-management of exercise habits by overcoming barriers to participation in existing, in-person pulmonary rehabilitation programs.

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.).

Effect of Antithrombotic Therapy on Clinical Outcomes in Outpatients With Clinically Stable Symptomatic COVID-19: The ACTIV-4B Randomized Clinical Trial.

Importance: Acutely ill inpatients with COVID-19 typically receive antithrombotic therapy, although the risks and benefits of this intervention among outpatients with COVID-19 have not been established. Objective: To assess whether anticoagulant or antiplatelet therapy can safely reduce major adverse cardiopulmonary outcomes among symptomatic but clinically stable outpatients with COVID-19. Design, Setting, and Participants: The ACTIV-4B Outpatient Thrombosis Prevention Trial was designed as a minimal-contact, adaptive, randomized, double-blind, placebo-controlled trial to compare anticoagulant and antiplatelet therapy among 7000 symptomatic but clinically stable outpatients with COVID-19. The trial was conducted at 52 US sites between September 2020 and June 2021; final follow-up was August 5, 2021. Prior to initiating treatment, participants were required to have platelet count greater than 100 000/mm3 and estimated glomerular filtration rate greater than 30 mL/min/1.73 m2. Interventions: Random allocation in a 1:1:1:1 ratio to aspirin (81 mg orally once daily; n = 164), prophylactic-dose apixaban (2.5 mg orally twice daily; n = 165), therapeutic-dose apixaban (5 mg orally twice daily; n = 164), or placebo (n = 164) for 45 days. Main Outcomes and Measures: The primary end point was a composite of all-cause mortality, symptomatic venous or arterial thromboembolism, myocardial infarction, stroke, or hospitalization for cardiovascular or pulmonary cause. The primary analyses for efficacy and bleeding events were limited to participants who took at least 1 dose of trial medication. Results: On June 18, 2021, the trial data and safety monitoring board recommended early termination because of lower than anticipated event rates; at that time, 657 symptomatic outpatients with COVID-19 had been randomized (median age, 54 years [IQR, 46-59]; 59% women). The median times from diagnosis to randomization and from randomization to initiation of study treatment were 7 days and 3 days, respectively. Twenty-two randomized participants (3.3%) were hospitalized for COVID-19 prior to initiating treatment. Among the 558 patients who initiated treatment, the adjudicated primary composite end point occurred in 1 patient (0.7%) in the aspirin group, 1 patient (0.7%) in the 2.5-mg apixaban group, 2 patients (1.4%) in the 5-mg apixaban group, and 1 patient (0.7%) in the placebo group. The risk differences compared with placebo for the primary end point were 0.0% (95% CI not calculable) in the aspirin group, 0.7% (95% CI, -2.1% to 4.1%) in the 2.5-mg apixaban group, and 1.4% (95% CI, -1.5% to 5.0%) in the 5-mg apixaban group. Risk differences compared with placebo for bleeding events were 2.0% (95% CI, -2.7% to 6.8%), 4.5% (95% CI, -0.7% to 10.2%), and 6.9% (95% CI, 1.4% to 12.9%) among participants who initiated therapy in the aspirin, prophylactic apixaban, and therapeutic apixaban groups, respectively, although none were major. Findings inclusive of all randomized patients were similar. Conclusions and Relevance: Among symptomatic clinically stable outpatients with COVID-19, treatment with aspirin or apixaban compared with placebo did not reduce the rate of a composite clinical outcome. However, the study was terminated after enrollment of 9% of participants because of an event rate lower than anticipated. Trial Registration: ClinicalTrials.gov Identifier: NCT04498273.

Effect of Antimicrobial Therapy on Respiratory Hospitalization or Death in Adults With Idiopathic Pulmonary Fibrosis: The CleanUP-IPF Randomized Clinical Trial.

Importance: Alteration in lung microbes is associated with disease progression in idiopathic pulmonary fibrosis. Objective: To assess the effect of antimicrobial therapy on clinical outcomes. Design, Setting, and Participants: Pragmatic, randomized, unblinded clinical trial conducted across 35 US sites. A total of 513 patients older than 40 years were randomized from August 2017 to June 2019 (final follow-up was January 2020). Interventions: Patients were randomized in a 1:1 allocation ratio to receive antimicrobials (n = 254) or usual care alone (n = 259). Antimicrobials included co-trimoxazole (trimethoprim 160 mg/sulfamethoxazole 800 mg twice daily plus folic acid 5 mg daily, n = 128) or doxycycline (100 mg once daily if body weight <50 kg or 100 mg twice daily if ≥50 kg, n = 126). No placebo was administered in the usual care alone group. Main Outcomes and Measures: The primary end point was time to first nonelective respiratory hospitalization or all-cause mortality. Results: Among the 513 patients who were randomized (mean age, 71 years; 23.6% women), all (100%) were included in the analysis. The study was terminated for futility on December 18, 2019. After a mean follow-up time of 13.1 months (median, 12.7 months), a total of 108 primary end point events occurred: 52 events (20.4 events per 100 patient-years [95% CI, 14.8-25.9]) in the usual care plus antimicrobial therapy group and 56 events (18.4 events per 100 patient-years [95% CI, 13.2-23.6]) in the usual care group, with no significant difference between groups (adjusted HR, 1.04 [95% CI, 0.71-1.53; P = .83]. There was no statistically significant interaction between the effect of the prespecified antimicrobial agent (co-trimoxazole vs doxycycline) on the primary end point (adjusted HR, 1.15 [95% CI 0.68-1.95] in the co-trimoxazole group vs 0.82 [95% CI, 0.46-1.47] in the doxycycline group; P = .66). Serious adverse events occurring at 5% or greater among those treated with usual care plus antimicrobials vs usual care alone included respiratory events (16.5% vs 10.0%) and infections (2.8% vs 6.6%); adverse events of special interest included diarrhea (10.2% vs 3.1%) and rash (6.7% vs 0%). Conclusions and Relevance: Among adults with idiopathic pulmonary fibrosis, the addition of co-trimoxazole or doxycycline to usual care, compared with usual care alone, did not significantly improve time to nonelective respiratory hospitalization or death. These findings do not support treatment with these antibiotics for the underlying disease. Trial Registration: ClinicalTrials.gov Identifier: NCT02759120.

Automated quantification of COVID-19 severity and progression using chest CT images.

OBJECTIVE: To develop and test computer software to detect, quantify, and monitor progression of pneumonia associated with COVID-19 using chest CT scans. METHODS: One hundred twenty chest CT scans from subjects with lung infiltrates were used for training deep learning algorithms to segment lung regions and vessels. Seventy-two serial scans from 24 COVID-19 subjects were used to develop and test algorithms to detect and quantify the presence and progression of infiltrates associated with COVID-19. The algorithm included (1) automated lung boundary and vessel segmentation, (2) registration of the lung boundary between serial scans, (3) computerized identification of the pneumonitis regions, and (4) assessment of disease progression. Agreement between radiologist manually delineated regions and computer-detected regions was assessed using the Dice coefficient. Serial scans were registered and used to generate a heatmap visualizing the change between scans. Two radiologists, using a five-point Likert scale, subjectively rated heatmap accuracy in representing progression. RESULTS: There was strong agreement between computer detection and the manual delineation of pneumonic regions with a Dice coefficient of 81% (CI 76-86%). In detecting large pneumonia regions (> 200 mm3), the algorithm had a sensitivity of 95% (CI 94-97%) and specificity of 84% (CI 81-86%). Radiologists rated 95% (CI 72 to 99) of heatmaps at least "acceptable" for representing disease progression. CONCLUSION: The preliminary results suggested the feasibility of using computer software to detect and quantify pneumonic regions associated with COVID-19 and to generate heatmaps that can be used to visualize and assess progression. KEY POINTS: • Both computer vision and deep learning technology were used to develop computer software to quantify the presence and progression of pneumonia associated with COVID-19 depicted on CT images. • The computer software was tested using both quantitative experiments and subjective assessment. • The computer software has the potential to assist in the detection of the pneumonic regions, monitor disease progression, and assess treatment efficacy related to COVID-19.

Any unique image biomarkers associated with COVID-19?

OBJECTIVE: To define the uniqueness of chest CT infiltrative features associated with COVID-19 image characteristics as potential diagnostic biomarkers. METHODS: We retrospectively collected chest CT exams including n = 498 on 151 unique patients RT-PCR positive for COVID-19 and n = 497 unique patients with community-acquired pneumonia (CAP). Both COVID-19 and CAP image sets were partitioned into three groups for training, validation, and testing respectively. In an attempt to discriminate COVID-19 from CAP, we developed several classifiers based on three-dimensional (3D) convolutional neural networks (CNNs). We also asked two experienced radiologists to visually interpret the testing set and discriminate COVID-19 from CAP. The classification performance of the computer algorithms and the radiologists was assessed using the receiver operating characteristic (ROC) analysis, and the nonparametric approaches with multiplicity adjustments when necessary. RESULTS: One of the considered models showed non-trivial, but moderate diagnostic ability overall (AUC of 0.70 with 99% CI 0.56-0.85). This model allowed for the identification of 8-50% of CAP patients with only 2% of COVID-19 patients. CONCLUSIONS: Professional or automated interpretation of CT exams has a moderately low ability to distinguish between COVID-19 and CAP cases. However, the automated image analysis is promising for targeted decision-making due to being able to accurately identify a sizable subsect of non-COVID-19 cases. KEY POINTS: • Both human experts and artificial intelligent models were used to classify the CT scans. • ROC analysis and the nonparametric approaches were used to analyze the performance of the radiologists and computer algorithms. • Unique image features or patterns may not exist for reliably distinguishing all COVID-19 from CAP; however, there may be imaging markers that can identify a sizable subset of non-COVID-19 cases.