Extracorporeal Life Support in Respiratory Failure.

Extracorporeal life support (ECLS) has a role in different types of respiratory failure including acute respiratory distress syndrome (ARDS), decompensated pulmonary hypertension, bridge to lung transplantation, and primary graft dysfunction after lung transplantation. ECLS in ARDS allows for lung-protective ventilation with the goal to reduce the risk of ventilator-induced lung injury. ECLS use in severe ARDS should be considered when conventional management strategies are not sufficient to safely support gas exchange. More research is needed to identify optimal mechanical ventilation during ECLS, weaning ECLS support, strategies for mobilization, sedation and anticoagulation, and long-term outcomes post-ECLS.

The Virtual Interview Experience: Perspectives of Pulmonary and Critical Care Fellowship Applicants.

Background: Because of the coronavirus disease (COVID-19) pandemic, graduate medical education programs adopted virtual interviews (VIs) as the default modality for the 2020 recruitment season. It is unknown whether VIs allowed applicants to effectively evaluate programs, and the best interview format for the future is unclear. Objective: To 1) assess pulmonary and critical care applicants' perceived ability to evaluate programs using VIs, 2) determine the attitudes of applicants toward the components of VIs, and 3) identify applicants' preferences for the future fellowship interview format. Methods: After the National Residency Matching Program medical subspecialty match, an electronic survey was sent to 1,067 applicants to pulmonary and critical care medicine programs asking them to compare their fellowship VI experience with their residency in-person interview (IPI) experience. Results: Three hundred six (29%) applicants responded to the survey, and 289 completed it (27%). There were 117 (40%) women and 146 (51%) White individuals. Most respondents believed that VIs hindered their ability to evaluate programs' culture, faculty-fellow relationships, location, facilities, and their own fit within the program. They believed they were able to evaluate the clinical experience, curriculum, and potential for academic development equally well compared with IPIs. The most helpful elements of VIs were the interview with the program director, meetings with the fellows, and interviews with faculty members. Less helpful elements included conference access, prerecorded program director presentations, virtual hospital and city tours, and video testimonials. One hundred twenty-three respondents (43%) chose VIs with an optional visit as their preferred future interview format, 85 (29%) chose IPIs, 54 (19%) wanted a choice between VIs and IPIs, and 27 (9%) chose VIs only. Conclusion: Most pulmonary and critical care medicine applicants preferred future interviews to include both VIs and the option of an in-person visit or interview. This study can assist programs in designing their future interview formats in a trainee-centric fashion.

In COVID-19 Patients Who Suffer In-Hospital Cardiac Arrest, Cardiopulmonary Resuscitation Outcomes May Be Impacted by Arrest Etiology and Local Pandemic Conditions.

OBJECTIVES: The utility and risks to providers of performing cardiopulmonary resuscitation after in-hospital cardiac arrest in COVID-19 patients have been questioned. Additionally, there are discrepancies in reported COVID-19 in-hospital cardiac arrest survival rates. We describe outcomes after cardiopulmonary resuscitation for in-hospital cardiac arrest in two COVID-19 patient cohorts. DESIGN: Retrospective cohort study. SETTING: New York-Presbyterian Hospital/Columbia University Irving Medical Center in New York, NY. PATIENTS: Those admitted with COVID-19 between March 1, 2020, and May 31, 2020, as well as between March 1, 2021, and May 31, 2021, who received resuscitation after in-hospital cardiac arrest. INTERVENTIONS: None. MEASUREMENT AND MAIN RESULTS: Among 103 patients with coronavirus disease 2019 who were resuscitated after in-hospital cardiac arrest in spring 2020, most self-identified as Hispanic/Latino or African American, 35 (34.0%) had return of spontaneous circulation for at least 20 minutes, and 15 (14.6%) survived to 30 days post-arrest. Compared with nonsurvivors, 30-day survivors experienced in-hospital cardiac arrest later (day 22 vs day 7; p = 0.008) and were more likely to have had an acute respiratory event preceding in-hospital cardiac arrest (93.3% vs 27.3%; p < 0.001). Among 30-day survivors, 11 (73.3%) survived to hospital discharge, at which point 8 (72.7%) had Cerebral Performance Category scores of 1 or 2. Among 26 COVID-19 patients resuscitated after in-hospital cardiac arrest in spring 2021, 15 (57.7%) had return of spontaneous circulation for at least 20 minutes, 3 (11.5%) survived to 30 days post in-hospital cardiac arrest, and 2 (7.7%) survived to hospital discharge, both with Cerebral Performance Category scores of 2 or less. Those who survived to 30 days post in-hospital cardiac arrest were younger (46.3 vs 67.8; p = 0.03), but otherwise there were no significant differences between groups. CONCLUSIONS: Patients with COVID-19 who received cardiopulmonary resuscitation after in-hospital cardiac arrest had low survival rates. Our findings additionally show return of spontaneous circulation rates in these patients may be impacted by hospital strain and that patients with in-hospital cardiac arrest preceded by acute respiratory events might be more likely to survive to 30 days, suggesting Advanced Cardiac Life Support efforts may be more successful in this subpopulation.

Latent Class Analysis Reveals COVID-19-related Acute Respiratory Distress Syndrome Subgroups with Differential Responses to Corticosteroids.

Rationale: Two distinct subphenotypes have been identified in acute respiratory distress syndrome (ARDS), but the presence of subgroups in ARDS associated with coronavirus disease (COVID-19) is unknown. Objectives: To identify clinically relevant, novel subgroups in COVID-19-related ARDS and compare them with previously described ARDS subphenotypes. Methods: Eligible participants were adults with COVID-19 and ARDS at Columbia University Irving Medical Center. Latent class analysis was used to identify subgroups with baseline clinical, respiratory, and laboratory data serving as partitioning variables. A previously developed machine learning model was used to classify patients as the hypoinflammatory and hyperinflammatory subphenotypes. Baseline characteristics and clinical outcomes were compared between subgroups. Heterogeneity of treatment effect for corticosteroid use in subgroups was tested. Measurements and Main Results: From March 2, 2020, to April 30, 2020, 483 patients with COVID-19-related ARDS met study criteria. A two-class latent class analysis model best fit the population (P = 0.0075). Class 2 (23%) had higher proinflammatory markers, troponin, creatinine, and lactate, lower bicarbonate, and lower blood pressure than class 1 (77%). Ninety-day mortality was higher in class 2 versus class 1 (75% vs. 48%; P < 0.0001). Considerable overlap was observed between these subgroups and ARDS subphenotypes. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RT-PCR cycle threshold was associated with mortality in the hypoinflammatory but not the hyperinflammatory phenotype. Heterogeneity of treatment effect to corticosteroids was observed (P = 0.0295), with improved mortality in the hyperinflammatory phenotype and worse mortality in the hypoinflammatory phenotype, with the caveat that corticosteroid treatment was not randomized. Conclusions: We identified two COVID-19-related ARDS subgroups with differential outcomes, similar to previously described ARDS subphenotypes. SARS-CoV-2 PCR cycle threshold had differential value for predicting mortality in the subphenotypes. The subphenotypes had differential treatment responses to corticosteroids.

Supervised Machine Learning Approach to Identify Early Predictors of Poor Outcome in Patients with COVID-19 Presenting to a Large Quaternary Care Hospital in New York City.

BACKGROUND: The progression of clinical manifestations in patients with coronavirus disease 2019 (COVID-19) highlights the need to account for symptom duration at the time of hospital presentation in decision-making algorithms. METHODS: We performed a nested case-control analysis of 4103 adult patients with COVID-19 and at least 28 days of follow-up who presented to a New York City medical center. Multivariable logistic regression and classification and regression tree (CART) analysis were used to identify predictors of poor outcome. RESULTS: Patients presenting to the hospital earlier in their disease course were older, had more comorbidities, and a greater proportion decompensated (<4 days, 41%; 4-8 days, 31%; >8 days, 26%). The first recorded oxygen delivery method was the most important predictor of decompensation overall in CART analysis. In patients with symptoms for <4, 4-8, and >8 days, requiring at least non-rebreather, age ≥ 63 years, and neutrophil/lymphocyte ratio ≥ 5.1; requiring at least non-rebreather, IL-6 ≥ 24.7 pg/mL, and D-dimer ≥ 2.4 µg/mL; and IL-6 ≥ 64.3 pg/mL, requiring non-rebreather, and CRP ≥ 152.5 mg/mL in predictive models were independently associated with poor outcome, respectively. CONCLUSION: Symptom duration in tandem with initial clinical and laboratory markers can be used to identify patients with COVID-19 at increased risk for poor outcomes.