Clinical Outcomes in Critically Ill Coronavirus Disease 2019 Patients: A Unique New York City Public Hospital Experience.

To explore demographics, comorbidities, transfers, and mortality in critically ill patients with confirmed severe acute respiratory syndrome coronavirus 2. DESIGN: Retrospective cohort study. SETTING: Data were collected from a large tertiary care public hospital ICU that is part of the largest public healthcare network in the United States. PATIENTS: One-hundred thirty-seven adult (≥ 18 yr old) ICU patients admitted between March 10, 2020, and April 7, 2020, with follow-up collected through May 18, 2020. INTERVENTIONS: None. MEASUREMENTS: Demographic, clinical, laboratory, treatment, and outcome data extracted from electronic medical records. MAIN RESULTS: The majority of patients were male (99/137; 72.3%) and older than 50 years old (108/137; 78.9%). The most reported ethnicity and race were Hispanic (61/137; 44.5%) and Black (23/137; 16.7%). One-hundred six of 137 patients had at least one comorbidity (77.4%). One-hundred twenty-one of 137 (78.1%) required mechanical ventilation of whom 30 (24.8%) moved to tracheostomy and 46 of 137 (33.6%) required new onset renal replacement therapy. Eighty-two of 137 patients (59.9%) died after a median of 8 days (interquartile range 5-15 d) in the ICU. Male sex had a trend toward a higher hazard of death (hazard ratio, 2.1 [1.1-4.0]) in the multivariable Cox model. CONCLUSIONS: We report a mortality rate of 59.9% in a predominantly Hispanic and Black patient population. A significant association between comorbidities and mortality was not found in multivariable regression, and further research is needed to study factors that impact mortality in critical coronavirus disease 2019 patients. We also describe how a public hospital developed innovative approaches to safely manage a large volume of interhospital transfers and admitted patients.

Point-of-care ultrasound in a pandemic: Practical guidance in COVID-19 units.

The coronavirus disease 2019 (COVID-19) pandemic has stretched our healthcare system to the brink, highlighting the importance of efficient resource utilization without compromising healthcare provider safety. While advanced imaging is a great resource for diagnostic purposes, the risk of contamination and infection transmission is high and requires extensive logistical planning for intrahospital patient transport, healthcare provider safety, and post-imaging decontamination. This dilemma has necessitated the transition to more bedside imaging. More so than ever, during the current pandemic, the clinical utility and importance of point-of-care ultrasound (POCUS) cannot be overstressed. It allows for safe and efficient beside procedural guidance and provides front line providers with valuable diagnostic information that can be acted upon in real-time for immediate clinical decision-making. The authors have been routinely using POCUS for the management of COVID-19 patients both in the emergency department and in intensive care units turned into "COVID-units." In this article, we review the nuances of using POCUS in a pandemic situation and maximizing diagnostic output from this bedside technology. Additionally, we review various methods and diagnostic uses of POCUS which can replace conventional imaging and bridge current literature and common clinical practices in critically ill patients. We discuss practical guidance and pertinent review of the literature for the most relevant procedural and diagnostic guidance of respiratory illness, hemodynamic decompensation, renal failure, and gastrointestinal disorders experienced by many patients admitted to COVID-units.

Respiratory Mechanics and Association With Inflammation in COVID-19-Related ARDS.

BACKGROUND: The novel coronavirus-associated ARDS (COVID-19 ARDS) often requires invasive mechanical ventilation. A spectrum of atypical ARDS with different phenotypes (high vs low static compliance) has been hypothesized in COVID-19. METHODS: We conducted a retrospective analysis to identify respiratory mechanics in COVID-19 ARDS. Berlin definition was used to categorize severity of ARDS. Correlational analysis using t test, chi-square test, ANOVA test, and Pearson correlation was used to identify relationship between subject variables and respiratory mechanics. The primary outcome was duration of mechanical ventilation. Secondary outcomes were correlation between fluid status, C- reactive protein, PEEP, and D-dimer with respiratory and ventilatory parameters. RESULTS: Median age in our cohort was 60.5 y with predominantly male subjects. Up to 53% subjects were classified as severe ARDS (median [Formula: see text] = 86) with predominantly low static compliance (median Cst- 25.5 mL/cm H2O). The overall mortality in our cohort was 61%. The total duration of mechanical ventilation was 35 d in survivors and 14 d in nonsurvivors. High PEEP (r = 0.45, P < .001) and D-dimer > 2,000 ng/dL (P = .009) correlated with significant increase in physiologic dead space without significant correlation with [Formula: see text]. Higher net fluid balance was inversely related to static compliance (r = -0.24, P = .045), and elevation in C- reactive protein was inversely related to [Formula: see text] (r = -0.32, P = .02). CONCLUSIONS: In our cohort of mechanically ventilated COVID-19 ARDS subjects, high PEEP and D-dimer were associated with increase in physiologic dead space without significant effect on oxygenation, raising the question of potential microvascular dysfunction.

Imaging algorithm for COVID-19: A practical approach.

The global pandemic of COVID-19 pneumonia caused by the novel coronavirus (SARS-CoV-2) has strained healthcare resources across the world with emerging challenges of mass testing, resource allocation and management. While reverse transcriptase-polymerase chain reaction (RT-PCR) test is the most commonly utilized test and considered the current gold standard for diagnosis, the role of chest imaging has been highlighted by several studies demonstrating high sensitivity of computed tomography (CT). Many have suggested using CT chest as a first-line screening tool for the diagnosis of COVID-19. However, with advancement of laboratory testing and challenges in obtaining a CT scan without significant risk to healthcare providers, the role of imaging in diagnosis has been questioned. Several imaging societies have released consensus statements and guidelines on utilizing imaging resources and optimal reporting. In this review, we highlight the current evidence on various modalities in thoracic imaging for the diagnosis of COVID-19 and describe an algorithm on how to use these resources in an optimal fashion in accordance with the guidelines and statements released by major imaging societies.