Faculty Bibliography

INTRODUCTION: Hospitals experienced substantial stress during the COVID-19 pandemic-threats to standard operations- but it is not well known how this stress manifested at individual hospitals. We aimed to understand patterns of hospital stress over time, where stress was located within hospitals, and correlations between individual stress measures.
METHOD(S): We conducted a weekly hospital stress survey from November 2020 through May 2021 among site leaders from the SCCM Discovery Severe Acute Respiratory Infection - Preparedness (SARI-PREP) multicenter prospective cohort study. The survey assessed hospital stress ordinally and also assessed ED and ICU stress and deviations from standard operating procedures. Pairwise comparisons of strain measures were calculated by Pearson's correlation coefficients (r).
RESULT(S): Eight hospitals across three health systems in New York, California, and Washington contributed 190 hospital-weeks of data. Sites reported unavailability of some hospital resources resulting in potentially avoidable patient harm during 3.5% of hospital-weeks (with at least one such week at four hospitals); alterations in care processes and/or staffing which were fully compensated for during 57.9% of weeks; and no stress during 38.6% of weeks. During one December 2020 week, hospital stress, ICU stress, and care deviations were all present at 100% of reporting sites. The most common care deviations were increased hospital staffing (39.5%) and cancelling elective surgeries (18.6%). Hospital stress and care deviations were highly correlated (r = 0.81, p < 0.0001). Stress was more common in ICUs (72.4%) than EDs (14.3%), and ICU and ED stress were not correlated (r = 0.19, p = 0.05). While ED stress rose and abated earlier, ICU stress and care deviations persisted (range 2-13 weeks longer) as local case rates declined.
CONCLUSION(S): Hospital stress during the pandemic varied in degree and type both within and among hospitals over time. Care deviations were common but potentially avoidable patient harm was rare. Systematic national assessments of hospital stress, both during and between pandemics, could inform more rapid, proactive public health responses to novel threats. Areas for further study include impacts from persistent low-level stress and longer-term consequences for hospitals and their communities

BACKGROUND:The COVID-19 pandemic overwhelmed New York City hospitals early in the pandemic. Shortages of ventilators and sedatives prompted tracheostomy earlier than recommended by professional societies. This study evaluates the impact of percutaneous dilational tracheostomy (PDT) in COVID+ patients on critical care capacity. METHODS:This is a single-institution prospective case series of mechanically ventilated COVID-19 patients undergoing PDT from April 1 to June 4, 2020 at a public tertiary care center. RESULTS:Fifty-five patients met PDT criteria and underwent PDT at a median of 13 days (IQR 10, 18) from intubation. Patient characteristics are found in Table 1. Intravenous midazolam, fentanyl, and cisatracurium equivalents were significantly reduced 48 hours post-PDT (Table 2). Thirty-five patients were transferred from the ICU and liberated from the ventilator. Median time from PDT to ventilator liberation and ICU discharge was 10 (IQR 4, 14) and 12 (IQR 8, 17) days, respectively. Decannulation occurred in 45.5% and 52.7% were discharged from acute inpatient care (Figure 1). Median follow-up for the study was 62 days. Four patients had bleeding complications postoperatively and 11 died during the study period. Older age was associated with increased odds of complication (OR 1.12, 95% CI 1.04, 1.23) and death (OR=1.15, 95% CI 1.05, 1.30). All operators tested negative for COVID-19 during the study period. CONCLUSION/CONCLUSIONS:These findings suggest COVID-19 patients undergoing tracheostomy within the standard time frame can improve critical care capacity in areas strained by the pandemic with low risk to operators. Long-term outcomes after PDT deserve further study.

Introduction: Tracheostomy in COVID-19 patients is a controversial and difficult clinical decision. A recent COVID-19 Severity Score (CSS) was validated to identify high-risk patients requiring hospitalization. We hypothesized that the CSS would be associated with survival in patients considered for tracheostomy.
Method(s): We reviewed 77 mechanically ventilated COVID-19 patients evaluated for percutaneous dilational tracheostomy (PDT) from March-June 2020 at a public tertiary care center. Decision for PDT was based on clinical judgment of the screening surgeons. The CSS was retrospectively calculated using mean biomarker values from admission to time of PDT consult. Primary end point was survival to discharge. The Youden index identified an optimal CSS cut point for survival.
Result(s): Mean CSS for 42 survivors vs 35 nonsurvivors was significantly different (CSS 52 vs 66; p = 0.003). The Youden index returned an optimal CSS of 55 (area under the curve 0.7; 95% CI, 43 to 72). Median CSS was 40 (interquartile range 27 to 49) in the Low CSS (<55 group) and 72 (interquartile range 66 to 93) in the high CSS (>= 55) group (Fig. 1a). Eighty-seven percent of low CSS patients underwent PDT, with 74% survival, and 61% of high CSS patients underwent PDT with only 41% surviving (Fig. 1b). Patients with high CSS had 77% lower odds of survival (odds ratio 0.2; 95% CI, 0.1 to 0.7).
Conclusion(s): Higher CSS was associated with decreased survival to discharge in patients evaluated for PDT, with a score > 55 predictive of mortality. The novel CSS can be a useful adjunct in determining which COVID-19 patients will benefit from tracheostomy. Further prospective validation of this tool is warranted. [Formula presented]
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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: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:= .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.

Respiratory failure is associated with increased mortality in COVID-19 patients. There are no validated lower airway biomarkers to predict clinical outcome. We investigated whether bacterial respiratory infections were associated with poor clinical outcome of COVID-19 in a prospective, observational cohort of 589 critically ill adults, all of whom required mechanical ventilation. For a subset of 142 patients who underwent bronchoscopy, we quantified SARS-CoV-2 viral load, analysed the lower respiratory tract microbiome using metagenomics and metatranscriptomics and profiled the host immune response. Acquisition of a hospital-acquired respiratory pathogen was not associated with fatal outcome. Poor clinical outcome was associated with lower airway enrichment with an oral commensal (Mycoplasma salivarium). Increased SARS-CoV-2 abundance, low anti-SARS-CoV-2 antibody response and a distinct host transcriptome profile of the lower airways were most predictive of mortality. Our data provide evidence that secondary respiratory infections do not drive mortality in COVID-19 and clinical management strategies should prioritize reducing viral replication and maximizing host responses to SARS-CoV-2.

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.

OBJECTIVES/OBJECTIVE:To evaluate the impact of ICU surge on mortality and to explore clinical and sociodemographic predictors of mortality. DESIGN/METHODS:Retrospective cohort analysis. SETTING/METHODS:NYC Health + Hospitals ICUs. PATIENTS/METHODS:Adult ICU patients with coronavirus disease 2019 admitted between March 24, and May 12, 2020. INTERVENTIONS/METHODS:None. MEASUREMENTS AND MAIN RESULTS/RESULTS:Hospitals reported surge levels daily. Uni- and multivariable analyses were conducted to assess factors impacting in-hospital mortality. Mortality in Hispanic patients was higher for high/very high surge compared with low/medium surge (69.6% vs 56.4%; p = 0.0011). Patients 65 years old and older had similar mortality across surge levels. Mortality decreased from high/very high surge to low/medium surge in, patients 18-44 years old and 45-64 (18-44 yr: 46.4% vs 27.3%; p = 0.0017 and 45-64 yr: 64.9% vs 53.2%; p = 0.002), and for medium, high, and very high poverty neighborhoods (medium: 69.5% vs 60.7%; p = 0.019 and high: 71.2% vs 59.7%; p = 0.0078 and very high: 66.6% vs 50.7%; p = 0.0003). In the multivariable model high surge (high/very high vs low/medium odds ratio, 1.4; 95% CI, 1.2-1.8), race/ethnicity (Black vs White odds ratio, 1.5; 95% CI, 1.1-2.0 and Asian vs White odds ratio 1.5; 95% CI, 1.0-2.3; other vs White odds ratio 1.5, 95% CI, 1.0-2.3), age (45-64 vs 18-44 odds ratio, 2.0; 95% CI, 1.6-2.5 and 65-74 vs 18-44 odds ratio, 5.1; 95% CI, 3.3-8.0 and 75+ vs 18-44 odds ratio, 6.8; 95% CI, 4.7-10.1), payer type (uninsured vs commercial/other odds ratio, 1.7; 95% CI, 1.2-2.3; medicaid vs commercial/other odds ratio, 1.3; 95% CI, 1.1-1.5), neighborhood poverty (medium vs low odds ratio 1.6, 95% CI, 1.0-2.4 and high vs low odds ratio, 1.8; 95% CI, 1.3-2.5), comorbidities (diabetes odds ratio, 1.6; 95% CI, 1.2-2.0 and asthma odds ratio, 1.4; 95% CI, 1.1-1.8 and heart disease odds ratio, 2.5; 95% CI, 2.0-3.3), and interventions (mechanical ventilation odds ratio, 8.8; 95% CI, 6.1-12.9 and dialysis odds ratio, 3.0; 95% CI, 1.9-4.7) were significant predictors for mortality. CONCLUSIONS:Patients admitted to ICUs with higher surge scores were at greater risk of death. Impact of surge levels on mortality varied across sociodemographic groups.

Mortality among patients with COVID-19 and respiratory failure is high and there are no known lower airway biomarkers that predict clinical outcome. We investigated whether bacterial respiratory infections and viral load were associated with poor clinical outcome and host immune tone. We obtained bacterial and fungal culture data from 589 critically ill subjects with COVID-19 requiring mechanical ventilation. On a subset of the subjects that underwent bronchoscopy, we also quantified SARS-CoV-2 viral load, analyzed the microbiome of the lower airways by metagenome and metatranscriptome analyses and profiled the host immune response. We found that isolation of a hospital-acquired respiratory pathogen was not associated with fatal outcome. However, poor clinical outcome was associated with enrichment of the lower airway microbiota with an oral commensal ( Mycoplasma salivarium ), while high SARS-CoV-2 viral burden, poor anti-SARS-CoV-2 antibody response, together with a unique host transcriptome profile of the lower airways were most predictive of mortality. Collectively, these data support the hypothesis that 1) the extent of viral infectivity drives mortality in severe COVID-19, and therefore 2) clinical management strategies targeting viral replication and host responses to SARS-CoV-2 should be prioritized.

Mortality among patients with COVID-19 and respiratory failure is high and there are no known lower airway biomarkers that predict clinical outcome. We investigated whether bacterial respiratory infections and viral load were associated with poor clinical outcome and host immune tone. We obtained bacterial and fungal culture data from 589 critically ill subjects with COVID-19 requiring mechanical ventilation. On a subset of the subjects that underwent bronchoscopy, we also quantified SARS-CoV-2 viral load, analyzed the microbiome of the lower airways by metagenome and metatranscriptome analyses and profiled the host immune response. We found that isolation of a hospital-acquired respiratory pathogen was not associated with fatal outcome. However, poor clinical outcome was associated with enrichment of the lower airway microbiota with an oral commensal ( Mycoplasma salivarium ), while high SARS-CoV-2 viral burden, poor anti-SARS-CoV-2 antibody response, together with a unique host transcriptome profile of the lower airways were most predictive of mortality. Collectively, these data support the hypothesis that 1) the extent of viral infectivity drives mortality in severe COVID-19, and therefore 2) clinical management strategies targeting viral replication and host responses to SARS-CoV-2 should be prioritized.