Faculty Bibliography

Although high-throughput data allow researchers to interrogate thousands of variables simultaneously, it can also introduce a significant number of spurious results. Here we demonstrate that correlation analysis of large datasets can yield numerous false positives due to the presence of outliers that canonical methods fail to identify. We present Correlations Under The InfluencE (CUTIE), an open-source jackknifing-based method to detect such cases with both parametric and non-parametric correlation measures, and which can also uniquely rescue correlations not originally deemed significant or with incorrect sign. Our approach can additionally be used to identify variables or samples that induce these false correlations in high proportion. A meta-analysis of various omics datasets using CUTIE reveals that this issue is pervasive across different domains, although microbiome data are particularly susceptible to it. Although the significance of a correlation eventually depends on the thresholds used, our approach provides an efficient way to automatically identify those that warrant closer examination in very large datasets.

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

OBJECTIVES: We designed a prospective cohort study to systematically study patients with severe acute respiratory infection (SARI) and improve hospital preparedness (SARI-PREP). The goal of this project is to evaluate the natural history, prognostic biomarkers, and characteristics, including hospital stress, associated with SARI clinical outcomes and severity.
METHOD(S): In collaboration with the Society of Critical Care Medicine Discovery Research Network and the National Emerging Special Pathogen Training and Education Center (NETEC), SARIPREP is an ongoing, prospective, observational, multi-center cohort study of hospitalized patients with respiratory viral infections. We collected patient demographics, signs, symptoms, and medications; microbiology, imaging, and other diagnostics; mechanical ventilation, hospital procedures, and other interventions; and clinical outcomes. Hospital leadership completed a weekly hospital stress survey. Respiratory, blood, and urine biospecimens were collected from patients on days 0, 3, 7-14 after study enrollment and at hospital discharge. MEASUREMENTS AND MAIN RESULTS: SARI-PREP enrollment began on April 4, 2020 and currently includes 674 patients. Here we report results from the first 400 patients: 216 are from the University of Washington Hospitals, Seattle WA, 142 from New York University, New York NY and 42 from University of Southern California, Los Angeles, CA. Almost all tested positive for SARS-CoV-2 infection (n=397), whereas 3 patients tested positive for an alternative viral pathogen. The mean (+/-SD) age of the patients was 57+/-16 years; 72% were men, 62% were White, 14% were Asian, 12% were Black, and 31% were Hispanic. Most of the patients were admitted to the intensive care unit (96%). The median (interquartile range) hospital length of stay was 22 (9-46) days. Rates of invasive mechanical ventilation (72%) and renal replacement therapy (19%) were common and the rate of hospital mortality was 35%.
CONCLUSION(S): Initial SARI-PREP analysis indicates enrollment of a diverse population of hospitalized patients primarily with SARSCoV-2 infection. The demographics and clinical outcomes of our cohort mirror other large critically ill cohorts of COVID-19 patients. Results of a concomitant, weekly, hospital stress assessment are reported separately

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.

BACKGROUND:Signifying the 2-compartments/1-disease paradigm, allergic rhinoconjunctivitis (ARC) and asthma (AA) are prevalent, comorbid conditions triggered by environmental factors (eg, house dust mites [HDMs]). However, despite the ubiquity of triggers, progression to severe ARC/AA is infrequent, suggesting either resilience or adaptation. OBJECTIVE:We sought to determine whether ARC/AA severity relates to maladaptive responses to disease triggers. METHODS:Adults with HDM-associated ARC were challenged repetitively with HDMs in an aeroallergen challenge chamber. Mechanistic traits associated with disease severity were identified. RESULTS:mucosal-associated invariant T cells, and deficiencies along the TLR-IRF-IFN antiviral pathway. Maladaptive traits tracking HDM-associated ARC also contributed to AA risk and severity models. CONCLUSIONS:Repetitive challenges with HDMs revealed that maladaptation to disease triggers may underpin ARC/AA disease severity. A combinatorial therapeutic approach may involve reversal of loss-of-beneficial-function traits (ineffectual epithelial integrity, TLR-IRF-IFN deficiencies), mitigation of gain-of-adverse-function traits (inflammation), and blocking of a detrimental crosstalk between the peripheral blood and airway compartments.

OBJECTIVES/OBJECTIVE:To assess the impact of percutaneous dilational tracheostomy in coronavirus disease 2019 patients requiring mechanical ventilation and the risk for healthcare providers. DESIGN/METHODS:Prospective cohort study; patients were enrolled between March 11, and April 29, 2020. The date of final follow-up was July 30, 2020. We used a propensity score matching approach to compare outcomes. Study outcomes were formulated before data collection and analysis. SETTING/METHODS:Critical care units at two large metropolitan hospitals in New York City. PATIENTS/METHODS:Five-hundred forty-one patients with confirmed severe coronavirus disease 2019 respiratory failure requiring mechanical ventilation. INTERVENTIONS/METHODS:Bedside percutaneous dilational tracheostomy with modified visualization and ventilation. MEASUREMENTS AND MAIN RESULTS/RESULTS:Required time for discontinuation off mechanical ventilation, total length of hospitalization, and overall patient survival. Of the 541 patients, 394 patients were eligible for a tracheostomy. One-hundred sixteen were early percutaneous dilational tracheostomies with median time of 9 days after initiation of mechanical ventilation (interquartile range, 7-12 d), whereas 89 were late percutaneous dilational tracheostomies with a median time of 19 days after initiation of mechanical ventilation (interquartile range, 16-24 d). Compared with patients with no tracheostomy, patients with an early percutaneous dilational tracheostomy had a higher probability of discontinuation from mechanical ventilation (absolute difference, 30%; p < 0.001; hazard ratio for successful discontinuation, 2.8; 95% CI, 1.34-5.84; p = 0.006) and a lower mortality (absolute difference, 34%, p < 0.001; hazard ratio for death, 0.11; 95% CI, 0.06-0.22; p < 0.001). Compared with patients with late percutaneous dilational tracheostomy, patients with early percutaneous dilational tracheostomy had higher discontinuation rates from mechanical ventilation (absolute difference 7%; p < 0.35; hazard ratio for successful discontinuation, 1.53; 95% CI, 1.01-2.3; p = 0.04) and had a shorter median duration of mechanical ventilation in survivors (absolute difference, -15 d; p < 0.001). None of the healthcare providers who performed all the percutaneous dilational tracheostomies procedures had clinical symptoms or any positive laboratory test for severe acute respiratory syndrome coronavirus 2 infection. CONCLUSIONS:In coronavirus disease 2019 patients on mechanical ventilation, an early modified percutaneous dilational tracheostomy was safe for patients and healthcare providers and associated with improved clinical outcomes.