Search

Abstract Objectives Patients hospitalized for COVID‐19 frequently develop hypoxemia and acute respiratory distress syndrome (ARDS) after admission. In non‐COVID‐19 ARDS studies, admission to hospital wards with subsequent transfer to intensive care unit (ICU) is associated with worse outcomes. We hypothesized that initial admission to the ward may affect outcomes in patient with COVID‐19 ARDS. Methods This was a retrospective study of consecutive adults admitted for COVID‐19 ARDS between March 2020 and March 2021 at Stanford Health Care. Mortality scores at hospital admission (Coronavirus Clinical Characterization Consortium Mortality Score [4C score]) and ICU admission (Simplified Acute Physiology Score III [SAPS‐III]) were calculated, as well as ROX index for patients on high flow nasal oxygen. Patients were classified by emergency department (ED) disposition (ward‐first vs. ICU‐direct), and 28‐ and 60‐day mortality and highest level of respiratory support within 1 day of ICU admission were compared. A second cohort (April 2021‒July 2022, n = 129) was phenotyped to validate mortality outcome. Results A total of 157 patients were included, 48% of whom were first admitted to the ward (n = 75). Ward‐first patients had more comorbidities, including lung disease. Ward‐first patients had lower 4C and similar SAPS‐III score, yet increased mortality at 28 days (32% vs. 17%, hazard ratio [HR] 2.0, 95% confidence interval [95% CI] 1.0‒3.7, p = 0.039) and 60 days (39% vs. 23%, HR 1.83, 95% CI 1.04‒3.22, p = 0.037) compared to ICU‐direct patients. More ward‐first patients escalated to mechanical ventilation on day 1 of ICU admission (36% vs. 14%, p = 0.002) despite similar ROX index. Ward‐first patients who upgraded to ICU within 48 h of ED presentation had the highest mortality. Mortality findings were replicated in a sensitivity analysis. Conclusion Despite similar baseline risk scores, ward‐first patients with COVID‐19 ARDS had increased mortality and escalation to mechanical ventilation compared to ICU‐direct patients. Ward‐first patients requiring ICU upgrade within 48 h were at highest risk, highlighting a need for improved identification of this group at ED admission.

The widespread presence of autoantibodies in acute infection with SARS-CoV-2 is increasingly recognized, but the prevalence of autoantibodies in non–SARS-CoV-2 infections and critical illness has not yet been reported. We profiled IgG autoantibodies in 267 patients from 5 independent cohorts with non–SARS-CoV-2 viral, bacterial, and noninfectious critical illness. Serum samples were screened using Luminex arrays that included 58 cytokines and 55 autoantigens, many of which are associated with connective tissue diseases (CTDs). Samples positive for anti-cytokine antibodies were tested for receptor blocking activity using cell-based functional assays. Anti-cytokine antibodies were identified in > 50% of patients across all 5 acutely ill cohorts. In critically ill patients, anti-cytokine antibodies were far more common in infected versus uninfected patients. In cell-based functional assays, 11 of 39 samples positive for select anti-cytokine antibodies displayed receptor blocking activity against surface receptors for Type I IFN, GM-CSF, and IL-6. Autoantibodies against CTD-associated autoantigens were also commonly observed, including newly detected antibodies that emerged in longitudinal samples. These findings demonstrate that anti-cytokine and autoantibodies are common across different viral and nonviral infections and range in severity of illness.

Here, the authors perform transcriptional profiling on tracheal aspirates of adults requiring mechanical ventilation for SARS-CoV2-induced acute respiratory distress syndrome (ARDS) and identify a dysregulated host response predicted to predicted to be potentially modulated by dexamethasone.

Abstract Several clinical calculators predict intensive care unit (ICU) mortality, however these are cumbersome and often require 24 h of data to calculate. Retrospective studies have demonstrated the utility of whole blood transcriptomic analysis in predicting mortality. In this study, we tested prospective validation of an 11-gene messenger RNA (mRNA) score in an ICU population. Whole blood mRNA from 70 subjects in the Stanford ICU Biobank with samples collected within 24 h of Emergency Department presentation were used to calculate an 11-gene mRNA score. We found that the 11-gene score was highly associated with 60-day mortality, with an area under the receiver operating characteristic curve of 0.68 in all patients, 0.77 in shock patients, and 0.98 in patients whose primary determinant of prognosis was acute illness. Subjects with the highest quartile of mRNA scores were more likely to die in hospital (40% vs 7%, p 24 h after emergency department presentation. Tests will target a 30-min turnaround time, allowing for rapid results early in admission. Moving forward, this test may provide valuable real-time prognostic information to improve triage decisions and allow for enrichment of clinical trials.

Abstract This article is one of ten reviews selected from the Annual Update in Intensive Care and Emergency Medicine 2020. Other selected articles can be found online at https://www.biomedcentral.com/collections/annualupdate2020. Further information about the Annual Update in Intensive Care and Emergency Medicine is available from http://www.springer.com/series/8901.

Abstract Objectives Studies have found that prolonged boarding time for intensive care unit (ICU) patients in the emergency department (ED) is associated with higher in‐hospital mortality. However, these studies introduced selection bias by excluding patients with ICU admission orders who were downgraded and never arrived in the ICU. Consequently, they may overestimate mortality in prolonged ED boarders. Methods This was a retrospective cohort study at a single center covering the period from August 14, 2015 to August 13, 2019. Adult ED patients with medical ICU admission orders and at least 6 hours of subsequent critical care in either the ED or the ICU were included. Patients were classified as having either prolonged (>6 hours) or non‐prolonged (≤6 hours) ED boarding. Downgraded patients were identified, and mortality was compared, both including and excluding downgraded patients. Results Of 1862 patients, 612 (32.9%) had prolonged boarding; at 6 hours after ICU admission order entry, they were still in the ED. The remaining 1250 (67.1%) had non‐prolonged boarding; at 6 hours after the ICU admission order entry, they were already in the ICU. In‐hospital mortality in the non‐prolonged boarding group was 18.9%. In the prolonged boarding group, 296 (48.4%) patients were downgraded in the ED and never arrived in the ICU. Including these ED downgrades, the mortality in the prolonged boarding group was 13.4% (risk difference ‐5.5%, 95% confidence interval [CI] ‐8.9% to ‐2.0%, P = 0.0031). When we excluded downgrades, the mortality in the prolonged boarding group increased to 17.4% (risk difference ‐1.5%, 95% CI ‐6.2% to 3.2%, P = 0.5720). The lower mortality in the prolonged group was attributable to lower severity of illness (mean emergency critical care SOFA [eccSOFA] difference: ‐0.8, 95% CI ‐1.1 to ‐0.4, P

Early in the COVID-19 pandemic, the World Health Organization stressed the importance of daily clinical assessments of infected patients, yet current approaches frequently consider cross-sectional timepoints, cumulative summary measures, or time-to-event analyses. Statistical methods are available that make use of the rich information content of longitudinal assessments. We demonstrate the use of a multistate transition model to assess the dynamic nature of COVID-19-associated critical illness using daily evaluations of COVID-19 patients from 9 academic hospitals. We describe the accessibility and utility of methods that consider the clinical trajectory of critically ill COVID-19 patients.

Objectives:. Given finite ICU bed capacity, knowledge of ICU bed utilization during the coronavirus disease 2019 pandemic is critical to ensure future strategies for resource allocation and utilization. We sought to examine ICU census trends in relation to ICU bed capacity during the rapid increase in severe coronavirus disease 2019 cases early during the pandemic. Design:. Observational cohort study. Setting:. Thirteen geographically dispersed academic medical centers in the United States. Patients/Subjects:. We obtained daily ICU censuses from March 26 to June 30, 2020, as well as prepandemic ICU bed capacities. The primary outcome was daily census of ICU patients stratified by coronavirus disease 2019 and mechanical ventilation status in relation to ICU capacity. Interventions:. None. Measurements and Main Results:. Prepandemic overall ICU capacity ranged from 62 to 225 beds (median 109). During the study period, the median daily coronavirus disease 2019 ICU census per hospital ranged from 1 to 84 patients, and the daily ICU census exceeded overall ICU capacity for at least 1 day at five institutions. The number of critically ill patients exceeded ICU capacity for a median (interquartile range) of 17 (12–50) of 97 days at these five sites. All 13 institutions experienced decreases in their noncoronavirus disease ICU population, whereas local coronavirus disease 2019 cases increased. Coronavirus disease 2019 patients reached their greatest proportion of ICU capacity on April 12, 2020, when they accounted for 44% of ICU patients across all participating hospitals. Maximum ICU census ranged from 52% to 289% of overall ICU capacity, with three sites less than 80%, four sites 80–100%, five sites 100–128%, and one site 289%. Conclusions:. From March to June 2020, the coronavirus disease 2019 pandemic led to ICU censuses greater than ICU bed capacity at fives of 13 institutions evaluated. These findings demonstrate the short-term adaptability of U.S. healthcare institutions in redirecting limited resources to accommodate a public health emergency.

BACKGROUND Elevated levels of inflammatory cytokines have been associated with poor outcomes among COVID-19 patients. It is unknown, however, how these levels compare with those observed in critically ill patients with acute respiratory distress syndrome (ARDS) or sepsis due to other causes.METHODS We used a Luminex assay to determine expression of 76 cytokines from plasma of hospitalized COVID-19 patients and banked plasma samples from ARDS and sepsis patients. Our analysis focused on detecting statistical differences in levels of 6 cytokines associated with cytokine storm (IL-1β, IL-1RA, IL-6, IL-8, IL-18, and TNF-α) between patients with moderate COVID-19, severe COVID-19, and ARDS or sepsis.RESULTS Fifteen hospitalized COVID-19 patients, 9 of whom were critically ill, were compared with critically ill patients with ARDS (n = 12) or sepsis (n = 16). There were no statistically significant differences in baseline levels of IL-1β, IL-1RA, IL-6, IL-8, IL-18, and TNF-α between patients with COVID-19 and critically ill controls with ARDS or sepsis.CONCLUSION Levels of inflammatory cytokines were not higher in severe COVID-19 patients than in moderate COVID-19 or critically ill patients with ARDS or sepsis in this small cohort. Broad use of immunosuppressive therapies in ARDS has failed in numerous Phase 3 studies; use of these therapies in unselected patients with COVID-19 may be unwarranted.FUNDING Funding was received from NHLBI K23 HL125663 (AJR); The Bill and Melinda Gates Foundation OPP1113682 (AJR and CAB); Burroughs Wellcome Fund Investigators in the Pathogenesis of Infectious Diseases #1016687 NIH/NIAID U19AI057229-16; Stanford Maternal Child Health Research Institute; and Chan Zuckerberg Biohub (CAB).

Natural cloud-to-ground (CG) lightning behaves differently over land and ocean. These differences likely reflect local variations in the speed at which storms develop over ocean, and are possibly contributed to by differences in the local aerosol composition. Earlier studies have reported statistically larger peak currents for negative CG first strokes over ocean than over land. This work focuses on differences in this relationship for first strokes, for subsequent strokes in existing channels to ground, and for subsequent strokes creating new ground contacts. This distinction will shed light on the mechanism responsible for the observed land:ocean differences, and can either support or refute the hypothesis that this difference is associated with the propagation of downward negative leaders in free space, driven by the vertical profile of electric field within and below the cloud. Results show that when compensated for detection threshold increases with increasing distance from land-based sensors, the distribution of estimated peak currents for subsequent strokes in existing (pre-ionized) channels to ground was indistinguishable from distributions for lightning that occurred inland, near shore, offshore, and in the distant ocean (~200 km offshore), with median values ranging between 14.4 and 15.1 kA. Conversely, the population of first strokes over distant ocean had much higher peak currents than those that occurred inland (median values of 23.1 kA vs. 17.3 kA, respectively), when corrected for detection threshold. These findings are consistent with the field-profile hypothesis noted above since peak currents for return strokes due to downward leaders that establish new channels (first strokes) would be impacted the most by the vertical profile of electric field near the cloud base, whereas the peak current for strokes in previously-established channels should be far less dependent on the field profile.

None Images in Emergency Medicine