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OBJECTIVES:. COVID-19 is a heterogenous disease. Biomarker-based approaches may identify patients at risk for severe disease, who may be more likely to benefit from specific therapies. Our objective was to identify and validate a plasma protein signature for severe COVID-19. DESIGN:. Prospective observational cohort study. SETTING:. Two hospitals in the United States. PATIENTS:. One hundred sixty-seven hospitalized adults with COVID-19. INTERVENTION:. None. MEASUREMENTS AND MAIN RESULTS:. We measured 713 plasma proteins in 167 hospitalized patients with COVID-19 using a high-throughput platform. We classified patients as nonsevere versus severe COVID-19, defined as the need for high-flow nasal cannula, mechanical ventilation, extracorporeal membrane oxygenation, or death, at study entry and in 7-day intervals thereafter. We compared proteins measured at baseline between these two groups by logistic regression adjusting for age, sex, symptom duration, and comorbidities. We used lead proteins from dysregulated pathways as inputs for elastic net logistic regression to identify a parsimonious signature of severe disease and validated this signature in an external COVID-19 dataset. We tested whether the association between corticosteroid use and mortality varied by protein signature. One hundred ninety-four proteins were associated with severe COVID-19 at the time of hospital admission. Pathway analysis identified multiple pathways associated with inflammatory response and tissue repair programs. Elastic net logistic regression yielded a 14-protein signature that discriminated 90-day mortality in an external cohort with an area under the receiver-operator characteristic curve of 0.92 (95% CI, 0.88–0.95). Classifying patients based on the predicted risk from the signature identified a heterogeneous response to treatment with corticosteroids (p = 0.006). CONCLUSIONS:. Inpatients with COVID-19 express heterogeneous patterns of plasma proteins. We propose a 14-protein signature of disease severity that may have value in developing precision medicine approaches for COVID-19 pneumonia.

OBJECTIVES:. Clinical deterioration of hospitalized patients is common and can lead to critical illness and death. Rapid response teams (RRTs) assess and treat high-risk patients with signs of clinical deterioration to prevent further worsening and subsequent adverse outcomes. Whether activation of the RRT early in the course of clinical deterioration impacts outcomes, however, remains unclear. We sought to characterize the relationship between increasing time to RRT activation after physiologic deterioration and short-term patient outcomes. DESIGN:. Retrospective multicenter cohort study. SETTING:. Three academic hospitals in Pennsylvania. PATIENTS:. We included the RRT activation of a hospitalization for non-ICU inpatients greater than or equal to 18 years old. INTERVENTIONS:. None. MEASUREMENTS AND MAIN RESULTS:. The primary exposure was time to RRT activation after physiologic deterioration. We selected four Cardiac Arrest Risk Triage (CART) score thresholds a priori from which to measure time to RRT activation (CART score ≥ 12, ≥ 16, ≥ 20, and ≥ 24). The primary outcome was 7-day mortality—death or discharge to hospice care within 7 days of RRT activation. For each CART threshold, we modeled the association of time to RRT activation duration with 7-day mortality using multivariable fractional polynomial regression. Increased time from clinical decompensation to RRT activation was associated with higher risk of 7-day mortality. This relationship was nonlinear, with odds of mortality increasing rapidly as time to RRT activation increased from 0 to 4 hours and then plateauing. This pattern was observed across several thresholds of physiologic derangement. CONCLUSIONS:. Increasing time to RRT activation was associated in a nonlinear fashion with increased 7-day mortality. This relationship appeared most marked when using a CART score greater than 20 threshold from which to measure time to RRT activation. We suggest that these empirical findings could be used to inform RRT delay definitions in further studies to determine the clinical impact of interventions focused on timely RRT activation.

Plasmalogens are plasma-borne antioxidant phospholipid species that provide protection as cellular lipid components during cellular oxidative stress. In this study we investigated plasma plasmalogen levels in human sepsis as well as in rodent models of infection. In humans, levels of multiple plasmenylethanolamine molecular species were decreased in septic patient plasma compared to control subject plasma as well as an age-aligned control subject cohort. Additionally, lysoplasmenylcholine levels were significantly decreased in septic patients compared to the control cohorts. In contrast, plasma diacyl phosphatidylethanolamine and phosphatidylcholine levels were elevated in septic patients. Lipid changes were also determined in rats subjected to cecal slurry sepsis. Plasma plasmenylcholine, plasmenylethanolamine, and lysoplasmenylcholine levels were decreased while diacyl phosphatidylethanolamine levels were increased in septic rats compared to control treated rats. Kidney levels of lysoplasmenylcholine as well as plasmenylethanolamine molecular species were decreased in septic rats. Interestingly, liver plasmenylcholine and plasmenylethanolamine levels were increased in septic rats. Since COVID-19 is associated with sepsis-like acute respiratory distress syndrome and oxidative stress, plasmalogen levels were also determined in a mouse model of COVID-19 (intranasal inoculation of K18 mice with SARS-CoV-2). 3 days following infection, lung infection was confirmed as well as cytokine expression in the lung. Multiple molecular species of lung plasmenylcholine and plasmenylethanolamine were decreased in infected mice. In contrast, the predominant lung phospholipid, dipalmitoyl phosphatidylcholine, was not decreased following SARS-CoV-2 infection. Additionally total plasmenylcholine levels were decreased in the plasma of SARS-CoV-2 infected mice. Collectively, these data demonstrate the loss of plasmalogens during both sepsis and SARS-CoV-2 infection. This study also indicates plasma plasmalogens should be considered in future studies as biomarkers of infection and as prognostic indicators for sepsis and COVID-19 outcomes.

OBJECTIVES:. Circulating nucleic acids, alone and in complex with histones as nucleosomes, have been proposed to link systemic inflammation and coagulation after trauma to acute kidney injury (AKI). We sought to determine the association of circulating nucleic acids measured at multiple time points after trauma with AKI risk. DESIGN:. We conducted a prospective cohort study of trauma patients, collecting plasma on presentation and at 6, 12, 24, and 48 hours, defining AKI over the first 6 days by Kidney Disease Improving Global Outcomes serum creatinine and dialysis criteria. We determined kinetics of plasma mitochondrial DNA (mtDNA), nuclear DNA (nDNA), and nucleosome levels across time points and associations with AKI using multivariable linear mixed-effects models, adjusted for injury characteristics and blood transfusions. We evaluated the association of presentation nucleic acid damage-associated molecular patterns (DAMP) concentrations with subsequent AKI, adjusting for injury severity using multivariable logistic regression. SETTING:. Academic level I trauma center. PATIENTS:. Trauma patients (n = 55) requiring intensive care for greater than or equal to 24 hours after presentation. INTERVENTIONS:. None. MEASUREMENTS AND MAIN RESULTS:. AKI developed in 17 patients (31%), a median of 12.0 hours (interquartile range, 6.2–24.1 hr) after presentation. mtDNA demonstrated a time-varying association with AKI (p = 0.022, interaction with time point), with differences by AKI status not emerging until 24 hours (β = 0.97 [95% CI, 0.03–1.90] log copies/uL; p = 0.043). Patients who developed AKI had higher nDNA across all time points (overall β = 1.41 log copies/uL [0.86–1.95 log copies/uL]; p < 0.001), and presentation levels were significantly associated with subsequent AKI (odds ratio [OR], 2.55 [1.36–4.78] per log copy/uL; p = 0.003). Patients with AKI had higher nucleosome levels at presentation (β = 0.32 [0.00–0.63] arbitrary unit; p = 0.048), a difference that was more pronounced at 24 hours (β = 0.41 [0.06–0.76]; p = 0.021) and 48 hours (β = 0.71 [0.35–1.08]; p < 0.001) (p = 0.075, interaction with time point). CONCLUSIONS:. Plasma nucleic acid DAMPs have distinct kinetics and associations with AKI in critically ill trauma patients. nDNA at presentation predicts subsequent AKI and may be amenable to targeted therapies in this population.

OBJECTIVES:. Physiological decompensation of hospitalized patients is common and is associated with substantial morbidity and mortality. Research surrounding patient decompensation has been hampered by the absence of a robust definition of decompensation and lack of standardized clinical criteria with which to identify patients who have decompensated. We aimed to: 1) develop a consensus definition of physiological decompensation and 2) to develop clinical criteria to identify patients who have decompensated. DESIGN:. We utilized a three-phase, modified electronic Delphi (eDelphi) process, followed by a discussion round to generate consensus on the definition of physiological decompensation and on criteria to identify decompensation. We then validated the criteria using a retrospective cohort study of adult patients admitted to the Hospital of the University of Pennsylvania. SETTING:. Quaternary academic medical center. PATIENTS:. Adult patients admitted to the Hospital of the University of Pennsylvania who had triggered a rapid response team (RRT) response between January 1, 2019, and December 31, 2020. INTERVENTIONS:. None. MEASUREMENTS AND MAIN RESULTS:. Sixty-nine experts participated in the eDelphi. Participation was high across the three survey rounds (first round: 93%, second round: 94%, and third round: 98%). The expert panel arrived at a consensus definition of physiological decompensation, “An acute worsening of a patient’s clinical status that poses a substantial increase to an individual’s short-term risk of death or serious harm.” Consensus was also reached on criteria for physiological decompensation. Invasive mechanical ventilation, severe hypoxemia, and use of vasopressor or inotrope medication were bundled as criteria for our novel decompensation metric: the adult inpatient decompensation event (AIDE). Patients who met greater than one AIDE criteria within 24 hours of an RRT call had increased adjusted odds of 7-day mortality (adjusted odds ratio [aOR], 4.1 [95% CI, 2.5–6.7]) and intensive care unit transfer (aOR, 20.6 [95% CI, 14.2–30.0]). CONCLUSIONS:. Through the eDelphi process, we have reached a consensus definition of physiological decompensation and proposed clinical criteria with which to identify patients who have decompensated using data easily available from the electronic medical record, the AIDE criteria.

BACKGROUND:. The U.S. Food and Drug Administration has to date granted approval or emergency use authorization to three vaccines against severe acute respiratory syndrome coronavirus 2 and coronavirus disease 2019. In clinical trials and real-use observational studies, the Pfizer-BioNTech BNT162b2 messenger RNA coronavirus disease 2019 vaccine, as well as the Moderna mRNA-1273 messenger RNA coronavirus disease 2019 vaccine, have demonstrated high efficacy and few adverse events. CASE SUMMARY:. A 20-year-old male college student in good health developed tinnitus and hematuria shortly after vaccination and progressed swiftly to a syndrome of: systemic inflammation; acute kidney injury requiring hemodialysis; acute, bilateral, complete sensorineural hearing loss; radiographic evidence of acute multifocal ischemic strokes; pericardial effusion complicated by tamponade physiology requiring pericardial evacuation; pleural effusions requiring evacuation; and systemic capillary leak. An extensive clinical and research investigation, including cytokine analysis, whole blood cytometry by time of flight, and whole exome sequencing, did not reveal a definitive explanatory mechanism. CONCLUSION:. While the overall safety profile of the BNT162b2 coronavirus disease 2019 vaccine remains excellent for the general population, rare serious events have been reported. In this report, we describe a case of multisystem inflammation and organ dysfunction of unknown mechanism beginning shortly after administration of the first dose of BNT162b2 coronavirus disease 2019 vaccine in a previously healthy recipient.

Abstract Background Enrichment strategies improve therapeutic targeting and trial efficiency, but enrichment factors for sepsis trials are lacking. We determined whether concentrations of soluble tumor necrosis factor receptor-1 (sTNFR1), interleukin-8 (IL8), and angiopoietin-2 (Ang2) could identify sepsis patients at higher mortality risk and serve as prognostic enrichment factors. Methods In a multicenter prospective cohort study of 400 critically ill septic patients, we derived and validated thresholds for each marker and expressed prognostic enrichment using risk differences (RD) of 30-day mortality as predictive values. We then used decision curve analysis to simulate the prognostic enrichment of each marker and compare different prognostic enrichment strategies. Measurements and main results An admission sTNFR1 concentration > 8861 pg/ml identified patients with increased mortality in both the derivation (RD 21.6%) and validation (RD 17.8%) populations. Among immunocompetent patients, an IL8 concentration > 94 pg/ml identified patients with increased mortality in both the derivation (RD 17.7%) and validation (RD 27.0%) populations. An Ang2 level > 9761 pg/ml identified patients at 21.3% and 12.3% increased risk of mortality in the derivation and validation populations, respectively. Using sTNFR1 or IL8 to select high-risk patients improved clinical trial power and efficiency compared to selecting patients with septic shock. Ang2 did not outperform septic shock as an enrichment factor. Conclusions Thresholds for sTNFR1 and IL8 consistently identified sepsis patients with higher mortality risk and may have utility for prognostic enrichment in sepsis trials.

Abstract Background Necroptosis, a form of programmed cell death mediated by receptor interacting serine/threonine-protein kinase-3 (RIPK3), is implicated in murine models of acute respiratory distress syndrome (ARDS). We hypothesized that plasma RIPK3 concentrations in sepsis and trauma would be associated with ARDS development and that plasma RIPK3 would reflect changes in lung tissue RIPK3 in a murine model of systemic inflammation. Methods We utilized prospective cohort studies of critically ill sepsis (n = 120) and trauma (n = 180) patients and measured plasma RIPK3 at presentation and 48 h. Patients were followed for 6 days for ARDS by the Berlin definition. We used multivariable logistic regression to determine the association of plasma RIPK3 with ARDS in each cohort, adjusting for confounders. In mice, we determined whether plasma and lung tissue RIPK3 levels rise concomitantly 4 h after injection with lipopolysaccharide and ZVAD-FMK, an apoptosis inhibitor. Results The change in plasma RIPK3 from presentation to 48 h (ΔRIPK3) was associated with ARDS in sepsis (OR 1.30, 95% CI 1.03–1.63, per ½ standard deviation) and trauma (OR 1.79, 95% CI 1.33–2.40). This association was not evident for presentation RIPK3 levels. Secondary analyses showed similar findings for the association of ΔRIPK3 with acute kidney injury and 30-day mortality. Mice injected with lipopolysaccharide and ZVAD-FMK had significantly higher plasma (p

Summary: Background: Acute respiratory distress syndrome (ARDS) is a common, but under-recognised, critical illness syndrome associated with high mortality. An important factor in its under-recognition is the variability in chest radiograph interpretation for ARDS. We sought to train a deep convolutional neural network (CNN) to detect ARDS findings on chest radiographs. Methods: CNNs were pretrained on 595 506 radiographs from two centres to identify common chest findings (eg, opacity and effusion), and then trained on 8072 radiographs annotated for ARDS by multiple physicians using various transfer learning approaches. The best performing CNN was tested on chest radiographs in an internal and external cohort, including a subset reviewed by six physicians, including a chest radiologist and physicians trained in intensive care medicine. Chest radiograph data were acquired from four US hospitals. Findings: In an internal test set of 1560 chest radiographs from 455 patients with acute hypoxaemic respiratory failure, a CNN could detect ARDS with an area under the receiver operator characteristics curve (AUROC) of 0·92 (95% CI 0·89–0·94). In the subgroup of 413 images reviewed by at least six physicians, its AUROC was 0·93 (95% CI 0·88–0·96), sensitivity 83·0% (95% CI 74·0–91·1), and specificity 88·3% (95% CI 83·1–92·8). Among images with zero of six ARDS annotations (n=155), the median CNN probability was 11%, with six (4%) assigned a probability above 50%. Among images with six of six ARDS annotations (n=27), the median CNN probability was 91%, with two (7%) assigned a probability below 50%. In an external cohort of 958 chest radiographs from 431 patients with sepsis, the AUROC was 0·88 (95% CI 0·85–0·91). When radiographs annotated as equivocal were excluded, the AUROC was 0·93 (0·92–0·95). Interpretation: A CNN can be trained to achieve expert physician-level performance in ARDS detection on chest radiographs. Further research is needed to evaluate the use of these algorithms to support real-time identification of ARDS patients to ensure fidelity with evidence-based care or to support ongoing ARDS research. Funding: National Institutes of Health, Department of Defense, and Department of Veterans Affairs.