The plasma proteome differentiates the multisystem inflammatory syndrome in children (MIS-C) from children with SARS-CoV-2 negative sepsis.

BACKGROUND: The Multi-System Inflammatory Syndrome in Children (MIS-C) can develop several weeks after SARS-CoV-2 infection and requires a distinct treatment protocol. Distinguishing MIS-C from SARS-CoV-2 negative sepsis (SCNS) patients is important to quickly institute the correct therapies. We performed targeted proteomics and machine learning analysis to identify novel plasma proteins of MIS-C for early disease recognition. METHODS: A case-control study comparing the expression of 2,870 unique blood proteins in MIS-C versus SCNS patients, measured using proximity extension assays. The 2,870 proteins were reduced in number with either feature selection alone or with a prior COMBAT-Seq batch effect adjustment. The leading proteins were correlated with demographic and clinical variables. Organ system and cell type expression patterns were analyzed with Natural Language Processing (NLP). RESULTS: The cohorts were well-balanced for age and sex. Of the 2,870 unique blood proteins, 58 proteins were identified with feature selection (FDR-adjusted P < 0.005, P < 0.0001; accuracy = 0.96, AUC = 1.00, F1 = 0.95), and 15 proteins were identified with a COMBAT-Seq batch effect adjusted feature selection (FDR-adjusted P < 0.05, P < 0.0001; accuracy = 0.92, AUC = 1.00, F1 = 0.89). All of the latter 15 proteins were present in the former 58-protein model. Several proteins were correlated with illness severity scores, length of stay, and interventions (LTA4H, PTN, PPBP, and EGF; P < 0.001). NLP analysis highlighted the multi-system nature of MIS-C, with the 58-protein set expressed in all organ systems; the highest levels of expression were found in the digestive system. The cell types most involved included leukocytes not yet determined, lymphocytes, macrophages, and platelets. CONCLUSIONS: The plasma proteome of MIS-C patients was distinct from that of SCNS. The key proteins demonstrated expression in all organ systems and most cell types. The unique proteomic signature identified in MIS-C patients could aid future diagnostic and therapeutic advancements, as well as predict hospital length of stays, interventions, and mortality risks.

A reduced proteomic signature in critically ill Covid-19 patients determined with plasma antibody micro-array and machine learning.

BACKGROUND: COVID-19 is a complex, multi-system disease with varying severity and symptoms. Identifying changes in critically ill COVID-19 patients' proteomes enables a better understanding of markers associated with susceptibility, symptoms, and treatment. We performed plasma antibody microarray and machine learning analyses to identify novel proteins of COVID-19. METHODS: A case-control study comparing the concentration of 2000 plasma proteins in age- and sex-matched COVID-19 inpatients, non-COVID-19 sepsis controls, and healthy control subjects. Machine learning was used to identify a unique proteome signature in COVID-19 patients. Protein expression was correlated with clinically relevant variables and analyzed for temporal changes over hospitalization days 1, 3, 7, and 10. Expert-curated protein expression information was analyzed with Natural language processing (NLP) to determine organ- and cell-specific expression. RESULTS: Machine learning identified a 28-protein model that accurately differentiated COVID-19 patients from ICU non-COVID-19 patients (accuracy = 0.89, AUC = 1.00, F1 = 0.89) and healthy controls (accuracy = 0.89, AUC = 1.00, F1 = 0.88). An optimal nine-protein model (PF4V1, NUCB1, CrkL, SerpinD1, Fen1, GATA-4, ProSAAS, PARK7, and NET1) maintained high classification ability. Specific proteins correlated with hemoglobin, coagulation factors, hypertension, and high-flow nasal cannula intervention (P < 0.01). Time-course analysis of the 28 leading proteins demonstrated no significant temporal changes within the COVID-19 cohort. NLP analysis identified multi-system expression of the key proteins, with the digestive and nervous systems being the leading systems. CONCLUSIONS: The plasma proteome of critically ill COVID-19 patients was distinguishable from that of non-COVID-19 sepsis controls and healthy control subjects. The leading 28 proteins and their subset of 9 proteins yielded accurate classification models and are expressed in multiple organ systems. The identified COVID-19 proteomic signature helps elucidate COVID-19 pathophysiology and may guide future COVID-19 treatment development.

Kinome and phosphoproteome reprogramming underlies the aberrant immune responses in critically ill COVID-19 patients.

SARS-CoV-2 infection triggers extensive host immune reactions, leading to severe diseases in certain individuals. However, the molecular basis underlying the excessive yet non-productive immune responses in severe COVID-19 remains incompletely understood. In this study, we conducted a comprehensive analysis of the peripheral blood mononuclear cell (PBMC) proteome and phosphoproteome in sepsis patients positive or negative for SARS-CoV-2 infection, as well as healthy subjects, using quantitative mass spectrometry. Our findings demonstrate dynamic changes in the COVID-19 PBMC proteome and phosphoproteome during disease progression, with distinctive protein or phosphoprotein signatures capable of distinguishing longitudinal disease states. Furthermore, SARS-CoV-2 infection induces a global reprogramming of the kinome and phosphoproteome, resulting in defective adaptive immune response mediated by the B and T lymphocytes, compromised innate immune responses involving the SIGLEC and SLAM family of immunoreceptors, and excessive cytokine-JAK-STAT signaling. In addition to uncovering host proteome and phosphoproteome aberrations caused by SARS-CoV-2, our work recapitulates several reported therapeutic targets for COVID-19 and identified numerous new candidates, including the kinases PKG1, CK2, ROCK1/2, GRK2, SYK, JAK2/3, TYK2, DNA-PK, PKCδ, and the cytokine IL-12.

Early Versus Late Feeding After Percutaneous Endoscopic Gastrostomy Placement in Trauma and Burn.

INTRODUCTION: Timing to resume feeds after percutaneous endoscopic gastrostomy (PEG) placement continues to vary among US trauma surgeons. The purpose of this study was to assess differences in meeting nutritional therapy goals and adverse outcomes with early versus late enteral feeding after PEG placement. METHODS: This retrospective review included 364 trauma and burn patients who underwent PEG placement. Data included patient characteristics, time to initiate feeds, rate feeds were resumed, % feed volume goals on postoperative days 0-7, and complications. Statistical analysis was performed comparing two groups (feeds ≤ 6 h versus > 6 h) and three subgroups (< 4 h, 4-6 h, ≥ 6 h) based on data quartiles. Chi-square/Fisher's exact test, independent-samples t-test, and one-way analysis of variance were used to analyze the data. RESULTS: Mean time to initiate feeds after PEG was 5.48 ± 4.79 h. Burn patients received early feeds in a larger proportion. A larger proportion of trauma patients received late feeds. The mean % of goal feed volume met on postoperative day 0 was higher in the early feeding group versus the late (P < 0.001). There were no differences in adverse events, even after subgroup analysis of those who received feeds < 4 h after PEG placement. CONCLUSIONS: Patients with early initiation of feeds after PEG placement achieve a higher percentage of goals on day 0 without an increased rate of adverse events. Unfortunately, patients routinely fall short of their target tube feeding goals.

Post-Intensive Care Sequelae in Pediatrics-Results of an Early Rehabilitation Implementation Study.

OBJECTIVES: To compare post-PICU discharge functioning, health-related quality of life (HRQL), and parental stress before and after the implementation of an early rehabilitation bundle. DESIGN AND SETTING: Prospective cohort substudy within an early rehabilitation implementation program, conducted at the PICUs at McMaster Children's Hospital and London Health Sciences, London, Ontario, Canada. INTERVENTIONS: A bundle consisting of: 1) analgesia-first sedation; 2) delirium monitoring and prevention; and 3) early mobilization. Patients with an anticipated 48-hour PICU length of stay were approached for consent to participate. PATIENTS: Critically ill children with an anticipated 48-hour PICU length of stay were approached for consent to participate. MEASUREMENTS AND MAIN RESULTS: Patient-/proxy-reported outcome measures were assessed at baseline, PICU discharge, and 1 and 3 months post-PICU discharge using: 1) Pediatric Evaluation of Disability Inventory Computer Adaptive Test to assess physical, social, cognitive, and responsibility/caregiver domains of functioning; 2) KIDSCREEN to assess HRQL; and 3) the Pediatric Inventory for Parents to assess caregiver stress. A total of 117 participants were enrolled. Patient demographic characteristics were similar in the pre- and post-intervention groups. Following bundle implementation, 30 of 47 respondents (63.8%) experienced functional decline and 18 of 45 (40%) experienced low HRQL at PICU discharge. Eighteen of 36 (50%) at 1 month and 14 of 38 (36.8%) at 3 months experienced either persistent functional decline and/or low HRQL; 2.8% and 2.6% at 1- and 3-month follow-up, respectively, experienced both persistent functional decline and low HRQL. There were no significant differences in the rates of persistent functional decline, low HRQL, or caregiver stress scores post-bundle compared with pre-rehabilitation bundle implementation. CONCLUSIONS: We were unable to adequately determine the efficacy of a rehabilitation bundle on patient-centered outcomes as this substudy was not powered for these outcomes. Our results did reveal that persistent low functioning is common in PICU survivors, more common than low HRQL, while experiencing both functional decline and low HRQL was uncommon.

Early Rehabilitation in Critically ill Children: A Two Center Implementation Study.

OBJECTIVES: To implement an early rehabilitation bundle in two Canadian PICUs. DESIGN AND SETTING: Implementation study in the PICUs at McMaster Children's Hospital (site 1) and London Health Sciences (site 2). PATIENTS: All children under 18 years old admitted to the PICU were eligible for the intervention. INTERVENTIONS: A bundle consisting of: 1) analgesia-first sedation; 2) delirium monitoring and prevention; and 3) early mobilization. MEASUREMENTS AND MAIN RESULTS: Primary outcomes were the duration of implementation, bundle compliance, process of care, safety, and the factors influencing implementation. Secondary endpoints were the impact of the bundle on clinical outcomes such as pain, delirium, iatrogenic withdrawal, ventilator-free days, length of stay, and mortality. Implementation occurred over 26 months (August 2018 to October 2020). Data were collected on 1,036 patients representing 4,065 patient days. Bundle compliance was optimized within 6 months of roll-out. Goal setting for mobilization and level of arousal improved significantly (p < 0.01). Benzodiazepine, opioid, and dexmedetomidine use decreased in site 1 by 23.2% (95% CI, 30.8-15.5%), 26.1% (95% CI, 34.8-17.4%), and 9.2% (95% CI, 18.2-0.2%) patient exposure days, respectively, while at site 2, only dexmedetomidine exposure decreased significantly by 10.5% patient days (95% CI, 19.8-1.1%). Patient comfort, safety, and nursing workload were not adversely affected. There was no significant impact of the bundle on the rate of delirium, ventilator-free days, length of PICU stay, or mortality. Key facilitators to implementation included institutional support, unit-wide practice guidelines, dedicated PICU educators, easily accessible resources, and family engagement. CONCLUSIONS: A rehabilitation bundle can improve processes of care and reduce patient sedative exposure without increasing patient discomfort, nursing workload, or harm. We did not observe an impact on short-term clinical outcomes. The efficacy of a PICU-rehabilitation bundle requires ongoing study. Lessons learned in this study provide evidence to inform rehabilitation implementation in the PICU setting.

COVID-19 plasma proteome reveals novel temporal and cell-specific signatures for disease severity and high-precision disease management.

Coronavirus disease 2019 (COVID-19) is a systemic inflammatory condition with high mortality that may benefit from personalized medicine and high-precision approaches. COVID-19 patient plasma was analysed with targeted proteomics of 1161 proteins. Patients were monitored from Days 1 to 10 of their intensive care unit (ICU) stay. Age- and gender-matched COVID-19-negative sepsis ICU patients and healthy subjects were examined as controls. Proteomic data were resolved using both cell-specific annotation and deep-analysis for functional enrichment. COVID-19 caused extensive remodelling of the plasma microenvironment associated with a relative immunosuppressive milieu between ICU Days 3-7, and characterized by extensive organ damage. COVID-19 resulted in (1) reduced antigen presentation and B/T-cell function, (2) increased repurposed neutrophils and M1-type macrophages, (3) relatively immature or disrupted endothelia and fibroblasts with a defined secretome, and (4) reactive myeloid lines. Extracellular matrix changes identified in COVID-19 plasma could represent impaired immune cell homing and programmed cell death. The major functional modules disrupted in COVID-19 were exaggerated in patients with fatal outcome. Taken together, these findings provide systems-level insight into the mechanisms of COVID-19 inflammation and identify potential prognostic biomarkers. Therapeutic strategies could be tailored to the immune response of severely ill patients.

Organ and cell-specific biomarkers of Long-COVID identified with targeted proteomics and machine learning.

BACKGROUND: Survivors of acute COVID-19 often suffer prolonged, diffuse symptoms post-infection, referred to as "Long-COVID". A lack of Long-COVID biomarkers and pathophysiological mechanisms limits effective diagnosis, treatment and disease surveillance. We performed targeted proteomics and machine learning analyses to identify novel blood biomarkers of Long-COVID. METHODS: A case-control study comparing the expression of 2925 unique blood proteins in Long-COVID outpatients versus COVID-19 inpatients and healthy control subjects. Targeted proteomics was accomplished with proximity extension assays, and machine learning was used to identify the most important proteins for identifying Long-COVID patients. Organ system and cell type expression patterns were identified with Natural Language Processing (NLP) of the UniProt Knowledgebase. RESULTS: Machine learning analysis identified 119 relevant proteins for differentiating Long-COVID outpatients (Bonferonni corrected P < 0.01). Protein combinations were narrowed down to two optimal models, with nine and five proteins each, and with both having excellent sensitivity and specificity for Long-COVID status (AUC = 1.00, F1 = 1.00). NLP expression analysis highlighted the diffuse organ system involvement in Long-COVID, as well as the involved cell types, including leukocytes and platelets, as key components associated with Long-COVID. CONCLUSIONS: Proteomic analysis of plasma from Long-COVID patients identified 119 highly relevant proteins and two optimal models with nine and five proteins, respectively. The identified proteins reflected widespread organ and cell type expression. Optimal protein models, as well as individual proteins, hold the potential for accurate diagnosis of Long-COVID and targeted therapeutics.

Plasma proteome of Long-COVID patients indicates HIF-mediated vasculo-proliferative disease with impact on brain and heart function.

AIMS: Long-COVID occurs after SARS-CoV-2 infection and results in diverse, prolonged symptoms. The present study aimed to unveil potential mechanisms, and to inform prognosis and treatment. METHODS: Plasma proteome from Long-COVID outpatients was analyzed in comparison to matched acutely ill COVID-19 (mild and severe) inpatients and healthy control subjects. The expression of 3072 protein biomarkers was determined with proximity extension assays and then deconvoluted with multiple bioinformatics tools into both cell types and signaling mechanisms, as well as organ specificity. RESULTS: Compared to age- and sex-matched acutely ill COVID-19 inpatients and healthy control subjects, Long-COVID outpatients showed natural killer cell redistribution with a dominant resting phenotype, as opposed to active, and neutrophils that formed extracellular traps. This potential resetting of cell phenotypes was reflected in prospective vascular events mediated by both angiopoietin-1 (ANGPT1) and vascular-endothelial growth factor-A (VEGFA). Several markers (ANGPT1, VEGFA, CCR7, CD56, citrullinated histone 3, elastase) were validated by serological methods in additional patient cohorts. Signaling of transforming growth factor-ß1 with probable connections to elevated EP/p300 suggested vascular inflammation and tumor necrosis factor-α driven pathways. In addition, a vascular proliferative state associated with hypoxia inducible factor 1 pathway suggested progression from acute COVID-19 to Long-COVID. The vasculo-proliferative process predicted in Long-COVID might contribute to changes in the organ-specific proteome reflective of neurologic and cardiometabolic dysfunction. CONCLUSIONS: Taken together, our findings point to a vasculo-proliferative process in Long-COVID that is likely initiated either prior hypoxia (localized or systemic) and/or stimulatory factors (i.e., cytokines, chemokines, growth factors, angiotensin, etc). Analyses of the plasma proteome, used as a surrogate for cellular signaling, unveiled potential organ-specific prognostic biomarkers and therapeutic targets.

The utility of syndecan-1 circulating levels as a biomarker in patients with previous or active COVID-19: a systematic review and meta-analysis.

BACKGROUND: With the emergence of coronavirus disease of 2019 (COVID-19), several blood biomarkers have been identified, including the endothelial biomarker syndecan-1, a surface proteoglycan. In the current systematic review and meta-analysis, we aimed to assess the diagnostic and prognostic role of syndecan-1 in COVID-19. METHODS: PubMed, Embase, Scopus, and Web of Science, as international databases, were searched for relevant studies measuring blood syndecan-1 levels in COVID-19 patients, COVID-19 convalescents, and healthy control subjects, in patients with different COVID-19 severities and/or in COVID-19 patients with poor outcomes. Random-effect meta-analysis was performed using STATA to calculate the standardized mean difference (SMD) and 95% confidence interval (CI) for the comparison between COVID-19 patients and healthy control subjects or COVID-19 convalescents and controls. RESULTS: After screening by title/abstract and full text, 17 studies were included in the final review. Meta-analysis of syndecan-1 levels in COVID-19 compared with healthy control subjects revealed that patients with COVID-19 had significantly higher syndecan-1 levels (SMD 1.53, 95% CI 0.66 to 2.41, P < 0.01). In contrast, COVID-19 convalescent patients did not show significant difference with non-convalescents (SMD 0.08, 95% CI -0.63 to 0.78, P = 0.83). Regarding disease severity, two studies reported that more severe forms of the disease were associated with increased syndecan-1 levels. Moreover, patients who died from COVID-19 had higher syndecan-1 levels compared with survivors (SMD 1.22, 95% CI 0.10 to 2.33, P = 0.03). CONCLUSION: Circulating syndecan-1 level can be used as a biomarker of endothelial dysfunction in COVID-19, as it was increased in COVID-19 patients and was higher in more severe instances of the disease. Further larger studies are needed to confirm these findings and further enlighten the role of syndecan-1 in clinical settings.

A Pediatric Cervical Spine Clearance Guideline Leads to Fewer Unnecessary Computed Tomography Scans and Decreased Radiation Exposure.

OBJECTIVES: Physical examination and computed tomography (CT) are useful to rule out cervical spine injury (CSI). Computed tomography scans increase lifetime cancer risk in children from radiation exposure. Most CSI in children occur between the occiput and C4. We developed a cervical spine (C-spine) clearance guideline to reduce unnecessary CTs and radiation exposure in pediatric trauma patients. METHODS: A pediatric C-spine clearance guideline was implemented in September 2018 at our Level 2 Pediatric Trauma Center. Guidance included CT of C1 to C4 to scan only high-yield regions versus the entire C-spine and decrease radiation dose. A retrospective cohort study was conducted comparing preguideline and postguideline of all pediatric trauma patients younger than 8 years screened for CSI from July 2017 to December 2020. Primary endpoints included the following: number of full C-spine and C1 to C4 CT scans and radiation dose. Secondary endpoints were CSI rate and missed CSI. Results were compared using χ 2 and Wilcoxon rank-sum test with P < 0.05 significant. RESULTS: The review identified 726 patients: 273 preguideline and 453 postguideline. A similar rate of total C-spine CTs were done in both groups (23.1% vs 23.4%, P = 0.92). Full C-spine CTs were more common preguideline (22.7% vs 11.9%, P < 0.001), whereas C1 to C4 CT scans were more common post-guideline (11.5% vs 0.4%, P < 0.001). Magnetic resonance imaging utilization and CSIs identified were similar in both groups. The average radiation dose was lower postguideline (114 vs 265 mGy·cm -1 ; P < 0.001). There were no missed CSI. CONCLUSIONS: A pediatric C-spine clearance guideline led to increasing CT of C1 to C4 over full C-spine imaging, reducing the radiation dose in children. LEVEL OF EVIDENCE: Level IV, therapeutic.

Elevated vascular transformation blood biomarkers in Long-COVID indicate angiogenesis as a key pathophysiological mechanism.

BACKGROUND: Long-COVID is characterized by prolonged, diffuse symptoms months after acute COVID-19. Accurate diagnosis and targeted therapies for Long-COVID are lacking. We investigated vascular transformation biomarkers in Long-COVID patients. METHODS: A case-control study utilizing Long-COVID patients, one to six months (median 98.5 days) post-infection, with multiplex immunoassay measurement of sixteen blood biomarkers of vascular transformation, including ANG-1, P-SEL, MMP-1, VE-Cad, Syn-1, Endoglin, PECAM-1, VEGF-A, ICAM-1, VLA-4, E-SEL, thrombomodulin, VEGF-R2, VEGF-R3, VCAM-1 and VEGF-D. RESULTS: Fourteen vasculature transformation blood biomarkers were significantly elevated in Long-COVID outpatients, versus acutely ill COVID-19 inpatients and healthy controls subjects (P < 0.05). A unique two biomarker profile consisting of ANG-1/P-SEL was developed with machine learning, providing a classification accuracy for Long-COVID status of 96%. Individually, ANG-1 and P-SEL had excellent sensitivity and specificity for Long-COVID status (AUC = 1.00, P < 0.0001; validated in a secondary cohort). Specific to Long-COVID, ANG-1 levels were associated with female sex and a lack of disease interventions at follow-up (P < 0.05). CONCLUSIONS: Long-COVID patients suffer prolonged, diffuse symptoms and poorer health. Vascular transformation blood biomarkers were significantly elevated in Long-COVID, with angiogenesis markers (ANG-1/P-SEL) providing classification accuracy of 96%. Vascular transformation blood biomarkers hold potential for diagnostics, and modulators of angiogenesis may have therapeutic efficacy.

Novel plasma protein biomarkers from critically ill sepsis patients.

BACKGROUND: Despite the high morbidity and mortality associated with sepsis, the relationship between the plasma proteome and clinical outcome is poorly understood. In this study, we used targeted plasma proteomics to identify novel biomarkers of sepsis in critically ill patients. METHODS: Blood was obtained from 15 critically ill patients with suspected/confirmed sepsis (Sepsis-3.0 criteria) on intensive care unit (ICU) Day-1 and Day-3, as well as age- and sex-matched 15 healthy control subjects. A total of 1161 plasma proteins were measured with proximal extension assays. Promising sepsis biomarkers were narrowed with machine learning and then correlated with relevant clinical and laboratory variables. RESULTS: The median age for critically ill sepsis patients was 56 (IQR 51-61) years. The median MODS and SOFA values were 7 (IQR 5.0-8.0) and 7 (IQR 5.0-9.0) on ICU Day-1, and 4 (IQR 3.5-7.0) and 6 (IQR 3.5-7.0) on ICU Day-3, respectively. Targeted proteomics, together with feature selection, identified the leading proteins that distinguished sepsis patients from healthy control subjects with ≥ 90% classification accuracy; 25 proteins on ICU Day-1 and 26 proteins on ICU Day-3 (6 proteins overlapped both ICU days; PRTN3, UPAR, GDF8, NTRK3, WFDC2 and CXCL13). Only 7 of the leading proteins changed significantly between ICU Day-1 and Day-3 (IL10, CCL23, TGFα1, ST2, VSIG4, CNTN5, and ITGAV; P < 0.01). Significant correlations were observed between a variety of patient clinical/laboratory variables and the expression of 15 proteins on ICU Day-1 and 14 proteins on ICU Day-3 (P < 0.05). CONCLUSIONS: Targeted proteomics with feature selection identified proteins altered in critically ill sepsis patients relative to healthy control subjects. Correlations between protein expression and clinical/laboratory variables were identified, each providing pathophysiological insight. Our exploratory data provide a rationale for further hypothesis-driven sepsis research.

The Volume of Thoracic Irrigation Is Associated With Length of Stay in Patients With Traumatic Hemothorax.

INTRODUCTION: Irrigation of the thoracic cavity at tube thoracostomy (TT) placement may decrease the rate of a retained hemothorax (RHTX); however, other resource utilization outcomes have not yet been quantified. This study evaluated the association of thoracic irrigation during TT with the length of stay and outcomes in patients with traumatic hemothorax (HTX). METHODS: A retrospective chart review was performed of adult patients receiving a TT for HTX at a single, urban Level 1 Trauma Center from January 2019 to December 2020. Those who underwent irrigation during TT at the discretion of the trauma surgeon were compared to a control of standard TT without irrigation. Death within 30 d, as well as TTs, placed at outside hospitals, during traumatic arrest or thoracic procedures, and for isolated pneumothoraces were excluded. The primary outcome was the length of stay as hospital-free, ICU-free, and ventilator-free days (30-day benchmark). Subgroup analysis by irrigation volume was conducted using one-way ANOVA testing with P < 0.05 considered statistically significant. RESULTS: Eighty-two (41.4%) of 198 patients underwent irrigation during TT placement. Secondary interventions, thoracic infections, and TT duration were not statistically different in the irrigated cohort. Hospital-free and ICU-free days were higher in the irrigated patients than in the controls. Groups irrigated with ≥1000 mL had significant more hospital-free days (P = 0.007) than those receiving less than 1000 mL. CONCLUSIONS: Patients with traumatic HTX who underwent thoracic irrigation at the time of TT placement had decreased hospital and ICU days compared to standard TT placement alone. Specifically, our study demonstrated that patients irrigated with a volume of at least 1000 mL had greater hospital-free days compared to those irrigated with less than 1000 mL.

When Is It Safe to Feed After Surgical Feeding Tube Placement? A Survey of EAST Members.

INTRODUCTION: Many critically ill trauma and surgical patients require nutritional support. Patients needing long-term enteral access often undergo placement of surgical feeding tubes, including percutaneous endoscopic gastrostomy tube, laparoscopic gastrostomy tube, and open gastrostomy tube. This study was performed to determine national practice patterns for feeding after feeding tube placement. METHODS: A 16-question online survey was administered to members of the Eastern Association for the Surgery of Trauma via Qualtrics about feeding practices after placement of the feeding tube. Questions included demographics, training, current practice, annual procedural volume, timing to resume feeds: <2, 6, 12, or 24 h, methods to advance feeds, and reasons behind management decisions. For comparison, responses were grouped into "early" (≤6 h) and "late" (18-24 h) groups. The chi-square test was used, and P < 0.05 was significant. RESULTS: Five hundred sixteen Eastern Association for the Surgery of Trauma members completed the survey. Most (95%) respondents worked at a level 1 or 2 trauma center, and 68% are in academic practice. The most common feeding tube placement was percutaneous endoscopic gastrostomy (median = 25/y, interquartile range = 15-40). Responses showed variability in timing of when feeds were resumed after procedure. Early feeding was not affected by age (≤42 y), trauma center designation, volume, or training programs at the respondent's hospital. Graduates of surgical critical care fellowship were less likely to feed early (P = 0.043). CONCLUSIONS: There is wide variability in feeding practices after surgical feeding tube placement. Given the large quantity of procedures performed, a randomized controlled trial should be performed to determine the optimal timing to resume feeds in critically ill patients.

Patients with severe COVID-19 do not have elevated autoantibodies against common diagnostic autoantigens.

OBJECTIVES: Infection by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), the causative pathogen of coronavirus disease 2019 (COVID-19) presents occasionally with an aberrant autoinflammatory response, including the presence of elevated circulating autoantibodies in some individuals. Whether the development of autoantibodies against self-antigens affects COVID-19 outcomes remains unclear. To better understand the prognostic role of autoantibodies in COVID-19, we quantified autoantibodies against 23 markers that are used for diagnosis of autoimmune disease. To this end, we used serum samples from patients with severe [intensive care unit (ICU)] and moderate (ward) COVID-19, across two to six consecutive time points, and compared autoantibody levels to uninfected healthy and ICU controls. METHODS: Acute and post-acute serum (from 1 to 26 ICU days) was collected from 18 ICU COVID-19-positive patients at three to six time points; 18 ICU COVID-19-negative patients (sampled on ICU day 1 and 3); 21 ward COVID-19-positive patients (sampled on hospital day 1 and 3); and from 59 healthy uninfected controls deriving from two cohorts. Levels of IgG autoantibodies against 23 autoantigens, commonly used for autoimmune disease diagnosis, were measured in serum samples using MSD® U-PLEX electrochemiluminescence technology (MSD division Meso Scale Discovery®), and results were compared between groups. RESULTS: There were no significant elevations of autoantibodies for any of the markers tested in patients with severe COVID-19. CONCLUSIONS: Sample collections at longer time points should be considered in future studies, for assessing the possible development of autoantibody responses following infection with SARS-CoV-2.

Pediatric Trauma Arrival Times and the Swing Shift.

BACKGROUND: Trauma center staff and trainees are often assigned to a day and night shift. However, for adult trauma, the swing shift has been found to offer superior clinical exposure compared with a standard day or night shift for trainees. We characterized patterns in pediatric trauma arrival times based on the hour, weekday, and month and studied whether or not the swing shift also maximizes exposure to hands-on experiences in managing pediatric trauma. METHODS: We performed a retrospective review of the trauma database at our urban, level 2 pediatric trauma center. We identified all the pediatric trauma activations in the last 13 years (2006-2018). A retrospective shift log was created, which included day (7:00 am to 7:00 pm), night (7:00 pm to 7:00 am), and swing (noon to midnight) shifts. The shifts were compared using the Wilcoxon match-pairs signed rank test. Weekends data were also compared with weekdays, and comparisons were also made for pediatric patients with Injury Severity Scores (ISS) >15. RESULTS: There were 3532 pediatric patients identified for our study. The swing shift had 1.98 times more activations than the night shift, and 1.33 more than the day shift (P < 0.001). The swing shift was also superior to both the day and night shifts for exposure to patients with Injury Severity Score greater than 15 (P < 0.001). Weekend days had 1.28 times more trauma than the weekdays (P < 0.001). Peak arrival time was between the hours of 3:00 pm and 9:00 pm, and patient age did not have an effect on this trend. CONCLUSIONS: Experience in managing pediatric trauma patients will improve for trainees who utilize the swing shift. In addition, the hours between 3:00 pm and 9:00 pm on weekends may represent a time of particularly high likelihood of pediatric trauma arrivals, which may require extra staff and hospital resources.Level of Evidence: Therapeutic Study, Level IV.

Effect of Transcatheter Aortic Valve Implantation vs Surgical Aortic Valve Replacement on All-Cause Mortality in Patients With Aortic Stenosis: A Randomized Clinical Trial.

Importance: Transcatheter aortic valve implantation (TAVI) is a less invasive alternative to surgical aortic valve replacement and is the treatment of choice for patients at high operative risk. The role of TAVI in patients at lower risk is unclear. Objective: To determine whether TAVI is noninferior to surgery in patients at moderately increased operative risk. Design, Setting, and Participants: In this randomized clinical trial conducted at 34 UK centers, 913 patients aged 70 years or older with severe, symptomatic aortic stenosis and moderately increased operative risk due to age or comorbidity were enrolled between April 2014 and April 2018 and followed up through April 2019. Interventions: TAVI using any valve with a CE mark (indicating conformity of the valve with all legal and safety requirements for sale throughout the European Economic Area) and any access route (n = 458) or surgical aortic valve replacement (surgery; n = 455). Main Outcomes and Measures: The primary outcome was all-cause mortality at 1 year. The primary hypothesis was that TAVI was noninferior to surgery, with a noninferiority margin of 5% for the upper limit of the 1-sided 97.5% CI for the absolute between-group difference in mortality. There were 36 secondary outcomes (30 reported herein), including duration of hospital stay, major bleeding events, vascular complications, conduction disturbance requiring pacemaker implantation, and aortic regurgitation. Results: Among 913 patients randomized (median age, 81 years [IQR, 78 to 84 years]; 424 [46%] were female; median Society of Thoracic Surgeons mortality risk score, 2.6% [IQR, 2.0% to 3.4%]), 912 (99.9%) completed follow-up and were included in the noninferiority analysis. At 1 year, there were 21 deaths (4.6%) in the TAVI group and 30 deaths (6.6%) in the surgery group, with an adjusted absolute risk difference of -2.0% (1-sided 97.5% CI, -∞ to 1.2%; P < .001 for noninferiority). Of 30 prespecified secondary outcomes reported herein, 24 showed no significant difference at 1 year. TAVI was associated with significantly shorter postprocedural hospitalization (median of 3 days [IQR, 2 to 5 days] vs 8 days [IQR, 6 to 13 days] in the surgery group). At 1 year, there were significantly fewer major bleeding events after TAVI compared with surgery (7.2% vs 20.2%, respectively; adjusted hazard ratio [HR], 0.33 [95% CI, 0.24 to 0.45]) but significantly more vascular complications (10.3% vs 2.4%; adjusted HR, 4.42 [95% CI, 2.54 to 7.71]), conduction disturbances requiring pacemaker implantation (14.2% vs 7.3%; adjusted HR, 2.05 [95% CI, 1.43 to 2.94]), and mild (38.3% vs 11.7%) or moderate (2.3% vs 0.6%) aortic regurgitation (adjusted odds ratio for mild, moderate, or severe [no instance of severe reported] aortic regurgitation combined vs none, 4.89 [95% CI, 3.08 to 7.75]). Conclusions and Relevance: Among patients aged 70 years or older with severe, symptomatic aortic stenosis and moderately increased operative risk, TAVI was noninferior to surgery with respect to all-cause mortality at 1 year. Trial Registration: isrctn.com Identifier: ISRCTN57819173.

Are Self-Inflicted Stab Wounds Less Severe Than Assaults? Analysis of Injury and Severity by Intent.

BACKGROUND: Although there is evidence that self-inflicted abdominal stab wounds are less severe than those from assault, it is unclear if this is true in other anatomic regions. This study compares severity and injury pattern between self-inflicted stab wounds (SISWs) and wounds from assault (ASW). MATERIALS AND METHODS: Stab wounds from our level I trauma registry from 2013 to 2018 were reviewed. Data included age, gender, self-inflicted versus assault, psychiatric or substance use history, anatomic location, operative intervention, injury severity, length of stay, and outcomes. RESULTS: Over the study period, 1390 patients were identified. History of psychiatric diagnoses or previous suicide attempts was more frequent in SISWs (47% versus 6.5%, P < 0.01; 35% versus 0.4%, P < 0.01). SISWs had a higher incidence of wounds to the neck and abdomen (44% versus 11%, P < 0.01; and 34% versus 26%, P = 0.02). Overall, injuries from ASW had a higher injury severity score, but more procedures were performed on SISWs (46% versus 34%, P < 0.01). SISWs to the neck were more likely to undergo procedures (26% versus 15%, P = 0.04). Median hospital charges were higher in patients with SISWs ($58.6 K versus $39.4 K, P < 0.01). CONCLUSIONS: SISWs have a distinct pattern of injuries, more commonly to the neck and abdomen, when compared with injuries resulting from ASW. The patients with SISWs have a higher rate of procedures, longer length of stay, and higher hospital charges despite low injury severity overall.

Novel severe traumatic brain injury blood outcome biomarkers identified with proximity extension assay.

OBJECTIVES: Severe traumatic brain injury (sTBI) patients suffer high mortality. Accurate prognostic biomarkers have not been identified. In this exploratory study, we performed targeted proteomics on plasma obtained from sTBI patients to identify potential outcome biomarkers. METHODS: Blood sample was collected from patients admitted to the ICU suffering a sTBI, using standardized clinical and computerized tomography (CT) imaging criteria. Age- and sex-matched healthy control subjects and sTBI patients were enrolled. Targeted proteomics was performed on plasma with proximity extension assays (1,161 proteins). RESULTS: Cohorts were well-balanced for age and sex. The majority of sTBI patients were injured in motor vehicle collisions and the most frequent head CT finding was subarachnoid hemorrhage. Mortality rate for sTBI patients was 40%. Feature selection identified the top performing 15 proteins for identifying sTBI patients from healthy control subjects with a classification accuracy of 100%. The sTBI proteome was dominated by markers of vascular pathology, immunity/inflammation, cell survival and macrophage/microglia activation. Receiver operating characteristic (ROC) curve analyses demonstrated areas-under-the-curves (AUC) for identifying sTBI that ranged from 0.870-1.000 (p≤0.005). When mortality was used as outcome, ROC curve analyses identified the top 3 proteins as Willebrand factor (vWF), Wnt inhibitory factor-1 (WIF-1), and colony stimulating factor-1 (CSF-1). Combining vWF with either WIF-1 or CSF-1 resulted in excellent mortality prediction with AUC of 1.000 for both combinations (p=0.011). CONCLUSIONS: Targeted proteomics with feature classification and selection distinguished sTBI patients from matched healthy control subjects. Two protein combinations were identified that accurately predicted sTBI patient mortality. Our exploratory findings require confirmation in larger sTBI patient populations.