The only known study evaluating SARS development in hospital workers was a retrospective study conducted prior to the widespread use of HFNC showing that development of SARS occurred in tracheal ...intubation (35%), HFNC 8%, and 38% (NIPPV) 3; this suggests that both non-invasive (including HFNC) and invasive ventilation approaches carry significant risk. ...since the data regarding transmission are unclear, we suggest, in addition to a negative pressure room, reverse isolation protection efforts with patients on HFNC wearing a mask over the nasal interface or a contained respiratory hood. 1. Comparison of high-flow nasal cannula versus oxygen face mask for environmental bacterial contamination in critically ill pneumonia patients: a randomized controlled crossover trial.
Red blood cell (RBC) transfusion is common in critically ill, postsurgical, and posttrauma patients in whom both systemic inflammation and immune suppression are associated with adverse outcomes. RBC ...products contain a multitude of immunomodulatory mediators that interact with and alter immune cell function. These interactions can lead to both proinflammatory and immunosuppressive effects. Defining clinical outcomes related to immunomodulatory effects of RBCs in transfused patients remains a challenge, likely due to complex interactions between individual blood product characteristics and patient‐specific risk factors. Unpacking these complexities requires an in‐depth understanding of the mechanisms of immunomodulatory effects of RBC products. In this review, we outline and classify potential mediators of RBC transfusion‐related immunomodulation and provide suggestions for future research directions.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
By the end of 2020, the US Centers for Disease Control and Prevention demonstrated that the cumulative rate of COVID-19-associated hospitalisations for patients <18 years of age was 23.9 per 100 000 ...population compared with adults 18 or older at 449.9 per 100 000 population.1 A recent assessment done by the Society of Critical Care Medicine estimated that the USA had 34.7 critical care beds per 100 000 population; 5% of which are paediatric critical care beds and 24% being neonatal intensive care beds.2 The resultant shortage of adult intensive care unit (AICU) resources due to the surge of COVID-19 infections sparked ingenuity in a time when the world was thrust into chaos. ...was standard of care for adults compromised with delays in management due to a lack of experience with diseases that require timely intervention, that is, delays to percutaneous coronary intervention in myocardial infarction or to alteplase administration in cerebrovascular accident? ...did ICU workflow and ICU personnel need change in PICUs whether adult patients who were triaged were COVID-19 or non-COVID-19, that is, in a pandemic is it prudent to triage the patient with the ‘pandemic disease’ to these settings or instead triage patients with known adult diseases (ie, chronic obstructive pulmonary disease exacerbation, pancreatitis, diabetic ketoacidosis, hyperglycaemic hyperosmolar state) to the PICU setting or for paediatric practitioners? ...with dual-trained internal medicine-paediatrics physicians and nurses, should there be a move in physician and nurse training for more adult (or paediatric) training to develop familiarity in clinical management?
Children have been less affected by the COVID-19 pandemic, but its repercussions on pediatric illnesses may have been significant. This study examines the indirect impact of the pandemic on a ...population of critically ill children in the United States.
Were there significantly fewer critically ill children admitted to PICUs during the second quarter of 2020, and were there significant changes in the types of diseases admitted?
This retrospective observational cohort study used the Virtual Pediatric Systems database. Participants were 160,295 children admitted to the PICU at 77 sites in the United States during quarters 1 (Q1) and 2 (Q2) of 2017 to 2019 (pre-COVID-19) and 2020 (COVID-19).
The average number of admissions was similar between pre-COVID-19 Q1 and COVID-19 Q1 but decreased by 32% from pre-COVID-19 Q2 to COVID-19 Q2 (20,157 to 13,627 admissions per quarter). The largest decreases were in respiratory conditions, including asthma (1,327 subjects in pre-COVID-19 Q2 (6.6% of patients) vs 241 subjects in COVID-19 Q2 (1.8%; P < .001) and bronchiolitis (1,299 6.5% vs 121 0.9%; P < .001). The percentage of trauma admissions increased, although the raw number of trauma admissions decreased. Admissions for diabetes mellitus and poisoning/ingestion also increased. In the multivariable model, illness severity-adjusted odds of ICU mortality for PICU patients during COVID-19 Q2 increased compared with pre-COVID-19 Q2 (OR, 1.165; 95% CI, 1.00-1.357; P = .049).
Pediatric critical illness admissions decreased substantially during the second quarter of 2020, with significant changes in the types of diseases seen in PICUs in the United States. There was an increase in mortality in children admitted to the PICU during this period.
Multidrug resistant (MDR) bacterial pathogens are a serious problem of increasing importance facing the medical community. MDR bacteria typically infect the most immunologically vulnerable: patients ...in intensive care units, patients with extensive comorbidities, oncology patients, hemodialysis patients, and other immune suppressed individuals are likely to fall victim to these pathogens. One promising novel approach to treatment of MDR bacteria is immuno-adjuvant therapy to boost patient immunity. Success with this strategy would have the major benefit of providing protection against a number of MDR pathogens.
This study had two main objectives. First, immunophenotyping of peripheral blood mononuclear cells from patients with sepsis associated with MDR bacteria was performed to examine for findings indicative of immunosuppression. Second, the ability of three immuno-adjuvants with distinct mechanisms of action to reverse CD4 and CD8 T cell dysfunction, a pathophysiological hallmark of sepsis, was evaluated.
Septic patients with MDR bacteria had increased expression of the inhibitory receptor PD-1 and its ligand PD-L1 and decreased monocyte HLA-DR expression compared to non-septic patients. All three immuno-adjuvants, IL-7, anti-PD-L1, and OX-40L, increased T cell production of IFN-γ in a subset of septic patients with MDR bacteria: IL-7 was most efficacious. There was a strong trend toward increased mortality in patients whose T cells failed to increase IFN-γ production in response to the three treatments.
Immuno-adjuvant therapy reversed T cell dysfunction, a key pathophysiological mechanism in septic patients with MDR bacteria.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Ongoing observational clinical research has prioritized understanding the human immune response to SARS-CoV-2 during the coronavirus disease 2019 (COVID-19) pandemic. Several recent studies suggest ...that immune dysregulation with early and prolonged adaptive immune system activation can result in cellular exhaustion. In this issue of the JCI, Files et al. compared cellular immune phenotypes during the first two months of COVID-19 in hospitalized and less severe, non-hospitalized patients. The authors utilized flow cytometry to analyze circulating peripheral blood mononuclear cells. Both patient cohorts maintained B and T cell phenotypes consistent with activation and cellular exhaustion throughout the first two months of infection. Additionally, follow-up samples from the non-hospitalized patient cohort showed that activation markers and cellular exhaustion increased over time. These findings illustrate the persistent nature of the adaptive immune system changes that have been noted in COVID-19 and suggest longer term effects that may shape the maintenance of immunity to SARS-CoV-2.
Sepsis, a disease of divergent pro- and anti-inflammatory-mediated pathways, has a high prevalence of morbidity and mortality, yet an understanding of potential unifying mediators between these ...pathways that may improve clinical outcomes is largely unclear. IL-10 has classically been designated an immunosuppressive cytokine, although recent data suggest that under certain conditions IL-10 can be immune stimulatory. We sought to further investigate the effect of IL-10 on innate and adaptive immunity in an in vitro human observational cohort study in patients with sepsis via modulation of IL-10 on IFN-γ production by T cells and TNF-α production and HLA-DR expression by monocytes. These results were compared with critically ill nonseptic patients and healthy volunteers. ELISpot analysis was performed using PBMC fraction from patient whole-blood samples. Finally, to provide additional potential clinical relevance, we examined the effect of IL-10 on T cell IFN-γ production in an in vivo cecal ligation and puncture model of sepsis using C57 black/J6 female mice. We found that inhibition of IL-10 significantly increased both production of T cell IFN-γ and monocyte TNF-α, whereas addition of IL-10 increased T cell IFN-γ production but decreased monocyte production of TNF-α and HLA-DR expression. There was no significant effect of IL-10 on control cohorts. IL-10-treated septic mice demonstrated increased IFN-γ production in splenocytes. Thus, IL-10 demonstrates both pro- and anti-inflammatory effects in the septic microenvironment, which is likely cell and context dependent. Further elucidation of relevant signaling pathways may direct future therapeutic targets.
The field of pediatric critical care has been hampered in the era of precision medicine by our inability to accurately define and subclassify disease phenotypes. This has been caused by heterogeneity ...across age groups that further challenges the ability to perform randomized controlled trials in pediatrics. One approach to overcome these inherent challenges include the use of machine learning algorithms that can assist in generating more meaningful interpretations from clinical data. This review summarizes machine learning and artificial intelligence techniques that are currently in use for clinical data modeling with relevance to pediatric critical care. Focus has been placed on the differences between techniques and the role of each in the clinical arena. The various forms of clinical decision support that utilize machine learning are also described. We review the applications and limitations of machine learning techniques to empower clinicians to make informed decisions at the bedside. IMPACT: Critical care units generate large amounts of under-utilized data that can be processed through artificial intelligence. This review summarizes the machine learning and artificial intelligence techniques currently being used to process clinical data. The review highlights the applications and limitations of these techniques within a clinical context to aid providers in making more informed decisions at the bedside.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
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