Monocytes from many critically ill patients show a low level of major histocompatibility complex type II (MHC II) expression. This phenomenon is believed to play a role in these patients' increased susceptibility to secondary infections. In the present study, we show that the level of monocyte human leukocyte antigen (HLA)-DR expression inversely correlates with the degree of severity of the sepsis syndrome. The defect of the monocyte HLA-DR expression resides in an intracellular sequestration of the MHC II molecules, a posttranslational effect. No significant decrease in the rate of transcription of HLA-DR, or its major transcriptional inducer, Class II transactivator, was noted. The levels of HLA-DR protein produced by monocytes from patients with septic shock were comparable to those from healthy volunteers. Plasma from patients with septic shock induced significant HLA-DR endocytosis resulting in decreased surface HLA-DR expression of normal donor monocytes. This effect was partially blocked by anti-interleukin (IL)-10 monoclonal antibody, but not by antagonists to transforming growth factor-beta1, prostaglandins, or beta-adrenergic agonists. Altogether, these data suggest that HLA-DR molecules are re-endocytosed and retained intracellularly in monocytes from patients with septic shock, and that this phenomenon is partially mediated by IL-10. IL-10 may represent a future target for immunomodulating patients with the sepsis syndrome or critically ill patients at risk of developing infections.

Background: Coronavirus disease 2019 (COVID-19) is associated with a high disease burden with 10% of confirmed cases progressing towards critical illness. Nevertheless, the disease course and predictors of mortality in critically ill patients are poorly understood. Methods: Following the critical developments in ICUs in regions experiencing early inception of the pandemic, the European-based, international RIsk Stratification in COVID-19 patients in the Intensive Care Unit (RISC-19-ICU) registry was created to provide near real-time assessment of patients developing critical illness due to COVID-19. Findings: As of April 22, 2020, 639 critically ill patients with confirmed SARS-CoV-2 infection were included in the RISC-19-ICU registry. Of these, 398 had deceased or been discharged from the ICU. ICU-mortality was 24%, median length of stay 12 (IQR, 5À21) days. ARDS was diagnosed in 74%, with a minimum P/F-ratio of 110 (IQR, 80À148). Prone positioning, ECCO2R, or ECMO were applied in 57%. Off-label therapies were prescribed in 265 (67%) patients, and 89% of all bloodstream infections were observed in this subgroup (n = 66; RR=3¢2, 95% CI [1¢7À6¢0]). While PCT and IL-6 levels remained similar in ICU survivors and non-survivors throughout the ICU stay (p = 0¢35, 0¢34), CRP, creatinine, troponin, D-dimer, lactate, neutrophil count, P/Fratio diverged within the first seven days (p<0¢01). On a multivariable Cox proportional-hazard regression model at admission, creatinine, D-dimer, lactate, potassium, P/F-ratio, alveolar-arterial gradient, and ischemic heart disease were independently associated with ICU-mortality. Interpretation: The European RISC-19-ICU cohort demonstrates a moderate mortality of 24% in critically ill patients with COVID-19. Despite high ARDS severity, mechanical ventilation incidence was low and associated with more rescue therapies. In contrast to risk factors in hospitalized patients reported in other studies, the main mortality predictors in these critically ill patients were markers of oxygenation deficit, renal and microvascular dysfunction, and coagulatory activation. Elevated risk of bloodstream infections underscores the need to exercise caution with off-label therapies.

Guidance on the application of Section 9.3 of the SAMS Guidelines "Intensive-care interventions" (2013) This document is available in English, French, German and Italian, cf. sams.ch/en/coronavirus. The German text is the authentic version.

In this study mechanical ventilation for acute respiratory failure in pulmonary fibrosis patients was associated with a 100% mortality, despite aggressive therapeutic and diagnostic procedures.

Background Identifying patients at high risk of hospital preventable readmission is an essential step towards selecting those who might benefit from specific transitional interventions. Objective Derive and validate a predictive risk score for potentially avoidable readmission (PAR) based on analysis of readmissions, with a focus on medication. Design/Setting/Participants Retrospective analysis of all hospital admissions to internal medicine wards between 2011 and 2014. Comparison between patients readmitted within 30 days and non-readmitted patients, as identified using a specially designed algorithm. Univariate and multivariate regression analyses of demographic data, clinical diagnoses, laboratory results, and the medication data of patients admitted during the first period (2011–2013), to identify factors associated with PAR. Using these, derive a predictive score with a regression coefficient-based scoring method. Subsequently, validate this score with a second cohort of patients admitted in 2013–2014. Variables were identified at hospital discharge. Results The derivation cohort included 7,317 hospital stays. Multivariate logistic regressions found significant associations with PAR for: [adjusted OR (95% CI)] hospital length of stay > 4 days [1.3 (1.1–1.7)], admission in previous 6 months [2.3 (1.9–2.8)], heart failure [1.3 (1.0–1.7)], chronic ischemic heart disease [1.7 (1.2–2.3)], diabetes with organ damage [2.2 (1.3–3.8)], cancer [1.4 (1.0–1.9)], metastatic carcinoma [1.9 (1.3–3.0)], anemia [1.2 (1.0–1.5)], hypertension [1.3 (1.1–1.7)], arrhythmia [1.3 (1.0–1.6)], hyperkalemia [1.4 (1.0–1.7)], opioid drug prescription [1.3 (1.1–1.6)], and acute myocardial infarction [0.6 (0.4–0.9)]. The PAR-Risk Score, derived from these results, demonstrated fair discriminatory and calibration power (C-statistic = 0.699; Brier Score = 0.069). The results for the validation cohort’s operating characteristics were similar (C-statistic = 0.687; Brier Score = 0.064). Conclusion This study identified routinely-available factors that were significantly associated with PAR. A predictive score was derived and internally validated.