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BP can be inferred from PPG using DBN-RBM modeling techniques. The results obtained with this technology are promising, but its intrinsic variability and its wide limits of agreement do not allow clinical application at this time.

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Sepsis is a transversal pathology and one of the main causes of death at the Intensive Care Unit (ICU). It has in fact become the tenth most common cause of death in western societies. Its mortality rates can reach up to 45.7% for septic shock, its most acute manifestation. For these reasons, the prediction of the mortality caused by sepsis is an open and relevant medical research challenge. This problem requires prediction methods that are robust and accurate, but also readily interpretable. This is paramount if they are to be used in the demanding context of real-time decision making at the ICU. In this brief paper, such a method is presented. It is based on a variant of the well-known support vector machine (SVM) model and provides an automated ranking of relevance of the mortality predictors. The reported results show that it outperforms in terms of accuracy alternative techniques currently in use, while simultaneously assessing the relative impact of individual pathology indicators.

Background: Few validated biomarker or clinical score combinations exist which can discriminate between cases of infection and other non-infectious conditions following activation of an in-hospital sepsis code, as well as provide an accurate severity assessment of the corresponding host response. This study aimed to identify suitable blood biomarker (MR-proADM, PCT, CRP and lactate) or clinical score (SOFA and APACHE II) combinations to address this unmet clinical need. Methods: A prospective, observational study of patients activating the Vall d'Hebron University Hospital sepsis code (ISC) within the emergency department (ED), hospital wards and intensive care unit (ICU). Area under the receiver operating characteristic (AUROC) curves, logistic and Cox regression analysis were used to assess performance. Results: 148 patients fulfilled the Vall d'Hebron ISC criteria, of which 130 (87.8%) were retrospectively found to have a confirmed diagnosis of infection. Both PCT and MR-proADM had a moderate-to-high performance in discriminating between infected and non-infected patients following ISC activation, although the optimal PCT cutoff varied significantly across departments. Similarly, MR-proADM and SOFA performed well in predicting 28-and 90-day mortality within the total infected patient population, as well as within patients presenting with a community-acquired infection or following a medical emergency or prior surgical procedure. Importantly, MR-proADM also showed a high association with the requirement for ICU admission after ED presentation [OR (95% CI) 8.18 (1.75-28.33)] or during treatment on the ward [OR (95% CI) 3.64 (1.43-9.29)], although the predictive performance of all biomarkers and clinical scores diminished between both settings. Conclusions: Results suggest that the individual use of PCT and MR-proADM might help to accurately identify patients with infection and assess the overall severity of the host response, respectively. In addition, the use of MR-proADM could accurately identify patients requiring admission onto the ICU, irrespective of whether patients

Multisystem Inflammatory Syndrome in Children (MIS-C) associated with COVID-19 is characterized by hypercytokinemia leading to overwhelming inflammation. We describe the use of a hemadsorption device as part of the supportive treatment for cytokine storm.

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BackgroundThe baseline endotoxin activity (EAT0) may predict the outcome of critically ill septic patients who receive Polymyxin‐B hemadsorption (PMX‐HA), however, the clinical implications of specific EA trends remain unknown.MethodsSubgroup analysis of the prospective, multicenter, observational study EUPHAS2. We included 50 critically ill patients with septic shock and EAT0 ≥ 0.6, who received PMX‐HA. The primary outcome of the study was the EA and SOFA score progression from T0 to 120 h afterwards (T120). Secondary outcomes included the EA and SOFA score progression in whom had EA at 48 h (EAT48) < 0.6 (EA responders, EA‐R) versus who had not (EA non‐responders, EA‐NR).ResultsSeptic shock was mainly caused by 27 abdominal (54%) and 17 pulmonary (34%) infections, predominantly due to Gram negative bacteria (39 patients, 78%). The SAPS II score was 67.5 [52.8–82.3] and predicted a mortality rate of 75%. Between T0 and T120, the EA decreased (p < 0.001), while the SOFA score and the Inotropic Score (IS) improved (p < 0.001). In comparison with EA‐NR (18 patients, 47%), the EA‐R group (23 patients, 53%) showed faster IS improvement and lower requirement of continuous renal replacement therapy (CRRT) during the ICU stay. Overall hospital mortality occurred in 18 patients (36%).ConclusionsIn critically ill patients with septic shock and EAT0 ≥ 0.6 who received PMX‐HA, EA decreased and SOFA score improved over 120 h. In whom high EA resolved within 48 h, IS improvement was faster and CRRT requirement was lower compared with patients with EAT48 ≥ 0.6.