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Jehovah's Witnesses (JW) refuse allogeneic blood transfusions and therefore pose a unique challenge in case of major surgery. This retrospective study reviewed an experience with JW patients who were undergoing open heart surgery.By using patient blood management strategies, 35 adult JW patients underwent cardiac surgery at Kepler University Hospital in Linz, Austria between 2008 and 2017. Outcomes were compared with patients who accepted blood transfusions (non-JW patients) by using propensity score matching.There were no significant differences in clinical and operative data between the groups. Twelve JW patients (34.3%) were pretreated with erythropoietin and iron, with a preoperative increase in mean hemoglobin of 2.0 g/dL. On admission, hemoglobin was 14.1 ± 1.1 g/dL in JW patients, compared with 13.2 ± 2.0 g/dL in non-JW patients (P = .022). The hematocrit in JW patients was higher throughout the hospital stay, even though 51.4% of non-JW patients received allogeneic red blood cell transfusions. The perioperative red blood cell loss was significantly lower in JW patients than in non-JW patients (619 ± 420 mL vs 929 ± 520 mL; P = .010). Major complication rates were not different between the groups. The hemoglobin at discharge was 11.5 ± 1.5 g/dL in JW patients compared with 10.3 ± 1.3 g/dL in non-JW patients (P.001). In-hospital mortality was 2.9% in each group, and long-term survival was comparable.By implementing patient blood management, open heart surgery in JW patients can be performed with low morbidity and mortality. Preoperative optimization of hemoglobin and minimization of perioperative blood loss are cornerstones in the prevention of blood loss, anemia, and transfusions.

For many years, in daily clinical practice, the traditional 10/30 rule (hemoglobin 10 g/dL – hematocrit 30%) has been the most commonly used trigger for blood transfusions. Over the years, this approach is believed to have contributed to a countless number of unnecessary transfusions and an unknown number of overtransfusion-related deaths. Recent studies have shown that lower hemoglobin levels can safely be accepted, even in critically ill patients. However, even these new transfusion thresholds are far beyond the theoretical limits of individual anemia tolerance. For this reason, almost all publications addressing the limits of acute anemia recommend physiological transfusion triggers to indicate the transfusion of erythrocyte concentrates as an alternative. Although this concept appears intuitive at first glance, no solid scientific evidence supports the safety and benefit of physiological transfusion triggers to indicate the optimal time point for transfusion of allogeneic blood. It is therefore imperative to continue searching for the most sensitive and specific parameters that can guide the clinician when to transfuse in order to avoid anemia-induced organ dysfunction while avoiding overtransfusion-related adverse effects. This narrative review discusses the concept of anemia tolerance and critically compares hemoglobin-based triggers with physiological transfusion for various clinical indications.

ZusammenfassungDie anhaltende unkontrollierte Blutung ist eine der führenden Todesursachen bei polytraumatisierten Patienten 1, 2, 3, 4, 5. Hypoperfusion durch große Blutverluste führt zu Gewebeschäden, generalisierter Immunantwort sowie Aktivierung des Gerinnungssystems und damit zu einer traumaassoziierten Koagulopathie (TAK) 4, 5. Durch eine adäquate, frühzeitige Behandlung der TAK können Morbidität und Mortalität signifikant reduziert werden.

A new method of the end-of-life prediction for filled elastomers has been introduced and applied on fatigue under uniaxial deformations in [1]. The method considers measured inhomogeneity size frequencies. The dimension of these inhomogeneities is assumed to be equal to the sizes of the initial cracks responsible for the final end-of-life of the elastomer. For an end-of-life prediction, the initial crack size information is inserted into a standard fracture mechanic law. Within a Monte Carlo simulation, several spatial realization steps of statistical initial crack size distributions over the deformation field of the investigated component or specimen are performed. Within each realization step, the minimum number of cycles until end-of-life is extracted and supplies a failure probability plot. Performing a large number of realizations provides the complete failure probability information. In this work, that concept is applied on fatigue under simple shear. The predicted failure probability values match the experimental findings from dynamic fatigue tests for the considered Styrene Rubber.

PLOS ONE 17(1), e0262110 (2022). doi:10.1371/journal.pone.0262110, Published by PLOS, San Francisco, California, US

We investigate machine learning models that identify COVID-19 positive patients and estimate the mortality risk based on routinely acquired blood tests in a hospital setting. However, during pandemics or new outbreaks, disease and testing characteristics change, thus we face domain shifts. Domain shifts can be caused, e.g., by changes in the disease prevalence (spreading or tested population), by refined RT-PCR testing procedures (taking samples, laboratory), or by virus mutations. Therefore, machine learning models for diagnosing COVID-19 or other diseases may not be reliable and degrade in performance over time. To countermand this effect, we propose methods that first identify domain shifts and then reverse their negative effects on the model performance. Frequent re-training and reassessment, as well as stronger weighting of more recent samples, keeps model performance and credibility at a high level over time. Our diagnosis models are constructed and tested on large-scale data sets, steadily adapt to observed domain shifts, and maintain high ROC AUC values along pandemics.

Objective The diagnosis of COVID-19 is based on the detection of SARS-CoV-2 in respiratory secretions, blood, or stool. Currently, reverse transcription polymerase chain reaction (RT-PCR) is the most commonly used method to test for SARS-CoV-2. Methods In this retrospective cohort analysis, we evaluated whether machine learning could exclude SARS-CoV-2 infection using routinely available laboratory values. A Random Forests algorithm with 28 unique features was trained to predict the RT-PCR results. Results Out of 12,848 patients undergoing SARS-CoV-2 testing, routine blood tests were simultaneously performed in 1357 patients. The machine learning model could predict SARS-CoV-2 test results with an accuracy of 86% and an area under the receiver operating characteristic curve of 0.74. Conclusion Machine learning methods can reliably predict a negative SARS-CoV-2 RT-PCR test result using standard blood tests.

A correlated lifetime prediction concept for load cases without static preload, which argues with crack growth and particle size distribution from 3D computer tomography, has been shown by Ludwig et al. (2015). This method is extended to non-relaxing load cases i.e. with a static preload dependency. A force controlled dynamic fatigue test for a dumbbell specimen is performed to investigate the service life. In addition, a crack growth investigation is carried out using single edge notched tensile (SENT) specimens in displacement control mode to characterize the tearing energy and crack growth rate. The study with carbon black reinforced HNBR rubber shows a correlation between the Wohler curve and the Paris-Erdogan plot. An extension of the empirical Paris-Erdogan equation considering static preload dependency allows the prediction of uniaxial lifetime statistics by means of particle size distribution. The calculated lifetime values are in reasonable concordance with the experimental findings.

OBJECTIVES Machine learning methods potentially provide a highly accurate and detailed assessment of expected individual patient risk before elective cardiac surgery. Correct anticipation of this risk allows for the improved counselling of patients and avoidance of possible complications. We therefore investigated the benefit of modern machine learning methods in personalized risk prediction for patients undergoing elective heart valve surgery. METHODS We performed a monocentric retrospective study in patients who underwent elective heart valve surgery between 1 January 2008 and 31 December 2014 at our centre. We used random forests, artificial neural networks and support vector machines to predict the 30-day mortality from a subset of 129 available demographic and preoperative parameters. Exclusion criteria were reoperation of the same patient, patients who needed anterograde cerebral perfusion due to aortic arch surgery and patients with grown-up congenital heart disease. Finally, the cohort consisted of 2229 patients with a 30-day mortality of 3.86% (86 of 2229 cases). This trial has been registered at clinicaltrials.gov (NCT03724123). RESULTS The final random forest model trained on the entire data set provided an out-of-bag area under the receiver operator characteristics curve (AUC) of 0.839, which significantly outperformed the European System for Cardiac Operative Risk Evaluation (EuroSCORE) (AUC = 0.704) and a model trained only on the subset of features EuroSCORE uses (AUC = 0.745). CONCLUSIONS Advanced machine learning methods can predict outcomes of valve surgery procedures with higher accuracy than established risk scores based on logistic regression on pre-selected parameters. This approach is generalizable to other elective high-risk interventions and allows for training models to the cohorts of specific institutions

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, 5-21) days. ARDS was diagnosed in 74%, with a minimum P/F-ratio of 110 (IQR, 80-148). 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 [1·7-6·0]). 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/F-ratio diverged within the first seven days (p

Background. - Anaemia and coagulopathy are common issues in critically ill patients. Transfusion can be lifesaving, however, is associated with potential life threatening adverse events. As an international transfusion guideline for this specific patient population is lacking, we hypothesize that a high heterogeneity in transfusion practices exists. In this pilot-study we assessed transfusion practice in a university hospital in the Netherlands and tested the feasibility of this protocol for an international multi-centre study.Methods. - A prospective single centre cohort study was conducted. For seven days all consecutive non-readmitted patients to the adult Intensive Care Unit (ICU) were included and followed for 28 days. Patients were prospectively followed until ICU discharge or up to day 28. Patient outcome data was collected at day 28. Workload for this study protocol was scored in hours and missing data.Results. - In total, 48 patients were included, needed in total three hours patient to include and collect all data, with 1.6% missing data showing the feasibility of the data acquisition. Six (12.5%) patients received red blood cells (RBCs), three patients (6.3%) received platelet concentrates, and two (4.2%) patients received plasma units. In total eight (16.7%) patients were transfused with one or more blood products. Median pre- and post-transfusion haemoglobin (Hb) levels were 7.6 (6.7-7.7) g/dL and 8.1 (7.6-8.7) g/dL, respectively.Conclusion. - In this pilot-study we proved the feasibility of our protocol and observed in this small population a restrictive transfusion practice for all blood products. (C) 2019 Societe francaise de transfusion sanguine (SFTS). Published by Elsevier Masson SAS. All rights reserved.

This work presents the lifetime prediction of elastomer component based on the particle distribution in the specimen, the crack growth properties and the appropriate crack criterion. A lifetime prediction using numerical simulation saves both cost and time and can be very helpful in the development phase of a product. On the basis of the obtained results, lifetime can be estimated and thus an appropriate measure such as geometry change or load adjustment can be adopted. The prediction is demonstrated using two kinds of elastomer samples: EPDM and NR under different load amplitudes. Lifetime prediction is accomplished by Monte Carlo simulation, which is based on the correlation between the value of J-integral and total energy density of the single-edge notched tension (SENT) sample. Due to the choice of an inelastic material law the J-integral is evaluated after establishment of stable load cycles as the stable value for a J-integral contour curve as a function of the contour curve distance from the crack tip. For lifetime prediction, a Python script was implemented for the commercial FEA system Abaqus as a postprocessing routine. The script is based on local lifetime evaluation, where evaluation is done element by element followed up by an accumulation. In addition, physical experiments are used for counting the particles in the materials, to characterise the crack growth and also to measure lifetime.

Die Hypnose stellt ein sehr altes und effektives Heilverfahren dar. In den letzten Jahrzehnten war die moderne Hypnose vor allem eine Domane der Psychotherapie. Jedoch gewinnt die Hypnose als therapeutisches Verfahren in der Medizin wieder zunehmend an Bedeutung. Hypnose kann bei einer Vielzahl von medizinischen Indikationen eingesetzt werden. In der Literatur finden sich zahlreiche Beweise fur ihre Wirksamkeit. Ziel war es, die Effektivitat der Hypnose in der stationaren Therapie chronischer Schmerzpatienten aufzuzeigen und ein Selbsthypnoseprogramm darzustellen, welches gut in die Schmerztherapie integriert werden kann. Eingeschlossen wurden alle stationaren chronischen Schmerzpatienten von Oktober 2012 bis April 2013 (Gruppe 1: Nichthypnosegruppe; Gruppe 2: Hypnosegruppe). Fur die Gruppe 2 wurde ein Protokoll fur Hypnosetherapie zusatzlich zum standardisierten schmerztherapeutischen Programm integriert. Das Hauptziel der Hypnosetherapie war vor allem ein Selbsthypnosetraining, damit eine hausliche weitere Umsetzung gewahrleistet werden konnte. Mittels standardisierter Testverfahren (u. a. Gesundheitsfragebogen fur Patienten [PHQ-9], Pain Disability Index [PDI], Generalized Anxiety Disorder [GAD-7] und numerische Rating-Skalen [NRS] zum Schmerz und allgemeinen Wohlbefinden) wurden die Daten vor und nach der Schmerztherapie ausgewertet. Die pra- und poststationaren standardisierten Testverfahren von 30 chronischen Schmerzpatienten konnten ausgewertet werden (17 Patienten ohne Hypnose, 13 Patienten mit Hypnose). Die Hauptdiagnose nach ICD-10 war bei allen Patienten „chronische Schmerzerkrankung“ (F45.41) mit einem MPSS-Stadium III. Der PDI war in der Hypnosegruppe signifikant gebessert (p = 0,019). Die weiteren Items zeigten alle einen Trend zur Besserung in der Hypnosegruppe (Ausnahme GAD-7) ohne eine statistische Signifikanz (p > 0,05). Die vorliegende Arbeit konnte in einem ersten kleinen Patientenkollektiv zeigen, dass die Integration der modernen Hypnosetherapie in die Behandlung von chronischen Schmerzpatienten im stationaren Setting ein weiterer sinnvoller therapeutischer Aspekt sein kann. Insbesondere die Anleitung zum Erlernen selbststandig durchzufuhrender Hypnosetechniken erscheint aufgrund der begrenzten stationaren Zeit sinnvoll zu sein. Es bedarf weiterer Untersuchungen, um diese ersten Ergebnisse zu unterstutzen.

BACKGROUND Pre-operative anaemia and transfusion are common among patients undergoing elective orthopaedic surgery. Application of 'patient blood management' might be the most effective way to reduce both anaemia and transfusion. Pre-operative administration of iron and/or erythropoietin (EPO) is one of the cornerstones of the first pillar of patient blood management, but in a daily clinical setting, efficacy and long-term safety of this measure have not been analysed thoroughly to date. OBJECTIVE To investigate the influence of pre-operative preparation (PREP) of patients with iron and/or EPO on peri-operative transfusion needs and long-term survival. DESIGN Single-centre, retrospective study. SETTING Anaesthesia department, University hospital. INTERVENTIONS Pre-operative preparation with iron and/or EPO versus no preparation. METHODS After approval of our local ethics committee, data of 5518 patients who received total hip or total knee replacement between 2008 and 2014 were included. Patients receiving iron and/or EPO were included in the PREP group, whereas patients without iron and/or EPO were included in the no preparation group. From the full data set, a bias-reduced subset of 662 patients was obtained by means of propensity score-matching to compare peri-operative red blood cell utilisation and long-term survival of patients between groups. RESULTS Patients in the PREP group needed a lower number of units of red blood cells than patients in the no preparation group (0.2 ± 0.8 vs. 0.5 ± 1.3, P

For carbon black reinforced Ethylene-Propylene-Diene Monomer Rubber (EPDM) fracture mechanics investigations by using a Single Edge Notched Tension sample (SENT) are presented. Filled elastomers under cyclic loading typically display inelastic effects like permanent set, strong nonlinear S-shaped stress-strain behaviour and stress induced softening (discontinuous damage) as well as cyclic softening (continuous damage) better known as Mullins effect. These unique properties give this material class an interesting and a complex aspect regarding the experimental observations and numerical modelling of fracture mechanics. In simulations with homogenous material, the J-integral given as the evaluation of the Eshelby stress tensor along a path integral around the crack shows no dependency on the chosen integration path. In contrast, dissipative materials show strong path dependency of the J-integral. When the chosen path is near to the crack tip, this effect is pronounced, due to the inelastic effects, which are very high at the crack tip compared to the rest of the sample. In the process zone, the J-integral value depends strongly on the chosen path around the crack tip. This phenomenon occurs due to the intensity of inelastic effects near the crack tip. The path-dependency of J-integral using the variational formulation of a crack problem in a dissipative material has been given in [16]. Stumpf and Le have proposed a new formulation of the boundary value problem for elastoplastic cracked body using variational formulation, where the finite deformation was considered. For cyclic displacement controlled loading, the elastomers show typical stress softening behaviour, i.e. the force-displacement curve of each cycle is lower than the previous cycle and higher than the following cycle. This occurs due to the continuous damage, whereby the bondings between polymer chains and the filler particles are partially damaged. At small external amplitudes, the stress softening effect is significant only in the vicinity of the crack tip, because of the hysteresis which is large compared to the rest of the sample. The evaluation of the J-integral for an SENT sample under cyclic displacement controlled loading shows clearly that the resulting energy flux at the crack tip decreases from the virgin curve until the last repetition. The values found are in good agreement with experimentally evaluated tearing energy. Hence J-integral evaluation while considering a stress softening reflecting material model can be a promising approach used for estimation of the crack propagation or for lifetime prediction.

Rheumatoid arthritis (RA) patients are at increased risk of infection. Aim of the present study was to investigate whether RA patients admitted to an intensive care unit (ICU) due to infection have higher Rheumatoid Arthritis Observation of Biologic Therapy (RABBIT) risk scores compared to control RA patients. Seventy-four RA patients (32.4% male) admitted to an ICU due to infection (from January 2002 to December 2013) and 74 frequency-matched control RA patients (16.2% male) were included in this cross-sectional study. There was strong evidence for a higher RABBIT risk score in ICU patients (median 2.0; IQR 1.3–3.2) as compared to controls (1.3; IQR 0.8–2.0; p

A stretch intensity factor for filled and unfilled elastomers is introduced for different mixtures. This stretch intensity factor allows for prediction of the analytically evaluated energy release rate for a cracked sample under uniaxial tension. Considering the opening mode from fracture mechanics (mode I ) was investigated. The continuum mechanical derivations are based on non-linear hyperelastic material behaviour, where the energy release rate is evaluated through a closed path integral very near to the crack tip. Here, the integrand includes asymptotic solution for strain, stress and energy density using the Ogden model. The decisive advantage of this method is to predict well the critical tearing energy values by the crack growth using the analytical energy release rate term. In this work the Mullins effect is not considered, since the cracked samples are tested without any preconditioning.

Background Venoarterial extracorporeal membrane oxygenation (VA-ECMO) may be life-saving in several clinical situations, but it is also one of the most invasive therapeutic procedures, with significant potential for life-threatening complications. Pulse pressure waves are typically very small or even absent at the onset of ECMO therapy, and will reappear with the improvement of cardiac function. A low pulse pressure may indicate low cardiac output due to heart failure during sustained ECMO support. A sudden loss of pulse pressure during ECMO therapy, however, may reveal complications like pericardial tamponade, hemothorax or pneumothorax. Near infrared spectroscopy (NIRS) has been shown to be useful in detecting cerebral and lower limb ischemic events during ECMO therapy and could furthermore improve differential diagnosis in the event pulsatility of the arterial pressure trace is lost. Methods We are reporting on 3 different complications of ECMO and their impact on arterial pulse pressure, arterial oxygen tension and regional tissue oxygenation measured by NIRS. Results Pericardial hematoma, overinflation of the lung, and tension pneumothorax may impede cardiac output during VA-ECMO and cause a loss of pulse pressure. Monitoring of regional tissue oxygenation using NIRS, in addition to arterial and mixed venous oxygen tension, may allow early recognition and treatment of ECMO complications. Conclusions Together with the appearance of a flat, non pulsatile arterial pressure trace as well as a reduction in mixed venous oxygen saturation the improvement of upper body rSO2 measured by NIRS enables timely recognition of complications that interfere with natural cardiac output during VA-ECMO.

Elastomers composites are viscoelastic materials and show a complex behaviour due to their non-linear response to external load, characterised in general by energy dissipation, residual set and material softening. For production reasons defects like micro-cracks and pores may be contained. A micro crack in a filled elastomer can occur between polymer-polymer, filler-polymer or filler-filler interfaces. Such a crack grows when the energy flux at the crack tip exceeds a critical value. Energy considerations at the crack shows that the energy released during the crack growth is not the total dissipated energy. The remaining energy is dissipated in the rest of the elastomer composite. In this study three different fracture criteria are compared: the tearing energy (Rivlin and Thomas, 1953), energy release rate (Gros and Seelig, 2011) and the J-integral (Rice, 1968). Tearing energy and energy release rate are based on the global energetic consideration and J-integral is based on the local energy observation. As a global criterion the tearing energy can be determined experimentally and numerically, whereas the J-integral is a local criterion at the crack tip and can be evaluated only numerically. The importance of local calculations lies in the determination of actually required tearing energy as well as the description of inelastic effects of elastomers at the crack tip. The analytical evaluation of the energy release rate allows for the prediction of the driving force at the crack tip without carrying out experiments for the determination of the tearing energy. Stumpf and Le (1990) have applied the variational principle to determine the energy flux at the mode I crack tip for a hyperelastic body. In this work only the trouser-sample is analysed. The load on this sample corresponds to the presented mode III from linear fracture mechanics. Here, the Ogden model is chosen (ABAQUS, 1998) as hyperelastic material model. The analytical determination of the energy release rate is calculated from the energy density function of this model. Results obtained from the experiments, simulations and analytical calculations are compared, where the analytical energy release rate turned out to be in closer accordance with the experimentally evaluated tearing energy than the J-Integral.

Purpose of review Trauma patients are considered a complex population of patients in emergency medicine and need extensive, specialized therapy. One major part is the prevention and treatment of the inflammatory response, which occurs in patients after severe injury resulting in complications like endotheliopathy. Likely as a consequence, coagulopathy occurs. Sterile inflammation is hard to address, especially because of the lack of a single activator. Moreover, it is a complex composition of factors that lead to a pathologic immune response. Our understanding of these patterns is increasing, but the complete pathophysiologic changes have yet to be investigated. Therefore, there is no specific target to treat inflammatory response in trauma patients at the moment. Recent findings There is increasing knowledge of the pathways and mediators that are responsible for the inflammatory response in patients after severe trauma. The endothelial glycocalyx has been identified to be an integral part of these mechanisms. There have been several new therapeutic approaches to diminish the inflammatory response. Summary Our increasing understanding of the immune system have led to new potential therapeutic perspectives. All of these approaches need further research to be validated. As the current therapies are based on empirical strategies and have not changed much over the years, new treatment options would be an important progress.

A concept for the estimation of lifetime cycles is discussed assuming non-dispersed filler particles as origins of initial cracks which propagate under dynamic load according to fatigue crack growth (FCG) characteristics until failure occurs. Reference EPDM compounds with glass spheres of well defined size show strong correlation of the fatigue to failure analysis (FFA) behavior of dumbbells with largest incorporated particles, but dependence on polymer filler interaction, too. For NR and EPDM compounds, the occurrence of incorporated large particles is investigated by computed tomography and evaluated to a flaw size statistic. Based on the assumption of initial crack sizes matching the flaw diameters and together with the characteristic material parameters from FCG analysis, a statistical concept for the prediction of FFA lifetime analysis is presented. Predictions for near-homogeneously deforming dumbbell samples with carbon black (CB) reinforced NR display a particle size distribution which in combination with FCG results allows to calculate quantitative lifetime accordant to experimental findings, i.e. compounding dependency by shorter lifetime for worse dispersion and geometry dependency by longer lifetime for smaller specimens. An extension of the prediction concept for non-homogeneous deformation states is shown through a Monte Carlo simulation varying the positions of flaws inside the sample together with a Finite Element Analysis based calculation of the accordant local J-integral value. The simulations of lifetime statistics for rotational-parabolic buffer samples made of CB filled NR or EPDM show significant effects in average value and distribution width similarly found in experiment. This lifetime prediction concept has the unique capability to take into account not only recipe controlled matrix properties as cyclic crack propagation resistivity but volume dependency and processing related dispersion state, too in a quantitative manner.

To deploy machine learning tools (random forests) to develop a model that reliably predicts hospital mortality in children with acute infections residing in low- and middle-income countries, using age and other variables collected at hospital admission.Post hoc analysis of a single-center, prospective, before-and-after feasibility trial.Rural district hospital in Rwanda, a low-income country in Sub-Sahara Africa.Infants and children greater than 28 days and less than 18 years of life hospitalized because of an acute infection.None.Age, vital signs (heart rate, respiratory rate, and temperature) capillary refill time, altered mental state collected at hospital admission, as well as survival status at hospital discharge were extracted from the trial database. This information was collected for 1,579 adult and pediatric patients admitted to a regional referral hospital with an acute infection in rural Rwanda. Nine-hundred forty-nine children were included in this analysis. We predicted survival in study subjects using random forests, a machine learning algorithm. Five prediction models, all including age plus two to five other variables, were tested. Three distinct optimization criteria of the algorithm were then compared. The in-hospital mortality was 1.5% (n = 14). All five models could predict in-hospital mortality with an area under the receiver operating characteristic curve ranging between 0.69 and 0.8. The model including age, respiratory rate, capillary refill time, altered mental state exhibited the highest predictive value area under the receiver operating characteristic curve 0.8 (95% CI, 0.78-0.8) with the lowest possible number of variables.A machine learning-based algorithm could reliably predict hospital mortality in a Sub-Sahara African population of 949 children with an acute infection using easily collected information at admission which includes age, respiratory rate, capillary refill time, and altered mental state. Future studies need to evaluate and strengthen this algorithm in larger pediatric populations, both in high- and low-/middle-income countries.

Background The ability to predict transfusions arising during hospital admission might enable economized blood supply management and might furthermore increase patient safety by ensuring a sufficient stock of red blood cells (RBCs) for a specific patient. We therefore investigated the precision of four different machine learning–based prediction algorithms to predict transfusion, massive transfusion, and the number of transfusions in patients admitted to a hospital. Study Design and Methods This was a retrospective, observational study in three adult tertiary care hospitals in Western Australia between January 2008 and June 2017. Primary outcome measures for the classification tasks were the area under the curve for the receiver operating characteristics curve, the F1 score, and the average precision of the four machine learning algorithms used: neural networks (NNs), logistic regression (LR), random forests (RFs), and gradient boosting (GB) trees. Results Using our four predictive models, transfusion of at least 1 unit of RBCs could be predicted rather accurately (sensitivity for NN, LR, RF, and GB: 0.898, 0.894, 0.584, and 0.872, respectively; specificity: 0.958, 0.966, 0.964, 0.965). Using the four methods for prediction of massive transfusion was less successful (sensitivity for NN, LR, RF, and GB: 0.780, 0.721, 0.002, and 0.797, respectively; specificity: 0.994, 0.995, 0.993, 0.995). As a consequence, prediction of the total number of packed RBCs transfused was also rather inaccurate. Conclusion This study demonstrates that the necessity for intrahospital transfusion can be forecasted reliably, however the amount of RBC units transfused during a hospital stay is more difficult to predict.

Purpose Surgical re-exploration due to postoperative bleeding is associated with increased morbidity and mortality. The aim of our study was to assess a potential association between the level of postoperative FXIII activity and need for re-exploration due to bleeding in patients undergoing cardiothoracic surgery. Materials and methods In our prospective single center observational cohort study, we enrolled patients who underwent elective cardiothoracic surgery. Patients who required re-exploration (RE group) were matched to patients from the study population (non-RE group). Results The study included 64 patients, out of a cohort of 678 patients, of whom 32 required surgical re-exploration due to bleeding within the first 24 h. Between patients of the RE and non-RE group, a significantly reduced FXIII activity was observed postoperatively (59.0 vs 71.1; p = .014). Multivariable analysis revealed reduced FXIII activity (p = .048) as a parameter independently associated with surgical re-exploration. Further, reduced FXIII activity (p = .037) and surgical re-exploration (p = .01) were significantly associated with increased 30 day mortality. In multivariable analysis re-exploration was independently associated with increased risk of 30 day mortality (p = .004, HR 9.68). Conclusions Reduced postoperative FXIII activity may be associated with the need for surgical re-exploration. Postoperative assessment of FXIII activity should therefore be considered in patients undergoing elective cardiothoracic surgery.

To compare the clinical judgement of electroencephalogram (EEG)-naïve anesthesiologists with an EEG-based measurement of anesthetic depth (AD) using the Narcotrend® monitor.In this prospective cohort study including 600 patients, AD during stable anesthesia was assessed by clinical judgement of the attending, EEG-blinded anesthesiologist (using a scale staging the AD as mid-adequate, adequate but fairly deep, or adequate but fairly light) and by simultaneously recorded Narcotrend measurements.In 42% of patients (n = 250), the anesthesiologist's clinical judgement was in agreement with anesthetic levels as measured by the Narcotrend monitor. In 46% of patients (n = 274), the anesthesiologist's judgement and the Narcotrend monitor differed by one AD level (minor discordance). Major discordance was observed in 76 (13%) measurements (judged deeper than measured, n = 29 [5%]; judged lighter than measured, n = 47 [8%]). In 7% of patients (n = 44), the Narcotrend index was outside the limits of adequate AD (too deep, n = 28 [5%]; too superficial, n = 16 [3%]). The overall level of agreement between the anesthesiologist's judgement and the Narcotrend monitor was not statistically significant (Cohen's kappa, -0.039; P = 0.17). Using a random forests algorithm, age, mean blood pressure, the American Society of Anesthesiologists classification, body mass index, and frailty were the variables with the highest relative feature importance to predict the level of agreement.These results suggest that clinical judgement of AD during stable anesthesia was not in agreement with EEG-based assessment of anesthetic depth in 58% of cases. Nevertheless, this finding could be influenced by the lack of validated scales to clinically judge AD.www.clinicaltrials.gov (NCT02766894); registered 10 May, 2016.RéSUMé: OBJECTIF: Notre objectif était de comparer le jugement clinique d’anesthésiologistes n’ayant pas accès à un électroencéphalogramme (EEG) à une mesure de la profondeur anesthésique (PA) fondée sur l’EEG utilisant le moniteur Narcotrend®. MéTHODE: Dans cette étude de cohorte prospective de 600 patients, la PA a été évaluée pendant la phase de maintien stable de l’anesthésie selon le jugement clinique de l’anesthésiologiste traitant, qui n’avait pas accès à l’EEG (sur une échelle évaluant la PA comme étant adéquate, adéquate mais relativement profonde ou adéquate mais relativement légère) et par des mesures simultanément enregistrées par le Narcotrend. RéSULTATS: Chez 42 % des patients (n = 250), le jugement clinique de l’anesthésiologiste concordait aux niveaux anesthésiques tels que mesurés par le moniteur Narcotrend. Chez 46 % des patients (n = 274), le jugement de l’anesthésiologiste et le moniteur Narcotrend différaient d’un niveau de PA (discordance mineure). Une discordance majeure a été observée dans 76 (13 %) mesures (jugées plus profondes que mesurées, n = 29 [5 %], jugées plus légères que mesurées, n = 47 [8 %]). Chez 7 % des patients (n = 44), l’indice Narcotrend était situé au-delà des limites d’une PA adéquate (trop profond, n = 28 [5 %]; trop superficiel, n = 16 [3 %]). Le niveau global de concordance entre le jugement de l’anesthésiologiste et le moniteur Narcotrend n’était pas significatif d’un point de vue statistique (kappa de Cohen, -0,039; P = 0,17). En se fondant sur un algorithme de forêt d’arbres décisionnels (random forests algorithm), l’âge, la tension artérielle moyenne, la classification selon l’American Society of Anesthesiologists, l’indice de masse corporelle et l’index de fragilité ont été identifiés comme les variables ayant la plus grande importance relative pour prédire le niveau de concordance. CONCLUSION: Ces résultats suggèrent que, dans 58 % des cas, le jugement clinique de la PA ne concordait pas à l’évaluation par EEG de la profondeur anesthésique pendant une phase de maintien stable de l’anesthésie. Toutefois, ces résultats pourraient être influencés par l’absence d’échelles validées pour juger la PA d’un point de vue clinique. ENREGISTREMENT DE L’éTUDE: www.clinicaltrials.gov (NCT02766894); enregistrée le 10 mai 2016.

Persistent, uncontrolled bleeding after trauma is one of the leading causes of fatalities in patients with severe injuries. 40% of trauma deaths are associated with massive haemorrhage. Hypoperfusion due to major loss of blood volume leads to tissue damage. In combination with acidosis and hypothermia, a generalized immune response with activation of coagulation is triggered. This leads to trauma-induced coagulopathy. A suitable, early treatment might lead to a significant reduction in morbidity and mortality.Die anhaltende unkontrollierte Blutung ist eine der führenden Todesursachen bei polytraumatisierten Patienten 1, 2, 3, 4, 5. Hypoperfusion durch große Blutverluste führt zu Gewebeschäden, generalisierter Immunantwort sowie Aktivierung des Gerinnungssystems und damit zu einer traumaassoziierten Koagulopathie (TAK) 4, 5. Durch eine adäquate, frühzeitige Behandlung der TAK können Morbidität und Mortalität signifikant reduziert werden.

The aim of this study was to evaluate, if and with what accuracy perioperative blood loss can be calculated by a machine learning algorithm prior to orthognathic surgery. The investigators implemented a random forest algorithm to predict perioperative blood loss. 1472 patients who underwent orthognathic surgery from 01/2006 to 06/2017 at our institution were screened and 950 patients were included and separated 80%/20% in a training set - utilized to generate the prediction model - and a testing set - utilized to estimate the accuracy of the model. The outcome variable was the correlation between actual perioperative blood loss and predicted perioperative blood loss in the testing set. Other study variables were the difference of actual and predicted perioperative blood loss and important factors influencing perioperative blood loss using random forest feature importance. Descriptive and bivariate statistics were computed and the P value was set at 0.05. There was a statistically significant correlation between actual perioperative blood loss and predicted perioperative blood loss (p 0.001). The mean difference was 7.4 ml with a standard deviation of 172.3 ml. The results of this study suggest that the application of a machine-learning algorithm allows a prediction of perioperative blood loss prior to orthognathic surgery.

A fracture mechanical model extended towards thermal dependence and validated for two technical elastomers based on EPDM and NR elastomers reinforced with an amount of 50 phr carbon black (CB). Both materials were characterized for fatigue to failure (FTF) and for fatigue crack growth (FCG) behavior. Both methods were performed at three different test temperatures. The particle size distribution of both compounds was counted using computed tomography (CT). The mean value of the experimental data and the calculation show a deviation up to one decade for EPDM and NR elastomer at 23 °C. However, for both materials the mean value of the experimental data and the calculation from the developed concept are in the confidence limits at 90 °C of the number of cycles.

BACKGROUND Restrictive intraoperative fluid management has been demonstrated to improve outcome of visceral and lung surgery in several studies. However, subsequent hypovolemia (HOV) may be accompanied by a decrease of anemia tolerance, resulting in increased transfusion needs. We therefore investigated the effect of volume status on anemia tolerance. STUDY DESIGN AND METHODS Eighteen domestic pigs of either sex (mean weight, 23.5 ± 4.8 kg) were anesthetized, ventilated, and randomized into three experimental groups: normovolemia (no intervention), HOV (blood loss of 40% of blood volume), and hypervolemia (HEV; volume infusion of 40% of blood volume). The animals were then hemodiluted until their individual critical hemoglobin concentrations (Hbcrit) were reached by the exchange of whole blood for hydroxyethyl starch (HES; 130:0.4). Subsequently, organ-specific hypoxia was assessed using pimonidazole tissue staining in relevant organs. Hemodynamic and metabolic variables were also investigated. RESULTS Despite significant differences in exchangeable blood volume, Hbcrit was the same in all groups (2.3 g/dL, NS). During HOV, tissue hypoxia was aggravated in the myocardium, brain, and kidneys, whereas tissue oxygenation of the liver and intestine was not influenced by volume status. HEV increased tissue hypoxia in the lungs, but did not impact tissue oxygenation of other organs. CONCLUSIONS The combination of hemorrhagic HOV with subsequent anemia leads to accentuated tissue hypoxia, revealed by a significant increase in pimonidazole binding at Hbcrit, in heart, lungs, brain, and kidney. The lungs were the only organ that showed increased tissue hypoxia after pretreatment of HES infusion and subsequent anemia by normovolemic hemodilution.

In this work, lifetime of carbon black filled elastomers is predicted based on a micro-flaw statistics lifetime concept. Within this concept two material models, the hyperelastic Yeoh model and the inelastic material model of rubber phenomenology (MORPH), are compared. The Yeoh model is chosen as a demonstrator for any hyperelastic material model. This model is not able to reproduce the characteristic material behaviour such as permanent set, softening effects and hysteresis and can only reproduce the nonlinearity of the stress-strain response. To overcome these deficiencies the hyperelastic models are typically fitted to the softening state of the material at a maximal (cyclic) load level. However, the results show that it is not foreseeable, which load level should be used for fitting the model to get a reasonable lifetime prediction. This is even more influenced by the restriction that only one parameter set has to be chosen to represent the inhomogeneous softening state of the material when arbitrary loads are applied. The above-mentioned characteristic properties of filled elastomers can be reproduced by the MORPH model. The lifetime prediction using this inelastic material model shows very good agreement with the measured values. Furthermore, the variable softening within the model adumbrate a good lifetime prediction quality of components with complex geometries.

In this paper, a new test specimen for fatigue testing is described. Most of the durability tests for elastomers are performed on dumbbell test specimen. Due to the load, the dumbbell shows stress concentration in the transition area. The newly concave test sample was developed through specific geometric changes in the dumbbell sample. These changes have minimized the stress concentration at transition area. The position of the fracture planes of the dumbbell and the concave test specimens are an indication of the stress concentration effect, since the concave did not occur any cracks in the transition area. The lifetime prediction of the dumbbell and the newly developed concave test sample at different load levels shows very good accordance with the measured values.

Pediatric cardiac surgery is associated with a substantial risk of bleeding, frequently requiring the administration of allogeneic blood products. Efforts to optimize preoperative hemoglobin, limit blood sampling, improve hemostasis, reduce bleeding, correct coagulopathy, and incorporate blood sparing techniques (including restrictive transfusion practices) are key elements of patient blood management (PBM) programs, and should be applied to the pediatric cardiac surgical population as across other disciplines. Many guidelines for implementation of PBM in adults undergoing cardiac surgery are available, but evidence regarding the implementation of PBM in children is limited to systematic reviews and specific guidelines for the pediatric cardiac population are missing. The objective of the task force from the Network for the Advancement of Patient Blood Management, Haemostasis and Thrombosis (NATA, www.nataonline.com) is to provide evidence-based recommendations regarding anemia management and blood transfusion practices in the perioperative care of neonates and children undergoing cardiac surgery, and to highlight potential areas where additional research is urgently required.

Hypnosis is probably one of the oldest therapies known to man. In the last decades modern hypnosis has mainly been used by psychotherapists; however, hypnosis is becoming increasingly more important as a therapeutic method in medicine. Hypnosis can be used for a variety of medical indications. In the literature there is much evidence for the effectiveness of hypnosis. The aim of the present investigation was to demonstrate the effectiveness of hypnosis in inpatient treatment of chronic pain patients and to present a self-hypnosis program, which can be easily integrated into pain therapy.From October 2012 to April 2013 all inpatient chronic pain patients were included (group 1: non-hypnosis group, group 2: hypnosis group). Concerning group 2 a standardized protocol for hypnotherapy was integrated in addition to the standardized pain management program. The main goal of hypnotherapy was to integrate a self-hypnosis training so that further implementation in a domestic setting could be guaranteed. By means of standardized test procedures, e. g. Patient Health Questionnaire (PHQ-9), Pain Disability Index (PDI), Generalized Anxiety Disorder (GAD-7) and Numerical Rating Scales (NRS) for pain and general well-being, data were evaluated before and after the pain therapy.The prestandardized and poststandardized test procedures of 30 chronic pain patients were evaluated (17 patients without hypnosis, 13 patients with hypnosis). The main diagnosis according to ICD-10 was "chronic pain disorder" (F45.41) with a MPSS stage III in all patients. The PDI was significantly improved in the hypnosis group (p = 0.019). The other items all showed a trend towards improvement in the hypnosis group (exception GAD-7) but without statistical significance (p 0.05).In a small patient collective, the present investigation was able to show that the integration of modern hypnotherapy into the treatment of chronic pain patients in an inpatient setting can be another useful therapeutic aspect. In particular, the instructions for learning independently seem to be useful due to the limited in-patient time. More research needs to be carried out to support our initial findings.

Anemia is one of the most important health-care problems of our time. As an entity per se, anemia is independently associated with significant morbidity and mortality. However, the reasons for anemia are manifold, and as a consequence, the symptom of “anemia” is also the final path of many different diseases. At the intensive care unit, the etiologies for anemia include blood loss due to bleeding, diagnostic blood withdrawal, red blood cell breakdown due to immune hemolytic anemias, or other types of hemoglobinopathies, or limited erythropoiesis due to nutritional deficiencies, or inflammation and inflammation-induced utilization disturbances of iron. Diagnosis of these entities requires adequate knowledge of the underlying pathophysiologies. The most obvious treatment of acute anemia, the transfusion of red blood cells, does not necessarily result in reduced morbidity and mortality, and as a consequence, other means to increase the red cell mass such as the application of iron or exogenous erythropoietin have gained more and more scientific interest.

The management of perioperative bleeding involves multiple assessments and strategies to ensure appropriate patient care. Initially, it is important to identify those patients with an increased risk of perioperative bleeding. Next, strategies should be employed to correct preoperative anaemia and to

BACKGROUND: Blood transfusion is used to treat acute anemia with the goal of increasing blood oxygen-carrying capacity as determined by hematocrit (Hct) and oxygen delivery (DO2). However, increasing Hct also increases blood viscosity, which may thus lower DO2 if the arterial circulation is a rigid hydraulic system as the resistance to blood flow will increase. The net effect of transfusion on DO2 in this system can be analyzed by using the relationship between Hct and systemic blood viscosity of circulating blood at the posttransfusion Hct to calculate DO2 and comparing this value with pretransfusion DO2. We hypothesized that increasing Hct would increase DO2 and tested our hypothesis by mathematically modeling DO2 in the circulation. METHODS: Calculations were made assuming a normal cardiac output (5 L/min) with degrees of anemia ranging from 5% to 80% Hct deficit. We analyzed the effects of transfusing 0.5 or more units of 300 cc of packed red blood cells (PRBCs) at an Hct of 65% and calculated microcirculatory DO2 after accounting for increased blood viscosity and assuming no change in blood pressure. Our model accounts for O2 diffusion out of the circulation before blood arriving to the nutritional circulation and for changes in blood flow velocity. The immediate posttransfusion DO2 was also compared with DO2 after the transient increase in volume due to transfusion has subsided. RESULTS: Blood transfusion of up to 3 units of PRBCs increased DO2 when Hct (or hemoglobin) was 60% lower than normal, but did not increase DO2 when administered before this threshold. CONCLUSIONS: After accounting for the effect of increasing blood viscosity on blood flow owing to increasing Hct, we found in a mathematical simulation of DO2 that transfusion of up to 3 units of PRBCs does not increase DO2, unless anemia is the result of an Hct deficit greater than 60%. Observations that transfusions occasionally result in clinical improvement suggest that other mechanisms possibly related to increased blood viscosity may compensate for the absence of increase in DO2.