Background The use of artificial colloids has declined in critical care, whereas they are still used in perioperative medicine. Little is known about the nephrotoxic potential in noncritically ill patients during routine surgery. The objective of this trial was to evaluate the influences of albumin 5% and balanced hydroxyethyl starch 6% (130/0.4) on renal function and kidney injury. Methods One hundred urologic patients undergoing elective cystectomy were randomly assigned for this prospective, single-blinded, controlled study with two parallel groups to receive either albumin 5% or balanced hydroxyethyl starch 6% (130/0.4) as the only perioperative colloid. The primary endpoint was the ratio of serum cystatin C between the last visit at day 90 and the first preoperative visit. Secondary endpoints were estimated glomerular filtration rate and serum neutrophil gelatinase-associated lipocalin until the third postoperative day and risk, injury, failure, loss, and end-stage renal disease criteria at postoperative days 3 and 90. Results The median cystatin C ratio was 1.11 (interquartile range, 1.01 to 1.23) in the albumin and 1.08 (interquartile range, 1.00 to 1.20) in the hydroxyethyl starch group (median difference = 0.03; 95% CI, –0.09 to 0.08; P = 0.165). Also, there were no significant differences concerning serum cystatin C concentrations; estimated glomerular filtration rate; risk, injury, failure, loss, and end-stage renal disease criteria; and neutrophil gelatinase-associated lipocalin. Infusion requirements, transfusion rates, and perioperative hemodynamics were similar in both groups. Conclusions With respect to renal function and kidney injury, this study indicates that albumin 5% and balanced hydroxyethyl starch 6% have comparable safety profiles in noncritically ill patients undergoing major surgery.

Induction of hypoxia-inducible-factor-1α (HIF-1α) pathway and HIF-target genes allow adaptation to hypoxia and are associated with reduced incidence of acute mountain sickness (AMS). Little is known about HIF-pathways in conjunction with inflammation or exercise stimuli under acute hypobaric hypoxia in non-acclimatized individuals. We therefore tested the hypotheses that (1) both hypoxic and inflammatory stimuli induce hypoxic-inflammatory signaling pathways in vitro, (2) similar results are seen in vivo under hypobaric hypoxia, and (3) induction of HIF-dependent genes is associated with AMS in 11 volunteers. In vitro, peripheral blood mononuclear cells (PBMCs) were incubated under hypoxic (10%/5% O2) or inflammatory (CD3/CD28) conditions. In vivo, Interleukin 1β (IL-1β), C-X-C Chemokine receptor type 4 (CXCR-4), and C-C Chemokine receptor type 2 (CCR-2) mRNA expression, cytokines and receptors were analyzed under normoxia (520 m above sea level (a.s.l.)), hypobaric hypoxia (3883 m a.s.l.) before/after exercise, and after 24 h under hypobaric hypoxia. In vitro, isolated hypoxic (p = 0.004) or inflammatory (p = 0.006) stimuli induced IL-1β mRNA expression. CCR-2 mRNA expression increased under hypoxia (p = 0.005); CXCR-4 mRNA expression remained unchanged. In vivo, cytokines, receptors, and IL-1β, CCR-2 and CXCR-4 mRNA expression increased under hypobaric hypoxia after 24 h (all p ≤ 0.05). Of note, proinflammatory IL-1β and CXCR-4 mRNA expression changes were associated with symptoms of AMS. Thus, hypoxic-inflammatory pathways are differentially regulated, as combined hypoxic and exercise stimulus was stronger in vivo than isolated hypoxic or inflammatory stimulation in vitro.

ObjectiveNormobaric (NH) and hypobaric hypoxia (HH) are associated with acute mountain sickness (AMS) and cognitive dysfunction. Only few variables, like heart-rate-variability, are correlated with AMS. However, prediction of AMS remains difficult. We therefore designed an expedition-study with healthy volunteers in NH/HH to investigate additional non-invasive hemodynamic variables associated with AMS.MethodsEleven healthy subjects were examined in NH (FiO2 13.1%; equivalent of 3.883 m a.s.l; duration 4 h) and HH (3.883 m a.s.l.; duration 24 h) before and after an exercise of 120 min. Changes in parameters of electrical cardiometry (cardiac index (CI), left-ventricular ejection time (LVET), stroke volume (SV), index of contractility (ICON)), near-infrared spectroscopy (cerebral oxygenation, rScO2), Lake-Louise-Score (LLS) and cognitive function tests were assessed. One-Way-ANOVA, Wilcoxon matched-pairs test, Spearman’s-correlation-analysis and Student’s t-test were performed.ResultsHH increased heart rate (HR), mean arterial pressure (MAP) and CI and decreased LVET, SV and ICON, whereas NH increased HR and decreased LVET. In both NH and HH cerebral oxygenation decreased and LLS increased significantly. After 24 h in HH, 6 of 11 subjects (54.6%) developed AMS. LLS remained increased until 24 h in HH, whereas cognitive function remained unaltered. In HH, HR and LLS were inversely correlated (r = − 0.692; p < 0.05). More importantly, the rScO2-decrease after exercise in NH significantly correlated with LLS after 24 h in HH (r = − 0.971; p < 0.01) and rScO2 correlated significantly with HR (r = 0.802; p < 0.01), CI (r = 0.682; p < 0.05) and SV (r = 0.709; p < 0.05) after exercise in HH.ConclusionsBoth acute NH and HH altered hemodynamic and cerebral oxygenation and induced AMS. Subjects, who adapted their CI had higher rScO2 and lower LLS. Furthermore, rScO2 after exercise under normobaric conditions was associated with AMS at high altitudes.

Background Machine learning algorithms are currently used in a wide array of clinical domains to produce models that can predict clinical risk events. Most models are developed and evaluated with retrospective data, very few are evaluated in a clinical workflow, and even fewer report performances in different hospitals. In this study, we provide detailed evaluations of clinical risk prediction models in live clinical workflows for three different use cases in three different hospitals. Objective The main objective of this study was to evaluate clinical risk prediction models in live clinical workflows and compare their performance in these setting with their performance when using retrospective data. We also aimed at generalizing the results by applying our investigation to three different use cases in three different hospitals. Methods We trained clinical risk prediction models for three use cases (ie, delirium, sepsis, and acute kidney injury) in three different hospitals with retrospective data. We used machine learning and, specifically, deep learning to train models that were based on the Transformer model. The models were trained using a calibration tool that is common for all hospitals and use cases. The models had a common design but were calibrated using each hospital’s specific data. The models were deployed in these three hospitals and used in daily clinical practice. The predictions made by these models were logged and correlated with the diagnosis at discharge. We compared their performance with evaluations on retrospective data and conducted cross-hospital evaluations. Results The performance of the prediction models with data from live clinical workflows was similar to the performance with retrospective data. The average value of the area under the receiver operating characteristic curve (AUROC) decreased slightly by 0.6 percentage points (from 94.8% to 94.2% at discharge). The cross-hospital evaluations exhibited severely reduced performance: the average AUROC decreased by 8 percentage points (from 94.2% to 86.3% at discharge), which indicates the importance of model calibration with data from the deployment hospital. Conclusions Calibrating the prediction model with data from different deployment hospitals led to good performance in live settings. The performance degradation in the cross-hospital evaluation identified limitations in developing a generic model for different hospitals. Designing a generic process for model development to generate specialized prediction models for each hospital guarantees model performance in different hospitals.

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The relationship between the natural menstrual cycle and the EGX as an indicator of vascular permeability may provide a new explanation for premenstrual edema in healthy women. This may be an attendant phenomenon of a regular physiological process, the hormonal downregulation of the vascular barrier during pregnancy.

In cardiac surgical patients, tranexamic acid (TXA) has been associated with an increased risk of convulsive seizure (CS). We aimed to investigate whether in patients undergoing isolated coronary artery bypass grafting (CABG) surgery the use of cardiopulmonary bypass (CPB) impacts the risk of CS. We studied 4198 propensity score matched patients. Patients who underwent CABG surgery without CPB, received a single bolus of 1 g TXA. Patients who underwent CABG with CPB, additionally received a TXA dose of 0.5 g in the CPB prime and an infusion of 0.2 g/h until the end of CPB. The risk of CS in the CPB group and the group without CPB was 0.7% and 0.6%, respectively (risk ratio 1.08, 95% confidence interval 0.51–2.30; P &gt; 0.99). Kidney function was significantly associated with the risk of CS (P = 0.005), the latter being highest in patients with glomerular filtration rates &lt;30 ml/min/1.73 m2 (2.2%) and lowest in those patients with values &gt;60 ml/min/1.73 m2 (0.4%). Our data in patients undergoing isolated CABG indicate no significant effect on CS risk by use of CPB when TXA doses of up to ∼2 g are given. However, caution regarding TXA administration is necessary in patients with renal impairment.

Adequate fluid therapy is highly important for the perioperative outcome of our patients. Both, hypovolemia and hypervolemia can lead to an increase in perioperative complications and can impair the outcome. Therefore, perioperative infusion therapy should be target-oriented. The main target is to maintain the patient's preoperative normovolemia by using a sophisticated, rational infusion strategy.Perioperative fluid losses should be discriminated from volume losses (surgical blood loss or interstitial volume losses containing protein). Fluid losses as urine or perspiratio insensibilis (0.5-1.0 ml/kg/h) should be replaced by balanced crystalloids in a ratio of 1:1. Volume therapy step 1: Blood loss up to a maximum value of 20% of the patient's blood volume should be replaced by balanced crystalloids in a ratio of 4(-5):1. Volume therapy step 2: Higher blood losses should be treated by using iso-oncotic, preferential balanced colloids in a ratio of 1:1. For this purpose hydroxyethyl starch can also be used perioperatively if there is no respective contraindication, such as sepsis, burn injuries, critically ill patients, renal impairment or renal replacement therapy, and severe coagulopathy. Volume therapy step 3: If there is an indication for red cell concentrates or coagulation factors, a differentiated application of blood and blood products should be performed.