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Background: Blood transfusion (BT) is a critical aspect of medical care for surgical patients in the Intensive Care Unit (ICU). Timely and accurate identification of BT needs can enhance patient outcomes and healthcare resource management., Methods: This study aims to determine whether a machine learning (ML) model can be trained to predict the need for blood transfusion (BT) in patients on the ICU after a wide range of surgeries, utilizing only data from the ICU., Results: This retrospective study analyzed data from 9,118 surgical ICU patients from the Amsterdam University Medical Centers database (UMCdb). The study included a primary analysis using data from 6 h before ICU admission up to 1, 2, 3, and 6 h after admission, and a secondary analysis using only the data from 6 h before ICU admission and only the data from the first hour after admission. The model integrated 32 relevant clinical variables and compared the performance of XGBoost and logistic regression (LR) algorithms., Conclusions: The model demonstrated an effective BT prediction, with XGBoost outperforming LR, particularly for a 12-hour prediction window. Notable differences in patient characteristics were observed among those who received BT and those who did not receive BT. The study establishes the feasibility of using ML for the prediction of BT in surgical ICU patients. It underlines the potential of ML models as decision support tools in healthcare, enabling early identification of BT needs., Competing Interests: Declarations. Ethics approval and consent to participate: The data extracted from UMCdb, which is publicly available and does not require individual informed consent, are de-identified in compliance with the Health Insurance Portability and Accountability Act and the European General Data Protection Regulation. The steering group of AmsterdamUMCdb has granted permission for the use of its data by third parties for research purposes, as per the data use agreement. This research, conducted on anonymized data, is exempt from the requirement of ethical review (see [18]). Consent for publication: Not applicable. Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

Enrolling in a clinical trial or study requires informed consent. Furthermore, it is crucial to ensure proper consent when storing samples in biobanks for future research, as these samples may be used in studies beyond their initial purpose. For pediatric studies, consent must be obtained from both the child and their legal guardians, requiring the recording of multiple consents at once. Electronic consent has become more popular recently due to its ability to prevent errors and simplify the documentation of multiple consents. However, integrating consent capture into existing study software structures remains a challenge. This report evaluates the usability of the generic Informed Consent Service (gICS) of the University Medicine Greifswald (UMG) for obtaining electronic consent in pediatric studies. The setup was designed to integrate seamlessly with the current infrastructure and meet the specific needs of a multi-user, multi-study environment. The study was conducted in a pediatric research setting, where additional informed consent was obtained separately for the biobank. Over a period of 54 weeks, 1061 children and adolescents aged 3 to 17 years participated in the study. Out of these, 348 agreed also to participate in the biobank. The analysis included a total of 2066 consents and assents, with 945 paper-based and 1121 electronic consents. The study assessed the error susceptibility of electronic versus paper-based consents and found a significant reduction rate of errors of 94.7%. These findings provide valuable insights into the use of gICS in various studies and the practical implementation of electronic consent software in pediatric medicine., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Danhauser et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Gene set analysis, a popular approach for analyzing high-throughput gene expression data, aims to identify sets of genes that show enriched expression patterns between two conditions. In addition to the multitude of methods available for this task, users are typically left with many options when creating the required input and specifying the internal parameters of the chosen method. This flexibility can lead to uncertainty about the "right" choice, further reinforced by a lack of evidence-based guidance. Especially when their statistical experience is scarce, this uncertainty might entice users to produce preferable results using a "trial-and-error" approach. While it may seem unproblematic at first glance, this practice can be viewed as a form of "cherry-picking" and cause an optimistic bias, rendering the results nonreplicable on independent data. After this problem has attracted a lot of attention in the context of classical hypothesis testing, we now aim to raise awareness of such overoptimism in the different and more complex context of gene set analyses. We mimic a hypothetical researcher who systematically selects the analysis variants yielding their preferred results, thereby considering three distinct goals they might pursue. Using a selection of popular gene set analysis methods, we tweak the results in this way for two frequently used benchmark gene expression data sets. Our study indicates that the potential for overoptimism is particularly high for a group of methods frequently used despite being commonly criticized. We conclude by providing practical recommendations to counter overoptimism in research findings in gene set analysis and beyond., (© 2024 The Author(s). Biometrical Journal published by Wiley‐VCH GmbH.)

Introduction: Secure Multi-Party Computation (SMPC) offers a powerful tool for collaborative healthcare research while preserving patient data privacy., State of the Art: However, existing SMPC frameworks often require separate executions for each desired computation and measurement period, limiting user flexibility., Concept: This research explores the potential of a client-driven metaprotocol for the Federated Secure Computing (FSC) framework and its SImple Multiparty ComputatiON (SIMON) protocol as a step towards more flexible SMPC solutions., Implementation: This client-driven metaprotocol empowers users to specify and execute multiple calculations across diverse measurement periods within a single client-side code execution. This eliminates the need for repeated code executions and streamlines the analysis process. The metaprotocol offers a user-friendly interface, enabling researchers with limited cryptography expertise to leverage the power of SMPC for complex healthcare analyses., Lessons Learned: We evaluate the performance of the client-driven metaprotocol against a baseline iterative approach. Our evaluation demonstrates performance improvements compared to traditional iterative approaches, making this metaprotocol a valuable tool for advancing secure and efficient collaborative healthcare research.

In the field of medical data analysis, converting unstructured text documents into a structured format suitable for further use is a significant challenge. This study introduces an automated local deployed data privacy secure pipeline that uses open-source Large Language Models (LLMs) with Retrieval-Augmented Generation (RAG) architecture to convert medical German language documents with sensitive health-related information into a structured format. Testing on a proprietary dataset of 800 unstructured original medical reports demonstrated an accuracy of up to 90% in data extraction of the pipeline compared to data extracted manually by physicians and medical students. This highlights the pipeline's potential as a valuable tool for efficiently extracting relevant data from unstructured sources.

This study explores the potential of federated learning (FL) to develop a predictive model of hypoxemia in intensive care unit (ICU) patients. Centralized learning (CL) and local learning (LL) approaches have been limited by the localized nature of data, which restricts CL approaches to the available data due to data privacy regulations. A CL approach that combines data from different institutions, could offer superior performance compared to a single-institution approach. However, the use of this method raises ethical and regulatory concerns. In this context, FL presents a promising middle ground, enabling collaborative model training on geographically dispersed ICU data without compromising patient confidentiality. This study is the first to use all five public ICU databases combined. The findings demonstrate that FL achieved comparable or even slightly improved performance compared to local or centralized learning approaches.

Our prototype system designed for clinical data acquisition and recording of studies is a novel electronic data capture (EDC) software for simple and lightweight data capture in clinical research. Existing software tools are either costly or suffer from very limited features. To overcome these shortcomings, we designed an EDC software together with a mobile client. We aimed at making it easy to set-up, modifiable, scalable and thereby facilitating research. We wrote the software in R using a modular approach and implemented existing data standards along with a meta data driven interface and database structure. The prototype is an adaptable open-source software, which can be installed locally or in the cloud without advanced IT-knowledge. A mobile web interface and progressive web app for mobile use and desktop computers is added. We show the software's capability, by demonstrating four clinical studies with over 1600 participants and 679 variables per participant. We delineate a simple deployment approach for a server-installation and indicate further use-cases. The software is available under the MIT open-source license. Conclusively the software is versatile, easily deployable, highly modifiable, and extremely scalable for clinical studies. As an open-source R-software it is accessible, open to community-driven development and improvement in the future., (© 2024. The Author(s).)

Objective: Postoperative nausea and vomiting (PONV) occurs in up to 30% of patients and its pathophysiology and mechanisms have not been completely described. Hypotension and a decrease in cardiac output are suspected to induce nausea. The hypothesis that intraoperative hypotension might influence the incidence of PONV was investigated., Material and Methods: The study was conducted as a retrospective large single center cohort study. The incidence of PONV was investigated until discharge from post anesthesia care unit (PACU). Surgical patients with general anesthesia during a 2-year period between 2018 and 2019 at a university hospital in Germany were included. Groups were defined based on the lowest documented mean arterial pressure (MAP) with group H50: MAP <50mmHg; group H60: MAP <60mmHg; group H70: MAP <70mmHg, and group H0: no MAP <70mmHg. Decreases of MAP in the different groups were related to PONV. Propensity-score matching was carried out to control for overlapping risk factors., Results: In the 2-year period 18.674 patients fit the inclusion criteria. The overall incidence of PONV was 11%. Patients with hypotension had a significantly increased incidence of PONV (H0 vs. H50: 11.0% vs.17.4%, Risk Ratio (RR): 1.285 (99%CI: 1.102-1.498), p  < 0.001; H0 vs. H60: 10.4% vs. 13.5%, RR: 1.1852 (99%CI: 1.0665-1.3172), p  < 0.001; H0 vs. H70: 9.4% vs. 11.2%, RR: 1.1236 (99%CI: 1.013 - 1.2454); p  = 0.0027)., Conclusion: The study demonstrates an association between intraoperative hypotension and early PONV. A more severe decrease of MAP had a pronounced effect.

When different researchers study the same research question using the same dataset they may obtain different and potentially even conflicting results. This is because there is often substantial flexibility in researchers' analytical choices, an issue also referred to as "researcher degrees of freedom". Combined with selective reporting of the smallest p-value or largest effect, researcher degrees of freedom may lead to an increased rate of false positive and overoptimistic results. In this paper, we address this issue by formalizing the multiplicity of analysis strategies as a multiple testing problem. As the test statistics of different analysis strategies are usually highly dependent, a naive approach such as the Bonferroni correction is inappropriate because it leads to an unacceptable loss of power. Instead, we propose using the "minP" adjustment method, which takes potential test dependencies into account and approximates the underlying null distribution of the minimal p-value through a permutation-based procedure. This procedure is known to achieve more power than simpler approaches while ensuring a weak control of the family-wise error rate. We illustrate our approach for addressing researcher degrees of freedom by applying it to a study on the impact of perioperative p a O 2 on post-operative complications after neurosurgery. A total of 48 analysis strategies are considered and adjusted using the minP procedure. This approach allows to selectively report the result of the analysis strategy yielding the most convincing evidence, while controlling the type 1 error-and thus the risk of publishing false positive results that may not be replicable., (© 2024. The Author(s).)

Weaning patients from mechanical ventilation (MV) is a critical and resource intensive process in the Intensive Care Unit (ICU) that impacts patient outcomes and healthcare expenses. Weaning methods vary widely among providers. Prolonged MV is associated with adverse events and higher healthcare expenses. Predicting weaning readiness is a non-trivial process in which the positive end-expiratory pressure (PEEP), a crucial component of MV, has potential to be indicative but has not yet been used as the target. We aimed to predict successful weaning from mechanical ventilation by targeting changes in the PEEP-level using a supervised machine learning model. This retrospective study included 12,153 mechanically ventilated patients from Medical Information Mart for Intensive Care (MIMIC-IV) and eICU collaborative research database (eICU-CRD). Two machine learning models (Extreme Gradient Boosting and Logistic Regression) were developed using a continuous PEEP reduction as target. The data is splitted into 80% as training set and 20% as test set. The model's predictive performance was reported using 95% confidence interval (CI), based on evaluation metrics such as area under the receiver operating characteristic (AUROC), area under the precision-recall curve (AUPRC), F1-Score, Recall, positive predictive value (PPV), and negative predictive value (NPV). The model's descriptive performance was reported as the variable ranking using SHAP (SHapley Additive exPlanations) algorithm. The best model achieved an AUROC of 0.84 (95% CI 0.83-0.85) and an AUPRC of 0.69 (95% CI 0.67-0.70) in predicting successful weaning based on the PEEP reduction. The model demonstrated a Recall of 0.85 (95% CI 0.84-0.86), F1-score of 0.86 (95% CI 0.85-0.87), PPV of 0.87 (95% CI 0.86-0.88), and NPV of 0.64 (95% CI 0.63-0.66). Most of the variables that SHAP algorithm ranked to be important correspond with clinical intuition, such as duration of MV, oxygen saturation (SaO2), PEEP, and Glasgow Coma Score (GCS) components. This study demonstrates the potential application of machine learning in predicting successful weaning from MV based on continuous PEEP reduction. The model's high PPV and moderate NPV suggest that it could be a useful tool to assist clinicians in making decisions regarding ventilator management., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Sheikhalishahi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: Hypoxia is an important risk factor and indicator for the declining health of inpatients. Predicting future hypoxic events using machine learning is a prospective area of study to facilitate time-critical interventions to counter patient health deterioration., Objective: This systematic review aims to summarize and compare previous efforts to predict hypoxic events in the hospital setting using machine learning with respect to their methodology, predictive performance, and assessed population., Methods: A systematic literature search was performed using Web of Science, Ovid with Embase and MEDLINE, and Google Scholar. Studies that investigated hypoxia or hypoxemia of hospitalized patients using machine learning models were considered. Risk of bias was assessed using the Prediction Model Risk of Bias Assessment Tool., Results: After screening, a total of 12 papers were eligible for analysis, from which 32 models were extracted. The included studies showed a variety of population, methodology, and outcome definition. Comparability was further limited due to unclear or high risk of bias for most studies (10/12, 83%). The overall predictive performance ranged from moderate to high. Based on classification metrics, deep learning models performed similar to or outperformed conventional machine learning models within the same studies. Models using only prior peripheral oxygen saturation as a clinical variable showed better performance than models based on multiple variables, with most of these studies (2/3, 67%) using a long short-term memory algorithm., Conclusions: Machine learning models provide the potential to accurately predict the occurrence of hypoxic events based on retrospective data. The heterogeneity of the studies and limited generalizability of their results highlight the need for further validation studies to assess their predictive performance., (© Lena Pigat, Benjamin P Geisler, Seyedmostafa Sheikhalishahi, Julia Sander, Mathias Kaspar, Maximilian Schmutz, Sven Olaf Rohr, Carl Mathis Wild, Sebastian Goss, Sarra Zaghdoudi, Ludwig Christian Hinske. Originally published in JMIR Medical Informatics (https://medinform.jmir.org).)

The COVID-19 pandemic has made it clear: sharing and exchanging data among research institutions is crucial in order to efficiently respond to global health threats. This can be facilitated by defining health data models based on interoperability standards. In Germany, a national effort is in progress to create common data models using international healthcare IT standards. In this context, collaborative work on a data set module for microbiology is of particular importance as the WHO has declared antimicrobial resistance one of the top global public health threats that humanity is facing. In this article, we describe how we developed a common model for microbiology data in an interdisciplinary collaborative effort and how we make use of the standard HL7 FHIR and terminologies such as SNOMED CT or LOINC to ensure syntactic and semantic interoperability. The use of international healthcare standards qualifies our data model to be adopted beyond the environment where it was first developed and used at an international level., (© 2023. Springer Nature Limited.)

Prolonged mechanical ventilation (PMV) after lung transplantation poses several risks, including higher tracheostomy rates and increased in-hospital mortality. Mechanical power (MP) of artificial ventilation unifies the ventilatory variables that determine gas exchange and may be related to allograft function following transplant, affecting ventilator weaning. We retrospectively analyzed consecutive double lung transplant recipients at a national transplant center, ventilated through endotracheal tubes upon ICU admission, excluding those receiving extracorporeal support. MP and derived indexes assessed up to 36 h after transplant were correlated with invasive ventilation duration using Spearman's coefficient, and we conducted receiver operating characteristic (ROC) curve analysis to evaluate the accuracy in predicting PMV (>72 h), expressed as area under the ROC curve (AUROC). PMV occurred in 82 (35%) out of 237 cases. MP was significantly correlated with invasive ventilation duration (Spearman's ρ = 0.252 [95% CI 0.129-0.369], p < 0.01), with power density (MP normalized to lung-thorax compliance) demonstrating the strongest correlation ( ρ = 0.452 [0.345-0.548], p < 0.01) and enhancing PMV prediction (AUROC 0.78 [95% CI 0.72-0.83], p < 0.01) compared to MP (AUROC 0.66 [0.60-0.72], p < 0.01). Mechanical power density may help identify patients at risk for PMV after double lung transplantation., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Ghiani, Kneidinger, Neurohr, Frank, Hinske, Schneider, Michel and Irlbeck.)

Background: Reverse-transcribed gene copies (retrocopies) have emerged as major sources of evolutionary novelty. MicroRNAs (miRNAs) are small and highly conserved RNA molecules that serve as key post-transcriptional regulators of gene expression. The origin and subsequent evolution of miRNAs have been addressed but not fully elucidated., Results: In this study, we performed a comprehensive investigation of miRNA origination through retroduplicated mRNA sequences (retro-miRs). We identified 17 retro-miRs that emerged from the mRNA retrocopies. Four of these retro-miRs had de novo origins within retrocopied sequences, while 13 retro-miRNAs were located within exon regions and duplicated along with their host mRNAs. We found that retro-miRs were primate-specific, including five retro-miRs conserved among all primates and two human-specific retro-miRs. All retro-miRs were expressed, with predicted and experimentally validated target genes except miR-10527. Notably, the target genes of retro-miRs are involved in key biological processes such as metabolic processes, cell signaling, and regulation of neurotransmitters in the central nervous system. Additionally, we found that these retro-miRs play a potential oncogenic role in cancer by targeting key cancer genes and are overexpressed in several cancer types, including liver hepatocellular carcinoma and stomach adenocarcinoma., Conclusions: Our findings demonstrated that mRNA retrotransposition is a key mechanism for the generation of novel miRNAs (retro-miRs) in primates. These retro-miRs are expressed, conserved, have target genes with important cellular functions, and play important roles in cancer., (© 2023. BioMed Central Ltd., part of Springer Nature.)

Mathematical models have been widely used during the ongoing SARS-CoV-2 pandemic for data interpretation, forecasting, and policy making. However, most models are based on officially reported case numbers, which depend on test availability and test strategies. The time dependence of these factors renders interpretation difficult and might even result in estimation biases. Here, we present a computational modelling framework that allows for the integration of reported case numbers with seroprevalence estimates obtained from representative population cohorts. To account for the time dependence of infection and testing rates, we embed flexible splines in an epidemiological model. The parameters of these splines are estimated, along with the other parameters, from the available data using a Bayesian approach. The application of this approach to the official case numbers reported for Munich (Germany) and the seroprevalence reported by the prospective COVID-19 Cohort Munich (KoCo19) provides first estimates for the time dependence of the under-reporting factor. Furthermore, we estimate how the effectiveness of non-pharmaceutical interventions and of the testing strategy evolves over time. Overall, our results show that the integration of temporally highly resolved and representative data is beneficial for accurate epidemiological analyses., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)

COVID-19 has been spreading widely since January 2020, prompting the implementation of non-pharmaceutical interventions and vaccinations to prevent overwhelming the healthcare system. Our study models four waves of the epidemic in Munich over two years using a deterministic, biology-based mathematical model of SEIR type that incorporates both non-pharmaceutical interventions and vaccinations. We analyzed incidence and hospitalization data from Munich hospitals and used a two-step approach to fit the model parameters: first, we modeled incidence without hospitalization, and then we extended the model to include hospitalization compartments using the previous estimates as a starting point. For the first two waves, changes in key parameters, such as contact reduction and increasing vaccinations, were enough to represent the data. For wave three, the introduction of vaccination compartments was essential. In wave four, reducing contacts and increasing vaccinations were critical parameters for controlling infections. The importance of hospitalization data was highlighted, as it should have been included as a crucial parameter from the outset, along with incidence, to avoid miscommunication with the public. The emergence of milder variants like Omicron and a significant proportion of vaccinated people has made this fact even more evident.

Study Objective: Early post-operative delirium is a common perioperative complication in the post anesthesia care unit. To date it is unknown if a specific anesthetic regime can affect the incidence of delirium after surgery. Our objective was to examine the effect of volatile anesthetics on post-operative delirium., Design: Single Center Observational Study., Setting: Post Anesthesia Care Units at a German tertiary medical center., Patients: 30,075 patients receiving general anesthesia for surgery., Measurements: Delirium was assessed with the Nursing Delirium Screening Scale at the end of the recovery period. Subgroup-specific effects of volatile anesthetics on post-operative delirium were estimated using generalized-linear-model trees with inverse probability of treatment weighting. We further assessed the age-specific effect of volatiles using logistic regression models., Main Results: Out of 30,075 records, 956 patients (3.2%) developed delirium in the post anesthesia care unit. On average, patients who developed delirium were older than patients without delirium. We found volatile anesthetics to increase the risk (Odds exp. (B) for delirium in the elderly 1.8-fold compared to total intravenous anesthesia. Odds increases with unplanned surgery 3.0-fold. In the very old (87 years or older), the increase in delirium is 6.2-fold. This result was confirmed with internal validation and in a logistic regression model., Conclusions: Our exploratory study indicates that early postoperative delirium is associated with the use of volatile anesthetics especially in the sub-cohort of patients aged 75 years and above. Further studies should include both volatile and intravenous anesthetics to find the ideal anesthetic in elderly patients., Competing Interests: Declaration of Competing Interest Thomas Saller reports financial support provided by Munich Clinican Scientist Program, Faculty of Medicine, LMU Munich., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Rationale: Steroid profiles in combination with a corticotropin stimulation test provide information about steroidogenesis and its functional reserves in critically ill patients., Objectives: We investigated whether steroid profiles before and after corticotropin stimulation can predict the risk of in-hospital death in sepsis., Methods: An exploratory data analysis of a double blind, randomized trial in sepsis (HYPRESS [HYdrocortisone for PRevention of Septic Shock]) was performed. The trial included adult patients with sepsis who were not in shock and were randomly assigned to placebo or hydrocortisone treatment. Corticotropin tests were performed in patients prior to randomization and in healthy subjects. Cortisol and precursors of glucocorticoids (17-OH-progesterone, 11-desoxycortisol) and mineralocorticoids (11-desoxycorticosterone, corticosterone) were analyzed using the multi-analyte stable isotope dilution method (LC-MS/MS). Measurement results from healthy subjects were used to determine reference ranges, and those from placebo patients to predict in-hospital mortality., Measurements and Main Results: Corticotropin tests from 180 patients and 20 volunteers were included. Compared to healthy subjects, patients with sepsis had elevated levels of 11-desoxycorticosterone and 11-desoxycortisol, consistent with activation of both glucocorticoid and mineralocorticoid pathways. After stimulation with corticotropin, the cortisol response was subnormal in 12% and the corticosterone response in 50% of sepsis patients. In placebo patients (n = 90), a corticotropin-stimulated cortisol-to-corticosterone ratio &gt; 32.2 predicted in-hospital mortality (AUC 0.8 CI 0.70-0.88; sensitivity 83%; and specificity 78%). This ratio also predicted risk of shock development and 90-day mortality., Conclusions: In this exploratory analysis, we found that in sepsis mineralocorticoid steroidogenesis was more frequently impaired than glucocorticoid steroidogenesis. The corticotropin-stimulated cortisol-to-corticosterone ratio predicts the risk of in-hospital death. Trial registration Clinical trial registered with www., Clinicaltrials: gov Identifier: NCT00670254. Registered 1 May 2008, https://clinicaltrials.gov/ct2/show/NCT00670254 ., (© 2022. The Author(s).)

During the onset of acute inflammation, rapid trafficking of leukocytes is essential to mount appropriate immune responses towards an inflammatory insult. Monocytes are especially indispensable for counteracting the inflammatory stimulus, neutralising the noxa and reconstituting tissue homeostasis. Thus, monocyte trafficking to the inflammatory sites needs to be precisely orchestrated. In this study, we identify a regulatory network driven by miR-125a that affects monocyte adhesion and chemotaxis by the direct targeting of two adhesion molecules, i.e., junction adhesion molecule A (JAM-A), junction adhesion molecule-like (JAM-L) and the chemotaxis-mediating chemokine receptor CCR2. By investigating monocytes isolated from patients undergoing cardiac surgery, we found that acute yet sterile inflammation reduces miR-125a levels, concomitantly enhancing the expression of JAM-A, JAM-L and CCR2. In contrast, TLR-4-specific stimulation with the pathogen-associated molecular pattern (PAMP) LPS, usually present within the perivascular inflamed area, resulted in dramatically induced levels of miR-125a with concomitant repression of JAM-A, JAM-L and CCR2 as early as 3.5 h. Our study identifies miR-125a as an important regulator of monocyte trafficking and shows that the phenotype of human monocytes is strongly influenced by this miRNA, depending on the type of inflammatory stimulus.

Background: A pre-existing anticoagulation treatment and predisposing diseases for thromboembolic events represent common problems in patients with sepsis or septic shock; however, these conditions are not addressed in current national guidelines for sepsis and septic shock. One of the aims of this nationwide survey in Germany was therefore to determine how intensive care physicians deal with these problems., Methods: From October 2019 to May 2020, we conducted a nationwide survey among German medical directors of intensive care units (ICU) addressing anticoagulation and drug-based prophylaxis of venous thromboembolism (VTE) in patients with sepsis and sepsis-induced coagulopathy. One focus was the procedure for patients with a pre-existing anticoagulation treatment or a previously known heparin-induced thrombocytopenia (HIT) type 2 (acute symptomatic vs. dating back years)., Results: In most of the participating ICUs pre-existing anticoagulation is largely continued with low molecular weight heparin preparations or unfractionated heparin. In patients with pre-existing HIT type 2 both acute symptomatic and dating back years, argatroban represents the drug of choice. There is a high degree of variability in the definition of the target values, usually being well above the range for pure VTE prophylaxis., Conclusion: Data on the continuation of anticoagulation beyond VTE prophylaxis with a subsequently increased risk of bleeding in patients with sepsis and septic shock is limited and treatment decisions are in many cases subject to individual consideration by the practitioner. The results of our survey imply the need for a systematic work-up of this topic in order to support daily practice in many ICUs with the required evidence., (© 2021. The Author(s).)

Background: Vasoplegic syndrome is associated with increased morbidity and mortality in patients undergoing cardiac surgery. This retrospective, single-center study aimed to evaluate the effect of early use of methylene blue (MB) on hemodynamics after an intraoperative diagnosis of vasoplegic syndrome (VS)., Methods: Over a 10-year period, all patients diagnosed with intraoperative VS (hypotension despite treatment with norepinephrine ≥0.3 μg/kg/min and vasopressin ≥1 IE/h) while undergoing heart surgery and cardiopulmonary bypass were identified, and their data were examined. The intervention group received MB (2 mg/kg intravenous) within 15 min after the diagnosis of vasoplegia, while the control group received standard therapy. The two groups were matched using propensity scores., Results: Of the 1022 patients identified with VS, 221 received MB intraoperatively, and among them, 60 patients received MB within 15 min after the diagnosis of VS. After early MB application, mean arterial pressure was significantly higher, and vasopressor support was significantly lower within the first hour ( p = 0.015) after the diagnosis of vasoplegia, resulting in a lower cumulative amount of norepinephrine ( p = 0.018) and vasopressin ( p = 0.003). The intraoperative need of fresh frozen plasma in the intervention group was lower compared to the control group ( p = 0.015). Additionally, the intervention group had higher creatinine values in the first three postoperative days ( p = 0.036) without changes in dialysis incidence. The 90-day survival did not differ significantly ( p = 0.270)., Conclusion: Our results indicate the additive effects of MB use during VS compared to standard vasopressor therapy only. Early MB administration for VS may significantly improve the patients' hemodynamics with minor side effects.

Background: The 11th revision of the International Classification of Diseases (ICD-11) will come into effect in January 2022. Among other things, The Third International Consensus Definitions for Sepsis and Septic Shock (SEPSIS‑3 definition) will be implemented in it. This defines sepsis as a "life-threatening organ dysfunction caused by a dysregulated host response to infection". The aim of the present secondary analysis of a survey on the topic of "sepsis-induced coagulopathy" was to evaluate whether the SEPSIS‑3 definition, 4 years after its international introduction, has arrived in everyday clinical practice of intensive care units (ICU) run by anesthesiologists in Germany and thus the requirements for its use of the ICD-11 are given., Methods: Between October 2019 and May 2020, we carried out a nationwide survey among German medical directors of ICUs. In a separate block of questions we asked about the definition of sepsis used in daily practice. In addition, we asked whether the quick-sequential (sepsis-related) organ failure assessment (qSOFA) score is used in screening for sepsis in the hospital to which to the participating ICU belongs., Results: A total of 50 medical directors from anesthesiological ICUs took part in the survey. In total, the ICUs evaluated stated that they had around 14% of the high-care beds registered in Germany. The SEPSIS‑3 definition is integrated into everyday clinical practice at 78.9% of the university hospitals and 84.0% of the participating teaching hospitals. In contrast, the qSOFA screening test is only used by 26.3% of the participating university hospitals, but at least 52% of the teaching hospitals and 80% of the other hospitals., Conclusion: The data show that both SEPSIS‑3 and qSOFA have become part of everyday clinical practice in German hospitals. The cautious use of qSOFA at university hospitals with simultaneous broad acceptance of the SEPSIS‑3 definition can be interpreted as an indication that the search for a suitable screening test for sepsis has not yet been completed., (© 2021. The Author(s).)

Aims: This study aimed to determine whether anthropometric markers of thoracic skeletal muscle and abdominal visceral fat tissue correlate with outcome parameters in critically ill COVID-19 patients., Methods: We retrospectively analysed thoracic CT-scans of 67 patients in four ICUs at a university hospital. Thoracic skeletal muscle (total cross-sectional area (CSA); pectoralis muscle area (PMA)) and abdominal visceral fat tissue (VAT) were quantified using a semi-automated method. Point-biserial-correlation-coefficient, Spearman-correlation-coefficient, Wilcoxon rank-sum test and logistic regression were used to assess the correlation and test for differences between anthropometric parameters and death, ventilator- and ICU-free days and initial inflammatory laboratory values., Results: Deceased patients had lower CSA and PMA values, but higher VAT values (p < 0.001). Male patients with higher CSA values had more ventilator-free days (p = 0.047) and ICU-free days (p = 0.017). Higher VAT/CSA and VAT/PMA values were associated with higher mortality (p < 0.001), but were negatively correlated with ICU length of stay in female patients only (p < 0.016). There was no association between anthropometric parameters and initial inflammatory biomarker levels. Logistic regression revealed no significant independent predictor for death., Conclusion: Our study suggests that pathologic body composition assessed by planimetric measurements using thoracic CT-scans is associated with worse outcome in critically ill COVID-19 patients., Competing Interests: All authors declare to have no conflict of interest. There was no funding for this retrospective study., (© 2021 Elsevier Ltd. All rights reserved.)

Background: In the context of sepsis and septic shock, coagulopathy often occurs due to the close relationship between coagulation and inflammation. Sepsis-induced coagulopathy (SIC) is the most severe and potentially fatal form. Anticoagulants used in prophylactic or therapeutic doses are discussed to potentially exert beneficial effects in patients with sepsis and/or SIC; however, due to the lack of evidence recent guidelines are limited to recommendations for drug prophylaxis of venous thromboembolism (VTE), while treatment of SIC has not been addressed., Methods: In order to determine the status quo of VTE prophylaxis as well as treatment of SIC in German intensive care units (ICU), we conducted a Germany-wide online survey among heads of ICUs from October 2019 to May 2020. In April 2020, the survey was supplemented by an additional block of questions on VTE prophylaxis and SIC treatment in coronavirus disease 2019 (COVID-19) patients., Results: A total of 67 senior doctors took part in the survey. The majority (n = 50; 74.6%) of the responses were from ICU under the direction of an anesthesiologist and/or a department of anesthesiology. Most of the participants worked either at a university hospital (n = 31; 47.8%) or an academic teaching hospital (n = 27; 40.3%). The survey results show a pronounced heterogeneity in clinical practice with respect to the prophylaxis of VTE as well as SIC treatment. In an exemplary case of pneumogenic sepsis, low molecular weight heparins (LMWH) were by far the most frequently mentioned group of medications (n = 51; 76.1% of the responding ITS). In the majority of cases (n = 43; 64.2%), anti-FXa activity is not monitored with the use of LMWH in prophylaxis doses. Unfractionated heparin (UFH) was listed as a strategy for VTE prophylaxis in 37.3% of the responses (n = 25). In an exemplary case of abdominal sepsis 54.5% of the participants (n = 36; multiple answers possible) stated the use of UFH or LMWH and UFH with dosage controlled by PTT is used on two participating ICUs. The anti-FXa activity under prophylactic anticoagulation with LMWH is monitored in 7 participating clinics (10.6%) in abdominal sepsis. Systematic screening for sepsis-associated coagulation disorders does not take place in most hospitals and patterns in the use of anticoagulants show significant variability between ICUs. In the case of COVID-19 patients, it is particularly noticeable that in three quarters of the participating ICUs the practice of drug-based VTE prophylaxis and SIC treatment does not differ from that of non-COVID-19 patients., Conclusion: The heterogeneity of answers collected in the survey suggests that a systematic approach to this topic via clinical trials is urgently needed to underline individualized patient care with the necessary evidence., (© 2021. The Author(s).)

Objective: To utilize, in an individual and institutional privacy-preserving manner, electronic health record (EHR) data from 202 hospitals by analyzing answers to COVID-19-related questions and posting these answers online., Materials and Methods: We developed a distributed, federated network of 12 health systems that harmonized their EHRs and submitted aggregate answers to consortia questions posted at https://www.covid19questions.org. Our consortium developed processes and implemented distributed algorithms to produce answers to a variety of questions. We were able to generate counts, descriptive statistics, and build a multivariate, iterative regression model without centralizing individual-level data., Results: Our public website contains answers to various clinical questions, a web form for users to ask questions in natural language, and a list of items that are currently pending responses. The results show, for example, that patients who were taking angiotensin-converting enzyme inhibitors and angiotensin II receptor blockers, within the year before admission, had lower unadjusted in-hospital mortality rates. We also showed that, when adjusted for, age, sex, and ethnicity were not significantly associated with mortality. We demonstrated that it is possible to answer questions about COVID-19 using EHR data from systems that have different policies and must follow various regulations, without moving data out of their health systems., Discussion and Conclusions: We present an alternative or a complement to centralized COVID-19 registries of EHR data. We can use multivariate distributed logistic regression on observations recorded in the process of care to generate results without transferring individual-level data outside the health systems., (© The Author(s) 2021. Published by Oxford University Press on behalf of the American Medical Informatics Association.)

Background: Coronavirus disease 2019 (COVID-19) has no confirmed specific treatments. However, there might be in vitro and early clinical data as well as evidence from severe acute respiratory syndrome and Middle Eastern respiratory syndrome that could inform clinicians and researchers. This systematic review aims to create priorities for future research of drugs repurposed for COVID-19., Methods: This systematic review will include in vitro, animal, and clinical studies evaluating the efficacy of a list of 34 specific compounds and 4 groups of drugs identified in a previous scoping review. Studies will be identified both from traditional literature databases and pre-print servers. Outcomes assessed will include time to clinical improvement, time to viral clearance, mortality, length of hospital stay, and proportions transferred to the intensive care unit and intubated, respectively. We will use the GRADE methodology to assess the quality of the evidence., Discussion: The challenge posed by COVID-19 requires not just a rapid review of drugs that can be repurposed but also a sustained effort to integrate new evidence into a living systematic review., Trial Registration: PROSPERO 2020 CRD42020175648.

Background and Purpose: Anesthesia regimen in patients undergoing mechanical thrombectomy (MT) is still an unresolved issue., Methods: We compared the effect of anesthesia regimen using data from the German Stroke Registry-Endovascular Treatment (GSR-ET) between June 2015 and December 2019. Degree of disability was rated by the modified Rankin Scale (mRS), and good outcome was defined as mRS 0-2. Successful reperfusion was assumed when the modified thrombolysis in cerebral infarction scale was 2b-3., Results: Out of 6,635 patients, 67.1% (n=4,453) patients underwent general anesthesia (GA), 24.9% (n=1,650) conscious sedation (CS), and 3.3% (n=219) conversion from CS to GA. Rate of successful reperfusion was similar across all three groups (83.0% vs. 84.2% vs. 82.6%, P=0.149). Compared to the CA-group, the GA-group had a delay from admission to groin (71.0 minutes vs. 61.0 minutes, P<0.001), but a comparable interval from groin to flow restoration (41.0 minutes vs. 39.0 minutes). The CS-group had the lowest rate of periprocedural complications (15.0% vs. 21.0% vs. 28.3%, P<0.001). The CS-group was more likely to have a good outcome at follow-up (42.1% vs. 34.2% vs. 33.5%, P<0.001) and a lower mortality rate (23.4% vs. 34.2% vs. 26.0%, P<0.001). In multivariable analysis, GA was associated with reduced achievement of good functional outcome (odds ratio [OR], 0.82; 95% confidence interval [CI], 0.71 to 0.94; P=0.004) and increased mortality (OR, 1.42; 95% CI, 1.23 to 1.64; P<0.001). Subgroup analysis for anterior circulation strokes (n=5,808) showed comparable results., Conclusions: We provide further evidence that CS during MT has advantages over GA in terms of complications, time intervals, and functional outcome.

Background: COVID-19 is a novel viral disease. Severe courses may present as ARDS. Several publications report a high incidence of coagulation abnormalities in these patients. We aimed to compare coagulation and inflammation parameters in patients with ARDS due to SARS-CoV-2 infection versus patients with ARDS due to other causes., Methods: This retrospective study included intubated patients admitted with the diagnosis of ARDS to the ICU at Munich university hospital. 22 patients had confirmed SARS-CoV2-infection (COVID-19 group), 14 patients had bacterial or other viral pneumonia (control group). Demographic, clinical parameters and laboratory tests including coagulation parameters and thromboelastometry were analysed., Results: No differences were found in gender ratios, BMI, Horovitz quotients and haemoglobin values. The median SOFA score, serum lactate levels, renal function parameters (creatinine, urea) and all inflammation markers (IL-6, PCT, CRP) were lower in the COVID-19 group (all: p < 0.05). INR (p < 0.001) and antithrombin (p < 0.001) were higher in COVID-19 patients. D-dimer levels (p = 0.004) and consecutively the DIC score (p = 0.003) were lower in this group. In ExTEM®, Time-to-Twenty (TT20) was shorter in the COVID-19 group (p = 0.047), these patients also had higher FibTEM® MCF (p = 0.005). Further, these patients presented with elevated antigen and activity levels of von-Willebrand-Factor (VWF)., Conclusion: COVID-19 patients presented with higher coagulatory potential (shortened global clotting tests, increased viscoelastic and VWF parameters), while DIC scores were lower. An intensified anticoagulation regimen based on an individual risk assessment is advisable to avoid thromboembolic complications., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Introduction: Timely measurement of direct oral anticoagulants (DOACs) is challenging, though clinically important. We tested the hypotheses, that thromboelastometry is able to detect dabigatran and rivaroxaban and discriminates between dabigatran and rivaroxaban as representatives of the two groups of DOACs., Methods and Materials: We conducted a prospective-observational study: In-vitro dose-effect-curves for rivaroxaban and dabigatran were performed (n = 10). Ex-vivo: Patients with indication of DOAC treatment (stroke; dabigatran/rivaroxaban) were included (n = 21). Blood samples were analyzed before first intake, at first estimated peak level and at 24 h after first but before following intake and 3 h after 24 h-intake. Standard and modified thromboelastometric-assays, using low tissue factor concentrations (TFTEM) or ecarin (ECATEM) were used. Receiver-operating-characteristics-curve-analysis (ROC), regression-analysis and two-way-ANOVA were performed., Results: In-vitro: TFTEM detected dabigatran and rivaroxaban (ROC&#95;AUC: 0.99; sensitivity/specificity: 100%/98%) but could not discriminate. Dabigatran prolongs CT ECATEM whereas rivaroxaban did not. Clotting Time (CT)-ratio TFTEM/ECATEM discriminated highly sensitive (100%) and specific (100%) between dabigatran and rivaroxaban even at very low concentrations (ROC&#95;AUC:1.0). CT ECATEM correlated with dabigatran spiked concentrations (r = 0.9985; p < 0.001) and CT TFTEM (r = 0.9363; p = 0.006) with rivaroxaban. Similarly results could be demonstrated with patient data: We confirmed the performance for the differentiation of CT-ratio TFTEM/ECATEM (sensitivity 100%/specificity 100%) at any time after first intake of either DOAC., Conclusion: The thromboelastometric tests TFTEM and ECATEM detect and differentiate rivaroxaban and dabigatran. Further investigations evaluate the other DOACs and the differentiation to phenprocoumon. However, results need to be confirmed in a larger study, and especially cut off values for differentiation need to be calculated from a larger sample size., Competing Interests: Declaration of competing interest The study was funded by a research grant from WIFOMED (Verein für Förderung von Wissenschaft und Forschung an der medizinischen Fakultät der Ludwig- Maximilians-Universität München) to Dr. Schäfer. Thromboelastometric machines and reagents were provided by TEM Innovations (Munich, Germany). The funding sponsors WIFOMED (Verein für Förderung von Wissenschaft und Forschung an der medizinischen Fakultät der Ludwig-Maximilians-Universität München) and (TEM Innovations) had no role in the collection, analysis or interpretation of data; in the writing of the manuscript, or in the decision to publish the results. S.T.S. received lecture fees by CSL Behring and research grants by Octapharma. P.G. received lecture fees by CSL Behring, T.W., T.K., V.B., K.F., L.K. and L.C.H. declare no conflict of interest. K.G. serves as medical director at TEM Innovations since 2012., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Objectives: Infections are major causes of morbidity and mortality in the early postoperative period after liver transplant. We observed a high rate of enterococcal infections at our center. Therefore, we added an intraoperative single shot of vancomycin to the standard regimen of meropenem given over 5 days. The aim of this study was to determine the prevalence of both Enterococcus faecium and Enterococcus faecalis infections during the first 28 days after surgery depending on the type of antibiotic prophylaxis and their implications on mortality and morbidity., Materials and Methods: Our retrospective cohort analysis included 179 patients: 93 patients received meropenem only and 86 patients were treated with meropenem plus vancomycin., Results: During the first 28 days after transplant, microbiological tests showed that 51 patients (28.5%) were positive for Enterococcus faecium and 25 patients (14.0%) were positive for Enterococcus faecalis. Enterococcus faecium infections appeared significantly more often in patients without vancomycin (P = .013). In the second week after transplant, there was a significant reduction in Enterococcus faecium infections in the meropenem plus vancomycin group (P = .015). Enterococcus faecalis infections occurred more often in the patients receiving meropenem alone, but results were not statistically significant (P = .194). There was a trend toward more frequent renal replacement therapy in the meropenem plus vancomycin group. We found no differences between the groups regarding survival after 1 and 2 years, length of hospital stay, or duration in the intensive care unit. Overall 1-year survival was 78.8% (141/179 patients)., Conclusions: Although postoperative Enterococcus species infections can be reduced after liver transplant by adding vancomycin to the intraoperative antibiotic regimen, it does not improve the long-term outcomes.

Background: Currently, no suitable clinical marker for detection of septic immunosuppression is available. We aimed at identifying microRNAs that could serve as biomarkers of T-cell mediated immunoparalysis in sepsis., Methods: RNA was isolated from purified T-cells or from whole blood cells obtained from septic patients and healthy volunteers. Differentially regulated miRNAs were identified by miRNA Microarray (n = 7). Validation was performed via qPCR (n = 31)., Results: T-cells of septic patients revealed characteristics of immunosuppression: Pro-inflammatory miR-150 and miR-342 were downregulated, whereas anti-inflammatory miR-15a, miR-16, miR-93, miR-143, miR-223 and miR-424 were upregulated. Assessment of T-cell effector status showed significantly reduced mRNA-levels of IL2, IL7R and ICOS, and increased levels of IL4, IL10 and TGF-β. The individual extent of immunosuppression differed markedly. MicroRNA-143, - 150 and - 223 independently indicated T-cell immunoparalysis and significantly correlated with patient's IL7R-/ICOS-expression and SOFA-scores. In whole blood, composed of innate and adaptive immune cells, both traits of immunosuppression and hyperinflammation were detected. Importantly, miR-143 and miR-150 - both predominantly expressed in T-cells - retained strong power of discrimination also in whole blood samples., Conclusions: These findings suggest miR-143 and miR-150 as promising markers for detection of T-cell immunosuppression in whole blood and may help to develop new approaches for miRNA-based diagnostic in sepsis.

MicroRNAs (miRNAs), small noncoding RNA molecules, have emerged as important regulators of almost all cellular processes. By binding to specific sequence motifs within the 3'- untranslated region of their target mRNAs, they induce either mRNA degradation or translational repression. In the human immune system, potent miRNAs and miRNA-clusters have been discovered, that exert pivotal roles in the regulation of gene expression. By targeting cellular signaling hubs, these so-called immuno-miRs have fundamental regulative impact on both innate and adaptive immune cells in health and disease. Importantly, they also act as mediators of tumor immune escape. Secreted by cancer cells and consecutively taken up by immune cells, immuno-miRs are capable to influence immune functions towards a blunted anti-tumor response, thus shaping a permissive tumor environment. This review provides an overview of immuno-miRs and their functional impact on individual immune cell entities. Further, implications of immuno-miRs in the amelioration of tumor surveillance are discussed., (Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.)

Over the past decade, evolutionarily conserved, noncoding small RNAs-so-called microRNAs (miRNAs)-have emerged as important regulators of virtually all cellular processes. miRNAs influence gene expression by binding to the 3'-untranslated region of protein-coding RNA, leading to its degradation and translational repression. In medicine, miRNAs have been revealed as novel, highly promising biomarkers and as attractive tools and targets for novel therapeutic approaches. miRNAs are currently entering the field of perioperative medicine, and they may open up new perspectives in anesthesia, critical care, and pain medicine. In this review, we provide an overview of the biology of miRNAs and their potential role in human disease. We highlight current paradigms of miRNA-mediated effects in perioperative medicine and provide a survey of miRNA biomarkers in the field known so far. Finally, we provide a perspective on miRNA-based therapeutic opportunities and perspectives.

MiRNAs control gene expression via recognition of specific sequences in the 3' untranslated region of target genes, leading to mRNA degradation and consequently translational repression. The regulatory impact of miRNAs does not only depend on their expression levels, but also on their targets' mRNA configuration. Via alternative polyadenylation mRNA isoforms are created that may or may not contain the respective miRNA target sequence, turning the regulatory between these two on or off. In the following article, we describe our protocol on how to combine a bioinformatics evaluation of a potential miRNA-target gene interaction using the public web framework miRIAD with 5' rapid amplification of cDNA ends (5'-RACE) in order to explore differential gene regulation by miRNAs through alternative polyadenylation.

MicroRNAs have established their role as important regulators of the epigenome. A considerable number of human miRNA genes are found in intronic regions of protein-coding host genes, in many cases adopting their regulatory circuitry. However, emerging evidence foreshadows an unprecedented importance for this relationship: Intronic miRNAs may protect the cell from overactivation of the respective host pathway, a setting that may trigger tumor development. AKT2 is a well-known proto-oncogene central to the PI3K/AKT pathway. This pathway is known to promote tumor growth and survival, especially in glioblastoma. Its intronic miRNA, hsa-miR-641, is scarcely investigated, however. We hypothesized that miR-641 regulates its host AKT2 and that this regulation may become dysfunctional in glioblastoma. We found that indeed miR-641 expression differs significantly between GBM tissue and normal brain samples, and that transfection of glioma cells with miR-641 antagonizes the PI3K/AKT pathway. Combining clinical samples, cell cultures, and biomolecular methods, we could show that miR-641 doesn't affect AKT2's expression levels, but down-regulates kinases that are necessary for AKT2-activation, thereby affecting its functional state. We also identified NFAT5 as a miR-641 regulated central factor to trigger the expression of these kinases and subsequently activate AKT2. In summary, our study is the first that draws a connecting line between the proto-oncogene AKT2 and its intronic miRNA miR-641 with implication for glioblastoma development., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Objective: The factors leading to the implementation of unplanned extracorporeal circulation during lung transplantation are poorly defined. Consequently, the authors aimed to identify patients at risk for unplanned extracorporeal circulation during lung transplantation., Design: Retrospective data analysis., Setting: Single-center university hospital., Participants: A development data set of 170 consecutive patients and an independent validation cohort of 52 patients undergoing lung transplantation., Interventions: The authors investigated a cohort of 170 consecutive patients undergoing single or sequential bilateral lung transplantation without a priori indication for extracorporeal circulation and evaluated the predictive capability of distinct preoperative and intraoperative variables by using automated model building techniques at three clinically relevant time points (preoperatively, after endotracheal intubation, and after establishing single-lung ventilation)., Measurements and Main Results: Preoperative mean pulmonary arterial pressure was the strongest predictor for unplanned extracorporeal circulation. A logistic regression model based on preoperative mean pulmonary arterial pressure and lung allocation score achieved an area under the receiver operating characteristic curve of 0.85. Consequently, the authors developed a novel 3-point scoring system based on preoperative mean pulmonary arterial pressure and lung allocation score, which identified patients at risk for unplanned extracorporeal circulation and validated this score in an independent cohort of 52 patients undergoing lung transplantation., Conclusions: The authors showed that patients at risk for unplanned extracorporeal circulation during lung transplantation could be identified by their novel 3-point score., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Eukaryotic genomes frequently exhibit interdependency between transcriptional units, as evidenced by regions of high gene density. It is well recognized that vertebrate microRNAs (miRNAs) are usually embedded in those regions. Recent work has shown that the genomic context is of utmost importance to determine miRNA expression in time and space, thus affecting their evolutionary fates over long and short terms. Consequently, understanding the inter- and intraspecific changes on miRNA genomic architecture may bring novel insights on the basic cellular processes regulated by miRNAs, as well as phenotypic evolution and disease-related mechanisms.

Aim: Pain therapy is strongly guided by patients' self-reporting. However, when self-reporting is not an option, pain assessment becomes a challenge and may lead to undertreatment of painful conditions. Pain is a complex and multifactorial phenomenon. Recent work has connected pain pathophysiology also with the inflammatory system. We therefore hypothesized that pain intensity could be predicted by cytokine-levels., Patients & Methods: In this observational, single-center study, we investigated 30 serum cytokines to predict pain intensity in a screening/follow-up set of 95 chronic pain patients and controls. We then prospectively validated soluble intercellular adhesion molecule-1 (sICAM-1)'s discriminatory capability (n = 21)., Results & Conclusion: sICAM-1 was significantly associated with patient-reported pain intensity and yielded differential serum levels in patients of varying degrees of pain intensity. Changes in pain ratings over time correlated with changes in sICAM-1 levels. Our findings suggest the possibility of a clinical use of sICAM-1 as a potential biomarker for pain intensity.

Study Design: A prospective evaluation of microRNA (miRNA) expression in patients with chronic low back pain (CLBP)., Objective: The aim of this study was to evaluate whether pain- and T cell-related miRNAs are differentially expressed in CLBP when compared with healthy volunteers and whether these miRNAs may distinguish between responders and nonresponders to a multidisciplinary treatment program., Summary of Background Data: CLBP is a common health problem worldwide. Multidisciplinary pain treatment programs have been proven as an effective treatment option. miRNAs are known to be important mediators of gene regulation in various processes, including pathophysiology of pain. The expression of miRNAs in CLBP and changes due to a multidisciplinary treatment programs are still unknown., Methods: Thirty-four patients with CLBP were enrolled (46.5 ± 12.7 yrs). CLBP was defined as low back pain with an average intensity of numerical rating scale (NRS) ≥3 during the last 4 weeks, persisting longer than 6 months, and not attributable to a recognized specific pathological condition. Expression of pain- and T cell-related miRNAs in human CD4 cells were determined using TaqMan assays and RealTime PCR. MiRNA expression in patients with CLBP was compared with the expression in healthy volunteers before a multidisciplinary treatment program started. The multidisciplinary outpatient program (4 weeks, 5 days a week, 8 h per day) is a clinically established outpatient program and comprises medical (examination, education), physical (exercise), work-related, and psychological therapy components. After the program, differentially expressed miRNAs in CLBP (before treatment) were analyzed once more. Expression of these miRNAs in patients who respond to the treatment (n = 14) was compared with those who did not respond (n = 20). Response to therapy was defined as reduction of pain of ≥50% (NRS) from baseline., Results: MiRNA-124a (patients: 0.79 ± 0.63 vs. healthy volunteers: 0.30 ± 0.16; P < 0.001), miRNA-150 (patients: 0.75 ± 0.21 vs. healthy volunteers: 0.56 ± 0.20; P = 0.025), and miRNA-155 (patients: 0.55 ± 0.14 vs. healthy volunteers: 0.38 ± 0.16; P = 0.017) were significantly upregulated in CLBP patients when compared with healthy volunteers. After the multidisciplinary treatment program, patients who respond to the treatment showed only an increase of miRNA-124a expression (before treatment: 0.54 ± 0.26 vs. after treatment: 1.05 ± 0.56, P = 0.007)., Conclusion: MiRNA-124a upregulation is associated with therapy response in a multidisciplinary treatment programs and might help to identify more specific and mechanism-based treatment strategies for CLBP., Level of Evidence: 3.

Database Url: http://www.miriad-database.org., (© The Author(s) 2017. Published by Oxford University Press.)