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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.)

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).)

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.

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: 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.

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.

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.

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.

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.

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

Background: Accumulating evidence indicates that neuropathic pain is a neuro-immune disorder with enhanced activation of the immune system. Recent data provided proof that neuropathic pain patients exhibit increased numbers of immunosuppressive regulatory T cells (Tregs), which may represent an endogenous attempt to limit inflammation and to reduce pain levels. We here investigate the molecular mechanisms underlying these alterations., Methods: Our experimental approach includes functional analyses of primary human T cells, 3'-UTR reporter assays, and expression analyses of neuropathic pain patients' samples., Results: We demonstrate that microRNAs (miRNAs) are involved in the differentiation of Tregs in neuropathic pain. We identify miR-124a and miR-155 as direct repressors of the histone deacetylase sirtuin1 (SIRT1) in primary human CD4(+) cells. Targeting of SIRT1 by either specific siRNA or by these two miRNAs results in an increase of Foxp3 expression and, consecutively, of anti-inflammatory Tregs (siRNA: 1.7 ± 0.4; miR-124a: 1.5 ± 0.4; miR-155: 1.6 ± 0.4; p < 0.01). As compared to healthy volunteers, neuropathic pain patients exhibited an increased expression of miR-124a (2.5 ± 0.7, p < 0.05) and miR-155 (1.3 ± 0.3; p < 0.05) as well as a reduced expression of SIRT1 (0.5 ± 0.2; p < 0.01). Moreover, the expression of these two miRNAs was inversely correlated with SIRT1 transcript levels., Conclusions: Our findings suggest that in neuropathic pain, enhanced targeting of SIRT1 by miR-124a and miR-155 induces a bias of CD4(+) T cell differentiation towards Tregs, thereby limiting pain-evoking inflammation. Deciphering miRNA-target interactions that influence inflammatory pathways in neuropathic pain may contribute to the discovery of new roads towards pain amelioration., Trial Registration: German Clinical Trial Register DRKS00005954.

Background: Despite substantial progress, pathogenesis and therapy of chronic pain are still the focus of many investigations. The ATP-gated P2X7 receptor (P2X7R) has previously been shown to play a central role in animal models of nociceptive inflammatory and neuropathic pain. Recently, we found that the adaptive immune system is involved in the pathophysiology of chronic nociceptive and neuropathic pain in humans. So far, data regarding P2X7R expression patterns on cells of the adaptive immune system of pain patients are scarce. We therefore analyzed the P2X7R expression on peripheral blood lymphocytes and monocytes, as well as serum levels of IL-1β in patients suffering from chronic nociceptive and neuropathic pain in comparison to healthy volunteers in order to identify individuals who might benefit from a P2X7R modulating therapy., Methods: P2X7R messenger RNA (mRNA) and protein expression were determined in patients with either chronic nociceptive low back pain (CLBP) or neuropathic pain (NeP), and in healthy volunteers by quantitative real-time PCR (qPCR) and by fluorescence-assisted cell-sorting (FACS), respectively. IL-1β serum levels were measured with a multiplex cytokine assay., Results: Compared to healthy volunteers, P2X7R mRNA (1.6-fold, p = 0.038) and protein levels were significantly increased on monocytes (NeP: 24.6 ± 6.2, healthy volunteers: 17.0 ± 5.4; p = 0.002) and lymphocytes (NeP: 21.8 ± 6.5, healthy volunteers: 15.6 ± 5.2; p = 0.009) of patients with NeP, but not in patients with CLBP. Similarly, IL-1β serum concentrations were significantly elevated only in NeP patients (1.4-fold, p = 0.04)., Conclusions: A significant upregulation of P2X7R and increased IL-1β release seems to be a particular phenomenon in patients with NeP. P2X7R inhibitors may therefore represent a potential option for the treatment of this frequently intractable type of pain. German Clinical Trial Register (DRKS): Registration Trial DRKS00005954.

About half of the known miRNA genes are located within protein-coding host genes, and are thus subject to co-transcription. Accumulating data indicate that this coupling may be an intrinsic mechanism to directly regulate the host gene's expression, constituting a negative feedback loop. Inevitably, the cell requires a yet largely unknown repertoire of methods to regulate this control mechanism. We propose APA as one possible mechanism by which negative feedback of intronic miRNA on their host genes might be regulated. Using in-silico analyses, we found that host genes that contain seed matching sites for their intronic miRNAs yield longer 32UTRs with more polyadenylation sites. Additionally, the distribution of polyadenylation signals differed significantly between these host genes and host genes of miRNAs that do not contain potential miRNA binding sites. We then transferred these in-silico results to a biological example and investigated the relationship between ZFR and its intronic miRNA miR-579 in a U87 cell line model. We found that ZFR is targeted by its intronic miRNA miR-579 and that alternative polyadenylation allows differential targeting. We additionally used bioinformatics analyses and RNA-Seq to evaluate a potential cross-talk between intronic miRNAs and alternative polyadenylation. CPSF2, a gene previously associated with alternative polyadenylation signal recognition, might be linked to intronic miRNA negative feedback by altering polyadenylation signal utilization.

Background: The classification of pain into nociceptive and neuropathic pain is based on characteristic symptoms and different pathophysiological mechanisms. In a recent investigation, we found a disrupted TH17/Treg balance in patients suffering from chronic unspecific low back pain (CLBP). These patients did not show any signs of neuropathy. There is evidence for a considerable impact of the immune system also in neuropathic pain. However, the role of the adaptive immune system is still unclear. In the present study, we investigated systemic T-cell subset responses and T-cell related cytokine profiles in patients with chronic neuropathic pain., Methods: We analyzed T-cell subsets, mRNA expression and T-cell-related cytokine profiles in 26 patients suffering from neuropathic pain in comparison to 26 healthy controls. Using multicolor flow cytometry (FACS), we quantified the number of T helper cells 1 (TH1), TH2, TH17 and regulatory T-cells (Tregs). Forkhead-Box-Protein 3 (FoxP3), Transforming growth factor-β (TGF-β) and RAR-related orphan receptor-γT (ROR-γT) mRNA expression was determined by quantitative real-time PCR (qPCR) and levels of pain-related cytokines were measured by Human Cytokine Multiplex Immunoassay (Macrophage inflammatory protein-1α (MIP-1α), Tumor necrosis factor-α (TNF-α), Interferon-γ (IFN-γ), Interleukin (IL) -4, IL-6, IL-10, IL-17, and IL-23)., Results: We found a TH17/Treg imbalance with significantly increased anti-inflammatory Tregs and decreased pro-inflammatory TH17 cells in patients with neuropathic pain as compared to healthy controls. These results were confirmed on mRNA level: Treg-related FoxP3 and TGF-β mRNA expression was elevated, whereas expression of TH17-related RORγT was reduced. Cytokine analyses revealed only marginal changes., Conclusions: Our investigation revealed a clear shift of T-cell subsets towards anti-inflammation in patients with neuropathic pain. Interestingly, this is quite similar to our previous findings in CLBP patients, but even more pronounced. Therefore, it remains to be elucidated in future investigations whether the immune changes represent an underlying pathophysiological mechanism or an epiphenomenon induced by ongoing pain and stress., German Clinical Trial Register (drks): Trial registration number: DRKS00005954.

MicroRNAs (miRNAs) are a class of small (∼22 nucleotides) non-coding RNAs that post-transcriptionally regulate gene expression by interacting with target mRNAs. A majority of miRNAs is located within intronic or exonic regions of protein-coding genes (host genes), and increasing evidence suggests a functional relationship between these miRNAs and their host genes. Here, we introduce miRIAD, a web-service to facilitate the analysis of genomic and structural features of intragenic miRNAs and their host genes for five species (human, rhesus monkey, mouse, chicken and opossum). miRIAD contains the genomic classification of all miRNAs (inter- and intragenic), as well as classification of all protein-coding genes into host or non-host genes (depending on whether they contain an intragenic miRNA or not). We collected and processed public data from several sources to provide a clear visualization of relevant knowledge related to intragenic miRNAs, such as host gene function, genomic context, names of and references to intragenic miRNAs, miRNA binding sites, clusters of intragenic miRNAs, miRNA and host gene expression across different tissues and expression correlation for intragenic miRNAs and their host genes. Protein-protein interaction data are also presented for functional network analysis of host genes. In summary, miRIAD was designed to help the research community to explore, in a user-friendly environment, intragenic miRNAs, their host genes and functional annotations with minimal effort, facilitating hypothesis generation and in-silico validations. Database URL: http://www.miriad-database.org., (© The Author(s) 2014. Published by Oxford University Press.)

Immunosuppressive signaling via the adenosine A2A receptor (A2AR) is an important pathway to control inflammation. In immune cells, expression levels of A2ARs influence responsiveness to inflammatory stimuli. However, mechanisms driving expressional changes of A2ARs are still largely elusive. In the current study, we have investigated the impact of microRNAs (miRNAs) on A2AR expression in human polymorphonuclear leukocytes (PMNs) and T cells. Bioinformatic analyses and reporter gene assays revealed that A2AR expression is controlled by miRNA-214, miRNA-15, and miRNA-16. We detected all three miRNAs in both human PMNs and T cells. However, in PMNs, up to 10-fold higher levels of miRNA-16 and miRNA-214 were detected as compared with T cells. Upon in vitro stimulation, no significant expressional changes occurred. Expression levels of all three miRNAs strongly differed between individuals. A2AR expression also exhibited significant differences between PMNs and T cells: In PMNs, more than a 60-fold increase was seen upon LPS stimulation, whereas in T cells only a 2-fold increase was observed upon anti-CD3/CD28 activation. The extent of A2AR upregulation in PMNs strongly differed between individuals (from less than 10-fold to more than 100-fold). In PMNs, the increase in A2AR mRNA expression upon stimulation was inversely correlated with the expression levels of miRNA-214, miRNA-15, and miRNA-16 (R = -0.87, P < 0.0001); no correlation was found in human T cells. These results indicate that individual miRNA profiles gain important influence on A2AR expression regulation in PMNs upon stimulation. Determination of miRNA expression levels may help to identify patients with an increased risk for severe inflammation.

Background: We analyzed prospectively whether MGMT (O(6)-methylguanine-DNA methyltransferase) mRNA expression gains prognostic/predictive impact independent of MGMT promoter methylation in malignant glioma patients undergoing radiotherapy with concomitant and adjuvant temozolomide or temozolomide alone. As DNA-methyltransferases (DNMTs) are the enzymes responsible for setting up and maintaining DNA methylation patterns in eukaryotic cells, we analyzed further, whether MGMT promoter methylation is associated with upregulation of DNMT expression., Methodology/principal Findings: ADULT PATIENTS WITH A HISTOLOGICALLY PROVEN MALIGNANT ASTROCYTOMA (GLIOBLASTOMA: N = 53, anaplastic astrocytoma: N = 10) were included. MGMT promoter methylation was determined by methylation-specific PCR (MSP) and sequencing analysis. Expression of MGMT and DNMTs mRNA were analysed by real-time qPCR. Prognostic factors were obtained from proportional hazards models. Correlation between MGMT mRNA expression and MGMT methylation status was validated using data from the Cancer Genome Atlas (TCGA) database (N = 229 glioblastomas). Low MGMT mRNA expression was strongly predictive for prolonged time to progression, treatment response, and length of survival in univariate and multivariate models (p<0.0001); the degree of MGMT mRNA expression was highly correlated with the MGMT promoter methylation status (p<0.0001); however, discordant findings were seen in 12 glioblastoma patients: Patients with methylated tumors with high MGMT mRNA expression (N = 6) did significantly worse than those with low transcriptional activity (p<0.01). Conversely, unmethylated tumors with low MGMT mRNA expression (N = 6) did better than their counterparts. A nearly identical frequency of concordant and discordant findings was obtained by analyzing the TCGA database (p<0.0001). Expression of DNMT1 and DNMT3b was strongly upregulated in tumor tissue, but not correlated with MGMT promoter methylation and MGMT mRNA expression., Conclusions/significance: MGMT mRNA expression plays a direct role for mediating tumor sensitivity to alkylating agents. Discordant findings indicate methylation-independent pathways of MGMT expression regulation. DNMT1 and DNMT3b are likely to be involved in CGI methylation. However, their exact role yet has to be defined.

Background: miRNAs are small, non-coding RNA molecules that mainly act as negative regulators of target gene messages. Due to their regulatory functions, they have lately been implicated in several diseases, including malignancies. Roughly half of known miRNA genes are located within previously annotated protein-coding regions ("intragenic miRNAs"). Although a role of intragenic miRNAs as negative feedback regulators has been speculated, to the best of our knowledge there have been no conclusive large-scale studies investigating the relationship between intragenic miRNAs and host genes and their pathways., Results: miRNA-containing host genes were three times longer, contained more introns and had longer 5' introns compared to a randomly sampled gene cohort. These results are consistent with the observation that more than 60% of intronic miRNAs are found within the first five 5' introns. Host gene 3'-untranslated regions (3'-UTRs) were 40% longer and contained significantly more adenylate/uridylate-rich elements (AREs) compared to a randomly sampled gene cohort. Coincidentally, recent literature suggests that several components of the miRNA biogenesis pathway are required for the rapid decay of mRNAs containing AREs. A high-confidence set of predicted mRNA targets of intragenic miRNAs also shared many of these features with the host genes. Approximately 20% of intragenic miRNAs were predicted to target their host mRNA transcript. Further, KEGG pathway analysis demonstrated that 22 of the 74 pathways in which host genes were associated showed significant overrepresentation of proteins encoded by the mRNA targets of associated intragenic miRNAs., Conclusions: Our findings suggest that both host genes and intragenic miRNA targets may potentially be subject to multiple layers of regulation. Tight regulatory control of these genes is likely critical for cellular homeostasis and absence of disease. To this end, we examined the potential for negative feedback loops between intragenic miRNAs, host genes, and miRNA target genes. We describe, how higher-order miRNA feedback on hosts' interactomes may at least in part explain correlation patterns observed between expression of host genes and intragenic miRNA targets in healthy and tumor tissue.

Medical errors rank high amongst leading causes of death. Especially in emergency care, when there is limited time to think, the "human factor", the interface between human action and the environmental system, has been recognized to be a critical part that determines the outcome. Recent models of human error are based on the principle that critical incidents are of multifactorial origin and reflect insufficiencies of the underlying system itself. The Human Simulation Center (HSC) was built specifically to train interaction between medical teams and to investigate the human factor in medical emergencies. In the following article we present "MevidIO", a live-monitoring and debriefing application framework. Developed for a full-scale simulation center designed to model error transduction in medical emergency care process chains, the framework integrates educational and scientific aspects.

Introduction: The goal of personalised medicine in the intensive care unit (ICU) is to predict which diagnostic tests, monitoring interventions and treatments translate to improved outcomes given the variation between patients. Unfortunately, processes such as gene transcription and drug metabolism are dynamic in the critically ill; that is, information obtained during static non-diseased conditions may have limited applicability. We propose an alternative way of personalising medicine in the ICU on a real-time basis using information derived from the application of artificial intelligence on a high-resolution database. Calculation of maintenance fluid requirement at the height of systemic inflammatory response was selected to investigate the feasibility of this approach., Methods: The Multi-parameter Intelligent Monitoring for Intensive Care II (MIMIC II) is a database of patients admitted to the Beth Israel Deaconess Medical Center ICU in Boston. Patients who were on vasopressors for more than six hours during the first 24 hours of admission were identified from the database. Demographic and physiological variables that might affect fluid requirement or reflect the intravascular volume during the first 24 hours in the ICU were extracted from the database. The outcome to be predicted is the total amount of fluid given during the second 24 hours in the ICU, including all the fluid boluses administered., Results: We represented the variables by learning a Bayesian network from the underlying data. Using 10-fold cross-validation repeated 100 times, the accuracy of the model in predicting the outcome is 77.8%. The network generated has a threshold Bayes factor of seven representing the posterior probability of the model given the observed data. This Bayes factor translates into p < 0.05 assuming a Gaussian distribution of the variables., Conclusions: Based on the model, the probability that a patient would require a certain range of fluid on day two can be predicted. In the presence of a larger database, analysis may be limited to patients with identical clinical presentation, demographic factors, co-morbidities, current physiological data and those who did not develop complications as a result of fluid administration. By better predicting maintenance fluid requirements based on the previous day's physiological variables, one might be able to prevent hypotensive episodes requiring fluid boluses during the course of the following day.