Value of Glycemic Indices for Delayed Cerebral Ischemia after Aneurysmal Subarachnoid Hemorrhage: A Retrospective Single-Center Study.

Delayed cerebral ischemia (DCI) is a severe complication following aneurysmal subarachnoid hemorrhage (aSAH), linked to poor functional outcomes and prolonged intensive care unit (ICU) stays. Timely DCI diagnosis is crucial but remains challenging. Dysregulated blood glucose, commonly observed after aSAH, may impair the constant glucose supply that is vital for brain function, potentially contributing to DCI. This study aimed to assess whether glucose indices could help identify at-risk patients and improve DCI detection. This retrospective, single-center observational study examined 151 aSAH patients between 2016 and 2019. Additionally, 70 of these (46.4%) developed DCI and 81 did not (no-DCI). To determine the value of glycemic indices for DCI, they were analyzed separately in patients in the period before (pre-DCI) and after DCI (post-DCI). The time-weighted average glucose (TWAG, p = 0.024), mean blood glucose (p = 0.033), and novel time-unified dysglycemic rate (TUDR140, calculated as the ratio of dysglycemic to total periods within a glucose target range of 70-140 mg/dL, p = 0.042), showed significantly higher values in the pre-DCI period of the DCI group than in the no-DCI group. In the time-series analysis, significant increases in TWAG and TUDR140 were observed at the DCI onset. In conclusion, DCI patients showed elevated blood glucose levels before and a further increase at the DCI onset. Prospective studies are needed to confirm these findings, as this retrospective, single-center study cannot completely exclude confounders and limitations. In the future blood glucose indices might become valuable parameters in multiparametric models to identify patients at risk and detect DCI onset earlier.

Early extubation after elective surgical aortic valve replacement during the COVID-19 pandemic.

BACKGROUND: Surgical aortic valve replacement (SAVR) is an established therapy for severe calcific aortic stenosis. Enhanced recovery after cardiac surgery (ERACS) protocols have been shown to improve outcomes for elective cardiac procedures. The COVID-19 pandemic prompted early extubation post-elective surgeries to preserve critical care resources. AIM OF THIS STUDY: To investigate the effects of extubating patients within 6 h post-elective SAVR on hospital and ICU length of stay, mortality rates, ICU readmissions, and postoperative pneumonia. STUDY DESIGN AND METHODS: The retrospective analysis at the University Hospital Aachen, Germany, includes data from 2017 to 2022 and compares a total of 73 elective SAVR patients. Among these, 23 patients were extubated within 6 h (EXT group), while 50 patients remained intubated for over 6 h (INT group). RESULTS: The INT group experienced longer postoperative ventilation, needed more vasopressor support, had a higher incidence of postoperative pneumonia, and longer ICU length of stay. No significant differences were noted in overall hospital length of stay, mortality, or ICU readmission rates between the groups. CONCLUSION: This study demonstrates that early extubation in high-risk, multimorbid surgical aortic valve replacement patients is safe, and is associated with a reduction of pneumonia rates, and with shorter ICU and hospital length of stays, reinforcing the benefits of ERACS protocols, especially critical during the COVID-19 pandemic to optimize intensive care use.

[Potential of a Telemedical, Inpatient-Outpatient Care Concept to Improve the Quality of Healthcare from the User's Perspective - An Acceptance Analysis of the TELnet@NRW Study]. / Potential eines telemedizinischen, sektorenübergreifenden Versorgungskonzeptes zur Qualitätssteigerung der Gesundheitsversorgung aus Nutzersicht ­ eine Akzeptanzanalyse der TELnet@NRW Studie.

OBJECTIVE: The aim of this study was to measure the acceptance of a telemedical, inpatient-outpatient care concept by physicians, patients and the relatives of patients. Based on a quantitative survey of acceptance, both the potential and success factors influencing the use of telemedicine were to be highlighted. METHODS: The TELnet@NRW study is a national, multicenter, cluster-randomized study in stepped-wedge design conducted from February 2017 to January 2020 for the purpose of documenting changes in the quality of care through telemedicine in an inpatient-outpatient network. Consultations were focused on intensive care medicine and infectious diseases. This current study used questionnaires for specific groups of patients to determine acceptance of the telemedical care concept practiced in the main study. The survey was anonymously conducted once in either digital or paper-based form during the reporting period. RESULTS: The answers of 126 questionnaires from physicians and 1686 questionnaires from patients and their relatives were evaluated. The physicians of both sectors attributed high potential (up to 88.4%) for telemedicine to improve guideline-adherent treatment. A trustworthy and appreciative communication during the telemedical consultation represented a positively reinforcing success factor. The additional workload generated by telemedicine inhibited acceptance, especially in the inpatient sector. A continuation of telemedicine beyond the end of the project was supported by the majority of surveyed physicians (inpatient 60.6%, outpatient 82.1%) as well as in patients and their relatives (inpatient 79.7%, outpatient 57.4%) in both sectors. CONCLUSION: There is widespread acceptance of telemedical, inpatient-outpatient care concepts among physicians, patients and their relatives. Low-effort processes and user-centered technology are crucial to increase the rate of use. Telemedicine has the potential to improve the quality of care and can serve as a robust component of sustainable healthcare in Germany.

Online Survey Study on the Needs of Former Intensive-Care Patients for the Development of a User-Friendly App.

The aim of this online-survey study is the development and evaluation of a mobile health application specifically designed to meet the needs of individuals who have previously undergone intensive-care treatment. User acceptance and perception play a crucial role in refining and optimizing the app's features and functionalities. By actively incorporating suggestions and insights from users, the goal is to enhance the overall usability and better cater to the diverse needs of individuals in post-intensive care recovery. This iterative approach ensures that the application remains responsive to the evolving requirements of its target audience. Overall, the emphasis is on creating a user-centric and adaptive tool for former intensive care patients, to develop a user-friendly mobile app.

Computational Simulation of Virtual Patients Reduces Dataset Bias and Improves Machine Learning-Based Detection of ARDS from Noisy Heterogeneous ICU Datasets.

Goal: Machine learning (ML) technologies that leverage large-scale patient data are promising tools predicting disease evolution in individual patients. However, the limited generalizability of ML models developed on single-center datasets, and their unproven performance in real-world settings, remain significant constraints to their widespread adoption in clinical practice. One approach to tackle this issue is to base learning on large multi-center datasets. However, such heterogeneous datasets can introduce further biases driven by data origin, as data structures and patient cohorts may differ between hospitals. Methods: In this paper, we demonstrate how mechanistic virtual patient (VP) modeling can be used to capture specific features of patients' states and dynamics, while reducing biases introduced by heterogeneous datasets. We show how VP modeling can be used for data augmentation through identification of individualized model parameters approximating disease states of patients with suspected acute respiratory distress syndrome (ARDS) from observational data of mixed origin. We compare the results of an unsupervised learning method (clustering) in two cases: where the learning is based on original patient data and on data derived in the matching procedure of the VP model to real patient data. Results: More robust cluster configurations were observed in clustering using the model-derived data. VP model-based clustering also reduced biases introduced by the inclusion of data from different hospitals and was able to discover an additional cluster with significant ARDS enrichment. Conclusions: Our results indicate that mechanistic VP modeling can be used to significantly reduce biases introduced by learning from heterogeneous datasets and to allow improved discovery of patient cohorts driven exclusively by medical conditions.

Ribonuclease inhibitor 1 emerges as a potential biomarker and modulates inflammation and iron homeostasis in sepsis.

Sepsis, marked by organ dysfunction, necessitates reliable biomarkers. Ribonuclease inhibitor 1 (RNH1), a ribonuclease (RNase) inhibitor, emerged as a potential biomarker for acute kidney injury and mortality in thoracoabdominal aortic aneurysm patients. Our study investigates RNH1 dynamics in sepsis, its links to mortality and organ dysfunction, and the interplay with RNase 1 and RNase 5. Furthermore, we explore RNH1 as a therapeutic target in sepsis-related processes like inflammation, non-canonical inflammasome activation, and iron homeostasis. We showed that RNH1 levels are significantly higher in deceased patients compared to sepsis survivors and correlate with creatine kinase, aspartate and alanine transaminase, bilirubin, serum creatinine and RNase 5, but not RNase 1. RNH1 mitigated LPS-induced TNFα and RNase 5 secretion, and relative mRNA expression of ferroptosis-associated genes HMOX1, FTH1 and HAMP in PBMCs. Monocytes were identified as the predominant type of LPS-positive PBMCs. Exogenous RNH1 attenuated LPS-induced CASP5 expression, while increasing IL-1ß secretion in PBMCs and THP-1 macrophages. As RNH1 has contradictory effects on inflammation and non-canonical inflammasome activation, its use as a therapeutic agent is limited. However, RNH1 levels may play a central role in iron homeostasis during sepsis, supporting our clinical observations. Hence, RNH1 shows promise as biomarkers for renal and hepatic dysfunction and hepatocyte injury, and may be useful in predicting the outcome of septic patients.

Observational study of missing SOFA score data frequency in RCTs relative to ICU length of stay.

The Sequential Organ Failure Assessment, also known as SOFA score, was introduced to assess organ dysfunction of critical ill patients. However, understanding the impact of missing SOFA scores in randomized controlled trials and how this affect the validity and applicability of the SOFA score as a surrogate endpoint for predicting mortality has been a matter of interest. To address this, a secondary analysis of a systematic review was conducted to quantify the relationship between SOFA scores and the prediction of mortality in critically ill adults in randomized controlled trials (RCTs). The systematic review being referred to included 87 RCTs with a total of 12,064 critically ill patients. This analysis focused on missing SOFA score data in relation to the length of stay on the intensive care unit (ICU) and the methods used to handle missing data. SOFA score measurements from the included studies were categorized into three time frames: Early (t ≤ 4 days), Intermediate (t = 5-10 days) and Late (t > 10 days) measurement. Only one study reported a complete data set for calculating the SOFA score for an Early measurement. When considering all methods used to address missing data, 32% of studies still had missing data for Early measurements, and this percentage increased to 64% for Late measurements. These findings suggested that, over time, the number of studies with incomplete data sets has been increasing. The longer a patient is treated on the ICU, the higher the number of missing data which can impact the validity of SOFA score analyses. There was no clear trend towards a specific method for compensating missing data. An exemplary calculation demonstrated that ignoring missing data may lead to an underestimated variability of the treatment effect. This, in turn, could bias the interpretation of study results by policy- and clinical decision-makers. Overall, there are several limitations that need to be considered when using SOFA score as a surrogate endpoint for mortality. When employed as an outcome, the SOFA score is frequently missing and most studies do not adequately describe the amount or nature of missing data, or the methods used to handle missing data in the analysis.

Diaphragm ultrasound in patients with prolonged weaning from mechanical ventilation.

Background: Several publications have examined diaphragmatic ultrasound using two-dimensional (2D) parameters in the context of weaning from mechanical ventilation (MV) and extubation. However, the studied cohorts had rather short duration of ventilation. Examinations on patients with prolonged weaning after long-term ventilation were missing. It was the aim of this study to assess of the diaphragm and peripheral musculature of patients undergoing prolonged weaning creating a chronological sequence of ultrasonic parameters during the course of weaning. Methods: This study was carried out as a monocentric, prospective observational cross-sectional study. Patients in prolonged weaning who were transferred to a specialized weaning unit were eligible for inclusion if they were ventilated invasively by means of an endotracheal tube or tracheal cannula and if their expected treatment period was at least 5 days. Diaphragmatic function and one representative peripheral muscle were examined in 50 patients between March 2020 and April 2021. The 2D sonographic parameters of diaphragm and diaphragmatic function consisted of diaphragmatic thickness (Tdi) at the end of inspiration and expiration, the fractional thickening (FT) and the diaphragmatic excursion. Additionally, the M. quadriceps femoris was sonographically assessed at two locations. The difference of measurements between the first and the last measuring timepoint were examined using the Wilcoxon signed-rank test. For a longer chronological sequence, the Friedman's rank sum test with subsequent Wilcoxon-Nemenyi-McDonald-Thompson test for multiple comparisons was carried out. Results: Fifty patients with prolonged weaning were included. The median duration of MV before transfer to the weaning unit was 11.5 [interquartile range (IQR) 10] days. Forty-one patients could be assessed over the full course of weaning, with 38 successfully weaned. Within these 41 patients, the sonographic parameters of the diaphragm slightly increased over the course of weaning indicating an increase in thickness and mobility. Especially parameters which represented an active movement reached statistical significance, i.e., inspiratory Tdi when assessed under spontaneous breathing [begin 3.41 (0.99) vs. end 3.43 (1.31) mm; P=0.01] and diaphragmatic excursion [begin 0.7 (0.8) vs. end 0.9 (0.6) cm; P=0.01]. The presence of positive end-expiratory pressure (PEEP) and pressure support did not influence the sonographic parameters significantly. The M. quadriceps femoris, in contrast, decreased slightly but constantly over the time [lower third: begin 1.36 (0.48) vs. end 1.28 (0.36) cm; P=0.054]. Conclusions: The present study is the first one to longitudinally analyse diaphragmatic ultrasound in patients with prolonged weaning. Sonographic assessment showed that Tdi and excursion increased over the course of prolonged weaning, while the diameter of a representative peripheral muscle decreased. However, the changes are rather small, and data show a wide dispersion. To allow a potential, standardized use of diaphragm ultrasound for diagnostic decision support in prolonged weaning, further studies in this specific patient group are required.

[Digital health progress hubs-data integration beyond university hospitals]. / Die digitalen Fortschrittshubs Gesundheit ­ Gemeinsame Datennutzung über die Universitätsmedizin hinaus.

The digital health progress hubs pilot the extensibility of the concepts and solutions of the Medical Informatics Initiative to improve regional healthcare and research. The six funded projects address different diseases, areas in regional healthcare, and methods of cross-institutional data linking and use. Despite the diversity of the scenarios and regional conditions, the technical, regulatory, and organizational challenges and barriers that the progress hubs encounter in the actual implementation of the solutions are often similar. This results in some common approaches to solutions, but also in political demands that go beyond the Health Data Utilization Act, which is considered a welcome improvement by the progress hubs.In this article, we present the digital progress hubs and discuss achievements, challenges, and approaches to solutions that enable the shared use of data from university hospitals and non-academic institutions in the healthcare system and can make a sustainable contribution to improving medical care and research.

Development of a machine learning model for prediction of the duration of unassisted spontaneous breathing in patients during prolonged weaning from mechanical ventilation.

PURPOSE: Treatment of patients undergoing prolonged weaning from mechanical ventilation includes repeated spontaneous breathing trials (SBTs) without respiratory support, whose duration must be balanced critically to prevent over- and underload of respiratory musculature. This study aimed to develop a machine learning model to predict the duration of unassisted spontaneous breathing. MATERIALS AND METHODS: Structured clinical data of patients from a specialized weaning unit were used to develop (1) a classifier model to qualitatively predict an increase of duration, (2) a regressor model to quantitatively predict the precise duration of SBTs on the next day, and (3) the duration difference between the current and following day. 61 features, known to influence weaning, were included into a Histogram-based gradient boosting model. The models were trained and evaluated using separated data sets. RESULTS: 18.948 patient-days from 1018 individual patients were included. The classifier model yielded an ROC-AUC of 0.713. The regressor models displayed a mean absolute error of 2:50 h for prediction of absolute durations and 2:47 h for day-to-day difference. CONCLUSIONS: The developed machine learning model showed informed results when predicting the spontaneous breathing capacity of a patient in prolonged weaning, however lacking prognostic quality required for direct translation to clinical use.

Effects of structured protocolized physical therapy on the duration of mechanical ventilation in patients with prolonged weaning.

PURPOSE: 20% of patients with mechanical ventilation (MV) have a prolonged, complex weaning process, often experiencing a condition of ICU-acquired weakness (ICUAW), with a severe decrease in muscle function and restricted long-term prognosis. We aimed to analyze a protocolized, systematic approach of physiotherapy in prolonged weaning patients and hypothesized that the duration of weaning from MV would be shortened. METHODS: ICU patients with prolonged weaning were included before (group 1) and after (group 2) introduction of a quality control measure of a structured and protocolized physiotherapy program. Primary endpoint was the tested dynamometric handgrip strength and the Surgical Intensive Care Unit Optimal Mobilization Score (SOMS). Secondary endpoints were weaning success rate, ventilator-free days, hospital mortality, the prevalence of ICUAW, infections and delirium. RESULTS: 106 patients were included. Both the SOMS and the handgrip test were significantly improved after introducing the program. Despite no differences in weaning success rates at discharge, the total length of MV was significantly shorter in group 2, which also had lower prevalence of infection and higher probability of survival. CONCLUSIONS: Protocolized, systematic physiotherapy resulted in an improvement of the clinical outcome in patients with prolonged weaning. Results were objectifiable with the SOMS and the handgrip test.

Insight into the mechanism of AML del(9q) progression: hnRNP K targets the myeloid master regulators CEBPA (C/EBPα) and SPI1 (PU.1).

Deletions on the long arm of chromosome 9 (del(9q)) are recurrent abnormalities in about 2 % of acute myeloid leukemia cases, which usually involve HNRNPK and are frequently associated with other known aberrations. Based on an Hnrnpk haploinsufficient mouse model, a recent study demonstrated a function of hnRNP K in pathogenesis of myeloid malignancies via the regulation of cellular proliferation and myeloid differentiation programs. Here, we provide evidence that reduced hnRNP K expression results in the dysregulated expression of C/EBPα and additional transcription factors. CyTOF analysis revealed monocytic skewing with increased levels of mature myeloid cells. To explore the role of hnRNP K during normal and pathological myeloid differentiation in humans, we characterized hnRNP K-interacting RNAs in human AML cell lines. Notably, RNA-sequencing revealed several mRNAs encoding key transcription factors involved in the regulation of myeloid differentiation as targets of hnRNP K. We showed that specific sequence motifs confer the interaction of SPI1 and CEBPA 5' and 3'UTRs with hnRNP K. The siRNA mediated reduction of hnRNP K in human AML cells resulted in an increase of PU.1 and C/EBPα that is most pronounced for the p30 isoform. The combinatorial treatment with the inducer of myeloid differentiation valproic acid resulted in increased C/EBPα expression and myeloid differentiation. Together, our results indicate that hnRNP K post-transcriptionally regulates the expression of myeloid master transcription factors. These novel findings can inaugurate novel options for targeted treatment of AML del(9q) by modulation of hnRNP K function.

Post-Mortem Extracorporeal Membrane Oxygenation Perfusion Rat Model: A Feasibility Study.

The development of biomedical soft- or hardware frequently includes testing in animals. However, large efforts have been made to reduce the number of animal experiments, according to the 3Rs principle. Simultaneously, a significant number of surplus animals are euthanized without scientific necessity. The primary aim of this study was to establish a post-mortem rat perfusion model using extracorporeal membrane oxygenation (ECMO) in surplus rat cadavers and generate first post vivo results concerning the oxygenation performance of a recently developed ECMO membrane oxygenator. Four rats were euthanized and connected post-mortem to a venous-arterial ECMO circulation for up to eight hours. Angiographic perfusion proofs, blood gas analyses and blood oxygenation calculations were performed. The mean preparation time for the ECMO system was 791 ± 29 s and sufficient organ perfusion could be maintained for 463 ± 26 min, proofed via angiographic imaging and a mean femoral arterial pressure of 43 ± 17 mmHg. A stable partial oxygen pressure, a 73% rise in arterial oxygen concentration and an exponentially increasing oxygen extraction ratio up to 4.75 times were shown. Considering the 3Rs, the established post-mortal ECMO perfusion rat model using surplus animals represents a promising alternative to models using live animals. Given the preserved organ perfusion, its use could be conceivable for various biomedical device testing.

Standardized Comparison of Voice-Based Information and Documentation Systems to Established Systems in Intensive Care: Crossover Study.

BACKGROUND: The medical teams in intensive care units (ICUs) spend increasing amounts of time at computer systems for data processing, input, and interpretation purposes. As each patient creates about 1000 data points per hour, the available information is abundant, making the interpretation difficult and time-consuming. This data flood leads to a decrease in time for evidence-based, patient-centered care. Information systems, such as patient data management systems (PDMSs), are increasingly used at ICUs. However, they often create new challenges arising from the increasing documentation burden. OBJECTIVE: New concepts, such as artificial intelligence (AI)-based assistant systems, are hence introduced to the workflow to cope with these challenges. However, there is a lack of standardized, published metrics in order to compare the various data input and management systems in the ICU setting. The objective of this study is to compare established documentation and retrieval processes with newer methods, such as PDMSs and voice information and documentation systems (VIDSs). METHODS: In this crossover study, we compare traditional, paper-based documentation systems with PDMSs and newer AI-based VIDSs in terms of performance (required time), accuracy, mental workload, and user experience in an intensive care setting. Performance is assessed on a set of 6 standardized, typical ICU tasks, ranging from documentation to medical interpretation. RESULTS: A total of 60 ICU-experienced medical professionals participated in the study. The VIDS showed a statistically significant advantage compared to the other 2 systems. The tasks were completed significantly faster with the VIDS than with the PDMS (1-tailed t59=12.48; Cohen d=1.61; P<.001) or paper documentation (t59=20.41; Cohen d=2.63; P<.001). Significantly fewer errors were made with VIDS than with the PDMS (t59=3.45; Cohen d=0.45; P=.03) and paper-based documentation (t59=11.2; Cohen d=1.45; P<.001). The analysis of the mental workload of VIDS and PDMS showed no statistically significant difference (P=.06). However, the analysis of subjective user perception showed a statistically significant perceived benefit of the VIDS compared to the PDMS (P<.001) and paper documentation (P<.001). CONCLUSIONS: The results of this study show that the VIDS reduced error rate, documentation time, and mental workload regarding the set of 6 standardized typical ICU tasks. In conclusion, this indicates that AI-based systems such as the VIDS tested in this study have the potential to reduce this workload and improve evidence-based and safe patient care.

A Potential Association between Ribonuclease 1 Dynamics in the Blood and the Outcome in COVID-19 Patients.

The COVID-19 pandemic caused by the new SARS-CoV-2 coronavirus is the most recent and well-known outbreak of a coronavirus. RNase 1 is a small endogenous antimicrobial polypeptide that possesses antiviral activity against viral diseases. In this study, we investigated a potential association between ribonuclease 1 and the outcome in COVID-19 patients and the impact of increased and decreased RNase 1 levels serum during the course of the disease. Therefore, two patient populations, Cohort A (n = 35) and B (n = 80), were subclassified into two groups, in which the RNase 1 concentration increased or decreased from time point one to time point two. We show that the RNase 1 serum levels significantly increased in the increasing group of both cohorts (p = 0.0171; p < 0.0001). We detect that patients in the increasing group who died had significantly higher RNase 1 serum levels at both time points in Cohort A (p = 0.0170; p = 0.0393) and Cohort B (p = 0.0253; p = 0.0034) than patients who survived. Additionally, we measured a significant correlation of RNase 1 serum levels with serum creatinine as well as creatinine clearance in the increasing and decreasing group at both time points of Cohort A. Based on these results, there is now good evidence that RNase 1 may play a role in renal dysfunction associated with ICU COVID-19 patients and that increasing RNase 1 serum level may be a potential biomarker to predict outcome in COVID-19 patients.

Recommendations on the structure, personal, and organization of intensive care units.

Background: Intensive care units (ICU) are central facilities of medical care in hospitals world-wide and pose a significant financial burden on the health care system. Objectives: To provide guidance and recommendations for the requirements of (infra)structure, personal, and organization of intensive care units. Design and setting: Development of recommendations based on a systematic literature search and a formal consensus process from a group of multidisciplinary and multiprofessional specialists from the German Interdisciplinary Association of Intensive Care and Emergency Medicine (DIVI). The grading of the recommendation follows the report from an American College of Chest Physicians Task Force. Results: The recommendations cover the fields of a 3-staged level of intensive care units, a 3-staged level of care with respect to severity of illness, qualitative and quantitative requirements of physicians and nurses as well as staffing with physiotherapists, pharmacists, psychologists, palliative medicine and other specialists, all adapted to the 3 levels of ICUs. Furthermore, proposals concerning the equipment and the construction of ICUs are supplied. Conclusion: This document provides a detailed framework for organizing and planning the operation and construction/renovation of ICUs.

Quality indicators in intensive care medicine for Germany - fourth edition 2022.

The measurement of quality indicators supports quality improvement initiatives. The German Interdisciplinary Society of Intensive Care Medicine (DIVI) has published quality indicators for intensive care medicine for the fourth time now. After a scheduled evaluation after three years, changes in several indicators were made. Other indicators were not changed or only minimally. The focus remained strongly on relevant treatment processes like management of analgesia and sedation, mechanical ventilation and weaning, and infections in the ICU. Another focus was communication inside the ICU. The number of 10 indicators remained the same. The development method was more structured and transparency was increased by adding new features like evidence levels or author contribution and potential conflicts of interest. These quality indicators should be used in the peer review in intensive care, a method endorsed by the DIVI. Other forms of measurement and evaluation are also reasonable, for example in quality management. This fourth edition of the quality indicators will be updated in the future to reflect the recently published recommendations on the structure of intensive care units by the DIVI.

Comparison of Drug-Related Problems in COVID-19 and Non-COVID-19 Patients Provided by a German Telepharmacy Service for Rural Intensive Care Units.

Telepharmacy is used to bridge the persisting shortage of specialist ward-based pharmacists, particularly in intensive care units (ICU). During the coronavirus disease 2019 (COVID-19), pharmacotherapy was rapidly developed, which resulted in multiple changes of guidelines. This potentially led to a differing risk for drug-related problems (DRPs) in ICUs. In this study, DRPs were detected in telepharmacy consultations of a German state-wide telemedicine network for adult patients in rural ICUs. The analysis included ICUs of ten general care hospitals with a total of 514 patients and 1056 consultations. The aim of this retrospective, observational cohort study was to compare and analyze the DRPs resulting from ICU patients with or without COVID-19. Furthermore, known risk groups for severe COVID-19 progression (organ insufficiency [kidney, liver], obesity, sex, and/or older age) were investigated with their non-COVID-19 counterparts. As a result, in both groups patients with acute renal insufficiency and without renal replacement therapy showed a significantly higher risk of being affected by one or more DRPs compared to patients with normal renal function. In COVID-19 patients, the initial recommendation of therapeutic anticoagulation (ATC-code B01AB 'Heparin group') resulted in significantly more DRPs compared to non-COVID-19 patients. Therefore, COVID-19 patients with therapeutic anticoagulation and all ICU patients with renal insufficiency should be prioritized for telepharmacy consultations.