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Background: Postoperative delirium (POD) is the most common neurological adverse event among elderly patients undergoing surgery. POD is associated with an increased risk for postoperative complications, long-term cognitive decline, an increase in morbidity and mortality as well as extended hospital stays. Delirium prevention and treatment options are currently limited. This study will evaluate the effect of transcranial electrical stimulation (tES) on the incidence of POD. Methods: We will perform a randomized, double-blind, sham-controlled trial using single-session postoperative application of tES in the recovery room in 225 patients (> 65 years) undergoing elective major surgery. Patients will be randomly allocated (ratio 1:1:1) to one of three study groups: (1) alpha-tACS over posterior parietal cortex [2 mA, 20 min], (2) anodal tDCS over left dorsolateral prefrontal cortex [2 mA, 20 min], (3) sham [2 mA, 30 s]. Delirium will be screened twice daily with the 3-min diagnostic interview Confusion Assessment Method (3D-CAM) in the 5 days following surgery. The primary outcome is the incidence of POD defined as at least one positive screening during the five first postoperative days compared between tACS and sham groups. Secondary outcomes include delirium severity, duration, phenotype, postoperative pain, postoperative nausea and vomiting, electroencephalographic (EEG) markers, and fluid biomarkers. Discussion: If effective, tES is a novel, easily applicable, non-invasive method to prevent the occurrence of POD. The comprehensive neurophysiological and biofluid assessments for markers of (neuro-)inflammation and neurodegeneration will shed light on the pathomechanisms behind POD and further elucidate the (after-)effects of tES. The potential implications for the postoperative recovery comprise enhanced patient safety, neurocognitive outcome, perioperative manageability but also reduced healthcare costs. Trial registration: German Clinical Trial Registry DRKS00033703. Registered on February 23, 2024. [ABSTRACT FROM AUTHOR]

Background: Measuring pain intensity in patients unable to communicate is a challenge on general wards. Observation‐based pain scoring tools have been used for patients with dementia or in critically ill intensive care unit (ICU) patients. However, there is no established or validated assessment tool for non‐ICU patients without dementia related cognitive deficiencies who cannot communicate. The "Behavioural Pain Scale Non‐Intubated" (BPS‐NI) and the "Pain Assessment In Advanced Dementia‐German" (PAINAD‐G) are potential tools to fill this gap. Methods: This study was performed with verbal non‐ICU patients on general wards at Charité Berlin. Two assessors independently rated pain intensity using the BPS‐NI and the PAINAD‐G along with patients' self‐ratings on the Numeric Rating Scale (NRS). The interrater‐reliability of BPS‐NI and PAINAD‐G was calculated and ROC‐analyses were performed to identify cut‐off values for medium and intense pain for each score. Effectiveness was calculated using percentage agreement. In total, 126 patients were included into analysis. Results: The BPS‐NI showed substantial congruence in interrater‐reliability (Cohens‐Kappa 0.71), whereas the PAINAD‐G showed moderate congruence (Kappa 0.48). Based on ROC‐analyses, for medium pain levels a cut‐off 4 (BPS‐NI) or 2 (PAINAD‐G) and for severe pain levels cut‐off 5 (BPS‐NI) and 3 (PAINAD‐G) would result in good accordance with self‐reported NRS for pain. Conclusion: The BPS‐NI shows a good validity in measuring pain intensity in patients on general wards and may possibly be used for patients unable to communicate. Using defined cut‐off values for BPS‐NI and PAINAD‐G, clinically relevant pain intensities in patients can reliably be detected. Significance: Measuring the pain intensity in patients unable to communicate is a common challenge on general wards. This study assessed reliability and applicability BPS‐NI and the PAINAD‐G in a general ward setting. Furthermore, it provides cut‐off values in order to estimate pain intensity and support analgesic response. [ABSTRACT FROM AUTHOR]

Background: Clinical practice guidelines are systematically developed statements intended to optimize patient care. However, a gapless implementation of guideline recommendations requires health care personnel not only to be aware of the recommendations and to support their content but also to recognize every situation in which they are applicable. To not miss situations in which recommendations should be applied, computerized clinical decision support can be provided through a system that allows an automated monitoring of adherence to clinical guideline recommendations in individual patients. Objective: This study aims to collect and analyze the requirements for a system that allows the monitoring of adherence to evidence-based clinical guideline recommendations in individual patients and, based on these requirements, to design and implement a software prototype that integrates guideline recommendations with individual patient data, and to demonstrate the prototype's utility in treatment recommendations. Methods: We performed a work process analysis with experienced intensive care clinicians to develop a conceptual model of how to support guideline adherence monitoring in clinical routine and identified which steps in the model could be supported electronically. We then identified the core requirements of a software system to support recommendation adherence monitoring in a consensus-based requirements analysis within the loosely structured focus group work of key stakeholders (clinicians, guideline developers, health data engineers, and software developers). On the basis of these requirements, we designed and implemented a modular system architecture. To demonstrate its utility, we applied the prototype to monitor adherence to a COVID-19 treatment recommendation using clinical data from a large European university hospital. Results: We designed a system that integrates guideline recommendations with real-time clinical data to evaluate individual guideline recommendation adherence and developed a functional prototype. The needs analysis with clinical staff resulted in a flowchart describing the work process of how adherence to recommendations should be monitored. Four core requirements were identified: the ability to decide whether a recommendation is applicable and implemented for a specific patient, the ability to integrate clinical data from different data formats and data structures, the ability to display raw patient data, and the use of a Fast Healthcare Interoperability Resources–based format for the representation of clinical practice guidelines to provide an interoperable, standards-based guideline recommendation exchange format. Conclusions: Our system has advantages in terms of individual patient treatment and quality management in hospitals. However, further studies are needed to measure its impact on patient outcomes and evaluate its resource effectiveness in different clinical settings. We specified a modular software architecture that allows experts from different fields to work independently and focus on their area of expertise. We have released the source code of our system under an open-source license and invite for collaborative further development of the system. [ABSTRACT FROM AUTHOR]

Introduction: The term "usability" describes how effectively, efficiently, and with what level of user satisfaction an information system can be used to accomplish specific goals. Computerized critical care information systems (CCISs) with high usability increase quality of care and staff satisfaction, while reducing medication errors. Conversely, systems lacking usability can interrupt clinical workflow, facilitate errors, and increase charting time. The aim of this study was to investigate and compare usability across CCIS currently used in Germany. Methods: In this study, German intensive care unit (ICU) nurses and physicians completed a specialized, previously validated, web-based questionnaire. The questionnaire assessed CCIS usability based on three rating models: an overall rating of the systems, a model rating technical usability, and a model rating task-specific usability. Results: We analyzed results from 535 survey participants and compared eight different CCIS commonly used in Germany. Our results showed that usability strongly differs across the compared systems. The system ICUData had the best overall rating and technical usability, followed by the platforms ICM and MetaVision. The same three systems performed best in the rating of task-specific usability without significant differences between each other. Across all systems, overall ratings were more dependent on ease-of-use aspects than on aspects of utility/functionality, and the general scope of the functions offered was rated better than how well the functions are realized. Discussion: Our results suggest that manufacturers should shift some of their effort away from the development of new features and focus more on improving the ease-of-use and quality of existing features. [ABSTRACT FROM AUTHOR]