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Background While early mobilization is commonly implemented in intensive care unit treatment guidelines to improve functional outcome, the characterization of the optimal individual dosage (frequency, level or duration) remains unclear. The aim of this study was to demonstrate that artificial intelligence-based clustering of a large ICU cohort can provide individualized mobilization recommendations that have a positive impact on the likelihood of being discharged home. Methods This study is an analysis of a prospective observational database of two interdisciplinary intensive care units in Munich, Germany. Dosage of mobilization is determined by sessions per day, mean duration, early mobilization as well as average and maximum level achieved. A k-means cluster analysis was conducted including collected parameters at ICU admission to generate clinically definable clusters. Results Between April 2017 and May 2019, 948 patients were included. Four different clusters were identified, comprising “Young Trauma,” “Severely ill & Frail,” “Old non-frail” and “Middle-aged” patients. Early mobilization (< 72 h) was the most important factor to be discharged home in “Young Trauma” patients (OR adj 10.0 [2.8 to 44.0], p  < 0.001). In the cluster of “Middle-aged” patients, the likelihood to be discharged home increased with each mobilization level, to a maximum 24-fold increased likelihood for ambulating (OR adj 24.0 [7.4 to 86.1], p  < 0.001). The likelihood increased significantly when standing or ambulating was achieved in the older, non-frail cluster (OR adj 4.7 [1.2 to 23.2], p  = 0.035 and OR adj 8.1 [1.8 to 45.8], p  = 0.010). Conclusions An artificial intelligence-based learning approach was able to divide a heterogeneous critical care cohort into four clusters, which differed significantly in their clinical characteristics and in their mobilization parameters. Depending on the cluster, different mobilization strategies supported the likelihood of being discharged home enabling an individualized and resource-optimized mobilization approach. Trial Registration : Clinical Trials NCT03666286, retrospectively registered 04 September 2018.

Seizures are a common reason for calling emergency medical services. A lack of guidelines on prehospital treatment in Germany leads to high transportation rates and reduced confidence in decision making by professionals. Our aim was to investigate the reasons for hospitalization and evaluate their necessity. A retrospective analysis of all emergency medical services records in Munich, Germany was performed in order to examine the reasons for hospitalization of patients with seizures and to evaluate their trajectory following admission to a university hospital. 8882 records were analyzed with 415 records reporting seizures (4.9%). Primary endpoint was transportation to hospital. In 380 cases (92%) patients were transported, of which 177 patients (47%) had known epilepsy; 35 patients (8%) were left at scene. Older patients and patients with higher amounts of administered medication at the scene were hospitalized significantly more often (p = 0.032 and p = 0.004, respectively). Median hospital length of stay was 1 night [IQR 1–2]. In patients with out-of-hospital seizures, high hospital transportation rates were evident, most of which could be considered as not indicated. One possible reason is the lack of guidelines in Germany, which leads to uncertainty among medical staff. This results in distress for the patients, their caregivers and consequently high costs.

Background This study aimed to assess the impact of duration of early mobilisation on survivors of critical illness. The hypothesis was that interventions lasting over 40 min, as per the German guideline, positively affect the functional status at ICU discharge. Methods Prospective single-centre cohort study conducted in two ICUs in Germany. In 684 critically ill patients surviving an ICU stay > 24 h, out-of-bed mobilisation of more than 40 min was evaluated. Results Daily mobilisation ≥ 40 min was identified as an independent predictor of an improved functional status upon ICU discharge. This effect on the primary outcome measure, change of Mobility-Barthel until ICU discharge, was observed in three different models for baseline patient characteristics (average treatment effect (ATE), all three models p  < 0.001). When mobilisation parameters like level of mobilisation, were included in the analysis, the average treatment effect disappeared [ATE 1.0 (95% CI − 0.4 to 2.4), p  = 0.16]. Conclusions A mobilisation duration of more than 40 min positively impacts functional outcomes at ICU discharge. However, the maximum level achieved during ICU stay was the most crucial factor regarding adequate dosage, as higher duration did not show an additional benefit in patients with already high mobilisation levels. Trial registration : Prospective Registry of Mobilization-, Routine- and Outcome Data of Intensive Care Patients (MOBDB), NCT03666286. Registered 11 September 2018—retrospectively registered, https://classic.clinicaltrials.gov/ct2/show/NCT03666286 .

Post-operative delirium is common in elderly patients and associated with increased morbidity and mortality. We evaluated in this pilot study whether a perioperative goal-directed hemodynamic optimization algorithm improves cerebral oxygenation and can reduce the incidence of delirium. Patients older than 70 years with high risk for post-operative delirium undergoing elective non-cardiac surgery were randomized to an intervention or control group. Patients in the intervention group received a perioperative hemodynamic optimization protocol based on uncalibrated pulse-contour analysis. Patients in the control group were managed according to usual standard of care. Incidence of delirium until day seven was assessed with confusion assessment method (CAM) and chart review. Cerebral oxygenation was measured with near-infrared spectroscopy. Delirium was present in 13 of 85 (15%) patients in the intervention group and 18 of 87 (21%) in the control group [risk difference -5.4%; 95% confidence interval, -16.8 to 6.1%; = 0.47]. Intervention did not influence length of stay in hospital or in-hospital mortality. Amounts of fluids and vasopressors applied, mean arterial pressure, cardiac index, and near-infrared spectroscopy values were comparable between groups. The hemodynamic algorithm applied in high-risk non-cardiac surgery patients did not change hemodynamic interventions, did not improve patient hemodynamics, and failed to increase cerebral oxygenation. An effect on the incidence of post-operative delirium could not be observed. [Clinicaltrials.gov], identifier [NCT01827501].

Background: Skeletal muscle mass depletion adversely affects critically ill patient outcomes. Standardized methods for assessing muscle mass in this population are limited, particularly regarding changes during ICU stays and their implications for risk stratification. Methods: In this secondary analysis of our prospective data registry of surgical ICU patients, we used a single slice extracted from a computed tomography scan to determine the patient’s direction of absolute change in skeletal muscle mass between two different time points (−14 d to +0 d and +5 d to +21 d) during his or her critical illness. Results: In total, 98 surgical patients were included in the final analysis. A decrease in a patient’s skeletal muscle mass is associated with prolonged mechanical ventilation compared to patients whose skeletal muscle mass remained the same or increased (415 vs. 42 h, p = 0.003). Patients losing skeletal muscle mass also needed to be ventilated more frequently (88.3% vs. 60.5%, p = 0.002), had a higher rate of tracheotomy (50.0% vs. 23.7%, p = 0.011), and had an increased ICU length of stay (22 vs. 13 days, p = 0.045). Conclusions: A decreased skeletal muscle index in early critical illness negatively impacts ventilation parameters, highlighting the importance of monitoring and managing muscle mass changes to optimize outcomes in ICU patients.

Background Alarm fatigue occurs when ICU personnel are exposed to an excessive number of alarms, resulting in desensitization, improper alarm management, and reduced patient safety. This study aimed to assess the extent of alarm fatigue among ICU nurses at a German university hospital using the Charité Alarm Fatigue Questionnaire (CAFQa) and to examine differences based on working hours and professional experience. Methods An observational cross-sectional study design was used. Data were collected via an online survey from nurses working in five intensive care units (ICUs) of a German university hospital between January and March 2024. The questionnaire comprised 27 items based on the Charité Alarm Fatigue Questionnaire (CAFQa). Additionally, participants rated their perceived alarm fatigue on a visual analogue scale ranging from 0 to 100%. Above that, participants were asked to provide information regarding their ICU experience and monthly workdays. Statistical significance was assessed using two-sample t-tests. Correlations between CAFQa scores and self-reported alarm fatigue were analysed using Pearson’s correlation coefficient. A p-value of < 0.05 was considered statistically significant. Results A total of 70 ICU nurses participated in the study. No significant differences in alarm fatigue were found between nurses working more than eight days per month and those working fewer days (t(56) = 1.00, p  = 0.32), and with more than one year of ICU experience and less experience, respectively (t(56) = 1.32, p  = 0.19). Complete CAFQa data were available for 59 participants. The mean CAFQa score was (17.7 ± 5.5) points out of 36 points ((49 ± 15) %), indicating moderate to high alarm fatigue. Individual scores ranged from 5 (14%) to 28 (78%). The average self-reported alarm fatigue was (47 ± 22) %. Conclusions Alarm fatigue is present among ICU nurses in moderate to high levels, but no significant differences were observed based on working hours or professional experience. Since alarm fatigue may have grave repercussions for nurses and patients, recognition and implementation of effective strategies to minimise it are crucial. Trial registration Clinical trial number: Not applicable.

Background In intensive care units (ICU) octogenarians become a routine patients group with aggravated therapeutic and diagnostic decision-making. Due to increased mortality and a reduced quality of life in this high-risk population, medical decision-making a fortiori requires an optimum of risk stratification. Recently, the VIP-1 trial prospectively observed that the clinical frailty scale (CFS) performed well in ICU patients in overall-survival and short-term outcome prediction. However, it is known that healthcare systems differ in the 21 countries contributing to the VIP-1 trial. Hence, our main focus was to investigate whether the CFS is usable for risk stratification in octogenarians admitted to diversified and high tech German ICUs. Methods This multicentre prospective cohort study analyses very old patients admitted to 20 German ICUs as a sub-analysis of the VIP-1 trial. Three hundred and eight patients of 80 years of age or older admitted consecutively to participating ICUs. CFS, cause of admission, APACHE II, SAPS II and SOFA scores, use of ICU resources and ICU- and 30-day mortality were recorded. Multivariate logistic regression analysis was used to identify factors associated with 30-day mortality. Results Patients had a median age of 84 [IQR 82–87] years and a mean CFS of 4.75 (± 1.6 standard-deviation) points. More than half of the patients (53.6%) were classified as frail (CFS ≥ 5). ICU-mortality was 17.3% and 30-day mortality was 31.2%. The cause of admission (planned vs. unplanned), (OR 5.74) and the CFS (OR 1.44 per point increase) were independent predictors of 30-day survival. Conclusions The CFS is an easy determinable valuable tool for prediction of 30-day ICU survival in octogenarians, thus, it may facilitate decision-making for intensive care givers in Germany. Trial registration The VIP-1 study was retrospectively registered on ClinicalTrials.gov (ID: NCT03134807 ) on May 1, 2017.

The Charité Alarm Fatigue Questionnaire (CAFQa) is a 9-item questionnaire that aims to standardize how alarm fatigue in nurses and physicians is measured. We previously hypothesized that it has 2 correlated scales, one on the psychosomatic effects of alarm fatigue and the other on staff's coping strategies in working with alarms. We aimed to validate the hypothesized structure of the CAFQa and thus underpin the instrument's construct validity. We conducted 2 independent studies with nurses and physicians from intensive care units in Germany (study 1: n=265; study 2: n=1212). Responses to the questionnaire were analyzed using confirmatory factor analysis with the unweighted least-squares algorithm based on polychoric covariances. Convergent validity was assessed by participants' estimation of their own alarm fatigue and exposure to false alarms as a percentage. In both studies, the χ2 test reached statistical significance (study 1: χ226=44.9; P=.01; study 2: χ226=92.4; P<.001). Other fit indices suggested a good model fit (in both studies: root mean square error of approximation <0.05, standardized root mean squared residual <0.08, relative noncentrality index >0.95, Tucker-Lewis index >0.95, and comparative fit index >0.995). Participants' mean scores correlated moderately with self-reported alarm fatigue (study 1: r=0.45; study 2: r=0.53) and weakly with self-perceived exposure to false alarms (study 1: r=0.3; study 2: r=0.33). The questionnaire measures the construct of alarm fatigue as proposed in our previous study. Researchers and clinicians can rely on the CAFQa to measure the alarm fatigue of nurses and physicians.

Background Hypalbuminemia is associated with numerous postoperative complications, so a perioperative albumin substitution is often considered. The objective of SuperAdd is to investigate whether substitution of human albumin, aiming to maintain a serum concentration > 30 g/l, can reduce postoperative complications in normovolemic surgical patients in comparison with standard care. Methods/design SuperAdd is a single-center, prospective, randomized, outcome-assessor blinded, patient blinded controlled trial. The primary outcome is the frequency of postoperative complications identified using the Postoperative Morbidity Survey graded ≥ 2 according to the Clavien-Dindo Score. Adult patients at risk to develop hypalbuminemia, i.e., ASA III or IV or high-risk surgery, are recruited after written informed consent was obtained. The albumin concentration is assessed before the induction of anesthesia and every 3 h until admission to the postanesthesia care unit. If albumin concentrations drop below 30 g/l, patients are randomly allocated to the control or the treatment group. The study intervention is a goal-directed human albumin substitution aimed at a concentration > 30 g/l during surgery and postanesthesia care unit stay. The patients in the control group are treated according to standard clinical care. Postoperative visits are to be performed on days 1, 3, 5, 8, and 15, as well as by telephone 6 months after surgery. Discussion SuperAdd is the first clinical trial in a surgical population investigating the effect of a goal-directed albumin substitution aiming at a serum level > 30 g/l. The nonrestrictive selection of patients guarantees that the patients without albumin screening will most likely not develop hypalbuminemia, thus ensuring generalizability of the study results. Trial registration EudraCT 2016-001313-24. Registered on 5 September 2016. Clinical Trials NCT03167645. Registered on 18 October 2016 and has the Universal Trial Number (UTN) U1111-1181-2625.

PurposePremorbid conditions affect prognosis of acutely-ill aged patients. Several lines of evidence suggest geriatric syndromes need to be assessed but little is known on their relative effect on the 30-day survival after ICU admission. The primary aim of this study was to describe the prevalence of frailty, cognition decline and activity of daily life in addition to the presence of comorbidity and polypharmacy and to assess their influence on 30-day survival.MethodsProspective cohort study with 242 ICUs from 22 countries. Patients 80 years or above acutely admitted over a six months period to an ICU between May 2018 and May 2019 were included. In addition to common patients’ characteristics and disease severity, we collected information on specific geriatric syndromes as potential predictive factors for 30-day survival, frailty (Clinical Frailty scale) with a CFS > 4 defining frail patients, cognitive impairment (informant questionnaire on cognitive decline in the elderly (IQCODE) with IQCODE ≥ 3.5 defining cognitive decline, and disability (measured the activity of daily life with the Katz index) with ADL ≤ 4 defining disability. A Principal Component Analysis to identify co-linearity between geriatric syndromes was performed and from this a multivariable model was built with all geriatric information or only one: CFS, IQCODE or ADL. Akaike’s information criterion across imputations was used to evaluate the goodness of fit of our models.ResultsWe included 3920 patients with a median age of 84 years (IQR: 81–87), 53.3% males). 80% received at least one organ support. The median ICU length of stay was 3.88 days (IQR: 1.83–8). The ICU and 30-day survival were 72.5% and 61.2% respectively. The geriatric conditions were median (IQR): CFS: 4 (3–6); IQCODE: 3.19 (3–3.69); ADL: 6 (4–6); Comorbidity and Polypharmacy score (CPS): 10 (7–14). CFS, ADL and IQCODE were closely correlated. The multivariable analysis identified predictors of 1-month mortality (HR; 95% CI): Age (per 1 year increase): 1.02 (1.–1.03, p = 0.01), ICU admission diagnosis, sequential organ failure assessment score (SOFA) (per point): 1.15 (1.14–1.17, p < 0.0001) and CFS (per point): 1.1 (1.05–1.15, p < 0.001). CFS remained an independent factor after inclusion of life-sustaining treatment limitation in the model.ConclusionWe confirm that frailty assessment using the CFS is able to predict short-term mortality in elderly patients admitted to ICU. Other geriatric syndromes do not add improvement to the prediction model. Since CFS is easy to measure, it should be routinely collected for all elderly ICU patients in particular in connection to advance care plans, and should be used in decision making.