Avatar and distance simulation as a learning tool - virtual simulation technology as a facilitator or barrier? A questionnaire-based study on behalf of Netzwerk Kindersimulation e.V.

Background Virtual simulation modalities have been implemented widely since the onset of the severe acute respiratory syndrome coronavirus 2 pandemic restrictions in March 2020, as educators face persistent restrictions to face-to-face education of medical students and healthcare professionals.There is paucity of published data regarding the benefits and barriers of distance and avatar simulation training modalities. Methods Following a 2-day virtual pediatric simulation competition facilitated by Netzwerk Kindersimulation e.V., using remote human avatars and distance simulation, we conducted a multicenter survey to explore the advantages and challenges of avatar and distance simulation among participants. We used a modified Delphi approach to draft and develop the 32-item online questionnaire with 7-point Likert-like scales (7 being the highest rating). Results Twenty participants answered our questionnaire. Respondents indicated both a high overall satisfaction (median of 5.0 [Q25-Q75: 4.0-6.0] ) for avatar and distance simulation 6.0 (5.0-6.0), respectively, as well as a high achieved psychological safety with both simulation types (5.0 [4.0-6.0] vs. 5.0 [4.0-6.0]). The most frequently reported profits of avatar and distance simulation included the elimination of travel distances, associated lower costs, less time spent attending the education activity, and effective communication and leadership training, especially with avatar simulation. Most often named challenges were technical problems, limited reception of non-verbal cues and a spatial distance from the team/educator. Discussion Based on the results of this pilot study, avatar and distance simulation can be employed successfully and appear to be good supplements to face-to-face simulation. Other studies are warranted to further explore the effectiveness of various types of virtual simulation compared to conventional presential simulation. We suggest using avatar-based simulation for targeted communication and leadership skills training and the application of distance simulation to bring simulation experts virtually to remote places where educator resources are lacking

A first assessment of the safe brain initiative care bundle for addressing postoperative delirium in the postanesthesia care unit.

BACKGROUND Postoperative delirium (POD) following surgery is a prevalent and distressing condition associated with adverse patient outcomes and an increased healthcare burden. OBJECTIVES To assess the effectiveness of the Safe Brain Initiative care bundle (SBI-CB) in reducing POD in the postanesthesia care unit (PACU). DESIGN A multicenter, quality-improvement initiative with retrospective analysis of collected data. SETTING The study was conducted in the operating rooms and postanesthesia care units (PACUs) of four hospitals across Denmark and Turkey. PATIENTS The convenience sample of patients were aged ≥18 years, scheduled for surgery, and could communicate verbally. Age, sex, preoperative delirium, and the American Society for Anesthesiology physical status classification were used in statistical methods to control for potential confounding influences. INTERVENTION The SBI-CB, 18 delirium-reducing recommendations aligned with international guidelines. The intervention included patient education, staff training, coordination meetings across centers, and a dashboard for the monitoring of outcomes in the PACU. MAIN OUTCOME MEASURES The primary outcome was the POD trend in the PACU during implementation months, assessed through Nu-DESC screening at up to three time points in the PACU. We also examined the length of hospital stay. RESULTS Data were collected from 18,697 adult patients across four hospitals. Initial POD incidence in the PACU after the first three months was 16.36% across all sites (n = 1021). POD in the PACU was observed across all age groups, with peak incidence in younger (18-35 years) and older (>75 years) patients. General anesthesia and longer surgical duration (>1 h) were identified as significant risk factors for POD in the PACU. Matched patients who experienced POD in the PACU had longer stays in hospital, with a mean increase from 35 to 69 h (p < 0.001). Implementation of the SBI-CB was associated with a decreased risk of POD in the PACU for each month of SBI-CB implementation (adjusted odds ratio 0.96, 95% confidence interval: [0.94, 0.97], p < 0.001). CONCLUSIONS The presented pragmatic implementation of a multidisciplinary care bundle, encompassing pre-, intra-, and postoperative measures alongside outcome monitoring, has the potential to significantly reduce the incidence of POD in the PACU. Improved patient outcomes may be achieved for general surgical departments with patient cohorts not typically considered at risk for developing POD. TRIAL REGISTRATION Clinicaltrials.gov, identifier NCT05765162

Hyperoxemia and excess oxygen use in early acute respiratory distress syndrome : Insights from the LUNG SAFE study

Publisher Copyright: © 2020 The Author(s). Copyright: Copyright 2020 Elsevier B.V., All rights reserved.Background: Concerns exist regarding the prevalence and impact of unnecessary oxygen use in patients with acute respiratory distress syndrome (ARDS). We examined this issue in patients with ARDS enrolled in the Large observational study to UNderstand the Global impact of Severe Acute respiratory FailurE (LUNG SAFE) study. Methods: In this secondary analysis of the LUNG SAFE study, we wished to determine the prevalence and the outcomes associated with hyperoxemia on day 1, sustained hyperoxemia, and excessive oxygen use in patients with early ARDS. Patients who fulfilled criteria of ARDS on day 1 and day 2 of acute hypoxemic respiratory failure were categorized based on the presence of hyperoxemia (PaO2 > 100 mmHg) on day 1, sustained (i.e., present on day 1 and day 2) hyperoxemia, or excessive oxygen use (FIO2 ≥ 0.60 during hyperoxemia). Results: Of 2005 patients that met the inclusion criteria, 131 (6.5%) were hypoxemic (PaO2 < 55 mmHg), 607 (30%) had hyperoxemia on day 1, and 250 (12%) had sustained hyperoxemia. Excess FIO2 use occurred in 400 (66%) out of 607 patients with hyperoxemia. Excess FIO2 use decreased from day 1 to day 2 of ARDS, with most hyperoxemic patients on day 2 receiving relatively low FIO2. Multivariate analyses found no independent relationship between day 1 hyperoxemia, sustained hyperoxemia, or excess FIO2 use and adverse clinical outcomes. Mortality was 42% in patients with excess FIO2 use, compared to 39% in a propensity-matched sample of normoxemic (PaO2 55-100 mmHg) patients (P = 0.47). Conclusions: Hyperoxemia and excess oxygen use are both prevalent in early ARDS but are most often non-sustained. No relationship was found between hyperoxemia or excessive oxygen use and patient outcome in this cohort. Trial registration: LUNG-SAFE is registered with ClinicalTrials.gov, NCT02010073publishersversionPeer reviewe

Patient-centered precision care in anaesthesia - the PC-square (PC)2 approach.

PURPOSE OF REVIEW This review navigates the landscape of precision anaesthesia, emphasising tailored and individualized approaches to anaesthetic administration. The aim is to elucidate precision medicine principles, applications, and potential advancements in anaesthesia. The review focuses on the current state, challenges, and transformative opportunities in precision anaesthesia. RECENT FINDINGS The review explores evidence supporting precision anaesthesia, drawing insights from neuroscientific fields. It probes the correlation between high-dose intraoperative opioids and increased postoperative consumption, highlighting how precision anaesthesia, especially through initiatives like Safe Brain Initiative (SBI), could address these issues. The SBI represents multidisciplinary collaboration in perioperative care. SBI fosters effective communication among surgical teams, anaesthesiologists, and other medical professionals. SUMMARY Precision anaesthesia tailors care to individual patients, incorporating genomic insights, personalised drug regimens, and advanced monitoring techniques. From EEG to cerebral/somatic oximetry, these methods enhance precision. Standardised reporting, patient-reported outcomes, and continuous quality improvement, alongside initiatives like SBI, contribute to improved patient outcomes. Precision anaesthesia, underpinned by collaborative programs, emerges as a promising avenue for enhancing perioperative care

The way towards ethical anesthesia care: no aim - no game - no fame or blame?

PURPOSE OF REVIEW This review explores the intricacies of ethical anesthesia, exploring the necessity for precision anesthesia and its impact on patient-reported outcomes. The primary objective is to advocate for a defined aim, promoting the implementation of rules and feedback systems. The ultimate goal is to enhance precision anesthesia care, ensuring patient safety through the implementation of a teamwork and the integration of feedback mechanisms. RECENT FINDINGS Recent strategies in the field of anesthesia have evolved from intraoperative monitorization to a wider perioperative patient-centered precision care. Nonetheless, implementing this approach encounters significant obstacles. The article explores the evidence supporting the need for a defined aim and applicable rules for precision anesthesia's effectiveness. The implementation of the safety culture is underlined. The review delves into the teamwork description with structured feedback systems. SUMMARY Anesthesia is a multifaceted discipline that involves various stakeholders. The primary focus is delivering personalized precision care. This review underscores the importance of establishing clear aims, defined rules, and fostering effective and well tolerated teamwork with accurate feedback for improving patient-reported outcomes. The Safe Brain Initiative approach, emphasizing algorithmic monitoring and systematic follow-up, is crucial in implementing a fundamental and standardized reporting approach within patient-centered anesthesia care practice

Immunocompromised patients with acute respiratory distress syndrome: Secondary analysis of the LUNG SAFE database

Background: The aim of this study was to describe data on epidemiology, ventilatory management, and outcome of acute respiratory distress syndrome (ARDS) in immunocompromised patients. Methods: We performed a post hoc analysis on the cohort of immunocompromised patients enrolled in the Large Observational Study to Understand the Global Impact of Severe Acute Respiratory Failure (LUNG SAFE) study. The LUNG SAFE study was an international, prospective study including hypoxemic patients in 459 ICUs from 50 countries across 5 continents. Results: Of 2813 patients with ARDS, 584 (20.8%) were immunocompromised, 38.9% of whom had an unspecified cause. Pneumonia, nonpulmonary sepsis, and noncardiogenic shock were their most common risk factors for ARDS. Hospital mortality was higher in immunocompromised than in immunocompetent patients (52.4% vs 36.2%; p &lt; 0.0001), despite similar severity of ARDS. Decisions regarding limiting life-sustaining measures were significantly more frequent in immunocompromised patients (27.1% vs 18.6%; p &lt; 0.0001). Use of noninvasive ventilation (NIV) as first-line treatment was higher in immunocompromised patients (20.9% vs 15.9%; p = 0.0048), and immunodeficiency remained independently associated with the use of NIV after adjustment for confounders. Forty-eight percent of the patients treated with NIV were intubated, and their mortality was not different from that of the patients invasively ventilated ab initio. Conclusions: Immunosuppression is frequent in patients with ARDS, and infections are the main risk factors for ARDS in these immunocompromised patients. Their management differs from that of immunocompetent patients, particularly the greater use of NIV as first-line ventilation strategy. Compared with immunocompetent subjects, they have higher mortality regardless of ARDS severity as well as a higher frequency of limitation of life-sustaining measures. Nonetheless, nearly half of these patients survive to hospital discharge. Trial registration: ClinicalTrials.gov, NCT02010073. Registered on 12 December 2013

Validation and utility of ARDS subphenotypes identified by machine-learning models using clinical data: an observational, multicohort, retrospective analysis

International audienceTwo acute respiratory distress syndrome (ARDS) subphenotypes (hyperinflammatory and hypoinflammatory) with distinct clinical and biological features and differential treatment responses have been identified using latent class analysis (LCA) in seven individual cohorts. To facilitate bedside identification of subphenotypes, clinical classifier models using readily available clinical variables have been described in four randomised controlled trials. We aimed to assess the performance of these models in observational cohorts of ARDS. Methods: In this observational, multicohort, retrospective study, we validated two machine-learning clinical classifier models for assigning ARDS subphenotypes in two observational cohorts of patients with ARDS: Early Assessment of Renal and Lung Injury (EARLI; n=335) and Validating Acute Lung Injury Markers for Diagnosis (VALID; n=452), with LCA-derived subphenotypes as the gold standard. The primary model comprised only vital signs and laboratory variables, and the secondary model comprised all predictors in the primary model, with the addition of ventilatory variables and demographics. Model performance was assessed by calculating the area under the receiver operating characteristic curve (AUC) and calibration plots, and assigning subphenotypes using a probability cutoff value of 0·5 to determine sensitivity, specificity, and accuracy of the assignments. We also assessed the performance of the primary model in EARLI using data automatically extracted from an electronic health record (EHR; EHR-derived EARLI cohort). In Large Observational Study to Understand the Global Impact of Severe Acute Respiratory Failure (LUNG SAFE; n=2813), a multinational, observational ARDS cohort, we applied a custom classifier model (with fewer variables than the primary model) to determine the prognostic value of the subphenotypes and tested their interaction with the positive end-expiratory pressure (PEEP) strategy, with 90-day mortality as the dependent variable. Findings: The primary clinical classifier model had an area under receiver operating characteristic curve (AUC) of 0·92 (95% CI 0·90–0·95) in EARLI and 0·88 (0·84–0·91) in VALID. Performance of the primary model was similar when using exclusively EHR-derived predictors compared with manually curated predictors (AUC=0·88 [95% CI 0·81–0·94] vs 0·92 [0·88–0·97]). In LUNG SAFE, 90-day mortality was higher in patients assigned the hyperinflammatory subphenotype than in those with the hypoinflammatory phenotype (414 [57%] of 725 vs 694 [33%] of 2088; p<0·0001). There was a significant treatment interaction with PEEP strategy and ARDS subphenotype (p=0·041), with lower 90-day mortality in the high PEEP group of patients with the hyperinflammatory subphenotype (hyperinflammatory subphenotype: 169 [54%] of 313 patients in the high PEEP group vs 127 [62%] of 205 patients in the low PEEP group; hypoinflammatory subphenotype: 231 [34%] of 675 patients in the high PEEP group vs 233 [32%] of 734 patients in the low PEEP group). Interpretation: Classifier models using clinical variables alone can accurately assign ARDS subphenotypes in observational cohorts. Application of these models can provide valuable prognostic information and could inform management strategies for personalised treatment, including application of PEEP, once prospectively validated. Funding: US National Institutes of Health and European Society of Intensive Care Medicine