Sedation with inhaled sevoflurane in the intensive care unit.

INTRODUCTION: Critically ill patients often develop the Post-Intensive Care Syndrome (PICS). Current sedation guidelines mainly rely on intravenous agents. Inhaled sedatives are a promising alternative with favorable pharmacokinetics and potential benefits in critical care settings. However, their application in Latin America remains unexplored. METHODS: Case-series study that included adult ICU patients who underwent deep sedation with sevoflurane using the SEDANA anesthetic conserving device. Data on demographics, sedation protocols, adverse events, and outcomes were collected. Statistical analysis assessed changes over time in laboratory parameters. RESULTS: Eleven patients were included, with sevoflurane administered via artificial airways. Inhaled sedation led to the successful cease of intravenous sedatives in 10 of 11 patients, and reduction of at least 30% in opioid dose. No significant adverse effects were observed. Barriers to adherence included device-related issues and challenges in healthcare staff training. CONCLUSION: Sevoflurane effectively achieved sedation goals in ICU patients, reducing the need for additional sedatives and opioids. Our findings support the safety and efficacy of inhaled sedatives in ICU settings and highlight the importance of further research in this area. Longer-term studies are needed to fully determine the impact of inhaled sedatives in ICU patients.

Introducción: Los pacientes críticamente enfermos a menudo desarrollan el Síndrome Post-Cuidados Intensivos (PICS). Las pautas actuales de sedación se basan principalmente en agentes intravenosos. Los sedantes inhalados son una alternativa prometedora con farmacocinética favorable y beneficios potenciales en entornos de cuidados críticos. Sin embargo, su aplicación en América Latina sigue sin explorarse. Métodos: Estudio de serie de casos que incluyó a pacientes adultos de UCI que recibieron sedación profunda con sevoflurano utilizando el dispositivo conservador anestésico SEDANA. Se recopilaron datos demográficos, protocolos de sedación, eventos adversos y resultados. El análisis estadístico evaluó los cambios en el tiempo en los parámetros de laboratorio. Resultados: Se incluyeron once pacientes, a quienes se les administró sevoflurano a través de vías respiratorias artificiales. Se incluyeron once pacientes, a quienes se les administró sevoflurano a través de vías respiratorias artificiales. La sedación inhalada llevó a la cesación exitosa de sedantes intravenosos en 10 de los 11 pacientes, con una reducción de al menos 30% la dosis de opioides. No se observaron efectos adversos significativos. Las barreras para la adherencia incluyeron problemas relacionados con el dispositivo y desafíos en la capacitación del personal de salud. Conclusión: El sevoflurano logró de manera efectiva los objetivos de sedación en pacientes de UCI, reduciendo la necesidad de sedantes y opioides adicionales. Nuestros hallazgos respaldan la seguridad y eficacia de los sedantes inhalados en entornos de UCI y resaltan la importancia de una mayor investigación en esta área. Se necesitan estudios a más largo plazo para determinar completamente el impacto de los sedantes inhalados en pacientes de UCI.

[Positioning therapy for intensive care patients]. / Lagerungstherapie bei Intensivpatienten.

The current S3 guideline, "Positioning Therapy and Mobilization of Critically Ill Patients in Intensive Care Units", introduces methodological changes and substantive updates compared to the previous version. Additionally, new evidence-based insights with specified PICO questions have been integrated, aiming for a more precise application of recommendations in clinical practice and thus enhancing the care of critically ill patients.A notable aspect is the more nuanced approach to early mobilization, which is recommended to commence within the first 72 hours of ICU admission. A staged concept and score-based mobilization schema facilitate improved patient rehabilitation. Mobilization should be standard of care, i.e., immobilization should be ordered by the physician. The guideline provides suggestions for the duration and additional mobilization measures to ensure patients stand, transfer actively from bed to chair, or walk as frequently as possible. These recommendations apply even during ECMO therapy, highlighting the importance of early mobilization.Further updates include semi-recumbent positions of at least 40° in intubated patients, with careful consideration of potential side effects. Continuous lateral rotation therapy (CLRT) is not advised due to the progress in intensive care therapy, shifting from deep sedation toward responsive patient management.Prone positioning (PP) involves rotating the patient 180° onto the ventral side. It is recommended as a therapeutic option for invasively ventilated patients with ARDS and impaired arterial oxygenation (PaO2/FiO2 <150mmHg), with a recommended minimum duration of 12 hours, ideally 16 hours. Special recommendations apply, for example, to COVID-19 patients with acute hypoxemic respiratory failure, where awake proning should be considered.Additionally, new chapters have been introduced focusing on assistive devices and neuromuscular electrical stimulation.

Key Research Areas for Building and Deploying a Common Data Model for an Intensive Medicine Data Space in Europe and Beyond.

Key Research Areas (KRAs) were identified to establish a semantic interoperability framework for intensive medicine data in Europe. These include assessing common data model value, ensuring smooth data interoperability, supporting data standardization for efficient dataset use, and defining anonymization requirements to balance data protection and innovation.

How to Accurately Detect Renal Replacement Therapy Weaning in Intensive Care: Data Quality and Standardization Considerations for the OMOP Common Data Model.

This study assesses the effectiveness of the Observational Medical Outcomes Partnership common data model (OMOP CDM) in standardising Continuous Renal Replacement Therapy (CRRT) data from intensive care units (ICU) of two French university hospitals. Our objective was to extract and standardise data from various sources, enabling the development of predictive models for CRRT weaning that are agnostic to the data's origin. Data for 1,696 ICU stays from the two data sources were extracted, transformed, and loaded into the OMOP format after semantic alignment of 46 CRRT standard concepts. Although the OMOP CDM demonstrated potential in harmonising CRRT data, we encountered challenges related to data variability and the lack of standard concepts. Despite these challenges, our study supports the promise of the OMOP CDM for ICU data standardization, suggesting that further refinement and adaptation could significantly improve clinical decision making and patient outcomes in critical care settings.

Intensive Care Quality Indicators Dashboard Using Observational Medical Outcomes Partnership Common Data Model.

This paper presents the development of a visualization dashboard for quality indicators in intensive care units (ICUs), using the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM). The dashboard enables the user to visualize quality indicator data using histograms, pie charts and tables. Our project uses the OMOP CDM, ensuring a seamless implementation of our dashboard across various hospitals. Future directions for our research include expanding the dashboard to incorporate additional quality indicators and evaluating clinicians' feedback on its effectiveness.

User Experience Design for Intensive Care Alarm Management.

Alarm fatigue is a pressing issue in intensive care units. Based on user experience design, including clinical shadowings and feedback loops, we developed a prototype for a redesigned patient monitor: The prototype moves away from today's threshold-based alarm systems. It combines a sleek design with machine learning driven clinical insights to mitigate alarm fatigue.

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.

Linking Dutch Intensive Care Registry Data to Socioeconomic Status Scores.

This study aimed to gain insight into the success rate of linking the NICE registry with SES data from CBS and to examine whether the characteristics of linked and non-linked patients differ. Although clinically relevant differences were found, in total 93,4% of the admissions were successfully linked.

A Comparative Analysis of Federated and Centralized Learning for SpO2 Prediction in Five Critical Care Databases.

This study explores the potential of federated learning (FL) to develop a predictive model of hypoxemia in intensive care unit (ICU) patients. Centralized learning (CL) and local learning (LL) approaches have been limited by the localized nature of data, which restricts CL approaches to the available data due to data privacy regulations. A CL approach that combines data from different institutions, could offer superior performance compared to a single-institution approach. However, the use of this method raises ethical and regulatory concerns. In this context, FL presents a promising middle ground, enabling collaborative model training on geographically dispersed ICU data without compromising patient confidentiality. This study is the first to use all five public ICU databases combined. The findings demonstrate that FL achieved comparable or even slightly improved performance compared to local or centralized learning approaches.

Optimizing ICU Care: Machine Learning and PCA for Early Prediction of Renal Replacement Therapy Requirement.

Forecasting the need for Renal Replacement Therapy (RRT) in intensive care units (ICUs) at an early stage can enhance patient outcomes and optimize resource allocation. The study aimed to develop a model for early prediction of Renal Replacement Therapy (RRT) requirement within 24 hours of ICU admission, utilizing machine learning techniques and SHapley Additive exPlanations (SHAP). It assessed various models including Random Forest (RF), Neural Network (NN), and XGBoost, using data from 34,000 ICU admissions. XGBoost showed superior performance in terms of AUPRC, while RF performed better in AUC-ROC. Results were consistent before and after Principal Component Analysis (PCA) and feature evaluation analysis. The top 10 feature models outperformed the PCA model while using fewer inputs. These findings suggest the potential utility of the developed models in accurately predicting RRT requirement within 24 hours of ICU admission, aiding in efficient critical care delivery.

Feasibility of forecasting future critical care bed availability using bed management data.

OBJECTIVES: This project aims to determine the feasibility of predicting future critical care bed availability using data-driven computational forecast modelling and routinely collected hospital bed management data. METHODS: In this proof-of-concept, single-centre data informatics feasibility study, regression-based and classification data science techniques were applied retrospectively to prospectively collect routine hospital-wide bed management data to forecast critical care bed capacity. The availability of at least one critical care bed was forecasted using a forecast horizon of 1, 7 and 14 days in advance. RESULTS: We demonstrated for the first time the feasibility of forecasting critical care bed capacity without requiring detailed patient-level data using only routinely collected hospital bed management data and interpretable models. Predictive performance for bed availability 1 day in the future was better than 14 days (mean absolute error 1.33 vs 1.61 and area under the curve 0.78 vs 0.73, respectively). By analysing feature importance, we demonstrated that the models relied mainly on critical care and temporal data rather than data from other wards in the hospital. DISCUSSION: Our data-driven forecasting tool only required hospital bed management data to forecast critical care bed availability. This novel approach means no patient-sensitive data are required in the modelling and warrants further work to refine this approach in future bed availability forecast in other hospital wards. CONCLUSIONS: Data-driven critical care bed availability prediction was possible. Further investigations into its utility in multicentre critical care settings or in other clinical settings are warranted.

Outcomes of different steroid dosing regimens in critical Covid-19 pneumonia at a Kenyan hospital: A retrospective cohort study.

BACKGROUND: Among therapeutic options for severe and critical COVID- 19 infection, dexamethasone six milligrams once daily for ten days has demonstrated mortality benefit and is guideline recommended at this dose. In practice, variable doses of steroids have been used, especially in critical care settings. Our study aimed to determine the pattern of steroid dosing and outcomes in terms of critical care mortality, occurrence of dysglycaemias, and occurrence of superadded infections in patients with critical COVID-19. METHODS: A retrospective cohort study was carried out on all eligible patients admitted to the Aga Khan University Hospital, Nairobi, with critical COVID-19 between 1st March 2020 and 31st December 2021. The intervention of interest was corticosteroids quantified as the average daily dose in milligrams of dexamethasone. A steroid dose of six milligrams once a day was compared to high dose steroid dosing, which was defined as any dose greater than this. The primary outcome measure was ICU mortality and secondary outcomes included occurrence of dysglycaemias, superadded infections and duration of critical care admission. RESULTS: The study included 288 patients. The median age was 61.2 years (IQR: 49.7, 72.5), with 71.2% of patients being male. The most common comorbidities were diabetes mellitus (60.7%), hypertension (58%), and heart disease (12.2%). The average oxygen saturation and C-reactive protein at admission were 82% [IQR: 70.0-89.0]and 113.0 [IQR: 54.0-186.0], respectively. Fifty-eight percent of patients received a standard dose (6mg) of steroids. The mortality rate was higher in the high-dose group compared to the standard-dose group; however, the difference was not statistically significant (47.9% vs 43.7% p = 0.549). The two most common steroid associated adverse effects were uncomplicated hyperglycemia (62.2%) and superimposed bacterial pneumonia (20.1%). The high-dose group had a higher incidence of uncomplicated hyperglycemia compared to the standard-dose group (63.6% vs 61.1%). However, the incidence of diabetic ketoacidosis was lower in the high dose group (0.6% vs 6.6%). Oxygen saturation at admission was associated with survival where it was lower among non-survivor patients with critical COVID-19. CONCLUSION: The study found that high-dose steroids in the treatment of critically ill patients with COVID-19 pneumonia did not confer any mortality benefit and were associated with an increased risk of dysglycemia and superimposed infections.

The impact of neurocritical patient transfer on outcomes: retrospective analysis of practice in the largest neurosurgical centre in Lithuania.

INTRODUCTION: Critical neurological conditions require urgent assessment and treatment. The quality of care and treatment provided during the transportation is important and related to the outcome of critically ill patients. We aimed to assess the quality of interhospital transportation of neurocritical patients in the largest neurosurgical cluster in Lithuania and identify possible outcome prediction variables. MATERIAL AND METHODS: A retrospective cohort study was conducted. We analysed the data from 106 neurocritical patients who were transported to the Hospital of Lithuanian University of Health Sciences Kaunas Clinics Neurosurgery Clinic in 2018. We collected the needed data from patients' medical history, referrals, and transfer sheets. In our research, we evaluated the quality of referrals and the quality of filling protocols. RESULTS: The transportation protocols showed that during the transferrals diuresis, end-tidal carbon dioxide (ETCO2), pupil size, and reaction to light were not routinely measured in any of the patients, as opposed to other vital signs. We found that less than half of referrals (42%) were informative and suitable for sending the patient to another hospital. Results showed that the first systolic arterial blood pressure (sABP) measured at Neuro-ICU is associated with patient outcomes. Higher sABP was seen in the group of patients with negative outcomes (death, continued need for care). CONCLUSIONS: This study demonstrated that monitoring of vital signs and neurological parameters as well as the quality of referrals were found to be the weakest links in the neurocritical patient transfer.

Device associated complications in the intensive care unit.

Invasive devices are routinely used in the care of critically ill patients. Although they are often essential components of patient care, devices such as intravascular catheters, endotracheal tubes, and ventilators are a common source of complications in the intensive care unit. Critical care practitioners who use these devices need to use strategies for risk reduction and understand approaches to management when adverse events occur. This review discusses the identification, prevention, and management of complications of vascular, airway, and mechanical support devices commonly used in the intensive care unit.

Distinct enterotypes and dysbiosis: unraveling gut microbiota in pulmonary and critical care medicine inpatients.

BACKGROUND: The gut-lung axis, pivotal for respiratory health, is inadequately explored in pulmonary and critical care medicine (PCCM) inpatients. METHODS: Examining PCCM inpatients from three medical university-affiliated hospitals, we conducted 16S ribosomal RNA sequencing on stool samples (inpatients, n = 374; healthy controls, n = 105). We conducted statistical analyses to examine the gut microbiota composition in PCCM inpatients, comparing it to that of healthy controls. Additionally, we explored the associations between gut microbiota composition and various clinical factors, including age, white blood cell count, neutrophil count, platelet count, albumin level, hemoglobin level, length of hospital stay, and medical costs. RESULTS: PCCM inpatients exhibited lower gut microbiota diversity than healthy controls. Principal Coordinates Analysis revealed marked overall microbiota structure differences. Four enterotypes, including the exclusive Enterococcaceae enterotype in inpatients, were identified. Although no distinctions were found at the phylum level, 15 bacterial families exhibited varying abundances. Specifically, the inpatient population from PCCM showed a significantly higher abundance of Enterococcaceae, Lactobacillaceae, Erysipelatoclostridiaceae, Clostridiaceae, and Tannerellaceae. Using random forest analyses, we calculated the areas under the receiver operating characteristic curves (AUCs) to be 0.75 (95% CIs 0.69-0.80) for distinguishing healthy individuals from inpatients. The four most abundant genera retained in the classifier were Blautia, Subdoligranulum, Enterococcus, and Klebsiella. CONCLUSIONS: Evidence of gut microbiota dysbiosis in PCCM inpatients underscores the gut-lung axis's significance, promising further avenues in respiratory health research.

Toward Precision in Critical Care Research: Methods for Observational and Interventional Studies.

Critical care trials evaluate the effect of interventions in patients with diverse personal histories and causes of illness, often under the umbrella of heterogeneous clinical syndromes, such as sepsis or acute respiratory distress syndrome. Given this variation, it is reasonable to expect that the effect of treatment on outcomes may differ for individuals with variable characteristics. However, in randomized controlled trials, efficacy is typically assessed by the average treatment effect (ATE), which quantifies the average effect of the intervention on the outcome in the study population. Importantly, the ATE may hide variations of the treatment's effect on a clinical outcome across levels of patient characteristics, which may erroneously lead to the conclusion that an intervention does not work overall when it may in fact benefit certain patients. In this review, we describe methodological approaches for assessing heterogeneity of treatment effect (HTE), including expert-derived subgrouping, data-driven subgrouping, baseline risk modeling, treatment effect modeling, and individual treatment rule estimation. Next, we outline how insights from HTE analyses can be incorporated into the design of clinical trials. Finally, we propose a research agenda for advancing the field and bringing HTE approaches to the bedside.

Impact of restricted family presence during the COVID-19 pandemic on critically ill patients, families, and critical care clinicians: a qualitative systematic review.

BACKGROUND: We aimed to synthesize the qualitative evidence on the impacts of COVID-19-related restricted family presence policies from the perspective of patients, families, and healthcare professionals from neonatal (NICU), pediatric (PICU), or adult ICUs. METHODS: We searched MEDLINE, EMBASE, Cochrane Databases of Reviews and Clinical Trials, CINAHL, Scopus, PsycINFO, and Web of Science. Two researchers independently reviewed titles/abstracts and full-text articles for inclusion. Thematic analysis was completed following appraising article quality and assessing confidence in the individual review findings using standardized tools. RESULTS: We synthesized 54 findings from 184 studies, revealing the impacts of these policies in children and adults on: (1) Family integrated care and patient and family-centered care (e.g., disruption to breastfeeding/kangaroo care, dehumanizing of patients); (2) Patients, families, and healthcare professionals (e.g., negative mental health consequences, moral distress); (3) Support systems (e.g., loss of support from friends/families); and (4) Relationships (e.g., loss of essential bonding with infant, struggle to develop trust). Strategies to mitigate these impacts are reported. CONCLUSION: This review highlights the multifaceted impacts of restricted visitation policies across distinct care settings and strategies to mitigate the harmful effects of these policies and guide the creation of compassionate family presence policies in future health crises. REGISTRATION: https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=290263 .

The impact of adhering to a quality indicator for sedation, analgesia, and delirium management on costs, revenues, and clinical outcomes in intensive care in Germany: A retrospective observational study.

BACKGROUND: Management of sedation, analgesia, and delirium influences morbidity, mortality, and quality of life in patients treated in intensive care. Assessing quality indicators as part of a quality management and assurance program is an established method to ensure process quality. Currently, there is limited research on the effect of evaluating quality indicators on economic outcomes. The aim of the study was to investigate the adherence to an indicator on management of sedation, analgesia and delirium, and explore potential effects on hospital economics and clinical outcomes. METHODS: In this retrospective cohort study, we analyzed routine data from 20,220 patient records from the hospital information system of a tertiary university hospital, collected from January 2012 to December 2019. We compared two predefined subgroups with either high indicator adherence or low indicator adherence regarding factors like disease severity scores, comorbidities, and outcome measures. We used logistic regression models to examine the influence of quality indicator adherence on economic measures such as Diagnosis-related group (DRG) incomes, revenue margins, and costs, and clinical outcomes. Additionally, we used propensity score matching to probe our findings. RESULTS: Overall revenue margins in this cohort were negative (-320€). High adherence to the quality indicator was associated with a positive revenue margin (+197€) compared to low adherence (-482€). Higher adherence was also associated with lower costs. Additionally, high adherence was associated with reduced mortality (OR 0.84, 95% CI 0.75-0.95) and reduced duration of mechanical ventilation and hospital stay (17 hours and 1 day respectively). CONCLUSION: Higher adherence to a quality indicator for sedation, analgesia, and delirium management was associated with economic returns and costs. We also found an association with lower mortality and reduced length of stay. Further research on these associations may help identify opportunities for quality improvement without increased resource use.