Active clinical trials for "Critical Illness"

This BRAIN-ICU-2 study [Bringing to light the Risk factors And Incidence of Neuropsychological dysfunction (dementia) in ICU Survivors, 2nd Study] is in direct response to PAR-17-038 and will determine ICU patients' main paths to decline, maintenance, or recovery of brain function. We will answer gaps in knowledge about long-term outcome of post-ICU brain disease by following the remaining ICU survivors from the original BRAIN-ICU-1 study with complete cognitive testing for the first time ever to 12 years (AIM 1). We will consent and enroll 567 new ICU patients at Vanderbilt and Rush Universities (i.e., BRAIN-ICU-2 cohort) and determine how detailed neuroimaging and cerebrospinal fluid samples can help reveal locations and mechanisms of injury beyond what we learned from the clinical information collected in our original study (AIM 2). Importantly, we are mirroring the existing world-renowned Rush Alzheimer's Disease Research Center brain bank program so that all patients enrolled in Aims 1 and 2 will able to donate their brains to science for the first-ever in-depth pathological study of those who do and do not get post-ICU dementia to define this disease formally (AIM 3)

The emerging SARS-COV2 virus has shed a new light on the cross-talks between the immune and the hemostatic system. In this study we aim to evaluate the dynamic change in coagulation caused by the modulation of the inflammatory response by interleukin-6 antagonist as assessed by viscoelastic methods in critically ill COVID-19 patients. Furthermore we try to draw attention to possible associations between the endothelial cell injury, inflammation and coagulation.

Following whole blood stimulation with mesenchymal stem cell derived exosomes, immune phenotype, cytokine release and mRNA expression patterns from critically ill patients with COVID-19 will be determined.

The only supportive therapy for patients with AKI is renal replacement therapy (RRT). In the ICU setting, continuous RRT (CRRT) is mostly favored. In a post-hoc analysis of the RICH trial (regional citrate versus systemic heparin anticoagulation for CRRT in critically ill patient with AKI), it was shown that the filter life span is associated with an increased rate of new infection and that the type of anticoagulants did not directly affect infection rate. The mechanisms of this infection rate is unknown.

Australian and New Zealand Intensive Care Society (ANZICS) has built a Center of Outcome and Resource Evaluation (CORE) adult patients database (APD) of adult critically ill patients. ANZICS CORE APD has built an international collaboration of ICU database. National Taiwan University Hospital has joined this international collaboration and built the data according to the APD data dictionary with same value domain attributes and data element attributes. We retrospectively collected the data of patients discharged from the March 1, 2019 to June 30, 2022. Data of this database are permitted to study clinical problems and predict the clinical outcomes of these critically ill patients using statistical methods and machine learning techniques.

The aim of this study was to identify and validate novel biomarkers including functional tests for detecting AKI, AKI progression and other poor outcomes.

Pediatric Intensive Care Unit (PICU) survival has increased substantially over the past three decades. Currently, an understanding of PICU morbidity and recovery among PICU survivors and their families is limited. Post-intensive care syndrome (PICS) consists of new or worsening impairments in physical, cognitive, or mental health status that arise and may persist after critical illness. The characteristics of PICS in children (PICS-p) are unknown. The objective of this study is to learn about pediatric recovery from critical illness to guide future intervention research to optimize child and family health.

Summary: Emerging data demonstrate long-term morbidity and mortality in those who survive critical illness. However, there is no data regarding long-term follow-up for ICU survivors. The investigators have begun the implementation of an ICU recovery clinic. Rationale: ICU survivors are at high risk for functional, cognitive and psychiatric impairments. However, methods to mitigate these impairments and improve recovery are lacking. Special follow-up clinics for survivors of critical illness have been proposed and implemented to some degree, but are uncommon.

Each year approximately 3000 patients are admitted to the intensive care unit (ICU) in the University Medical Center Groningen (UMCG). In-hospital mortality of patients with emergency admission approaches 25%. Predicting outcome in the first hours after ICU admission, however, remains a challenge. An vast amount of scoring systems has been developed for mortality prediction. Well known models, such as the LODS, MODS, CCI, SOFA, ODIN and the different generations of the APACHE, MPM and SAPS, are increasingly compared with new models, such as the SICULA, ICNARC, ANZROD and SMS-ICU. The predictive value of scoring systems deteriorates over time due to changes in patient characteristics and treatment, making it crucial to update existing models or develop new models. Other reasons given for the need of models are the complexity and lack of availability of variables in some of the existing scoring systems, the better discriminating value while using simple, standardly measured variables, and the limited generalizability of some scoring systems in different patient populations. Not only are simple systems (such as the CIS and SMS-ICU) found to be at least as predictive for mortality as complex models such as the APACHE IV, but, while using simplified systems, mortality can also be reasonably predicted within only a few hours after admission. Both simplicity and the potential to predict mortality shortly after admission increase the usability, and consequently the reliability, of those prediction models. This increases the potential of those models to be used in practice. Most studies however compare only two to four models in their patient population and lack in their description of the performance of the different models. Parameters necessary to compare the performance of models are at least calibration, discrimination, negative predicting value, positive predicting value, sensitivity and specificity. Lacking an adequate description of the performance of the model limits to what extent the study can be used to compare models in different populations. Thus, all usable models should be compared with newly build models, and the performance of the different models should be extensively described to allow comparison of the models. Not only models based on simple, readily available variables available within hours after admission are promising, but also the concept of combining measurements straight after ICU admission with information on the course of illness. It is likely that the course of a variable over time is more indicative than a static measurement. This study will provide a structure in which every patient admitted to the ICU will be investigated and included within 3 hours and after 12 hours after admission, making longitudinal measurements and various add-on studies possible. Longitudinal measurements are the first example of an add-on study; another example is the capability of nurses and physicians to predict outcome. Current evidence suggests that physicians might predict mortality more accurately than scorings systems. This finding may, however, be highly biased, since at least physicians play a major role in end-of-life decision making. More recent studies also focus on the accuracy of nurses in predicting mortality, with diverse outcomes. The role of other health care professionals, like residents and students, remain to be studied. Implementing a systematic data collection process is the first step towards making data-driven research possible, a growing need in medical disciplines such as critical care, which requires increasingly more accurate prognostic models. Therefore, the aim of this study is to systematically collect data of all selected variables, thus minimizing incompleteness, and allowing for the calculation of mortality prediction scores according to currently available mortality or severity of disease prediction models. Moreover, during investigation reliability of measurements could be checked for validity. This creates the possibility to compare the performance of all models in one population and identify models which are useful to predict severity of disease. A registry will be created with this primary objective which also provides the opportunity to start multiple ''add-on'' studies for specific research questions. Examples of add-on studies are 1) the association between time-dependent variables which are longitudinally measured, and mortality/acute and chronic co-morbidity, 2) the association between fluid status and acute kidney injury, and 3) not only the capability of the treating physician to predict mortality, but also the capability of the nurses, residents and students to do so. Purpose: The purpose of this study is to expand the infrastructure for a registry with longitudinal and repeated measurements, shortly after admittance, which is flexible to incorporate temporarily added specific research questions on the outcome of critically ill patients.

The study aims to demonstrate the relationship between intra-abdominal hypertension (IAH) and abundant microaspirations in mechanically ventilated cirrhotic.